Container Orchestration
Container orchestration platforms manage where containers run, how many replicas are active, how they communicate, and what happens when one fails. Kubernetes is the dominant platform. We design and operate production clusters that are reliable, observable, and manageable by the team that inherits them.
Orchestration platforms and tools
Container Orchestration
Kubernetes
Production Kubernetes with deployment manifests, resource management, health checks, autoscaling, RBAC, and network policies.
View service →AWS · Kubernetes
Amazon EKS
Managed Kubernetes on AWS. Node group configuration, IAM Roles for Service Accounts, EBS storage, and Cluster Autoscaler.
View service →Kubernetes · Packaging
Helm
Helm chart authoring for packaging and versioning Kubernetes applications. Values files per environment and release management.
View service →Kubernetes is the operating system for containers
Kubernetes schedules containers onto nodes, restarts them when they fail, routes traffic between them, and scales them up or down based on load. Think of it the way you would think of an operating system: it handles the infrastructure so application code does not have to. The trade-off is real operational complexity that requires active management.
Cluster design comes before workloads
The network configuration, node group sizing, storage class setup, and RBAC model need to be correct before the first application workload is deployed. Retrofitting these after the fact is significantly harder than designing them upfront. We spend time on cluster design before running any application code in a cluster.
Packaging with Helm
Raw Kubernetes manifests work for simple deployments but become difficult to manage across environments as configuration differences accumulate. Helm charts parameterize the manifests so that the same chart can be deployed to development, staging, and production with environment-specific values rather than duplicated manifests.
Observability is a first-class concern
A Kubernetes cluster without Prometheus metrics, structured application logs, and distributed tracing is difficult to operate. We deploy the observability stack alongside the application workloads so the team has data from the first deployment, not after the first outage.
Common questions
Running containers in production?
If you are setting up a Kubernetes cluster or need help with an existing one, reach out and we will assess the requirements before any work begins.
Get in touchPurcellville, Virginia · US-based engineering