Dokcer to Kubernetes
Significant Changes improve reliability and container mngmnt
🔥 Problems with Docker (standalone/Compose):
~Manual container deployment using
docker runordocker-compose~No self-healing — containers crashed and stayed down until restarted manually
~Scaling required custom scripts and manual load balancing
~Poor resource utilization across nodes; no bin-packing or autoscheduling
~No central visibility into container health, logs, or metrics
~Configuration drift between staging and production environments
~Service discovery between containers was managed manually or with external tools
~Zero support for rolling updates, leading to downtime during deployments
🛠️ Solutions using Kubernetes:
✅ Defined deployments, services, and config maps using declarative YAML manifests
✅ Used Kubernetes Deployments for rollout strategies, health checks, and self-healing
✅ Implemented Horizontal Pod Autoscaling (HPA) based on CPU/memory usage
✅ Managed secrets and configs securely via Kubernetes Secrets and ConfigMaps
✅ Centralized monitoring and logging with Prometheus + Grafana + Loki
✅ Utilized K8s Namespaces to separate dev, staging, and prod environments
✅ Enabled service discovery and internal DNS using built-in kube-dns
✅ Performed rolling updates and canary releases without downtime
✅ Here’s a summary of what we achieved:
✅ ~80% reduction in manual deployment effort using declarative infrastructure
✅ Zero downtime deployments using rolling update and readiness probes
✅ ~40% better resource utilization due to Kubernetes scheduler
✅ Faster incident recovery with self-healing Pods and node failover
✅ Improved observability — real-time logs, metrics, and health dashboards
✅ Environment consistency across staging and prod using Helm charts and GitOps
✅ Simplified scaling — automated HPA and cluster autoscaler
✅ DevOps velocity boost — infrastructure changes via CI/CD into Kubernetes
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