DevOps Engineering | Applied AI Consulting

Accelerating CI/CD Efficiency From Jenkins to GitHub Actions for Seamless Automation

Wed, 23 Oct 2024 18:10:34 +0000

Accelerating CI/CD Efficiency: From Jenkins to GitHub Actions for Seamless Automation

Transforming Development Workflows with Enhanced Security and Streamlined Processes

Company Overview

Client/Customer Overview:

The client is an organization that has been using Jenkins for years to manage their CI/CD processes. With a growing focus on optimizing operations, they were looking for more efficient, secure, and cost-effective CI/CD tools to address issues related to their existing setup. The business needed a solution that would streamline development workflows, improve security, and reduce operational overhead.

Feature-Rich Environment: The new CI/CD tool offers a wide array of features, including seamless integration with popular development and deployment platforms, allowing for smoother workflows.

Enhanced Security Measures: The product incorporates advanced security protocols and compliance features, ensuring that the CI/CD process adheres to industry standards and best practices.

Scalability and Performance: It is designed to scale effortlessly with the organization’s growth, ensuring high performance even during peak workloads.

Automation Capabilities: The tool automates various aspects of the CI/CD pipeline, reducing manual effort and minimizing the risk of human error.

User-Friendly Interface: The product provides an intuitive and user-friendly interface, enabling teams to quickly adopt the tool and reduce the learning curve associated with new technology.

Challenges

Security vulnerabilities

The old Jenkins server was difficult to update, posing significant security risks.

Complex setup

Jenkins required complex configurations, making even small changes time-consuming.

High costs

The continuous operation of Jenkins servers (24/7) resulted in high operational costs.

Performance inefficiencies

The Jenkins CI/CD pipelines were slower compared to newer alternatives like GitHub Actions

Let’s discuss your use cases

Contact Sales

Operations Conducted

Alternative tool evaluation

The team explored other CI/CD options and chose GitHub Actions for its simplicity and integration with GitHub Enterprise.

Migration

They started with low-risk CI/CD pipelines to GitHub Actions and gradually moved their backend, frontend, and mobile services.

QA automation

The team also migrated the QA automation and mobile CI/CD for Android and iOS to GitHub Actions.

Strategic Approach

Seamless migration to GitHub Actions

The client adopted GitHub Actions due to its ease of use, eliminating the need for manual setup and reducing dependency on external infrastructure.

Improved security

GitHub-managed runners ensured up-to-date systems, significantly reducing security risks by 40%.

Optimized resource usage

The GitHub Enterprise plan was fully leveraged, maximizing resource utilization by 70% through built-in features like caching.

Enhanced developer productivity

By reducing complex setup and configurations, the team focused more on development, minimizing time spent on CI/CD management by 30%.

Positive Influence

Reduced CI/CD runtime

Significantly faster pipelines helped in optimizing release cycles and increasing overall efficiency by 30%.

Enhanced security

Compliance with SOC 2 audit standards was achieved, improving the business’s security posture by 20%.

Cost savings

Reduced human effort on complex setups and optimized usage of GitHub resources led to overall cost reductions of 90% on CICD servers.

Long-term Scalability

Custom dashboards: The team is working on building a consolidated dashboard for CI/CD monitoring and reporting, improving visibility.
Refined permission management: Plans include implementing least-privilege access controls for GitHub Actions to improve security.
Credential management: The client will enhance secret and credential management within GitHub Actions to ensure safer operations.
Broader adoption: The solution can be scaled to support other projects, enhancing efficiency and security across different teams and departments.

Key Takeaways

Migrating from Jenkins to GitHub Actions has resulted in significant improvements in operational efficiency, security, and cost-effectiveness. The streamlined CI/CD process has empowered the client’s development teams to focus more on product innovation while ensuring that their infrastructure remains secure and scalable for future needs.

Customer Testimonials

Switching to GitHub Actions has been a game-changer for our CI/CD workflows. The migration process was smooth, and the reduction in operational overhead and security risks has significantly improved our development efficiency. We can now focus on delivering value without worrying about complex infrastructure management.
Head of QA Engineer

Accelerating Integration with a Robust API Platform: How a Leading Automation Provider Transformed Their Processes Using AWS Services

Fri, 23 Aug 2024 16:28:07 +0000

Accelerating Integration with a Robust API Platform: How a Leading Automation Provider Transformed Their Processes Using AWS Services

Streamlining Operations: Leveraging AWS to Enhance Automation Through a Powerful API Platform

Company Overview

A leading company in the automation platform domain, this organization provides innovative solutions for enterprise automation, including digital transformation, process improvement, and growth strategies. Their platform addresses complex challenges such as information access, approval processes, high transaction volumes, and compliance issues. The company’s integrated payment solutions and process automation tools are revolutionizing enterprises by making operations more efficient and streamlined.

Issue

Time-Consuming Integrations: Building and maintaining point-to-point integrations for each client was resource-intensive and inefficient.

Lengthy Integration Process: Integrating with third-party ERPs and payment systems took 8-12 weeks per client, delaying project timelines.

Limited Scalability: The existing process constrained the ability to serve multiple clients simultaneously, limiting growth.

Need for a Scalable Solution: A scalable, reusable integration framework was required to streamline and accelerate the onboarding process for new clients.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

API-Based Integration Gateway: Implemented a robust API-based Integration Gateway using AWS services like Amazon API Gateway, AWS Lambda, and others to streamline integrations.

Custom Solution Architecture: Designed a four-component architecture (Flow, Filter, Transformer, Adopter) to efficiently manage and transform inputs for various ERP systems, enhancing compatibility and flexibility.

Automated CI/CD Pipelines: Established automated CI/CD pipelines to ensure continuous integration and deployment, minimizing manual intervention and enhancing system reliability.

Impact

Accelerated Time-to-Market & Customer Onboarding

Significantly improved the accuracy and efficiency of email content classification and follow-ups. Reduced integration and deployment times by 80%, enabling faster rollout of new features and rapid onboarding of new clients in under a week.

Operational Efficiency & Cost Savings

Automated over 30 tasks and implemented a reusable integration framework, leading to a 60% increase in efficiency and a 40% reduction in operational costs.

Scalability & Enhanced User Experience

Scalable architecture supported increased workloads and customer demands, while a simplified, user-friendly interface improved client satisfaction and expanded customer capacity by 80%.

Customer Testimonials

The API platform developed by Applied AI Consulting has been a game-changer for us. It has significantly reduced manual efforts and errors, enabling us to onboard 80% more customers with ease. Their work has truly elevated our capabilities.
CTO 7Targets.ai

Accelerating Private Sector Bank’s App Releases with AWS and DevOps Expertise by Applied AI Consulting

Fri, 23 Aug 2024 16:15:05 +0000

Accelerating Private Sector Bank’s App Releases with AWS and DevOps Expertise by Applied AI Consulting

Streamlining Development and Deployment Pipelines for Faster, Secure, and Scalable Banking Solutions

Company Overview

One of the leading private sector banks in India, this financial institution provides a wide array of services including retail banking, corporate banking, and wealth management. With a commitment to customer-centric innovation, the bank offers an extensive range of products such as savings accounts, loans, fixed deposits, and credit cards. The bank serves millions of customers across the country through its extensive network of branches and digital banking platforms. Known for its robust infrastructure and innovative solutions, the bank continuously strives to enhance customer experience and operational efficiency.

Issue

Slow App Release Cycle: The bank struggled to release apps quickly, hindered by the manual management of its IT infrastructure.

Legacy System Bottlenecks: Outdated infrastructure caused extended software development cycles and made it difficult to maintain high app quality.

Inefficient IT Management: The centralized, manually operated IT infrastructure was not only time-consuming but also prone to errors and costly to maintain.

Technical Debt: The accumulation of technical debt due to outdated coding practices stifled innovation and reduced the bank’s ability to be agile.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

CI/CD Pipelines: Enabled faster and more reliable deployments by automating the software release process.

Infrastructure-as-Code: Utilized Terraform to streamline deployment speed, cut costs, and reduce errors through automated infrastructure management.

App Containerization: Enhanced scalability and security, accelerating the time to market and improving overall application performance.

Impact

Faster App Releases

Implementing CI/CD pipelines reduced the app release cycle time by 40%, allowing the bank to quickly roll out new features and updates to meet customer demands.

Enhanced Reliability and Security

By employing Infrastructure-as-Code with Terraform and app containerization with AWS ECS, the bank achieved a 99.9% uptime, reducing the risk of downtime and data breaches.

Cost Efficiency

Automation of manual processes and reduced technical debt led to a 30% decrease in operational costs, allowing the bank to allocate resources more effectively.

Customer Testimonials

The collaboration with Applied AI Consulting has revolutionized our approach to infrastructure management. Their strategic implementation of CI/CD and containerization has drastically improved our time-to-market, while also reducing technical debt. The automation of our infrastructure has led to unprecedented levels of efficiency and reliability. This partnership has been crucial in our journey towards a more agile and innovative banking platform.
VP of Engineering Leading Private Sector Bank

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Fri, 23 Aug 2024 15:50:57 +0000

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Company Overview

A leading company in the content marketing domain, this organization helps brands and their customers connect through high-quality, relevant content. The platform enables companies to produce and disseminate their own content, improving customer acquisition, building brand loyalty, and sustaining interest in their offerings. Known for its innovative approach and commitment to quality, the company serves a diverse clientele, including top brands and enterprises, ensuring their content marketing strategies are effective and impactful.

Issue

Ensuring consistent and reliable deployments across multiple environments.

Reducing manual testing efforts and increasing the efficiency of the QA process.

Automating repetitive tasks to free up resources for more strategic activities.

Enhancing the overall quality and performance of their content marketing platform.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Streamlined UI testingby implementing Python Selenium for automation, enhancing efficiency and reducing manual testing efforts.**

Developed automated test scriptsto validate critical functionalities across various environments, ensuring consistent performance.

Integrated automation with CI/CD pipelines** for continuous testing and deployment, along with providing training and documentation for seamless adoption by development and QA teams.

Impact

Increase in Deployment Success

Significantly reduced failed deployments and rollbacks, enhancing reliability in the deployment process.

Reduction in Manual Testing

Freed up the QA team to focus on complex tasks, driving efficiency and strategic improvements.

Enhanced Quality and Customer Satisfaction

Improved platform performance and reliability, supporting faster, more dependable releases aligned with company growth and innovation goals.

Customer Testimonials

Applied AI Consulting’s mastery in Python Selenium automation was a game-changer for us. Their ability to integrate seamlessly with our CI/CD pipeline drastically improved our deployment success rate by 50%, while cutting down manual testing by 70%. Their innovative approach and commitment to excellence have significantly elevated our platform's performance, enabling us to deliver faster and more reliable releases.
CTO marxeed.com

Facilitating DevOps with Application Modernization & Architecture Reboot for a Leading Content Marketing Platform

Fri, 23 Aug 2024 15:29:44 +0000

Facilitating DevOps with Application Modernization & Architecture Reboot for a Leading Content Marketing Platform

Boosting Deployment Efficiency, Scalability, and Cost Savings While Enhancing Security

Company Overview

A leading company in the content marketing domain, this organization helps brands and their customers connect through high quality, relevant content. The platform enables companies to produce and disseminate their own content, improving customer acquisition, building brand loyalty, and sustaining interest in their offerings. The company also owns a marketing analytics software that helps marketers compute ROI and improve outcomes across integrated digital and social channels.

Issue

Need for migration and modernization to handle peak load efficiently

Challenges in deployment, maintenance and support existing applications

Need a revamp existing infrastructure to enable automation and DevOps, supporting continuous upgrades

Let’s discuss your use cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Contact Sales

Similar Use Cases

Solution

Containerization and Orchestration: Containerized applications with Docker and deployed them in Kubernetes (K8s) for enhanced management, scalability, and resilience.

Automated Deployment and Testing: Used GitHub Actions for CI/CD automation, AWS CloudFormation for Infrastructure as Code, and Selenium and OWASP for automated and security testing.

Monitoring, Alerts and Cost Optimization: Implemented CloudWatch for monitoring and alerts, integrated GitHub and Slack for CI/CD notifications, and utilized AWS Lambda for efficient resource management and cost savings.

