DevOps adoption journey of an HRMS company

Introduction

This case-study explores the DevOps journey of a leading HRMS solutions provider based in Gurugram, India, known for simplifying HR operations for businesses. This company deploys a range of software products on the cloud to serve their global customer base.

Problem

1. Lack of real-time collaboration between development and operations teams.
2. Manual deployment processes leading to increased downtime during updates.
3. Database performance bottlenecks affecting application responsiveness.
4. High-availability concerns, especially during peak usage periods.

Objectives

1. Enhance collaboration between development and operations teams.
2. Implement automated deployment processes to reduce downtime.
3. Optimize database performance for improved application responsiveness.
4. Ensure high availability of services, minimizing downtime during peak usage.

Implementation

1. Automated Deployment:
   • Migrated to GitLab from SVN for Git repositories.
   • Implemented CI/CD automation for all services to build, test and deploy automatically.
   • Established automated testing to ensure code reliability before deployment.
   • Utilized Docker images for environments for consistency across development and production environments.
2. Database Optimization:
   • Setup monitoring to analyze Database bottlenecks and issues.
   • Optimized Database setup configuration and implemented query optimization strategies.
   • Utilized database indexing and caching mechanisms.
   • Scheduled regular database maintenance tasks to ensure optimal performance.
3. High-Availability Measures:
   • Implemented redundant server architecture to mitigate single points of failure on AWS EC2 instances.
   • Designed and implemented application load balancing strategies for even distribution of traffic on AWS.
   • Set up automated monitoring and alerting systems to proactively identify and address potential issues.
4. Collaboration through ChatOps:
   • Introduced Slack and Jira to facilitate real-time communication and manage DevOps and Infra requests.
   • ChatOps has been implemented to trigger builds and deployments from Slack / Jira and to be notified about DevOps and Infra activities.

Results

1. Deployment Metrics:
   • 84% reduction in deployment time and 30% more deployments.
   • 99.9% uptime achieved during peak usage periods.
2. Database Performance Metrics:
   • 55% improvement in database query response time.
   • 88% reduction in incidents related to database performance.
3. Collaboration Metrics:
   • 40% reduction in communication-related bottlenecks.
   • 28% increase in cross-functional team efficiency.

Challenges

1. High Availability Complexity:
   • Fine-tuning high-availability for multiple services to ensure seamless performance.
   • Learning: Regular simulations and testing are crucial for identifying and addressing potential issues.
2. Automated Testing Challenges:
   • Overcoming initial delays in setting up, and using automated testing.
   • Learning: Continuous feedback and iterations to improve the collaboration between development and testing teams.
3. Team Adoption:
   • Initial resistance to change required thorough communication and training.
   • Learning: Ongoing education and support are essential for team adoption.

Conclusion

The implementation of DevOps and ChatOps solutions has significantly improved collaboration, deployment efficiency, and database performance which led to high availability, guaranteeing service uptime for its users globally. We continuously monitor and refine the processes to sustain and build upon these improvements.