Running Kubernetes Worker Nodes with Amazon EC2

OneData Software implements Kubernetes-based application architectures on AWS by running EKS clusters that use EC2 worker nodes configured for both cost efficiency and scalability. Drawing from their EKS case studies (e.g. ConstructionOPS) and AWS consulting expertise, they build architectures that optimize the worker node layer — selecting appropriate EC2 instance types, using managed/self-managed node groups, auto-scaling, multi-AZ placement, and aligning node capacity to workload demand.

Key Aspects of What OneData Does

1. EC2 Worker Nodes vs Other EKS Node Options o Use Amazon EC2 instances for worker nodes in EKS clusters when workloads require performance, control, custom machine types, or when cost savings are possible compared to serverless options. o Mix of managed node groups and self-managed nodes when fine control is needed.

2. Instance Right-sizing & Spot / Savings Plans o Evaluate workload profiles (CPU / memory / I/O usage) to choose appropriate EC2 types. o Potential use of EC2 Spot or Reserved/Savings Plans to reduce compute costs while maintaining availability.

3. Auto-Scaling & Elasticity o Use EKS features + Kubernetes tools (Cluster Autoscaler, node auto-scaling, etc.) to scale node counts up/down with demand. o Multi-AZ node deployments to ensure availability and resiliency.

4. Cost Optimization Techniques o Use mix of instance types, instance sizes; leverage cost-effective families (Graviton or similar) for suitable workloads. o Pod scheduling optimizations (binpack, balanced distribution). o Shut down / scale down unused node capacity during low usage.

5. Operational Management & DevOps Best Practices o Infrastructure as Code (Terraform / CloudFormation) to define node groups, EC2 configurations, autoscaling policies. o Monitoring of node health, pod-placement, resource usage; logging and alerting via tools like CloudWatch, Prometheus, Grafana. o Secure node configuration (IAM roles, security groups, updates / patching of EC2 worker nodes).

6. Multi-Environment / Isolation / Versioning o Support for dev / staging / production EKS clusters or namespaces with separate node pools to isolate workloads. o Rolling deployments, blue/green or canary strategies across nodes.

7. Use-Case Driven Workloads o Containerized microservices, batch jobs, background processing, CI/CD pipelines, etc. o Workloads may vary: compute-intensive tasks, GPU/accelerated compute, I/O bound services — node types chosen accordingly.

Benefits

• Lower cost per compute unit vs overprovisioned nodes or serverless cluster options for persistent workloads.

• More predictability & control over performance and resource limits.

• Ability to choose EC2 family / instance types adapted to workload (e.g. Graviton, burstable, etc.).

• Resilience through AZ redundancy, node health management.

• Flexibility: custom configurations, more control over worker nodes than fully serverless models.