Impact

Scalability and Performance

Containerization and auto-scaling enabled seamless handling of increased traffic, significantly improving peak load management.

Deployment Efficiency

Automated CI/CD pipelines reduced deployment time from several hours to minutes, streamlining release cycles and minimizing downtime.

Cost Optimization

Enhanced scalability, reliability, and security of applications, achieving significant cost savings through resource optimization.

Customer Testimonials

Applied AI Consulting transformed our platform with modernized IT infrastructure and DevOps practices. Their expertise improved our deployment speed, scalability, and security, significantly reducing costs and boosting our ability to connect with customers. They've been an invaluable partner in our digital transformation.
Head of Marketing Marxeed

Streamlining Development Operations: Migrating from GitLab to GitHub for a Leading Content Marketing Platform

Fri, 23 Aug 2024 11:20:11 +0000

Streamlining Development Operations: Migrating from GitLab to GitHub for a Leading Content Marketing Platform

Optimizing Development Operations by Migrating from GitLab to GitHub for Enhanced Efficiency and Cost Savings

Company Overview

A leading company in the content marketing domain, this organization helps brands and their customers connect through high-quality, relevant content. The platform enables companies to produce and disseminate their content, improving customer acquisition, building brand loyalty, and sustaining interest in their offerings. The company also owns marketing analytics software that helps marketers compute ROI and improve outcomes across integrated digital and social channels.

Issue

The existing GitLab solution was costly, impacting the budget for development operations.

GitLab’s integration with other tools in the development pipeline was insufficient.

The need for a more scalable version control system to handle increased workloads.

Ensuring a smooth migration from GitLab to GitHub with minimal disruption to ongoing projects.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Migration Execution: Planned and executed the migration to GitHub, transferring all repositories, issues, and CI/CD pipelines accurately.

Enhanced Tool Integration: Integrated GitHub with Jira for project management and Slack for communication and also integrated GitHub Actions for automating build, test, and deployment processes.

Training and Support: Conducted training sessions for the development team to ensure effective use of GitHub’s features.

Impact

Operational Cost Savings

Migration to GitHub reduced operational costs through its cost-effective pricing model.

Improved Scalability

GitHub’s scalable infrastructure effectively managed increased workloads, supporting business growth.

Increased Productivity

Integration with various collaboration tools and streamlined workflows boosted team productivity.

Customer Testimonials

Applied AI Consulting’s expertise in building custom AI solutions with ML and NLP, along with their scalable AWS implementation, significantly enhanced our product’s performance. Their innovative approach and commitment to quality have driven tangible improvements, greatly benefiting our customers.
CTO 7Targets.ai

Building a Hybrid Payment Platform from Scratch on AWS Stack

Fri, 23 Aug 2024 11:18:02 +0000

Building a Hybrid Payment Platform from Scratch on AWS Stack

Company Overview

A leading company in the payment processing industry, this organization specializes in providing secure and efficient payment solutions for businesses of all sizes. Known for its innovative approach, the company offers a comprehensive range of services, including online payment gateways, mobile payments, and point-of-sale systems. With a focus on reliability and customer satisfaction, the company serves a diverse clientele, ensuring seamless and secure transactions.

Issue

Ensuring the platform could scale to handle increasing transaction volumes.

Implementing robust security measures to protect sensitive payment data.

Integrating with multiple payment gateways and financial institutions, like Stripe, Plaid etc.

Maintaining high availability and reliability.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Architected a hybrid payment platform on AWS ECSwith auto-scaling capabilities to manage fluctuating transaction volumes efficiently, leveraging AWS Lambda and AWS Fargate for serverless operations to minimize operational overhead.

Implemented robust security measuresutilizing AWS IAM for access control and encryption for data protection both at rest and in transit, ensuring compliance and safeguarding sensitive financial information.

Integrated multiple payment gateways and financial institutions via APIs and established CI/CD pipelines to automate updates and maintenance, ensuring seamless and efficient deployment processes.

Impact

Scalable and Secure hybrid payment

Ensured reliable transaction processing with high availability and minimal downtime.

Security Measures

Safeguarded sensitive payment data, maintaining robust protection against potential threats.

Streamlined operations

Through CI/CD pipelines, leading to more efficient and continuous delivery of updates.

Driving Quality and Reliability for Modern Mobile and Web Applications

Wed, 21 Aug 2024 15:26:41 +0000

Driving Quality and Reliability for Modern Mobile and Web Applications

Building a Modern Mobile and Web Application with Robust CI/CD Automation and AI-Powered Multi-Device Testing

Company Overview

A leading start-up in the online consulting platform domain, this company focuses on connecting end-users with top industry professionals for expert consultation services. Known for its innovative approach and cutting-edge technology, the company aims to provide seamless and efficient solutions for both consultants and clients, ensuring high-quality interactions and problem-solving experiences. Applied AI Consulting has created the modern stack with payment gateway integration for this customer. This case study is focused on quality engineering.

Issue

Cross-Platform Compatibility: Building a modern application that supports both mobile and web platforms can introduce challenges in ensuring consistent functionality and user experience.

Testing Coverage: Ensuring thorough and reliable UI and API testing to cover all possible use cases and scenarios, which is crucial for maintaining application quality and reliability.

Automation Integration: Integrating automation testing into the CI/CD pipeline effectively, ensuring that automated tests run seamlessly with each deployment to catch issues early.

Performance and Reliability: Maintaining high performance and reliability of the application across multiple platforms and under varying load conditions.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Developed and Integrated Automation Frameworks: Created a Selenium-Python-based framework for UI testing and a pyTest framework for API testing, integrating them with the CI/CD pipeline.

Executed Cross-Platform Testing: Utilized aiTest for automation across multiple devices, browsers, and versions, including API quality validation with Postman collections.

Enhanced Communication and Visibility: Provided test execution updates and analytics through Slack and email, and demonstrated automation results in end-of-iteration demos.

Impact

Enhanced Quality and User Experience

Achieved very high application quality with minimal defects and ensured a seamless user experience across devices and browsers.

Accelerated Release Cycles

Reduced testing time by 40% through CI/CD integration and automation, leading to faster feature releases and updates.

Cost Savings and Performance Improvement

Decreased testing-related costs by 30% and improved application performance, contributing to higher user retention and scalable growth.

Customer Testimonials

Applied AI Consulting has been instrumental in driving the quality and reliability of our mobile and web applications. Their expertise in building a modern stack with seamless payment gateway integration has allowed us to provide our users with a smooth and efficient experience. The team's commitment to excellence and their innovative approach have significantly enhanced our platform's performance, ensuring we meet the high standards our clients expect.
Founder Click to Connect

Reduced Operational Cost by 70%: Migrating from Rundeck to AWS Batch for a Leading Content Marketing Platform

Wed, 21 Aug 2024 15:01:07 +0000

Reduced Operational Cost by 70%: Migrating from Rundeck to AWS Batch for a Leading Content Marketing Platform

Transforming Cost Efficiency: How Migrating to AWS Batch Slashed Operational Costs by 70% for a Content Marketing Leader

Company Overview

Issue

High Operational Costs: Elevated costs associated with using Rundeck for batch processing.

Need for Scalability: Requirement for a more scalable and efficient solution to manage growing workloads.

Migration Disruption: Ensuring minimal disruption during the transition from Rundeck to the new solution.

Performance Enhancement: Improving the overall performance and reliability of batch processing operations.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Migration to AWS Batch Movedbatch processing operations from Rundeck to AWS Batch, leveraging AWS’s scalable infrastructure for enhanced performance and efficiency.**

Automation & Orchestration **Implemented AWS Lambda for job management and AWS Step Functions for orchestrating complex workflows and managing job dependencies.

Monitoring & Transition Utilized AWS CloudWatch for monitoring and alerting, ensuring smooth operations and a seamless transition with minimal downtime through meticulous planning.

Impact

Cost Savings & Efficiency

Migrating to AWS Batch reduced operational costs by 70%and automated batch processing, cutting job execution time by40%

Scalability & Reliability

Leveraged AWS Batch’s scalable architecture to efficiently handle increased workloads, supporting effective business growth

Resource Optimization

Reduced manual intervention and improved operational efficiency, enabling better allocation of resources to strategic initiatives.

Ensuring Performance and Scalability for Demand Generation Tech with Advanced Automation Testing

Wed, 21 Aug 2024 14:37:36 +0000

Ensuring Performance and Scalability for Demand Generation Tech with Advanced Automation Testing

Company Overview

A leading company in the demand generation technology sector, this organization provides data-driven marketing solutions to help businesses drive revenue growth. With a comprehensive suite of services, including lead generation, data management, and analytics, the company supports its clients in enhancing their marketing effectiveness. Known for its innovative approach and robust technology infrastructure, the company continuously seeks to improve its product offerings and operational efficiency.

Issue

Create a TestNG Maven framework for UI automation and RestAssured for API automation.

Perform functional UI and API automation and performance testing (load testing) to support 25,000 concurrent users on API calls and 5,000 concurrent users on UI with 30 million plus records in the database.

Integrate automation with the CI/CD pipeline.

Maintaining high availability and reliability.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Accelerated multi-browser testing and load testingby leveraging AAIC’s aiTest, ensuring comprehensive UI and backend performance validation.**

Developed a robust TestNG Maven frameworkwith Selenium and Java for UI automation, and RestAssured for API automation, enabling efficient and scalable testing.

Drastically reduced build qualification time** by implementing parallel test runs, cutting UI test time to 9 minutes and API test time to just 2-3 minutes.

Impact

Comprehensive Framework

Led by a QA lead, AAIC’s 5-member QA team architected and implemented a robust testing framework, covering functional UI and API automation, and enabling large-scale load testing.

High-Scale Load Testing

Successfully conducted load tests for 25,000 concurrent API users and 5,000 concurrent UI users, with a database of over 30 million records, ensuring the application’s performance and scalability under heavy load.

Seamless CI/CD Integration

Integrated automation with the CI/CD pipeline, enabling rapid and efficient build qualification tests, boosting confidence in the application’s readiness for deployment.

Mitigating Vulnerabilities for a Leading Construction Logistics Platform

Wed, 21 Aug 2024 14:36:38 +0000

Mitigating Vulnerabilities for a Leading Construction Logistics Platform

Mitigated vulnerabilities, enhanced platform security with robust monitoring, and ensured minimal disruption during the process to maintain business continuity.

Company Overview

A leading company in the construction logistics domain, this organization provides innovative solutions to streamline trucking operations. Their platform connects contractors, fleet owners, and material producers, facilitating efficient scheduling, dispatching, and tracking of construction materials. Known for its robust technology and customer-centric approach, the company aims to enhance productivity and reduce operational costs in the construction industry.

Issue

Immediate need to address the critical Log4j vulnerabilities in their systems.

Ensuring minimal disruption to ongoing operations while mitigating the vulnerabilities.

Enhancing the security posture of their platform to prevent future vulnerabilities.

Implementing a comprehensive monitoring and alerting system to detect and respond to security threats promptly.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Option Evaluation and Decision: Presented the client with two infrastructure provisioning and deployment options: Terraform and Helm or AWS CloudFormation.

Containerization and DevOps Pipeline Implementation: containerization for a portable computing environment with VMs, and developed a DevOps pipeline to automate testing, integration, and deployment.

Legacy IT Infrastructure Modernization: Codified and managed the client’s legacy IT infrastructure using AWS CloudFormation, providing a robust Infrastructure-as-Code (IaC) solution.

Impact

Faster Threat Response

Reduced threat detection and response times by 50% through real-time monitoring and automated remediation

Enhanced Security and Compliance

Improved overall security and ensured compliance with industry standards, addressing Log4j vulnerabilities.

Operational Resilience and Cost Savings

Maintained business continuity with minimal disruption and reduced the risk of future vulnerabilities, potentially saving up to 40% in remediation costs.

