We design, deploy and improve Kubernetes and Amazon EKS environments with a focus on reliability, security, scalability, networking and operational visibility.
AWS, Google Cloud, Microsoft Azure, Hetzner
Kubernetes is an open-source container orchestration platform that schedules, scales and restarts containerized applications across a cluster of machines. A production Kubernetes platform adds what surrounds it — networking, ingress, autoscaling, RBAC, secrets, monitoring, logging and an upgrade process — so teams can run workloads on it reliably.
Kubernetes provides powerful orchestration, but production environments require thoughtful architecture and operational discipline. Creating a cluster takes minutes; operating one reliably depends on decisions about workload architecture, networking, resource management, security and observability.
We help teams build Kubernetes platforms — self-managed or on Amazon EKS — that are easier to deploy, monitor, secure, scale and maintain as workloads and team size grow.
Pods are managed directly instead of through controllers, losing Kubernetes' self-healing benefits.
Pods without requests/limits set starve their neighbors or become invisible to the scheduler.
Any pod can reach any other pod by default, with no NetworkPolicies restricting traffic.
Nobody can quickly tell which service is failing when something goes wrong in the cluster.
Kubernetes version upgrades are postponed because nobody trusts the process to go smoothly.
Design production-ready cluster structures and workload organization, on self-managed Kubernetes or Amazon EKS.
Set up and configure Kubernetes environments for application workloads.
Configure services, ingress, networking and traffic routing.
Implement autoscaling, health checks and resilience patterns.
Apply NetworkPolicies, RBAC and Pod Security Standards to limit blast radius.
Integrate monitoring and logging, and manage version upgrades safely.
Review workloads and platform needs.
Plan cluster and workload architecture.
Stand up clusters and workloads.
Apply network and access controls.
Add monitoring and logging.
Tune scaling and resource usage.
Standardized cluster and workload patterns.
Autoscaling matched to real demand.
Monitoring and logging built into the platform.
Helm-based workflows reduce deployment drift.
We build repeatable delivery workflows that connect source control, testing, infrastructure, security and deployment into a reliable engineering process — using Jenkins, GitHub Actions, GitLab CI/CD and Docker.
We create internal developer platforms, self-service infrastructure and golden paths that give engineering teams a consistent, supported way to provision and manage infrastructure.
We bring metrics, logs and traces together — using Prometheus, Grafana, AWS CloudWatch and the ELK Stack — to help engineering teams understand system behavior, identify issues and respond with real operational context.
We help teams improve production reliability through measurable service objectives, incident response processes, capacity planning and practical operational automation.
More on this and related topics.
Running Kubernetes in production requires more than creating a cluster. Explore the architecture, security, networking, scaling and observability practices that matter.
Cloud optimization is more than deleting unused resources. Learn how rightsizing, architecture and workload visibility can improve efficiency.
Internal platforms can reduce infrastructure complexity by giving development teams standardized and self-service workflows.
EKS removes the operational burden of managing the control plane yourself, which is usually worth it unless you have a specific reason to self-host. We assess your team size, existing AWS footprint and operational capacity before recommending either.
Yes. We plan upgrades against your actual workload compatibility, test in a non-production environment first, and roll out in a way designed to avoid surprise downtime — rather than deferring upgrades indefinitely.
Resource requests and limits are the foundation — we tune these based on real observed usage, then layer in the Horizontal Pod Autoscaler and Cluster Autoscaler so capacity tracks actual demand. For a deeper cost review, see Cloud Cost Optimization & FinOps.
Sometimes, yes. If your workload does not need multi-service orchestration or has simple scaling needs, a simpler container host or managed platform may serve you better. We'll tell you honestly if Kubernetes is not the right fit yet.
Tell us what you're building, where you're facing infrastructure challenges, and what you want to improve.
Not sure where to start? Request a free infrastructure audit →
