Kubernetes consulting – from cluster design to operations.

Kubernetes consulting: when Kubernetes pays off – and when it doesn't

Kubernetes consulting starts with the question of whether Kubernetes is the right platform for your application at all. Kubernetes is an orchestration system for containers: it starts applications across several servers, replaces failed instances automatically, spreads load and rolls out new versions step by step. That pays off when several services work together, when load fluctuates strongly or when releases need to be automated and highly available.

It comes with effort that is easy to overlook in planning. Networking, storage, permissions, certificates and regular version upgrades are part of every cluster and need people who understand them. For a single application with modest load, a well-run server or a managed container service is therefore often the simpler solution. We'll tell you honestly in the intro call.

We support Kubernetes projects from cluster design to operations. Kubernetes consulting is one of four services you get from ByteFactory from a single source.

Managed Kubernetes (EKS, AKS, GKE) or self-hosted?

With managed Kubernetes, the provider runs the control plane: the API server, the scheduler and the etcd database. You remain responsible for everything above it: networking, permissions, applications and, depending on the offering, the worker nodes. Managed offerings take part of the operational burden off your hands.

A self-hosted cluster runs on servers in an EU data center or on your own hardware and gives you full control and full data sovereignty. In return, etcd backups, certificates, control-plane upgrades and handling control-plane failures become the job of your team or your service provider. For a few small clusters this effort weighs heavily. For large or strictly regulated environments, self-hosting can be cheaper or make requirements achievable in the first place.

Which option fits depends on your requirements for cost, data protection and operations, not on a preference for a product. We compare both options against these criteria and put the result in writing before anything is built. When building and running clusters, we rely on infrastructure as code and GitOps deployments so the cluster is reproducible rather than hand-crafted. With GitOps, the desired state lives in a Git repository, which makes changes traceable.

Security: RBAC, policies and the supply chain

A freshly installed cluster is not hardened automatically. Without network policies, for example, all pods may talk to each other, and Kubernetes secrets are only Base64-encoded by default, not encrypted.

RBAC (role-based access control) defines who may do what in the cluster. Following the principle of least privilege, users and services get only the permissions their task requires. Network policies define which applications may talk to each other. They only take effect if the network plugin in use enforces them. Secrets belong encrypted or in an external secrets-management system, not in plain text in a repository. Resource limits prevent a faulty service from consuming the capacity of an entire node.

Then there is the supply chain. A container image is attack surface too: outdated base images and known vulnerabilities in dependencies are typical entry points. Vulnerability scans, slim base images and signed images whose signature the cluster verifies before starting them all help. With a suitable admission policy, images without a valid signature can be blocked from being deployed at all.

For us, security is part of the build, not a later project: least-privilege RBAC, network policies, properly managed secrets, resource limits and verified container images belong to it.

Operations: monitoring, upgrades and costs under control

Monitoring collects metrics and logs from nodes, pods and applications. Alerting reports when something deviates from target values. Alerts on symptoms users would feel, such as error rates and response times, make more sense than alerts on raw values like CPU utilization alone. That way problems surface before customers notice them.

Upgrades are mandatory, not optional: the Kubernetes project publishes new minor versions several times a year and maintains only the most recent ones with security patches. The goal of an upgrade strategy is a version change without downtime. That takes several replicas per service, health checks, pod disruption budgets and a tested way back.

Costs are part of operations as well. Generously oversized resource requests reserve capacity nobody uses, and idle nodes cost money all the same. Realistic requests and limits, autoscaling and a view of costs per namespace or team keep the cluster economical. In the end there is either operations by us or a clean handover to your team, including documentation.

Kubernetes with GDPR and EU regions in mind

Kubernetes is first of all just a platform. The applications on it process personal data, and logs too can contain IP addresses or user identifiers. The GDPR question is therefore decided by location and contract: in which region do nodes, volumes, backups and the container registry run? Who processes the data on your behalf? As soon as a service provider processes personal data for you, a data processing agreement under Article 28 GDPR is required.

All three major managed offerings provide regions in the EU. You choose the region at setup, and data only stays in the EU if backups, logs and registries are located there too. If a provider belongs to a group outside the EU, you should clarify with your data protection officer whether transfers to third countries play a role.

Whether a setup is GDPR-compliant overall also depends on organizational and contractual points that you, as the controller, have to settle. If the first step is moving existing systems, we describe the approach under cloud migration.

How working together runs

The start is a free 30-minute intro call with the engineer who will also run your cluster. Tell us briefly which applications are to run and where they are operated today.

Week 1 is the assessment: we understand workloads, requirements and the existing infrastructure. Week 2 brings the architecture, meaning target design, costs and migration path, in writing, before anything is built. After that we set up the cluster, move applications step by step and involve your team. How long this takes depends on the number and complexity of the applications. Then we take over operations, including monitoring, upgrades and further development, or hand over cleanly to your team.

We take over existing clusters after an assessment of configuration, security and deployments, or tell you plainly if a rebuild is cheaper.

We also run websites ourselves: how we develop and host them is described under website development.