Customer Testimonials

AAIC has been fantastic to work with. They're proactive and always spot opportunities for improvement. Their attention to detail and commitment to excellence make our collaboration truly rewarding.
Eric Johnson, Director, DevOps truxnow.com

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start Up

Wed, 21 Aug 2024 12:48:08 +0000

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start-Up

Enhancing User Experience with Secure Payments, Real-Time Notifications, and Automated Deployments

Company Overview

Issue

Ensuring high availability and scalability of the mobile and web applications.

Integrating a reliable and secure payment gateway.

Automating the deployment processes to reduce downtime and improve efficiency.

Maintaining high performance and user experience during peak loads.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Successfully deployed the ClickToConsult mobile application on both the App Store and Play Store, leveraging Firebase for push notifications and AWS Lambda for backend processes, ensuring scalability and cost efficiency.

Implemented a robust web-based interface for managing administrative activities, with integrated Razorpay payment gateway for secure transactions, providing a seamless experience for users and administrators.

Set up CI/CD pipelines for automated deployments across the mobile and web platforms, minimizing downtime and facilitating smooth, efficient updates.

Impact

Launch of a Scalable Consulting Platform

Successfully launched a scalable and high-performing online consulting platform, ensuring seamless interactions and enhanced user experience.

Secure Payments and User Trust

Integrated a secure and reliable payment gateway, boosting user trust and satisfaction through secure transactions.

Cost Efficiency with Serverless Architecture

Achieved significant cost savings and operational efficiency by utilizing serverless architecture and automated deployments.

A USA-Based Fintech Startup Achieved Faster Releases and Scalability Through AAIC’s DevOps Pipeline and Infrastructure-as-Code

Wed, 21 Aug 2024 12:45:56 +0000

A USA-Based Fintech Startup Achieved Faster Releases and Scalability Through AAIC’s DevOps Pipeline and Infrastructure-as-Code

Boost Speed and Scale with AAIC’s DevOps and IaC

Company Overview

A leading company in the fintech sector, this organization specializes in providing innovative financial technology solutions to streamline and enhance payment processing for businesses. Known for its cutting-edge approach and customer-centric services, the company offers a wide range of products, including digital wallets, payment gateways, and financial analytics tools. The company is committed to delivering high-performance, secure, and scalable solutions to its diverse clientele.

Issue

Slow and manual deployment processes, causing delays in software releases and increasing time-to-market.

Difficulty in managing infrastructure efficiently, leading to high operational costs and resource allocation issues.

The need for a scalable solution to handle increasing transaction volumes and user demands.

Ensuring security and compliance with industry standards for financial transactions.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Automated Deployment & Reliable Releases: Designed and implemented a DevOps pipeline, utilizing CI/CD for faster, more reliable releases, and efficient maintenance.

Infrastructure & Scalability: Used Infrastructure-as-Code (IaC) with AWS CloudFormation for efficient infrastructure management, and implemented containerization with Docker and Kubernetes for scalability and application portability.

Security Enhancements: Strengthened security with AWS Identity and Access Management (IAM) and encryption for data at rest and in transit.

Impact

Faster Deployment & Cost Efficiency

Accelerated deployment cycles from weeks to hours and significantly reduced operational costs through efficient infrastructure management and automation.

Scalability & Performance

Achieved high scalability to seamlessly handle increased transaction volumes.

Security & Compliance

Enhanced security and compliance with industry standards to protect sensitive financial data.

Facilitating DevOps and Infrastructure Modernization for Zykrr: A Seamless Transition from Azure to AWS

Tue, 20 Aug 2024 17:16:35 +0000

Facilitating DevOps and Infrastructure Modernization for Zykrr: A Seamless Transition from Azure to AWS

Seamless Azure to AWS Transition Enhancing DevOps and Infrastructure Modernization

Company Overview

Zykrr is a leading platform that provides real-time visibility, insights, and control over customer interactions across various channels such as SMS, WhatsApp, QR codes, email, kiosks, websites, and in-app communications. Their AI/ML-enabled platform delivers actionable insights and real-time visibility, enhancing customer and employee interactions. With a focus on automating critical customer experience management functions, Zykrr aims to deliver exceptional customer experiences and predict future actions based on sentiment analysis.

Issue

Migration & Modernization: Recreating the existing Azure setup on AWS while maintaining functionality and architecture.

Infrastructure Setup: Building and deploying a new application infrastructure on AWS, adhering to specified requirements and timelines.

Maintenance & Support: Reducing the efforts associated with deploying, maintaining, and supporting applications by leveraging AWS services.

Optimized Infrastructure: Achieving a robust, scalable, and secure AWS infrastructure.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Infrastructure Setup: Built Zykrr’s AWS infrastructure using S3 for scalable storage, EKS for managed Kubernetes, and RDS for PostgreSQL.

Application Deployment: Deployed React front-end on AWS CloudFront and S3, back-end microservices on EKS with Helm charts, and configured PostgreSQL and Redis on RDS and Elasticache.

Security & Performance: Secured infrastructure with network measures, API Gateway, and Application Load Balancer; ensured high availability and fault tolerance through multi-AZ deployments and CDN acceleration.

Impact

Successful Migration

Achieved a seamless migration from Azure to AWS with all functionalities intact.

Enhanced Deployment Efficiency

Streamlined deployment processes with AWS services, reducing operational overhead.

Enhanced Scalability, Reliability, & Cost Efficiency

Leveraged AWS’s scalability features for effective peak load management and high availability while implementing resource optimization strategies to achieve cost savings and efficient resource management.

Customer Testimonials

Applied AI Consulting’s expertise in building custom AI solutions with ML and NLP, along with their scalable AWS implementation, significantly enhanced our product’s performance. Their innovative approach and commitment to quality have driven tangible improvements, greatly benefiting our customers.
CTO 7Targets.ai

Driving Quality and Reliability for Modern Mobile and Web Applications: A Case Study for a Leading Online Consulting Platform

Tue, 20 Aug 2024 15:53:13 +0000

Driving Quality and Reliability for Modern Mobile and Web Applications: A Case Study for a Leading Online Consulting Platform

Developed a modern app with mobile and web support, integrated automated testing using Selenium, pyTest, and aiTest, and validated API quality with Postman for consistent, reliable results.

Company Overview

A leading start-up in the online consulting platform domain, this company focuses on connecting end-users with top industry professionals for expert consultation services. Known for its innovative approach and cutting-edge technology, the company aims to provide seamless and efficient solutions for both consultants and clients, ensuring high-quality interactions and problem-solving experiences. Applied AI Consulting created the modern stack with payment gateway integration for this customer, emphasizing quality engineering to ensure reliability and performance.

Issue

Building a modern application with mobile and web support for their consulting platform.

Ensuring application reliability and quality through comprehensive UI and API testing.

Integrating automation testing into the CI/CD pipeline to streamline releases and improve efficiency.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Agile Collaboration and Automation Framework Development: Collaborated closely with the development team in an agile environment to create test cases and architect a selenium-python-based UI automation framework and a pyTest-based API automation framework.

Advanced Testing with aiTest and CI/CD Integration: Utilized aiTest for executing automated tests across various devices and browsers, integrated with CI/CD pipelines to ensure consistent testing across QA, pre-prod, and prod environments, and validated API quality using Postman.

Real-Time Communication and Iteration Demos: Provided real-time updates on test execution and analytics via Slack and email, and conducted end-of-iteration demos to showcase automation progress and results.

Impact

Email Optimization

Modern App Development with Automation Integration: Successfully built a modern application supporting both mobile and web platforms, integrating an automation suite into the CI/CD pipeline for consistent and reliable testing.

Productivity Boost

Robust Testing Frameworks: Developed a selenium-python-based UI automation framework and a pyTest framework for API automation, ensuring comprehensive and dependable test coverage.

Scalable Infrastructure

Cross-Platform Testing and API Validation: Leveraged aiTest for automated testing across multiple devices and browsers, and integrated Postman for API quality validation and scalable testing.

Customer Testimonials

Applied AI Consulting has been instrumental in transforming our development and deployment processes. Their innovative approach to integrating automation into our CI/CD pipeline has allowed us to scale efficiently while maintaining top-tier application reliability. The cost savings and operational efficiency gains we've experienced have been profound, enabling us to focus more on strategic growth. Their ability to seamlessly blend technical expertise with a deep understanding of our business needs has made them an invaluable partner.
VP of Engineering

Boosting Healthcare Application Quality with Advanced QA Automation by Applied AI Consulting

Tue, 20 Aug 2024 15:40:35 +0000

Boosting Healthcare Application Quality with Advanced QA Automation

Company Overview

A leading health tech platform for the discovery, evidence generation, and clinical delivery for precision medicine. They help doctors and drug hunters make better decisions about providing the right therapy to the right patients at the right time. Over the past 10+ years, Velsera has developed industry-leading clinical software, knowledge, and perspectives on genetic diseases, including oncology, rare, and hereditary diseases. Their customer base includes some of the largest and most prestigious biopharma/biotech companies, government agencies, non-profits, clinical institutions, AMCs, diagnostic lab groups, and partnerships with OEM lab instrument providers and diagnostic assay developers.

Issue

Automation of over 1000 test cases across various sub-products, features, and modules to ensure efficient and consistent testing.

Need for a reliable and maintainable testing framework that could support the complexity and scale of the test cases.

Requirement of seamless integration with CI/CD pipeline, enabling automated testing during nightly builds.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Selected BDD Framework: Utilized Serenity for UI automation and Karate for API automation, leveraging BDD principles to enhance clarity and collaboration.

Successful Implementation: Automated the required test cases within the specified timelines, ensuring alignment with project goals.

CI/CD Integration: Integrated the automated framework with the CI/CD pipeline, enabling faster and more reliable software delivery.

Impact

Reduced Testing Cycle Time

Automation reduced testing cycle time by 50%, accelerating time-to-market for new features.

Improved Application Quality

Early detection of critical issues and increased test coverage led to fewer production issues and higher application quality.

Enhanced Customer Satisfaction

The integration of high-quality automation scripts into the CI/CD pipeline boosted customer satisfaction and retention.

Customer Testimonials

Applied AI Consulting’s expertise in building custom AI solutions with ML and NLP, along with their scalable AWS implementation, significantly enhanced our product’s performance. Their innovative approach and commitment to quality have driven tangible improvements, greatly benefiting our customers.
CTO 7Targets.ai

Capital Market Platform Journey to Enhanced Scalability and Efficiency

Tue, 20 Aug 2024 15:27:41 +0000

Transforming Financial Services with AWS: Capital Market Platform Journey to Enhanced Scalability and Efficiency

Seamlessly Modernizing and Scaling a Capital Market Platform on AWS with Enhanced Monitoring and Collaboration

Company Overview

A leading financial services company focused on global emerging markets, this organization delivers up-to-date market insights from major financial centers to local investors. Known for its intelligence-driven approach, the company provides valuable information to help investors navigate diverse market conditions effectively. The company is committed to leveraging advanced technologies to enhance its services and maintain a competitive edge in the financial sector.

Issue

Migrating and modernizing the content management application to AWS.

Implementing AWS cloud operations and DevOps for continuous integrations and deployments.

Enhancing scalability and reliability of the applications.

Setting up efficient monitoring and operations dashboards.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Containerized and Scalable Deployment: Containerized the EMFI application using AWS ECS Fargate and set up an ALB for traffic distribution and auto-scaling.

Automated CI/CD and Infrastructure Management: Implemented CI/CD pipelines, automated environment deployments with ASG, and managed AWS services using Terraform.

Enhanced Monitoring and Migration: Established a Datadog dashboard for monitoring and facilitated migration from private GitLab to public GitHub.

Impact

Cloud Migration and Modernization

Successfully migrated the content management application to AWS, modernizing its infrastructure.

Scalability and Reliability

Achieved high scalability and reliability through containerization and automated deployments.

Improved Monitoring and Collaboration

Enhanced system visibility with Datadog and streamlined version control by migrating to GitHub.

Customer Testimonials

Applied AI Consulting’s expertise in building custom AI solutions with ML and NLP, along with their scalable AWS implementation, significantly enhanced our product’s performance. Their innovative approach and commitment to quality have driven tangible improvements, greatly benefiting our customers.
CTO 7Targets.ai

Boosting Marketing Campaigns with AI: Enhancing Deployment Pipelines for a Leading AI Powered Recommendation Engine

Tue, 20 Aug 2024 15:23:08 +0000

Boosting Marketing Campaigns with AI: Enhancing Deployment Pipelines for a Leading AI Powered Recommendation Engine

Enhanced release speed, automated processes, scaled performance, and improved issue resolution.

