Docker & Kubernetes
Containerise your application, eliminate environment inconsistencies, and deploy on Kubernetes with rolling updates that push code without dropping a single request — with HPA auto-scaling and Prometheus/Grafana observability built in.
Why containers solve real deployment problems
The classic "it works on my machine" problem isn't just a developer frustration — it's a source of production incidents. A PHP version mismatch, a different OpenSSL version, a missing system extension — any of these can cause a production deployment to fail in ways that are hard to reproduce locally. Docker eliminates this by packaging the application, its runtime, and all dependencies into a single image that runs identically in development, staging, and production. If the container passes tests in CI, the same image is deployed to production — no differences.
For Laravel applications, containerisation means building separate images for the PHP-FPM web container, the Nginx reverse proxy, and the queue worker — each with appropriate resource limits and health checks. Multi-stage Docker builds keep the production image lean: build tools and development dependencies are excluded from the final image, reducing attack surface and container startup time. We also set up private image registries (AWS ECR or Docker Hub) with image scanning to catch known vulnerabilities before they reach production.
Kubernetes for production workloads
Kubernetes provides the orchestration layer that makes containerised applications production-ready: scheduling containers across multiple nodes, performing rolling deployments that replace old pods with new ones without downtime, restarting containers that fail health checks, and scaling horizontally when CPU or memory thresholds are breached. For most web applications, AWS EKS (Elastic Kubernetes Service) is the right choice — it manages the control plane, integrates natively with AWS networking, and supports Fargate for serverless pod scheduling when you don't want to manage EC2 node pools.
We configure Kubernetes deployments with readiness and liveness probes matched to your application's startup time and health characteristics, resource requests and limits sized to actual workload measurements, Horizontal Pod Autoscalers that scale based on CPU, memory, or custom metrics, and PodDisruptionBudgets that prevent your entire deployment being taken down simultaneously during node maintenance. Secrets are stored in AWS Secrets Manager and injected into pods at runtime via the Kubernetes Secrets Store CSI driver — never in ConfigMaps or environment variable manifests committed to version control.