Complexity beyond the team's capacity
A small team can end up spending more time operating the cluster than building the product it was meant to support.
Cloud & DevOps · Kubernetes
Kubernetes consulting services that start with whether you need it
Kubernetes is excellent at running many services reliably across many machines. It is also complex. We help you decide, then build and run clusters that your team can understand.
What is Kubernetes?
Kubernetes consulting services help organizations decide whether Kubernetes fits their workloads, then design, set up and operate clusters to run containerized applications. Kubernetes schedules containers across a group of machines, restarts failed ones, scales them with demand and rolls out new versions gradually. Most teams are best served by a managed offering such as Amazon EKS, Google GKE or Azure AKS rather than running the control plane themselves.
Kubernetes is often adopted because it is popular rather than because the workload needs it. The result can be a cluster that costs more than the application it hosts, YAML nobody fully understands, and upgrades postponed until the provider forces them. When Kubernetes is the right choice, it still needs deliberate design: networking, access control, resource requests, observability and an upgrade routine.
Where Kubernetes adoption goes wrong
Wasted capacity
Missing or inflated resource requests leave nodes half empty or cause containers to be killed under load.
Permissive defaults
Cluster-admin access for everyone, no network policies and secrets in plain manifests are common in first clusters.
Upgrade debt
Kubernetes versions have limited support windows, and clusters left behind face deprecated APIs and forced upgrades.
Our Kubernetes service
Readiness assessment
An honest comparison of Kubernetes against Docker Compose on a VM or a managed container service for your specific workloads, team and budget.
Managed cluster setup
EKS, GKE, AKS or DigitalOcean Kubernetes clusters defined with infrastructure as code, with node pools, networking, ingress and DNS configured.
Application packaging
Helm charts or Kustomize overlays for your services, with resource requests, probes, disruption budgets and configuration per environment.
GitOps and CI/CD
Deployments driven from Git using tools such as Argo CD or Flux, or directly from CI pipelines, with rolling, blue-green or canary strategies.
Observability and autoscaling
Metrics, logs and alerts for cluster and application health, plus horizontal pod autoscaling and node autoscaling based on real usage.
Ongoing cluster operations
Version upgrades, add-on updates, capacity reviews, cost reviews and incident support for clusters we build or inherit.
Included capabilities
- Managed control plane (EKS, GKE, AKS)
- Cluster defined as code
- Namespaces per team or environment
- Ingress controller with automatic TLS
- Helm charts or Kustomize overlays
- Liveness and readiness probes
- Horizontal pod and node autoscaling
- Network policies and RBAC
- External secrets integration
- Documented upgrade procedure
What Kubernetes changes for your business
Self-healing workloads
Failed containers are restarted and rescheduled automatically onto healthy nodes.
Gradual rollouts
New versions replace old ones progressively, and a failed rollout can be reversed quickly.
Efficient use of capacity
Correct resource requests and autoscaling pack workloads onto fewer machines.
One platform for many services
Every service is deployed, monitored and scaled the same way.
Where it makes the biggest difference
Multi-service SaaS platforms
Products made of many services that deploy independently and need to scale separately.
Variable or spiky traffic
Workloads whose load changes sharply through the day or season, where autoscaling saves capacity during quiet periods.
Consolidating many applications
An organization running dozens of small services on separate servers that wants one consistent platform to run them.
Inherited clusters
A team that took over a cluster it didn't build and needs it documented, secured, upgraded and right-sized.
Deciding, building and running a cluster
The first step can end with a recommendation not to use Kubernetes at all.
Assess fit
Review workloads, traffic patterns, availability needs and team skills, and recommend Kubernetes or a simpler option.
Design the cluster
Provider, regions, node pools, networking, access model and the add-ons the cluster genuinely needs.
Build
Create the cluster and supporting resources with infrastructure as code, in a non-production environment first.
Package applications
Write charts or manifests with correct resources, probes and configuration for each service.
Wire up delivery
Connect CI/CD or GitOps so deployments are versioned, reviewed and reversible.
Go live
Move production traffic in stages with monitoring and a rollback plan.
Operate
Upgrades, capacity and cost reviews on a regular schedule, done by your team, by us, or jointly.
What it connects to
Kubernetes
- Amazon EKS
- Google Kubernetes Engine (GKE)
- Azure Kubernetes Service (AKS)
- DigitalOcean Kubernetes
- Helm and Kustomize
- Argo CD or Flux
- Prometheus and Grafana
- cert-manager and external DNS
Built with
Is Kubernetes the right platform?
| Criterion | Docker Compose on a VM | Managed container service | Managed Kubernetes |
|---|---|---|---|
| Examples | Compose on Hetzner, DigitalOcean or Hostinger VPS | AWS ECS/Fargate, Google Cloud Run, Azure Container Apps | EKS, GKE, AKS |
| Learning curve | Low | Moderate | Steep |
| Availability | Single host unless extended | Multi-zone handled by provider | Multi-node, self-healing |
| Day-to-day operations | Patch the server, update images | Mostly managed | Upgrades, add-ons, capacity planning |
| Choose it when | One or a few apps, steady load | You want scaling without cluster management | Many services, a platform team, portability across providers |
Security, quality and scale
Role-based access control
Namespaced roles so developers, CI systems and operators each get only the access they need.
Network policies
Traffic between services restricted to what each one actually requires.
Secrets outside manifests
Secrets pulled from a cloud secrets manager or vault rather than stored in Git in plain form.
Planned scaling
Autoscaling limits and disruption budgets set so the cluster grows under load without overwhelming databases behind it.
What working with us looks like
Honest about fit
We will recommend against Kubernetes when Docker Compose or a managed container service would serve you better.
Managed services first
We use managed control planes so your team isn't maintaining Kubernetes internals.
Understandable setups
Clusters are kept to the add-ons you need and documented so they can be run by people other than us.
Developers on the team
We can adapt applications for Kubernetes (probes, graceful shutdown, statelessness), not just write manifests.
What it costs
Fixed-price packages with the scope written down, paid stage by stage. Your project goes live once it's fully paid.
Related services, technologies and industries
Sources and further reading
Official documentation and guidance if you want to read more about this topic.
Kubernetes: questions we hear most
Does our business need Kubernetes?
Many businesses do not need Kubernetes. If you run one or a few applications with steady traffic, Docker Compose on a well-managed server or a managed container service is usually simpler and cheaper. Kubernetes earns its complexity when you run many services, need automatic scaling across machines or want one consistent platform for many teams.
Should we run our own Kubernetes or use a managed service?
Use a managed service such as EKS, GKE or AKS unless you have a strong reason not to. The provider runs and patches the control plane, which removes a large share of the operational burden. Self-managed clusters make sense mainly for on-premises or specialized requirements.
Can databases run on Kubernetes?
They can, using stateful sets and persistent volumes, but for most business databases a managed database service is the safer choice. Running stateful systems on Kubernetes adds backup, failover and upgrade responsibilities that a managed service handles for you.
How often do Kubernetes clusters need upgrading?
Regularly, because each Kubernetes minor version is supported for a limited period and managed providers eventually retire old versions. We plan upgrades as a routine task, testing them in a non-production cluster and checking for deprecated APIs first.
Can you take over a cluster someone else built?
Yes. We start with a review of the cluster's configuration, access, workloads, costs and version status, then document it and fix the highest-risk issues before taking on routine operations.
Next step
Get a straight answer on Kubernetes
Describe your services and traffic. We'll tell you whether Kubernetes fits, what the alternatives look like and what each would take to run.