Company Overview

A leading product in AIdriven marketing solutions, this product provides innovative tools to help marketers plan campaign content and generate marketing collateral based on campaign keywords. The company’s product, Marxeed, leverages Generative AI to deliver personalized recommendations and automate content creation, significantly enhancing marketing efficiency and effectiveness.

Issue

Ensuring the deployment of new features without disrupting ongoing operations.

Improving the maturity of deployment pipelines to support frequent and reliable releases.

Maintaining high performance and scalability to handle increasing user demand.

Automating the testing and deployment processes to reduce manual intervention and errors.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Implemented advanced CI/CD pipelinesusing Jenkins and AWS CodePipeline for automated build, test, and deployment processes, with automated testing frameworks like Selenium and JUnit to ensure high-quality releases.

Utilized AWS Elastic Beanstalkfor scalable application deployment and management, complemented by comprehensive monitoring and logging with AWS CloudWatch and the ELK Stack for real-time visibility and issue resolution.

Conducted regular training sessions for development and operations teams to streamline the deployment process and enforce best practices.

Impact

Increased Release Frequency

Boosted feature release rate by 46%, enabling faster delivery of new capabilities.

Enhanced Deployment Efficiency

Achieved 60% reduction in manual errors and deployment times through high automation.

Improved System Performance

Handled 35% more user load seamlessly and reduced issue resolution time by 40% with enhanced monitoring and logging.

Customer Testimonials

Partnering with Applied AI Consulting was a game-changer for us. Their expertise in automating our deployment pipelines and improving scalability has drastically reduced our time-to-market. The seamless integration of advanced CI/CD processes has not only enhanced our operational efficiency but also ensured that our platform can effortlessly handle increased user demand.
Sanju, Product Owner Marxeed

Top Logistics software company accelerates releases by direct feature branch deployment strategy

Wed, 12 Jun 2024 13:19:03 +0000

Streamlining Development with Our New Dev Deployment Strategy

In the fast-paced world of software development, efficient and reliable deployment processes are crucial. A Logistic software company faced challenges with their existing deployment strategy, particularly when it came to testing service dependencies before deploying to QA. To address these issues and enhance their workflow, we devised a new Dev Deployment Strategy that directly deploys feature branches to the Dev environment. Here’s a breakdown of why we made these changes, what they entail, and how they are implemented.

Why a Change Was Needed

Our client’s previous deployment process often led to failures when deploying directly to the QA environment. This was mainly because service dependencies were not thoroughly tested beforehand. The team wanted a way to test their code in a lower environment before merging it to QA, without the added complexity of merging into the dev branch first. The primary goal was to streamline the testing and deployment process, making it faster and more reliable.

What the New Strategy Involves

After extensive discussions, we established a Dev Deployment Strategy that allows feature branches to be deployed directly to the Dev environment. This approach offers several benefits:

Risk Reduction: It minimizes the risk of untested code being merged into the QA environment.
Efficiency: It speeds up the testing process by allowing developers and testers to work on feature branches without needing to merge them into a central dev branch.
Dependency Testing: It facilitates microservice dependency testing on feature branches, ensuring that any issues are caught early.
Simplified Merging: By eliminating the need to merge feature branch code into a specific branch for testing, we save valuable time and reduce complexity.

How We Implemented the New Strategy

To set up the Dev deployment workflow quickly, we leveraged GitHub Action reusable workflows. Here’s a step-by-step look at our implementation:

Java JAR Versioning: We automated the process of changing the Java JAR version from V2 to V1 , ensuring that both JARs remain separate.
Repository Integration: We integrated the new DEV deploy workflow into over 30 repositories.
Daily Refresh: Using cron jobs in GitHub Action, we refresh the Dev environment with the latest changes from QA every morning.

This setup ensures that the Dev environment is consistently up-to-date with the latest stable code from QA, while also allowing feature branches to be tested independently.

The Value of Our New Strategy

Implementing this new Dev Deployment Strategy has brought significant improvements:

Reduced Deployment Failures: By catching issues in the Dev environment before they reach QA, we’ve reduced the risk of deployment failures.
Faster Testing: The streamlined process speeds up testing, allowing developers and testers to work more efficiently.
Enhanced Dependency Testing: Feature branches can now be tested with their dependencies in a realistic environment, improving overall code quality.
Improved Release Process: By reducing the need for frequent merges between the dev and QA branches, we’ve made our release process smoother and more predictable.
Better Time Utilization: Developers can now test their code directly in the Dev environment, optimizing their time and efforts.

In summary, our new Dev Deployment Strategy has revolutionized our client’s development workflow. By directly deploying feature branches to the Dev environment, we’ve created a faster, more reliable, and more efficient process that benefits both their development and testing teams. This strategy not only enhances the ability to catch issues early but also ensures a smoother and more streamlined path from development to production.

How AAIC Enabled a Global Financial Services Company Leverage DevOps to Deliver Financial Market Intelligence in Near-Real Time

Wed, 21 Feb 2024 11:12:36 +0000

Executive Summary

EMFI Group is a global financial services company specializing in delivering intelligence-driven services with a focus on emerging markets. EMFI provides up-to-date market information from major financial centers of the world to local investors.

Challenges

Market information and business intelligence are by their nature ephemeral and require constant updates to be useful.

Although EMFI was already on AWS cloud, the organization was in urgent need of modernization of their Content Management Application, so as to cut the time needed to build & deploy new application infrastructure by more than 99 percent.

EMFI partnered with Applied AI Consulting (AAIC) to leverage AWS Services in deploying, maintaining, and supporting their existing applications and use the Devops building blocks to implement a robust Cloud-based automation framework with a view to enabling DevOps on their platforms.

About AAIC

Applied AI Consulting (AAIC) is a bespoke AI and Cloud Consulting Service. The core team comprises industry veterans with 25+ years of cumulative experience in building, architecting, and delivering cutting-edge technology solutions focused on resolving customer pain points.

Partner Solution

AAIC’s engagement focused on EMFI’s Cloud operations, with a view to enabling DevOps for EMFI workloads and CIs in their AWS cloud.

AAIC engineers team worked with EMFI technical leadership and product owner team to develop modernized business solutions, in the following ways:

Containerizing using AWS ECS Fargate service. Fargate’s serverless nature meant quicker deployment. In addtion to being a serverless compute engine for containers, Fargate works with both Amazon ECS and Amazon EKS.

The use of AWS Fargate means EMFI doesn’t need to provision or manage servers, as AWS Fargate manages server infrastructure. This allows EMFI to double down on innovating and developing its applications. And of course, to pay only for the resources needed to run their containers.

Building CI/CD pipeline for EMFI application using AWS Developer tools such as AWS CodeBuild, AWS CodePipeline, AWS CodeDeploy and Amazon CloudWatch services. Automated building and deployment of application code to the ECS cluster every time code changes meant a signiﬁcant saving in time and effort.
Setting up AWS Automatic Load Balancer (ALB) which distributes the incoming traffic across multiple targets, such as EC2 instances, containers, and IP addresses, which automatically scales workloads.
Setting up Operations/Monitoring dashboard with the help of AWS Cloudwatch. The dashboard includes details about ECS services like CPU/Memory utilization, Disk Space utilization, Network Insights, ECS service task status, and ECS service deployment status. This gave developers an instant and real-time view of their infrastructure, allowing them to spot and stop potential issues before they occurred.
Help in migrating private GitLab to public SaaS GitHub. Git, an open-source version-control system saves snapshots of a software project, allowing users to maintain a record of all changes. Unlike conventional version control, Git allows users to work on different versions, manage the simultaneously and test them by merging the ideal variant seamlessly. This freedom to work on multiple versions simultaneously is an invaluable asset for DevOps teams. Using GitHub allows EMFI to leverage the large and growing GitHub community and its contributions by way of functionality that might otherwise be missing.
Automation of the application scaling, with the implementation of Cloudwatch alarms and app auto-scaling policies. These policies involve target tracking policies and scheduled-based policies that will increase or decrease task count in ECS service based on the specified criteria or schedule to handle the workload.
Creating application infrastructure with AWS services using Terraform. (Terraform’s familiarity with EMFI developers, made it the IaC tool of choice) This includes building a scalable and secure network layer (using AWS VPC, AWS WAF, NACL, VPC Endpoints, etc.), database layer (using AWS RDS) and application layer with logging and monitoring enabled (using AWS ECS, AWS Cloudwatch, etc.)

Architecture

Architecture defines a high-level model of solution and describes how the resources are interlinked with each other. Within AWS the architecture utilized load balancers to distribute incoming traffic across ECS Fargate containers which provided stability across the application

Deployed AWS Services

AWS ServiceUsage of service ECSAmazon Elastic Container Service (Amazon ECS) is a highly scalable, fastcontainer management service that makes it easy to run, stop, and manage containers on a cluster.ECS ClusterAn Amazon ECS cluster is a regional grouping of one or more container instances on which you can run task requests.ECS Task DefinitionTask definition is basically the blueprint describing the docker containers that are used to run the application.ECS ServiceService defines the minimum and the maximum tasks that are running from a single task definition at any given point.EC2 InstanceEC2 stands for Elastic Compute Cloud. It is nothing but a basic computer virtually present in AWS cloud which you can access and do whatever you can do on a basic computer.VPCA virtual private cloud (VPC) is a secure, isolated private cloud hosted within a public cloud.ALBThe Application Load Balancer is a feature of Elastic Load Balancing that allows a developer to configure and route incoming end-user traffic to applications based in the AWS public cloud.IAMAWS Identity and Access Management (IAM) enables you to manage access to AWS services and resources securely.RDSAmazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.

Results and Benefits

Being on AWS opens up an array of new services and technologies that are now significantly more accessible to the average IT group
AWS opens up new possibilities to integrate, including best of breed tools & services to connect to other systems
Use of Terraform provides create, change, and version infrastructure safely and efficiently.
Elasticity, load balancing and the capability to scale automatically is a big bonus which added robustness in the system and increased capability to handle the 3x load.

About the Partner

AAIC is a digital technology services company providing Digital Engineering, Cloud Engineering services, and AI-powered Digital Marketing services. We design & build digital platforms and products with Cloud and Opensource at the focal point by working on cutting-edge technologies.

Site: 91SpringBoard, Sky Loft, Creativity Mall,

Opposite Golf Course, Yerawada, Pune, India 411006

www.appliedaiconsulting.com

Meeting 7Targets’ Automation Targets

Tue, 30 Jan 2024 09:36:00 +0000

7Targets

7Targets is a SaaS B2B company in the Sales and Marketing domain focused on lead nurturing. The company’s flagship product ‘AI Sales Assistant’ provides users with the capability to automate emails creation and conduct follow-ups of received leads. It is also able to read received responses and act accordingly.*

Customer challenge

Despite offering an AI driven solution (for lead development) and SaaS product, 7Targets team was performing manual deployments in their environments. This made the development process highly susceptible to human errors, reduced efficiency, and affected the code quality.

7Targets team was looking was faster, efficient upgrade and rollback process in the application deployments.

