Chandan Bhardwaj

Overview: Architected a unified, enterprise-grade CI/CD platform using GitHub Actions, enabling standardized pipelines across diverse technology stacks including React, Node.js, Python, Java, and GCP Data Platform and other Techs workloads.

Scope: Platform design, pipeline templating, secrets governance, automated rollback strategies, canary deployments.

Impact: Reduced average deployment time by ~50% (2× faster deployments) with improved reliability through automated validation and canary rollout patterns.

Overview: Orchestrated phased migration of microservices to managed Kubernetes with Istio sidecar proxies for security and observability.

Scope: Migration planning, workload assessment, canary routing, mTLS enforcement, ingress controls, observability integration.

Impact: Improved traffic management capabilities, stronger security boundaries (mTLS), and accelerated feature rollout across services.

Overview: Implemented collection and visualization of deployment frequency, lead time, MTTR, and change failure rate using modern data pipelines.

Scope: Metrics ingestion, ETL pipelines, dashboard design, alerting rules, and playbooks based on observability insights.

Impact: Teams gained measurable targets and continuous improvement processes anchored in real-time engineering metrics.

Overview: Created standardized template libraries and workflow blueprints for data orchestration and cloud provisioning.

Scope: Template design, documentation, governance rules, adoption support, and version management.

Impact: Accelerated team onboarding with consistent, secure resource patterns and reduced manual provisioning errors.

Overview: Rationalized alerting rules, implemented automated runbooks, and defined service-level objectives (SLOs) to reduce noise.

Scope: Alert tuning, runbook automation, SLO definition, on-call schedules, and incident playbooks.

Impact: 40% fewer false alerts, improved mean time to recovery (MTTR), and better incident prioritization.

Overview: Managed comprehensive data migration strategy with automated validation checks and modernization of ETL pipelines.

Scope: Migration planning, schema transformation, data validation automation, performance tuning, and compliance checks.

Impact: 99.9% observed data integrity during migration with zero data loss and automated post-migration verification.