Container Orchestration
We set up and manage container orchestration platforms using Kubernetes (EKS, GKE, AKS) and Docker Swarm for teams that need automated deployment, scaling, and lifecycle management of containerized applications. Our Kubernetes configurations include production-grade cluster setup with node auto-scaling, pod resource management, network policies, and RBAC access controls. We containerize applications using multi-stage Docker builds that produce minimal images — typically 50-150MB for Node.js services and 20-80MB for Go services — reducing pull times and attack surface. For teams already running containers, we optimize existing clusters: right-sizing resource requests to reduce waste by 20-40%, implementing horizontal pod autoscaling based on custom metrics, and configuring rolling deployments with health-check-based rollback. Typical orchestration projects run 3-8 weeks, covering cluster provisioning, application containerization, Helm chart creation, monitoring setup, and team training.
Provision production Kubernetes clusters on EKS, GKE, or AKS with node auto-scaling, multi-AZ distribution, and infrastructure-as-code management via Terraform.
Containerize applications with multi-stage Docker builds producing minimal images (50-150MB for Node.js, 20-80MB for Go) with non-root users and read-only filesystems.
Create Helm charts for repeatable application deployments with environment-specific value files for development, staging, and production configurations.
Configure horizontal pod autoscaling based on CPU, memory, and custom metrics (request rate, queue depth) with scale-up response times under 60 seconds.
Implement rolling deployment strategies with configurable max surge and max unavailable settings, plus automated rollback on readiness probe failures.
Set up Kubernetes RBAC with namespace isolation, service accounts per workload, and network policies restricting pod-to-pod communication to defined paths.
Deploy monitoring stacks (Prometheus, Grafana) with pre-built dashboards for cluster health, pod resource usage, and application-level metrics with alerting rules.
Configure persistent storage with StorageClasses, PersistentVolumeClaims, and automated backup policies for stateful workloads (databases, file storage).
Right-size resource requests and limits based on actual usage data, reducing cluster cost by 20-40% while maintaining performance headroom for traffic spikes.
Deliver team training sessions covering kubectl operations, Helm chart management, log access, scaling procedures, and incident response runbooks for production clusters.