Specific project-level challenges were:

Increased development and deployment time with increased backlog.
Increased release cycles for production upgrades
Process did not allow optimal utilization of resources

Solution

To address the specific challenges faced by the client, Applied AI Consulting designed the following solution:

Implemented GitLab for versioning control. Git is a popular open source code repository as well as a software development platform for collaborative working on DevOps projects. Not only is the platform free (although there is a paid version, too.), unlike GitHub, it offers CI/CD capabilities, and a location for online code storage and issue tracking.
GitLab repository allows hosting of different versions, enabling users to inspect code and roll back to a desired version in the event of any problems. GitLab supports each stage of the software development lifecycle, enabling DevOps capabilities. It comes with a continuous integration (CI) Capabilities built in, which allows development teams to automate code building and testing. GitLab also provides security features, presenting developers with scans—within their native CI pipeline—and dashboard assists showing vulnerabilities. (CI/CD stands for Continuous Integration-Continuous Delivery/Deployment. It is a set of practices that allows developers to introduce automation into software development stages—building, testing, deployment, etc.—so they can make changes to the code and deploy them in production without waiting for a release window).
GitLab flow model was implemented for branching strategy.
GitLab is built on the same basis as GitHub, and offers similar functionality for source code management but has the advantage of being free for individuals and small businesses, compared to GitHub which charges for private repositories. For these reasons, and because the client was familiar with GitLab, AAIC chose to implement GitLab as the version control system. Gitlab CIs were set up to be triggered whenever any commit was made to the corresponding branch of each repository. Viz. As soon as the code was merged into develop and main branch, Gitlab CI would get triggered and pull the code from repository and trigger the build the code.
Based on the repository storage type, GitLab CI generates Zip files and container images with the libraries and tools needed to upload those to the selected AWS S3 bucket and AWS Elastic Container Registry (ECR) respectively for respective development and production environment.
Upon successful build, Another Gitlab CI job will be triggered and it will deploy the artifacts (Containers and Lambda Zip files ) to the Lambda and ECS environments.
At the end, series of automated tests are executed to verify deployments and, in the event of any glitches, Gitlab CI rollbacks implemented to deploy the previously stable running version of the application.

Tech Stack

Several AWS services used as part of the solution, including

AWS S3, AWS ECR, AWS Lambda, AWS ECS Fargate,

Go Live Date: December 2023

Outcome(s)/results

With fully automated CI/CD solution, any possibility of human prone errors was eliminated, which speeded up the entire development cycle
With automation in the development cycle, the time to market of this SaaS application was reduced to 80% with three to five upgrades on daily basis
As the development lifecycle was automated, developers can now spend more time in development rather than in operations.

Architecture diagrams of the speciﬁc customer deployment

About AAIC

We are automation experts, with a majority (>60%) of our workforce AWS-certified. We assist you in applying intelligence to the Cloud and DevOps, as our name suggests. Our AWS certified experts create high-performing cloud apps by utilizing intelligence components and smart integrations to accelerate your digital transformation journey.

What is DevOps

Wed, 21 Dec 2022 10:31:53 +0000

Not everyone has the same idea about DevOps. For some it is a culture, others describe it as processes or practices, for others is a set of tools. Part of the problem is that the term itself is so broad and includes so many factors that it is not easy to clearly define it or set its boundaries.

The simplest—and probably the most popular—definition describes DevOps as the intersection of Development and Operations. The problem arises when we try to set the boundaries of where Development ends and Operations takes over and vice versa.

The Need for DevOps

To begin with, why do we even need something like DevOps? To understand this, we need to look at the release process.

When you develop an application, the end goal is always the same—no matter whether the team follows a waterfall strategy or agile or any other—and that is to deliver the application to the user.

Say, you have an idea for an application. You will bring it to life by first defining its functionality and setting out its features, then you will code the application, following which, you will test it, and finally host it on a server—probably a public server along with all the security it needs, viz. firewalls, access rules, etc. This is a stripped-down description of the steps any application deployment needs. But the story doesn’t end here.

You still need to monitor your application and check whether it is running as desired: are there any bugs, can the architecture handle high traffic loads, are users facing any problems? If any issues crop up, you, of course, need to fix them. Even if everything is fine, you may want to add new features, and further improve performance: maybe by provisioning better servers or making the application faster. But this isn’t the end… there’s still lots to do. And every time you make any changes to the application, be it the code or underlying infrastructure, you need to redeploy it to make it accessible to end users. Now there will be multiple iterations post the initial launch and you need to keep track of the updates, so you also need to establish a versioning system and keep track of them. The cycle of launch-update-relaunch is an endless cycle and DevOps helps streamline this by establishing a continuous delivery process. DevOps, in short, enables you to make endless improvements to your application, test the changes and deliver the updated application to your end users without interruption.

Challenges

There are several bottlenecks and roadblocks that slow down the deployment process and they can be listed as under:

Lack of collaboration

Lack of collaboration between developers and Operations is the biggest challenge. These are actually separate aspects of the process. Developers are only concerned with creating (coding) the application and Operations personnel are responsible for running the application. Operations are running the application but often aren’t aware of how it works, so any attempt to tinker with the code is a recipe for disaster. Typically, developers will complete the coding but the documentation may be incomplete or just not good enough for the Operations team to deploy. If there are many usage issues, Operations simply throws it back to the Development team with improvement recommendations. All this means release takes longer; sometimes days and weeks and maybe even months.

Checklists as bottlenecks

Sometimes handover from developer to Operations is governed by bureaucratic checklists that set out what needs to be completed, who needs to approve what, and so on. The problem with this is that it results in further delays as a lot of these tasks must be completed manually, checked, and verified before handing over.

Differentiated goals

Developers are primarily focused on pushing out new features fast. This is their objective, whereas Operations want to ensure the application runs in a stable fashion. To ensure this, the Operations team, traditionally, tends to delay the release until all the i’s have been dotted and the t’s crossed. Since Operations usually isn’t familiar with code the process is a slow one. For instance, let’s say a new set of features has been developed but these features end up consuming so many resources in production that servers get overwhelmed and the application crashes. Now Operations needs to get it up and running again. Since fire-fighting is Operations’ responsibility, Developers are not are quality conscious as they should be, focusing more on the speed of churn than stability Even though it is the common goal of everyone in the organization to deliver high-quality applications to the end-users, quickly, in practice, there is conflict as both teams focus on their immediate goals.

Security challenges

Just as the Operations team evaluates the changes to make sure it won’t break anything in a production environment, so too must the Security team evaluate changes to ensure they don’t impact security systems. The only problem with this is when done in a traditional setup, this process is another bottleneck as it involves the same kind of bureaucratic process as we saw in the Operations check. So it will take another couple of days or weeks, further slowing down the deployment process. When DevOps incorporates automation of security checks, it is known as DevSecOps.

Manual processes

In a traditional setup, many of the tasks that are part of the deployment process are done manually and this slows down things considerably. For instance, Operations tasks are done manually by directly executing commands on the servers, patching, writing and running small scripts/programs, manually creating deployment environment and infrastructure, configuring access to servers, manually configuring Jenkins, and so on. All this manual effort is not just time-consuming, it is also prone to errors, and it is very hard to trace who executed what and when. So if something were to happen to the infrastructure, it would be very difficult to replicate the exact state quickly.

DevOps aims to resolve all these and focus on creating a fully automated streamlined process. We do this by removing the bottlenecks, one at a time, until we have a fully-optimized process that makes application releases easy and so fast, you can have multiple releases a day, instead of days or weeks, or months, like previously.

Defining DevOps

Per the official definition, DevOps is a combination of

cultural philosophies
Practices
Tools

All of which aim to make the release process error-free and speedy.

The traditional definition of DevOps slowly evolved as the actual implementation of DevOps by individual companies was not uniform, but it eventually developed concrete patterns, and one of the changes that came from this was the creation of a specific role: the DevOps Engineer. The DevOps engineer could be either a developer doing DevOps or an Operations engineer only doing DevOps or a separate role. But the sole job responsibility would be to focus only on creating a streamlined process for release. And this process centers around the familiar process known as CI/CD, or continuous integration, continuous delivery/deployment.

What every DevOps Engineer Should Know

While DevOps engineers may not be working on the actual programming of the application, they need to understand versioning and how developers work, and how to prepare an application for release, this includes:

Understanding how Git works, which Git workflow the development teams are using, how the application is configured, tested, etc.
How the application is configured to interact with other services/databases

automated workflows

Development of underlying Infrastructure, i.e. creation and configuration of servers, be it on-prem or in the cloud. This means proficiency with Linux servers, as these are the most commonly used ones.
How to set up, and administer a Linux server, Linux commands, and Linux file system so the developer can use the Command Line Interface
Basics of networking and security…configuring firewalls, how IPs address ports, opening some ports so the application can be accessed from outside; DNS and how it works

A DevOps engineer needn’t have advanced operating system skills or networking and security skills, or even how to administer servers from end-to-end. There are already specialists for these tasks. The DevOps engineer’s job is to understand all of the above only to the extent needed to prepare the server to run the application, rather than take over management of the servers and infrastructure.

Containers: As containers have become the de facto infrastructure nowadays, the DevOps engineer needs to understand how to manage containerized applications. This means acquiring proficiency in popular container tools, like Docker. This means how to build docker images from your application, and save these in a Docker image repository, like Nexus or Docker hub.
CI/CD pipelines and associated software

DevOps job is basically to release new application versions, fixes, etc, in a continuous and efficient, and automated way. To do this the DevOps engineer needs to know how to run tests, package the application as a jar or zip file, and deploy it. So they need to know software like Maven, Gradle (for Java), and NPM (for Javascript apps).

Now, this doesn’t have to be done manually, instead, the DevOps engineer needs to build an automated pipeline so all of the above is done in a sequential manner. This means knowledge of Jenkins, which is the most popular build automation tool. Next is connecting the pipeline to the git repository to get the code. This is the key part of the Continuous Integration process. Next is continuous testing and bug fixes if needed before deploying the new feature or bug fix. And this is Continuous Deployment. Along the way, it should also send notifications to the respective teams about pipeline state and failed deployments.

Continuous Integration/Continuous Deployment pipeline

In a Nutshell

Basically, DevOps connects Development and Operations teams. While there is no need to be a master in either of these areas, some basic knowledge of both is needed. Above all, DevOps engineers need to know all the tools and practices needed to build automated pipelines that can get the code for the new releases, test it, fix it—if there are bugs—and deploy it. This is a continuous process which is why the symbol for DevOps has become the infinity symbol, showing movement from Development to Operations in a continuous cycle.

A DevOps exercise to cut short deployment time while ramping up security and savings for a leading tech hiring platform

Wed, 21 Sep 2022 11:09:16 +0000

The Client

Cutshort is a tech hiring platform in India. The platform connects employers with top management systems, engages with them, identifies the best candidates, and closes positions in a way that enables hirers to execute their vision quickly.

Cutshort is more than just a networking platform; it uses AI algorithms and gamification to source and connect talent to opportunity. Its high rate of success rate has quickly made it the leading tech hiring platform in the subcontinent.

The Challenge

AI processes were helping hiring automation and recruitment efficiency, but the competition to attract high-quality candidates is fierce, and Cutshort needed its systems to be revamped on a continuous basis to allow fresh updates to the system (for instance, chatbots to collect information beyond resumes, automated scheduling of interviews, etc.). This called for a certain degree of DevOps muscularity.

Migrating the entire solution infrastructure to AWS would take care of availability and scalability in terms of workload, traffic, and peak hours. But it also needed to be cost-effective, and secure. This would be enabled through implementation of AWS security measures on all Cutshort’s AWS accounts with the ability to receive notifications for all alerts.

Cutshort engaged Applied AI Consulting (AAIC) to resolve their challenges and execute the entire project.

Solution

It was clear from the outset that DevOps adoption was the answer to Cutshort’s specific issues. Automation, coupled with quick development and equally speedy deployment would allow them to increase their productivity, optimize processes and enjoy a stronger collaborative work environment.

AWS Partner AAIC kicked off the project by interacting with the client’s engineering, product management, and IT team to fully understand the application’s functional and business requirements from the perspective of the end-user and took the below key steps to provide the following solution:

AAIC redesigned the organization’s IT architecture to include use of ECS Fargate with Autoscaling & SPOT instead of ECS NodeGroups. This will help Cutshort save on costs as well as enable it to scale automatically
Cutshort wasn’t using any Infrastructure-as-a-Code (IaaC) tool; we brought in Terraform, so they could spin up new solution infrastructure in a few minutes and deploy it seamlessly using a CI pipeline.
With the help of Terraform, AAIC created a new infrastructure using Amazon Elastic Container Service for Cutshort which was secured with the help of AWS services and resources such as AWS WAF, NACL’s, and internal load balancers. We also implemented alerts and notiﬁcations using Amazon Cloudwatch and Amazon Simple Notification Service (SNS).
AAIC optimized Cutshort’s AWS accounts by getting them on AWS’s savings plan. This will create significant cost benefits for the organization.
Another step towards helping them in managing their accounts was to set up consolidated billing. Getting one bill for multiple accounts means easier tracking of charges, and scrutiny of cost and usage data. Plus the ability to combine usage across all accounts, allows the organization to benefit from such features as volume pricing discounts, savings plans, and discounts on reserved instances. Since there is no fee for consolidated billing, it was another saving.
Cutshort was using G-suite for various reasons, including email, calendar, docs, etc. We made it easier for them to manage access and user permissions, by integrating it with IAM Identity Center, giving Cutshort’s administrators single sign-on centralized access to all their AWS accounts.

