Cluster architecture
Right-sized cluster design, node groups, and capacity planning for your workloads, not a copy of someone else's blog post.
Kubernetes & Platform Engineering
Kubernetes platforms your team can actually run.
Kubernetes should make shipping easier, not turn into a second job. We build platforms where developers can ship safely, operators can sleep, and no one needs to be a cluster guru to get work done.
Honest guidance
When Kubernetes is right, and when it isn't.
Kubernetes is a powerful tool, not a badge of sophistication. Part of our job is telling you when a simpler platform would serve you better.
| Situation | Kubernetes may be right | A simpler platform may be better |
|---|---|---|
| Team size and skill | A team of 5+ engineers, some with container experience, planning to operate the platform. | A small team with no container background and no budget to learn a platform. |
| Workload shape | Many services, uneven traffic, independent release cadences, batch jobs, autoscaling needs. | A handful of services with predictable traffic that managed containers can handle directly. |
| Portability goals | Explicit multi-cloud, on-prem, or edge requirements; avoiding provider lock-in matters. | Single-cloud is fine and managed services already cover the need. |
| Operational appetite | Your team wants to invest in a platform layer that pays back over time. | Your team wants maximum leverage per hour, and Kubernetes would be overhead, not leverage. |
Our default position
If you're an early-stage team or running a small number of workloads, we'll usually steer you toward managed services first. Kubernetes earns its keep at scale, not as a starting credential.
Platform foundations
The nine layers of a platform your team can trust.
We build each layer deliberately, so the platform stays simple to operate and cheap to run, even as it grows.
Workload deployment patterns
Deployments, stateful services, batch jobs, and autoscaling that match how your product actually behaves.
GitOps & CI/CD
Pull-based delivery where the repository is the source of truth, and every change is reviewable and rollbackable.
Ingress & networking
Service meshes only where they help, sensible ingress strategies, and DNS/TLS handled cleanly.
Secrets & configuration
Secrets managed safely and rotated on schedule, with configuration that's versioned and environment-aware.
Policy & security guardrails
Guardrails that keep insecure patterns out of clusters by default, without turning delivery into a form-filling exercise.
Observability
Metrics, logs, and traces wired to the questions your team actually asks, with alerts that mean something.
Backup & recovery
State protection and recovery drills for the systems that matter, so "restore" isn't a theory.
Upgrade strategy
Predictable upgrade cycles and a defined support window, so the platform ages gracefully instead of accumulating risk.
Outcomes
What "good" looks like.
A well-built platform is quiet. Releases happen, incidents stay small, and engineers spend their time on product, not on cluster forensics.
- Faster, safer releases. Small, frequent deployments with automatic rollback paths and no release-day fear.
- Consistent environments. Dev, staging, and production that behave alike, because they're defined alike.
- Clear ownership. Someone, not a committee, owns every part of the platform, and it shows.
- Actionable observability. Dashboards and alerts that lead to fixes, not to more dashboards.
- Less operational toil. Fewer manual heroics, fewer 2am pages, more time for the roadmap.
How we think
We speak fluent cluster, so you don't have to.
When we talk about your platform, we talk in terms of outcomes: release frequency, recovery time, cost per request. When we get our hands on it, we get specific.
Whether it's a misbehaving ingress, a noisy autoscaler, or a GitOps rollout that needs untangling, we can read the system and explain it in plain language.
$ kubectl rollout status deploy/api
Waiting for deployment "api" rollout to finish: 4 of 6 updated replicas are available...
deployment "api" successfully rolled out
$ kubectl get events --sort-by=.lastTimestamp
Normal SuccessfulCreate scale to 6
Warning BackOff pod api-7f9c failed readiness
$ argocd app diff api
spec.replicas: 4 → 6 (replicaset drift)
# root cause found in minutes, not meetings
Common questions
Kubernetes questions we hear often.
We already have Kubernetes, it's just hard to operate. Can you help without a rewrite?
Almost always, yes. Most painful platforms are a few deliberate improvements away from being comfortable. We start by understanding what's actually breaking, then fix the highest-leverage issues first.
Do we need to hire a platform team before adopting Kubernetes?
No. A good platform should reduce the expertise needed to ship, not increase it. We design so your existing engineers can operate it, and we train alongside the build.
Managed Kubernetes (EKS, GKE, AKS) or self-managed?
Managed, almost always. Running a control plane yourself is rarely the highest-leverage use of your team's time. We'll quantify the trade-off if your situation is unusual.
Is Kubernetes a good fit for a small or early-stage product?
Often not. We'll be direct about that. Many teams are better served by managed containers or PaaS-style services until their workload complexity justifies a platform.
How do you handle upgrades and security patches?
We set up a version policy, an upgrade cadence, and automated checks so updates become routine. Then we document it well enough that your team can run it.
Make Kubernetes work for your team.
Whether you're adopting Kubernetes, taming an existing cluster, or deciding it's not the right tool, we'll help you find the honest answer.