The Client
Skyword is a content marketing platform that helps bring brands and their customers closer through high-quality relevant content. Companies can also use the platform to produce and disseminate their own content to improve new customer acquisition, build brand loyalty and sustain interest in what the company does, and how it does it. Skyword maintains a digital publication called Content Standard. The publication offers interesting and original content for public consumption on topics related to content marketing.
Skyword also owns TrackMaven, a marketing analytics software that helps marketers compute ROI and improve outcomes on 18 integrated digital and social channels.
Project Goals
Skyword’s IT infrastructure needed to be migrated and modernized. In addition, Skyword was facing challenges in deploying, maintaining, and supporting its existing applications. The company needed to revamp its infrastructure to facilitate automation and DevOps for ongoing upgrades.
The Solution
AAIC engineers team worked with Skyword technical leadership and the Product owner team to develop a modernized business solution which included the following steps:
The application was containerized—i.e. a form of virtualization wherein the application is run in isolated spaces called containers. Containers share OS (unlike Virtual Machines). Everything the application needs to run, i.e. libraries, configuration files, etc., is encapsulated in its container. As a result, the containerized app can run on different types of infrastructure, from bare metal to VMs without any need to refactor it to the particular environment.
- Skyword’s application was packaged and bundled as a Docker image before being deployed in Kubernetes (aka, K8s) clusters. This will enable better management, such as rollouts/rollbacks, service discovery, load balancing, storage orchestration, and self-healing (This refers to automatically replacing and restarting containers that fail) and rescheduling containers when nodes die.
- Automation and version control are at the heart of all DevOps practices, and to enable this we adopted GitHub as our repository for code and configuration files. These files are also used to implement CI/CD. GitHub Actions would be used to generate Java (JAR) files, which will be packaged as Docker images along with dependant libraries and set up for automated deployment to AWS Auto Scaling Groups on the client’s cloud. (WAR/JAR files are digitally signed to signify the origin of source code, making it easy to developers to identify version, test, and deploy the web application)
- To save time that would otherwise be spent in resource management, we templatized setting up of resources using AWS CloudFormation an Infrastructure as Code service that takes care of provisioning and configuring resources, so you don’t have to individually do it each time. CloudFormation eliminates manual errors, speeds up, and simplifies application development, scaling, and application integration.
- As part of the testing protocol, we implemented Selenium an open source testing tool to synchronize and orchestrate tests as per pre-set triggers, which were defined in the CI/CD delivery pipeline.
- To ensure security was given its just due, we implemented OWASP, an open-source security testing tool. OWASP helps identify diverse vulnerabilities before fresh releases went into production. Monitoring and security go hand in hand, and to enable thorough security, we enabled automated alerts by setting up GitLab with Slack. This would automatically share the status of CI/CD deployments and monitor for failures, reducing the impact on the business. CloudWatch metrics and logs were also used to monitor the system.
- From a cost-optimization perspective Lambda functions were written to scale the environment up and down.
- TrackMaven dashboard was set up for operations and monitoring
Architecture
Standard 3 Tier architecture was used to save information on clients securely in the Cloud. Clients can log in with appropriate IAM security, Plus Group Rules and Security.
Within AWS architecture, we utilized Amazon’s Elastic Load Balancers combined with Auto Scaling Groups to balance the traffic across multiple instances and automate the creation/termination of instances across multiple Availability Zones.
A number of components were also split out from the current infrastructure to make it more modular and fault-tolerant, while assuring redundancy across several geographic locations.
Tech Stack
- AWS Amazon Simple Storage Service (Amazon S3)
S3 is an object storage service. To store the images formatted by the openross application (an fast, open, and dynamic open source image resizer) S3 buckets were used.
- AWS Elastic File System (EFS)
EFS is a regional service that stores data across multiple Availability Zones assuring high availability and durability.
- AWS Cloudwatch Log Group
Amazon CloudWatch Logs were used to monitor, store, and access application logs.
- AWS Application Load Balancer
ALB was used for distributing incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones.
- AWS Route53 Hosted Zones
Route 53, highly available and scalable DNS web service, was used for routing internet traffic to Skyword applications.
- AWS Secrets Manager
All of Skyword’s application secrets or properties are stored in AWS Secrets Manager.
- AWS Key Management Service
AWS Key Management Service, an AWS managed service was used to create, encrypt, and control master keys used to encrypt data.
- AWS Elasticache (Redis)
Amazon ElastiCache is a Redis-compatible in-memory data store service. It was used for session management in Skyword’s web application.
- AWS Certificate Manager
It is a service that lets you easily provision, manage, and deploy public and private Secure Sockets Layer/Transport Layer Security (SSL/TLS) certificates for use with AWS services and internal connected resources.
- AWS System Manager Session Manager
Session Manager is a fully managed AWS Systems Manager capability that lets users manage their EC2 instances, on-premises instances, and virtual machines (VMs) through an interactive one-click browser-based shell or through the AWS CLI.
- AWS Identity and Access Management
It was implemented to manage access to AWS services and resources securely.
Application Modernization: Steps & Benefits
AWS Relational Database Service (RDS) was used for the data layer in conjunction with AWS Aurora, a MySQL-compatible Relational Database Management Service which was designed from the ground up to run on AWS.
Deployment Application Instance creation, launch, and updating is managed using AMI (Amazon Machine Image.) In order to update AMI i.e., modifying WAR/JAR files present in the AMI, AMI bakery is used. It also provides support for deploying it into the respective auto-scaling group. AMI deployment is done in a blue-green fashion where a new instance will be launched and only after launch will the older or previous instance will be terminated. AWS Lambda function has been set up in the environment. The Lambda function is responsible for scaling up or scaling down autoscaling groups. It can be scheduled to scale up or scale down at a specific rate.
Version Control
Git VCS was used to manage the versioning of the infrastructure. a Git repository, with all of the relevant setup & configuration scripts, along with any relevant documentation, provides detailed information on how to recreate the infrastructure from scratch. This, combined with CloudFormation, enables the automated creation of almost all architected AWS services.
Migration Benefits
Significant improvement in Uptime, which can be monitored with 3rd party tools and confirmed. Implementation of the new pipeline helps to reduce time of the deployment from 11 mins to 5 mins.
No single point of failure
Ability to innovate
Being on AWS opens up an array of new services and technologies, from new storage engines like Redshift or services like Amazon Machine Learning or Lambda, earlier implementation was taking hours to send notification during data processing & involved manual efforts to reboot k8s pods. AAIC automated this manual task using a lambda service which reduced the resolution time to 15 mins
Integration to other systems like WordPress and third party APIs are simple with this devops solution.
Cost Optimization
With the deployment and output of AWS Migration Evaluator, Skyword was able to see detailed reports of their inventory.
Utilization of resources was analyzed, and this helped in right-sizing the company’s AWS solutions. Some of Skyword’s existing resources were over-provisioned and right-sizing their resources resulted in significant cost savings.
Approx 30-35% reduction in the cost by selecting appropriate instances and deleting unused resources in AWS. Earlier the pods requested cpu and memory was higher which was resulting in high configuration spot instances, optimized solution given by AAIC resulted in this cost reduction.
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.