Tech Stack

Outcomes

25% – 30% Cost Savings-

With new infrastructure, and the introduction of features like AWS Savings plan and Consolidated Billing, and their application across their AWS accounts, Cutshort has been able to save 25-30% of their cost compared to earlier budgets.

Speedy Deployment-

Implementation of CodeDeploy and GitHub Actions (A CI/CD tool) has made deployment significantly speedier. Cutshort is now able to move changes to production easily and faster than ever. Earlier production changes happened, at best, once in two weeks but now they are happening in barely two days.

About AAIC

AAIC has a certified cloud engineering team that provides the needed expertise and service to move your on-premises data center to AWS Cloud. It takes the code from existing version control to the open-source library GitHub, debugs, and makes it operational on AWS. During the entire 5 step process, AAIC solution architects and our cloud engineering team work closely with your team to deliver a secure, scalable, and high-performing solution, post-migration.

Want to Implement a Secure and Scalable Infrastructure on AWS?

Mon, 20 Jun 2022 06:19:41 +0000

As per statistics, Scalability and Security are two major concerns of any growing company. In this blog, we will focus on the Scalability challenges and a proven strategy to deploy your solution infrastructure on AWS with all the security measures supported by AWS.

Scalability issues arise when an application receives more users than expected. At that point, the tech team begins to look for someone who can magically add more nodes to the system and scale the application.

However, this is not the right way to approach scalability. Decisions for scalability should be made early in the development process. Even before you’ve decided on frontend and backend technology.

Well, As a result of scalability issues, a tech hiring platform came to us with the idea of deploying their infrastructure on AWS. They wanted their solution to be highly available and scalable based on the workload, traffic, and peak hours.

Tired of manual Testing? Try AITest!

Benefits of Deploying Your Solution Infrastructure on AWS

Over 7,500 government agencies and 5,000 educational institutions use AWS, isn’t it worth considering? Check out the incredible benefits AWS brings to your organization:

How to Implement a Secure and Scalable Infrastructure on AWS

Consider the following steps to implement a secure and scalable infrastructure on AWS:

Create an architecture using tools like ECS Fargate with Autoscaling & SPOT instead of ECS NodeGroups to save the cost as well as to scale automatically.
Introduce Infrastructure-as-Code (IaC) tool like terraform to spin up a new solution infrastructure in a few minutes.
Consider the AWS savings plan and how it can benefit the overall cost.
If required, set up the AWS organization for consolidated billing.
Integrate the G-Suite with AWS Single-Sign-On to manage access centrally across their AWS Organization
Create a new infrastructure that was secured with the help of AWS services and resources such as AWS WAF, NACLs, and internal load balancers.

Bonus Tip: Implement alerts and notifications with the help of AWS Cloudwatch and SNS.

Would you like to get into the architecture diagram? See here

Scalability is a mysterious and powerful magic everybody wants for their business. And AAIC has the AWS magicians in its team who help you scale on-demand Using AWS tools, Auto Scaling, and Elastic Load Balancing.

Besides AWS expertise, we help companies master performance and collaboration through our DevOps services.

Want to know more? Book a free 30 minutes consultation call

Are You Affected by Employee Swipe-in/swipe-out Latency Issues?

Mon, 20 Jun 2022 05:59:07 +0000

If you are in a position of leadership in a business where employees’ time on the floor (ToF) and time on campus (Tic) values are important in measuring business revenue. And you’re experiencing latency issues as you process data from various controllers.

Then this particular blog is for You!

We had a client who was operating in an IT service industry with over 2 lakh employees and clients on six continents.

They were facing a one-day latency in processing 1.8 lakh+ employees’ swipe-in and swipe-out data from various controllers. That’s why they approached the AAIC team and we have helped them have a robust solution.

Interested to know more? Stay tuned!

Want to Scale Your business? Hire experts

The Challenges Faced Because of the Swipe-in/Swipe-out Latency Issues

You may be familiar with the tedious process of extracting data from various controllers. Not just that, there are other direct and indirect challenges you may have faced because of the Swipe-in/Swipe-out latency issues.

Direct

Indirect

Leadership lacks good insights into all the data that was being collected through the sensors.

Unable to leverage the data to help with the betterment of the staff and provide a proactive level of security to female employees.

Solution Steps Taken To Record Real-Time Data

We helped the client process all swipe-in and swipe-out records in real-time using the AWS services. The code for the solution is designed keeping in mind the best practices of product development, so that it is easily packaged and distributed to its customers, thereby increasing their business while using the same solution internally.

The solution was built to provide the following

Near real-time door swipe in/out data to be available to any employee on customer internal portals and mobile devices for Employee Time on Floor (ToF) and Employee Time in Campus (TIC).
Maximum delay of 3-4 minutes from swipe to generate ToF and TIC reports.
Report displaying within 200 Milliseconds of request.
Processing of 1.5 million swipes a day across 8000 controllers located across India.
Allowing Employees to manually override/edit Time in Campus timings.
Allowed employees to edit the last 14 days’ TIC.
Visibility of 3 months of data (not real-time but on-demand).
Instant notifications to managers and HR updating if,
A female employee is working alone on the floor
A female employee is working alone but will be joined by ‘N’ employee(s)
A female employee is leaving late or the Swipe IN/OUT card reader is not working.
AWS QuickSight dashboards that provide the following intelligence:
Female employee shift trend analytics
Employees having low/high floor time
Number of times employees go out of the floor on an average
Average time spent by the employee out of the floor Number of employees expected on campus over holiday/weekends

Connect with Top AWS Professionals

Swipe-in/swipe-out Latency Issues Solution Highlights

A highly scalable and flexible solution using AWS Managed Services that provides faster ingestion and processing times of large volumes of data along with easy and secure integration capabilities with existing customer applications.
REAN Cloud design not just solved the immediate real-time availability of Tof and TiC but also included Machine Learning capabilities into the solution to provide additional reports such – as alone women on the floor, holiday schedules, etc.
The system was improved to provide the employees with an option to quickly make edits to their erroneous attendance records due to tail-gating or malfunctioned sensors.
Optimizations in infrastructure costs were observed as the solution leveraged the use of serverless microservices technology along with AWS Managed Services for all components which are billed in a pay-as-you-go model.

You might agree that we at AAIC not just solved the problem but also optimized the infrastructure cost using the serverless microservices technology. Our AWS experts know managed services well and how they are going to impact your processes.

Do you have any queries? Talk to our experts!

Transformed AI-based Assistant with AWS Lambda & sentiment analysis

Tue, 07 Jun 2022 06:30:05 +0000

One of our customers called 7Targets offers AI Sales Assistant with lead nurturing and email writing capabilities. These sales assistants read the received responses and follow up accordingly within minutes.

Being an email-based AI Assistant, 7Targets wanted to make sure that a scalable and working solution is created to send and receive the emails. The received email is read, categorized, understood and entities extracted from. So that further action can be taken by the assistant.

But 7Targets wanted to scale the AI Assistants with the following abilities:

To send email evenly distributed over time to avoid sudden spike.
To read the email received and decide the next action to be taken by the ‘AI Sales Assistant’ after proper categorization of the received email.
To extract entities like date, phone number, title, etc from the email received.
To Set up a pipeline for continuous deployment with proper testing in the pipeline.

This is how we offered the following solutions to enhance the abilities of the AI Assistants:

Created the step functions (state machines process-lead, process-lead-response, etc.) with various lambda functions for each step.
Where the received email is accepted in the s3 bucket using SES.
Process the received response and categorize based on sentiment and certain properties available in the response like date, etc.
Handle any bounce and complaint email responses.

This has helped 7Targets to solve the problem of sending the email and then the follow-up email. The right categorization of the received email, based on which lead state was updated and the action ahead was decided by a state machine.

Along with categorization from the email text, there was also a need for entity detection like date, phone number, etc. which was done as part of this implementation. For example, if an email was received and categorized to be ‘Out of Office’ then the return date was identified from the email so that the assistant can follow up after the leads return to the office instead of following up in the Out of office period.

We used the following third-party applications:

Debounce and Zerobounce APIs are used to validate the emails of each lead. This is the first step in the process-lead step function
3rd party CRM like Hubspot, ZohoCRM is used and the 7Targets AI Assistant solution interacts with that solution

With our solutions, 7Targets achieved the following results:

Able to grow per day email sending from 1K to like 10K and per day and can still grow more with the present solution.
Able to process the response at a similar level but the responses are not as high as email sending.
Will proper limits and thresholds be set and with continuous monitoring of failure for lambda and step functions the limits and thresholds are changed.
The container in Fargate is auto-configured to scale up and down.
The Continuous deployment pipelines are helping with automated zero-downtime deployments to QA and then production setup

Empower your chatbot with us

At AAIC, we are instrumental in offering AI-powered automation inclined with AWS cloud services. Our AWS certified team closely sits with you to understand all your requirements to offer you the best solutions. We make your solutions scalable and affordable. And also with us, you can significantly reduce your software development time.

We used the following technologies to help 7Targets:

AWS Stepfunctions, AWS Lambda, AWS RDS, AWS Comprehend, AWS S3, AWS SES, AWS ECR, AWS Fargate, AWS SNS, AWS SQS, AWS API Gateway, AWS Cloudwatch, AWS ELB, AWS Cognito, AWS WAF, AWS CloudFormation, AWS DMS, AWS Route53

Need AWS consultation? Book a free consultation call.

Release 46% More Features with Mature Deployment Pipeline.

Wed, 01 Jun 2022 06:55:43 +0000

Product managers are always looking for ways to improve their products, optimize the user experience, make the product more valuable, and therefore increase user engagement.

But, how often do they get success?

Well, it depends on the speed of feature releases.

Let’s say, you build an app and release the beta version for public testing and feedback.

And Feedback came.

Your users showed that specific features needed to be added, modified, etc.

Now, what will happen if you lag or delay the release of the required features?

Well, your users will switch to your competitor who not just listens to the feedback but also releases the required features at a faster pace.

Don’t worry! Here we will demonstrate how you can release 46% more features with a mature deployment pipeline and beat the competition.

Tired of manual testing costs? Talk to our experts

Why You Fail To Release Features When Required

Let’s understand this with a real example. One of our clients had three environments to manage: development, quality assurance, and production.

Every day they were making small changes and moving them to the testing environment. It was then moved to production if everything went well.

And because there was no automation in place, they were facing the following challenges.

So you got it! Right?

Now, let’s move toward the solution.

Steps To Release 46% more Features with a Mature Deployment Pipeline

Follow the steps below to do the frequent releases without deployment error.

Add pipelines for automated releases.
Include multiple stages in pipelines like quality checks, automated tests, vulnerability checks, etc.
Add parallel and automated deployment.

Continuing the above example of a client experiencing deployment challenges, here is a closer look at the steps we took:

Assisted in performing automated releases with pipelines that included quality tests, dependency, vulnerability, static code analysis, and deploy production stages.
Provided a PR pipeline and environment-specific deployment pipeline for 10+ microservices.

We designed it in such a way that all of their code even though It is in a single repository for

different services the right service is deployed as per the code change. Along with

deployment to the white-listed setups.

This type of individual service build and deployment was possible with the right design and

configuration of various dependencies each service has on different code components in the repository.

Need DevOps Engineers? Hire experts

Technologies we Used in the Mature Deployment Pipeline

Connect with Top AWS Professionals

DevOps Pipeline For Faster Releases

To help you better understand the process steps, here goes a graphical look at the DevOps pipeline for faster releases.

