Prakash Hulamani

• Applied AI/LLM-driven techniques including Prophet models, Z-score, and score-based anomaly detection to proactively identify system anomalies and improve incident triage with an Incident Analyzer.
• Enabled advanced deployment strategies by implementing Flagger for canary releases.
• Dashboard as Code (DAAC) to standardize observability across environments.
• Actively participated in Major Incident Management (MIM) calls, performing real-time troubleshooting, issue containment, and root cause analysis to minimize downtime.
• Developed comprehensive observability dashboards capturing MTTD (Mean Time to Detect), MTTR (Mean Time to Resolve), and latency percentiles (p90, p95, p99) to track reliability and user experience metrics.
• Designed GitHub branching strategies, automated repo setup and permissions, and enforced naming/package guidelines for consistency.
• Built CI/CD pipelines using GitHub Actions, Azure DevOps, and Jenkins, integrating security tools (Polaris, Black Duck, SonarQube, Trivy).
• Managed Docker image tagging, automated integration/component/E2E testing, and published reports via GitHub Pages.
• Handled library and artifact management using Nexus and GitHub Packages; created reusable workflows and composite actions.
• Deployed applications to AKS using Helm; implemented Blue-Green and Canary deployments with Helm, kubectl, and Kustomize.
• Managed secrets with Azure Key Vault; automated SPN rotation and database IP whitelisting across Azure services (Postgres, Redis, Cosmos).
• Used Terraform for standardized infra creation with validation, formatting, and uniform workflows for init, plan, and apply.
• Built self-service tools for pod restarts, heap/thread dumps, DB query execution, and K8s scaling in lower environments.
• Developed CI/CD dashboards and application metrics using Grafana, Prometheus, and Datadog; created custom alerting rules.
• Automated DB script deployments and optimized GitHub runner usage via parallel processing and early job cancellation.
• Led DR solutions using Akamai GTM, regional failover mechanisms, and DB volume health checks.
• Supported Kafka-based event-driven architecture and on-prem G2C/C2G infrastructure with LB and OHS setups.
• Contributed to Service Mesh adoption to improve traffic control, security, and observability.

• Application Containerization & Kubernetes Migration
  Successfully migrated 60+ applications to containers using Kubernetes.
  Developed Jenkins Pipeline to automate the CI/CD process for application migrations.
• Infrastructure & Security Setup
  Configured Nginx as a reverse proxy for all applications.
  Implemented SSL certificates for enhanced security across all applications.
  Deployed Prometheus & Grafana for monitoring and health checks.
• Cloud Migration & AWS Setup
  Migrated applications from physical servers to AWS.
  Configured AWS services:
  EC2, VPC, S3, Route 53 Load Balancers (LB), Auto Scaling, SNS
  Established CI/CD pipelines using:
  AWS CodeCommit, CodePipeline, CodeBuild, CodeDeploy
• Monitoring & Observability
  Set up Prometheus & Grafana for real-time monitoring and alerting.

Core Responsibilities Key Achievements

• Managed CI/CD pipelines (Jenkins, Ansible, Docker) for 60+ apps, reducing deployment time by 40%.
• Automated deployments using Ansible Playbooks and Jenkins, eliminating manual errors.
• Led cloud migration to AWS (EC2, ELB, S3, VPC) and optimized costs by cleaning unused resources.
• Resolved critical production incidents (memory leaks, outages) via heap/thread dump analysis.
• Monitored systems using Prometheus, Grafana, Kibana for proactive issue resolution.
• Cut infrastructure costs 30% by migrating from physical servers to AWS microservices.
• Reduced deployment failures by 60% through automated Spinnaker-based microservices rollouts.
• Trained 10+ team members on DevOps tools, improving team productivity by 25%.