Lifecycle Management

DevOps lifecycle management is the end-to-end process of planning, building, testing, deploying, operating, monitoring, and improving applications and infrastructure. The goal is to deliver high-quality, secure, and reliable software quickly and efficiently, leveraging automation and collaboration across development and operations teams.

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DevOps Lifecycle Stages & Best Practices

1. Planning

   • Define goals, requirements, and architecture collaboratively (Dev, Ops, Product).

   • Use tools: Jira, Azure Boards, Trello.

   • Best Practice: Involve all stakeholders early to avoid misalignment.

2. Development

   • Write code using version control (Git, GitHub, Azure Repos, GitLab).

   • Use feature branches and pull requests for collaboration.

   • Example:

     git checkout -b feature/add-login
     git push origin feature/add-login

   • Best Practice: Enforce code reviews and automated linting.

3. Testing

   • Automate unit, integration, and security tests in CI pipelines (GitHub Actions, Azure Pipelines, GitLab CI).

   • Example:

     # .github/workflows/ci.yml
     jobs:
       test:
         runs-on: ubuntu-latest
         steps:
           - uses: actions/checkout@v3
           - name: Run tests
             run: make test

   • Best Practice: Shift-left testing—run tests early and often.

4. Deployment

   • Use Infrastructure as Code (Terraform, Bicep, CloudFormation) and configuration management (Ansible, Puppet).

   • Deploy with CI/CD tools (GitHub Actions, Azure Pipelines, ArgoCD, Flux).

   • Example:

     terraform apply -auto-approve
     ansible-playbook site.yml
     kubectl apply -f deployment.yaml

   • Best Practice: Automate rollbacks and use blue/green or canary deployments.

5. Operations

   • Monitor infrastructure and applications (Prometheus, Grafana, Azure Monitor, CloudWatch, Stackdriver).

   • Use container orchestration (Kubernetes) for scalability and resilience.

   • Example:

     kubectl get pods -A
     az monitor metrics list --resource <resource>

   • Best Practice: Set up alerting for critical failures.

6. Monitoring

   • Collect metrics, logs, and traces (ELK, Loki, Datadog, New Relic).

   • Visualize and analyze data to detect issues and trends.

   • Example:

     • Use Grafana dashboards for real-time monitoring.

     • Set up log aggregation with Fluentd or Logstash.

   • Best Practice: Monitor both application and infrastructure layers.

7. Feedback & Continuous Improvement

   • Gather feedback from users, stakeholders, and monitoring tools.

   • Use retrospectives and blameless postmortems to improve processes.

   • Track improvements in Jira, GitHub Projects, or Azure Boards.

   • Best Practice: Foster a culture of continuous learning and automation.

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Real-Life Example: Cloud-Native DevOps Pipeline

1. Plan features in Jira and document architecture in Confluence.

2. Develop microservices in feature branches, push to GitHub.

3. Run automated tests and security scans in GitHub Actions.

4. Deploy infrastructure with Terraform and apps with Helm on AKS/EKS/GKE.

5. Monitor with Prometheus and Grafana; set up alerts in PagerDuty.

6. Review incidents and update runbooks in Git.

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Common Pitfalls

• Manual deployments and configuration drift

• Lack of automated testing or code reviews

• Siloed teams and poor communication

• Ignoring monitoring and feedback loops

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References

• Azure DevOps Documentation

• AWS DevOps Blog

• Google Cloud DevOps Solutions

• Terraform Docs

• Kubernetes Docs