The competitive market demands faster releases not only for startups but also for established players. As you could see, how we helped the leading sales company in making faster releases without error. That ultimately helped them build the authority in the market.

Would you like to be the leader in your industry? Connect with us today!

Enhance your day-to-day operations through Amazon workspaces and IaC

Tue, 31 May 2022 07:37:23 +0000

How many businesses go down for a non-scalable environment and increasing costs?

Automating manual infrastructure is one of the biggest challenges businesses face today.

With the rise of ‘Infrastructure as Code (IaC)’, there is a huge rush to automate the infrastructure and run as IaaC.

Manual infrastructure deployment results in errors and it is time-consuming.

We interact with many CEOs regularly and they have mentioned some of the issues they are:

Lack of expertise in using AWS services resulted in doubtful decisions.
Non-scalable environment
Manual deployment of AWS infrastructure and application deployment for each new environment was time taking and error-prone.
Some packages fail to install on EC2 servers for unknown reasons.
Lack of a sound development environment.

Automating the AWS deployment architecture using Terraform code can scale the infrastructure.

Want to automate? Let’s talk.

And the benefits of deploying Infrastructure as Code (IaC) are:

Decreased risks

When you provision all your infrastructure manually with one person and when this person leaves your company, there is a chance that this person may take all knowledge to another company.

When you implement IaC, it minimizes all such risks. IaC empowers you with infrastructure as a reproducible block of code with less error.

Such infrastructure resides in a source code repository. Any change and history are visible to all.

Stable environments for faster iterations

Usually, manually configured environments slow down your product development. This happens when you want to change the architecture of the product to enhance customer satisfaction.

When you have IaaC, your environment is stable, easy to modify, and consistent. Your infrastructure lives as code along with your product. Such harmony helps you to develop new features for the product faster.

Wish to have a stable environment? We have solutions for you.

Cost optimization

When your entire infrastructure is visible you can see what is running and what is not. You can easily optimize your costs to maintain profit margins. Such optimization is so easy with IaaC.

Self-documenting

Infrastructure as Code is self-documenting in the sense that when a new developer joins your organization, he/she can understand the logic just by reading it. With this, you can easily add more people to your team. It significantly reduces your onboarding time to your project.

In addition to IaaC, the following solutions can be beneficial too:

Installing and configuring the servers using Ansible.

Providing configured Amazon workspaces for their day-to-day operations.
Guidance to use Global Accelerator.
Use Gitlab for Issue tracking, Continuous integration, and Continuous deployment pipeline features.

Bring organization-wide automation with us.

Why choose us?

At AAIC, we help you build better products faster. As a Cloud System Integrator (CSI) and DevOps Service Provider, we enable enterprises to transform securely by accelerating the migration of their application and big-data workloads to the cloud with improved governance.

Offer fully automated Terraform code for development and production environment within a month.
CI/CD pipeline for automated deployment.
Create Ansible automation for EC2 configuration within 5 days.
Enhance your day-to-day operations through Amazon workspaces
Solve any support tasks within 24 hrs.

We also help you master performance and collaboration within your team through our specially designed DevOps Services which

Helps you decide on the CI/CD platform based on your application suitability
Quickly select the best suitable pipeline for your application
Contain easy-to-use and standard templates that can be modified to suit your unique application.
Incorporates templates based on recommended architecture.
Provides templates that have been used in production for multiple customers with varying degrees of application complexity

One of our customers specializes in messaging and mobility solutions. Their mobile solutions give customers an undisputed improvement in Visibility, Velocity, and Reach while upgrading levels of Standardization and Decentralization.

Read this case study to understand how we have automated their infrastructure with IaaC.

If you have any query, talk to our expert.

How To Achieve Faster Releases and Scalability through DevOps Pipeline

Fri, 27 May 2022 09:17:18 +0000

Today, every VP of engineering looks for ways to make continuous & faster releases to production!

Why not? It makes a huge difference to one’s rate of success.

What if I tell you that selecting the right partner can make it easy for you.

Being the right partner, we help businesses like yours make faster releases of new or revised software features every single time.

How?

Through our specially designed DevOps pipeline and Infrastructure as a code.

Tired of manual testing costs? Talk to our experts

Although, We have already helped many companies in our journey so far.

Today we are going to share a story of a USA-based fintech startup, its challenges, and the solution steps we took. Proceeding ahead you will also see the architecture diagram along with the technologies we used.

So, stay tuned!

Key Challenges a Fintech Startup Faces

With the rise in fintech startups, funding, and the urgency to deliver fast, 2 key challenges are always there:

Solution-Steps for Slower Releases and Scalability Challenge

While having any solution it’s important to have a one-to-one discussion with the engineering and product development team. Understand all the upfront challenges and then make a sketch plan of solutions.

Keeping in mind the above 2 key challenges, our solution majorly includes these key steps:

A Pipeline design for their frontend and backend while integrating Github so that they can keep track of all the changes that have been pushed to the repository.
Creation of Infrastructure as a code to help startups automate infrastructure provisioning allowing them to develop, deploy and scale with less risk and low cost.

Now let’s have a look at how our CI/CD and backend pipeline helps the fintech startup to have a scalable solution:

Technology we Used To Make Faster Releases For Fintech Startup

Need AWS Professionals? Hire experts

Now, wrapping up let’s look at the key aspects we focused on while delivering a scalable solution to a Fintech Startup:

Apart from the fintech-specific solution, we help companies master performance and collaboration within their team through our specially designed DevOps services.

Want to know more? Book a free 30 minutes consultation call

Proven tips to bridge both digital and cash payment platforms with a hybrid app

Fri, 27 May 2022 08:05:25 +0000

How many times do you receive candies instead of changes in any retail shop?

If you don’t have a sweet tooth, it is irritating! Isn’t it?

Well, it is difficult to manage leftover coins and bills in a physical payment environment.

Like this only, one of our customers was finding it difficult to manage leftover coins and bills. With this, customer satisfaction was declining. Hence, the client was looking for a digital payment solution that can make the best use of the leftover coins.

Building a scalable and secured payment app isn’t easy! Here are some tips that might come in handy for you.

Need more help? Book a free consultation call

Develop the Backend APIs

First, you can build the backend APIs for all the back-end services from the server side. You can use NodeJS for writing the APIs and to serve the demands of the app, admin portal, and POS system.

Develop the Frontend Application Framework

You have to develop the mobile app for Android and iOS. And for this, you can use Flutter to develop a cross-platform mobile app faster. Flutter empowers you to develop apps for Android and iOS using the same code. It can save you precious time!

Integrate your app with the POS App

It’s time to integrate the application with the POS app in native Android technology to avoid any unknown system-specific issues.

Hire the best AWS team

Integrate a payment gateway

Now you can integrate a payment gateway with the app to store and manage the user’s bank accounts with security. It can help you to get away with compliance-related issues.

Integrate an SMS gateway

Your team can integrate an SMS gateway service now. With this, the end-users can get OTP SMS. This comes with scalability. Depending on the increasing user base, you can accommodate more numbers by scaling the OTP service. In addition, you can also integrate a cloud messaging service for push notifications.

Deploy AWS ECS

You must use Amazon Elastic Container Service (AWS ECS) to build the server of the app. The auto-scaling and CI/CD allow you to grow as per demands and release apps faster than before. It allows you to rent VMs as per the need of your app and traffic.

Download the full case study

Build a hybrid payment app from scratch with us

We at AAIC are instrumental in building payment apps with optimum security. Our team of certified AWS architects and engineers can digitize your whole infrastructure to accelerate your revenue and customer satisfaction. Everything we do right from planning to execution, we follow all AWS technologies along with a hyper-automation approach to incline the right cloud strategy.

If you have any more questions, talk to our experts.

Top 6 secrets to build a DevOps culture

Wed, 18 May 2022 10:40:55 +0000

I talk to many CEOs regularly. They are struggling with a long go to market duration, frequent feature releases, fixing issues in the production faster, and scaling the products.

In this blog, I am discussing how adopting DevOps can help you overcome these issues.

I am also highlighting how to nurture your organizations to adopt a DevOps culture.

INSPIRE THE CONTINUOUS IMPROVEMENT

To nurture a DevOps culture, as a leader you must inspire your team to use continuous improvement.

DevOps brings end-to-end responsibility, which brings constant changes to any organization.

Businesses must practice adaptability to the changes whether it is new customer needs, new technologies, or legislation changes.

The culture of adopting continuous improvement helps your team to get used to the CI/CD pipeline, which is an integral part of DevOps.

Want to know more? Talk to us.

FOCUS ON CUSTOMER NEEDS

When you start focussing on fulfilling customer needs, it’s become easy to nurture a DevOps culture in your organization.

With DevOps, you get data. The automated processes always create data and you should constantly review all the data to ensure that performance targets are met.

But you should focus on the right data, such as the duration between the initial code commit and changes in the production.

Also, you must check the error rate while you deploy new software in the production environment and the meantime recover during any service interruption.

However, always focus on the matrices that matter to your customers.

END-TO-END ACCOUNTABILITY

When you look at the conventional software development model, you can see that the developers and operations play separate roles.

But DevOps makes both these groups work together as a team, which is fully responsible for the end-to-end deployment of the apps.

The core pillar of DevOps is to control and take responsibility for services from “concept to grave.”

I think the gap between developers writing code and the operation team deploying the same is full of inefficiencies. These can occur from differences in production, performance, and unpredictable environments.

Let us help you to adopt a DevOps culture

HYBRID IT AUTOMATION

How much time do you need to respond to your customer feedback?

You must automate your process to strive for continuous improvement.

It speeds up your cycle time. Businesses are experiencing notable development in automated tools to integrate processes including the CI/CD pipeline.

You must automate your

Infrastructure provisioning
Building new software
Deploying software and new system
All tests from functionality to security compliance

In addition, your DevOps team can create indigenous automated processes. You can train your system to deploy apps faster with more reliability.

Want to know how to synchronize your team with automation?

NURTURE A COLLABORATIVE ENVIRONMENT

I think that the prime motive behind DevOps is to combine both development and operations to build a unilateral team driven by common objectives.

Brands need to inspire their development and operations teams to communicate regularly, share ideas, and resolve issues together to achieve this.

I think breaking down silos is essential to bring both these branches together.

Businesses need to align people, processes, and tools toward customer success.

This happens only when you, as a CEO or CTO, try to nurture a collaborative culture together.

When you shift your siloed working culture towards a collaborative environment, your business faces a cultural shift and it should follow a top-down approach.

Hence, getting the right people who are confident enough for this cultural shift is essential.

EMBRACE FAILURE AND FAIL TEST

Gone are the days when you keep on measuring your team’s effectiveness based on their success.

As per my understanding, DevOps culture needs a fail-fast approach to grow. It is just the opposite way of measuring success based on efficiency.

Let me tell you why.

The faster you fail, the faster you discover the successful way to do it. The core idea behind this is not to maximize failure but to inspire your development team to experiment with failure in a structured environment.

The faster they fail, the quicker they can discover ways to enhance the apps. Originally the fail-fast approach is popular in agile methodology.

But you can migrate it into DevOps also. But here the managers need to control the costs of failure, especially when it affects your customer services.

If you allow your developers to fail early during the development process, they can detect the defects and errors before the same goes for deployment.

HOW CAN AAIC HELP YOU?

At AAIC we are automation-driven. With the support of excellent DevOps and AWS certified teams, we are accelerating your time to market. With us, you can develop and deploy your apps faster. We have been working with top American companies to speed up their development cycle.

We also understand how critical it is to build best the DevOps practices with the right cloud alignment.

To know more, book a free consultation call.

AAIC is technology services company that provide high-end engineering services and is proficient in enterprise class for IT-delivery.AAIC focus on Automation in Cloud and DevOps

Save Your Time With AMI Cleanup Pipeline

Tue, 29 Mar 2022 12:15:42 +0000

What is the AMI Cleanup Pipeline?

The AMI Cleanup pipeline helps you clean up your old unused AMI and related snapshots.

Goals of AMI Cleanup Pipeline

An Amazon Machine Image (AMI) is a packaged environment containing a software configuration and other parts required to set up an instance.
As it contains the built solutions/artifacts, we end up creating AMIs for every new feature or release or even for testing the changes.
Thus, to clean up the older AMIs, we can use this AMI Cleanup Pipeline.

