How we helped scale a video analytics platform - A DevOps Case Study

The client has developed an application for broadcasters, telecommunication and media companies to deliver better-monetized video experiences. The application works by capturing data, standardizing, synchronizing, and routing it to data points where clients require them. The profiled company asked to have their name blinded to protect their confidentiality.

• Bring DevOps Culture to its Software Development life cycle.
• Faster Development Cycle with Better collaboration between teams (Business, Dev, and Ops)
• Automating deployment, scheduling, and scaling of containerized applications.
• Application Deployment, Orchestration, and Automation scripts should be portable across multiple Cloud Vendors.
• Implement Automated Scripts and AutoScaling Infrastructure on demand.

• Find a partner with DevOps Consulting Experience 
• Architecture design for better scalability and response.
• Resistance to failures and infrastructure issues.
• The infrastructure and orchestration supporting the product needed refinement to support customer growth and remove single points of failure.

• After evaluating the requirements, our team configured the environments in Kubernetes Cluster and helped the development team to deploy the application as containers/ pods in a highly scalable and fault-tolerant environment.

• Initially, the deployments were handled manually and once we educated the development team about the DevOps culture, we configured multiple environments (Dev, Staging, and Production) and automated the continuous delivery pipeline.

• While automating the pipeline using Jenkins, we prevented risky deployment and increased productivity.

• The team also automated integration, testing, and release tasks by building necessary automation scripts in line with identified technology stack and configuring and setup the environment.

• Kafka has been used in this application for building real-time data pipelines, generating a high volume of data with the lowest latency. It is horizontally scalable, fault-tolerant, and wicked fast.

• Casandra, Postgres, and Redis clusters were implemented in this project.

• The Activelobby team did phase-wise Agile scrum process tasks with sprints. Lastly, we were able to establish operational visibility, monitoring, and reporting for performance measurement.

• The company achieved the following with Activelobby Association

• Improved Software Quality and accelerated the number of software releases.

• Collaboration between development, testing, and operations functions.

• Can run more complete and comprehensive testing scenarios.

• Release Automation was achieved.

• Our clients have streamlined their development and deployment processes to DevOps which in turn generated

        revenue with a happier and much more satisfied client base.