Talk to our AWS Experts

Benefits of AMI Cleanup Pipeline

The AMIs built into your AWS account have a heavy impact on your monthly bill. So in order to optimize cost, we must delete the unused AMIs since they are increasing the cost even if they are used or not.The AMI cleanup pipeline will help you delete these old unused AMIs.These AMIs are used by snapshots that can not be deleted before de-registering the AMI.

Want to know more?

Key features of the AMI Cleanup Pipeline

AMI

An Amazon Machine Image (AMI) offers the information needed to launch an instance. You must define an AMI when you initiate an instance.

Amazon EBS Snapshots

You can back up the data on your Amazon EBS volumes to Amazon S3 by taking point-in-time snapshots. Snapshots are incremental backups. This implies that only the blocks on the device that have changed after your latest snapshot are saved. It decreases the time needed to create the snapshot and saves a lot on storage costs by not duplicating data. Each snapshot contains all the information that is needed to restore your data (from the moment when the snapshot was taken) to a new EBS volume.

Our Solution Architecture with AMI Cleanup Pipeline

We integrated the AMI Cleanup Pipeline in our Devops-in-a-box platform to deliver better solutions to our customers.

Need AWS Consultation?

Well, we are an Advanced AWS consultant now.

How we help one of our customers with the AMI Cleanup Pipeline?

Our customer’s app involved autoscaling-based deployment. The Autoscaling group helps us to scale out (add EC2 instances) to match an increased load and scale in (remove EC2 instances) to match the decreased load.

So whenever any instance goes down, the autoscaling group handles it quickly by launching another instance with the help of AMI.

Amazon Machine Image (AMI) provides the information required to launch an instance. You must specify an AMI before you launch an instance. Our customer’s app is an EC2-based application.

Let’s say in the app we want to add a new feature, so we will write code for it and create an AMI and we will push the code changes to development/production.

Again, we have a new feature to be added on top of the previous one, so we again repeat the same procedure. So for 10 new features, we created 10 new AMIs.

Also here we are not considering the AMIs that we created for testing purposes, so let’s say we created 5 AMIs for testing each new feature that itself creates 50 AMIs for 10 new features.

But we don’t need the AMIs that we created in the beginning, as they are of no use to us. If we don’t delete these old AMIs we will end up paying for AMIs, that are old and unused.

Instead of manually finding old and unused AMIs and de-registering them, in our client’s app we used AMI Cleanup Pipeline which de-registers all the old, unused AMIs automatically.

When you deregister an AMI, it doesn’t affect any instances that you’ve already initiated from the AMI or any snapshots created during the AMI creation process. You’ll carry on to incur usage costs for these instances and storage costs for the snapshot.

Therefore, you should terminate any instances and delete any snapshots that you’re finished with. The snapshots cannot be deleted before registering AMIs. For cleaning up the old unused AMIs we can use python or bash script.

In python, we have a Boto3 library that can be used to access/connect with AWS resources. We will execute a python program in our pipeline to de-register the AMIs.

Let’s connect!

Published By

Pranav Kakade

DevOps Champion

Pranav is an earnest developer who is passionate about big data. He loves to build pipelines that accelerate the delivery time of our solutions to the customers. He loves sports in his free time.

Implemented a Secure and Scalable Infrastructure on AWS

Thu, 23 Dec 2021 10:36:06 +0000

Implemented a secure and scalable infrastructure on AWS

The Challenge

Cutshort wanted to deploy its solution infrastructure in AWS that will be highly available and scalable based on the workload, traffic, and peak hours. Also, it should be the cost effective. In addition, they wanted to implement all the security measures in their AWS accounts which are supported by the AWS and to be able to receive notification for all the possible alerts.

Partner Solution

For the client, DevOps adoption was key. They were looking to increase their productivity, optimize processes and enjoy a stronger collaborative work environment through DevOps

As AWS Partner, AAIC Interacted with client’s engineering, product management and IT team to fully comprehend the application’s functional and business requirements from the perspective of end-user and took the below key steps to provide the solution:

AAIC proposed them a new architecture which suggested to use ECS Fargate with Autoscaling & SPOT instead of ECS NodeGroups to save the cost as well as to scale automatically.
Also, Cutshort wasn’t using any Infrastructure-as-a-Code (IaaC) tool so we introduced them with terraform and how it can help them to spin up a new solution infrastructure in few minutes.
Told them about AWS savings plan and how it can benefit on the overall cost.
Help them to setup the AWS organization for consolidated billing.

Integrated their G-Suite with AWS Single-Sign-On to manage access centrally across their AWS Organization

With the help of terraform, AAIC created a new infrastructure for cutshort which was secured with the help of AWS services and resources such as AWS WAF, NACL’s, internal load balancers. Also, implemented alerts and notifications with the help of AWS Cloudwatch and SNS.

AWS Technologies Used

AWS ECS, AWS Load Balancers, AWS WAF, AWS SNS, AWS Cloudwatch Log Group

Results and Benefits

With new infrastructure, Cutshort started to save almost 25-30% cost compared to the earlier ones. As AAIC introduced them with Savings Plan and its benefits, they applied it in their AWS organization and started to get the benefits of it on the overall cost.

The deployment now became easier because of CodeDeploy and Github Actions (A CI/CD tool) and they were now able to move the changes to prod easily and faster. Earlier they used to make production changes once in two weeks but now they are started to do it in two days.

About the Partner

AAIC has a certified cloud engineering team that provides the needed expertise and service to move your on-premises data center to AWS Cloud. It takes the code from existing version control to open-source library GitHub, debug and make it operational on AWS. During the entire 5 step process, AAIC solution architects and cloud engineering team worked closely with the client team to deliver a secure, scalable, and performant solution post-migration.

EMFI

Thu, 23 Dec 2021 09:57:58 +0000

Executive Summary

EMFI Group is an intelligence-driven financial services company with a focus on global emerging markets. EMFI delivers up-to-date market color from major financial centers of the world to local investors who might operate in a very different context.

In this case study, we will describe how AAIC helped EMFI to achieve migration and modernization for their Financial Services Application. The efforts on deploying, maintaining, and supporting the existing applications were reduced with the help of AWS Services. Also, How EMFI achieved optimal automation and DevOps on their platforms.

Applied AI Consulting (AAIC) is a bespoke AI and Cloud Consulting Service. The core team is comprised of industry veterans with cumulative 25+ years of experience in building, architecting, and delivering cutting-edge technology solutions focused on solving customer pain points.

Partner Solution

The proposal covers the engagement of AAIC with EMFI, a leader in an intelligence-driven financial company. The engagement is focused on Cloud operations and DevOps for EMFI workloads and CIs in the AWS cloud.

The AAIC engineers team worked with EMFI technical leadership and the Product owner team to develop modernized business solutions Primarily involving the below objectives.

Containerizing the EMFI application using AWS ECS Fargate service.
Building CI/CD pipeline for EMFI application using AWS Developer tools such as Code Build, CodePipeline, and CodeDeploy services which will automatically build and deploy application code to the ECS cluster every time code changes.
Setting up ALB which distributes the incoming traffic across containers which automatically scales workloads.
Setting up Operations/Monitoring dashboard with the help of AWS Cloudwatch service. The dashboard includes details about ECS services like CPU/Memory utilization, Disk Space utilization, Network Insights, ECS service task status, and ECS service deployment status.
Help in migrating private GitLab to public SaaS GitHub.
Automating the scaling of the application with the implementation of cloudwatch alarms and app auto-scaling policies. These policies involve target tracking policies and scheduled-based policies that will increase or decrease task count in ECS service based on the specified criteria or schedule to handle the workload.
Creating application infrastructure with AWS services using Terraform. This includes building a scalable and secure network layer (using AWS VPC, AWS WAF, NACL, VPC Endpoints, etc.), database layer (using AWS RDS) and application layer with logging and monitoring enabled (using AWS ECS, AWS Cloudwatch, etc.)

Architecture

Architecture defines a high-level model of solution and describes how the resources are interlinked with each other. Within the AWS the architecture utilized load balancers to distribute incoming traffic across ECS Fargate containers which provided stability across the application.

Deployed AWS Services

AWS ServiceUsage of serviceECSAmazon Elastic Container Service (Amazon ECS) is a highly scalable, fast container management service that makes it easy to run, stop, and manage containers on a cluster.ECS ClusterAn Amazon ECS cluster is a regional grouping of one or more container instances on which you can run task requests.ECS Task DefinitionTask definition is basically the blueprint describing the docker containers that are used to run the applicationECS ServiceService defines the minimum and the maximum tasks that are running from a single task definition at any given point.EC2 InstanceEC2 stands for Elastic Compute Cloud. It is nothing but a basic computer virtually present in AWS cloud which you can access and do whatever you can do on a basic computer.VPCA virtual private cloud (VPC) is a secure, isolated private cloud hosted within a public cloud.ALBThe Application Load Balancer is a feature of Elastic Load Balancing that allows a developer to configure and route incoming end-user traffic to applications based in the AWS public cloud.IAMAWS Identity and Access Management (IAM) enables you to manage access to AWS services and resources securely.RDSAmazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.

Results and Benefits

Being on AWS open ups an array of new services and technologies that are now significantly more accessible to the average IT group.
Being on AWS opens up new possibilities to integrate including best-of-breed tools & services to connect to other systems.
The use of Terraform provides create, change, and version infrastructure safely and version infrastructure safely and efficiently.
Elasticity, load balancing, and the capability to scale automatically are a big bonus.

About the Partner

Site: 91SpringBoard, Sky Loft, Creativity Mall, Opposite Golf Course, Yerawada, Pune, India 411006

DevOps Engineering | Applied AI Consulting

Accelerating CI/CD Efficiency From Jenkins to GitHub Actions for Seamless Automation

Accelerating CI/CD Efficiency: From Jenkins to GitHub Actions for Seamless Automation

Company Overview

Client/Customer Overview:

Challenges

Operations Conducted

Alternative tool evaluation

Migration

QA automation

Strategic Approach

Seamless migration to GitHub Actions

Improved security

Optimized resource usage

Enhanced developer productivity

Positive Influence

Reduced CI/CD runtime

Enhanced security

Cost savings

Long-term Scalability

Key Takeaways

Customer Testimonials

Related services

Accelerating Integration with a Robust API Platform: How a Leading Automation Provider Transformed Their Processes Using AWS Services

Accelerating Integration with a Robust API Platform: How a Leading Automation Provider Transformed Their Processes Using AWS Services

Company Overview

Issue

Similar Use Cases

Solution

Impact

Accelerated Time-to-Market & Customer Onboarding

Operational Efficiency & Cost Savings

Scalability & Enhanced User Experience

Customer Testimonials

Related services

Accelerating Private Sector Bank’s App Releases with AWS and DevOps Expertise by Applied AI Consulting

Accelerating Private Sector Bank’s App Releases with AWS and DevOps Expertise by Applied AI Consulting

Company Overview

Issue

Similar Use Cases

Solution

Impact

Faster App Releases

Enhanced Reliability and Security

Cost Efficiency

Customer Testimonials

Related services

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Company Overview

Issue

Similar Use Cases

Solution

Impact

Increase in Deployment Success

Reduction in Manual Testing

Enhanced Quality and Customer Satisfaction

Customer Testimonials

Related services

Facilitating DevOps with Application Modernization & Architecture Reboot for a Leading Content Marketing Platform

Facilitating DevOps with Application Modernization & Architecture Reboot for a Leading Content Marketing Platform

Company Overview

Issue

Similar Use Cases

Solution

Impact

Scalability and Performance

Deployment Efficiency

Cost Optimization

Customer Testimonials

Related services

Streamlining Development Operations: Migrating from GitLab to GitHub for a Leading Content Marketing Platform

Streamlining Development Operations: Migrating from GitLab to GitHub for a Leading Content Marketing Platform

Company Overview

Issue

Similar Use Cases

Solution

Impact

Operational Cost Savings

Improved Scalability

Mitigating Vulnerabilities for a Leading Construction Logistics Platform

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start Up