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Containers and orchestration

Kubernetes

The standard platform for running containers at scale. Kubernetes is an open-source container orchestration platform originally designed at Google and now maintained under the Cloud Native Computing Foundation. It schedules containers across a cluster of machines, restarts failed workloads, handles service discovery and rolling updates, and scales applications. It is available as a managed service on every major cloud and can run on your own hardware.

When it is the right choice

  • You run many services that need consistent deployment, scaling and recovery
  • You need to share GPU and compute capacity across teams and workloads
  • You want the same platform across clouds or on your own servers
  • Not the right choice for one or two simple services; a managed container service or a plain VM costs less to run

How we use it

  • Build clusters with Terraform on EKS, GKE, AKS or bare metal, with GitOps through Argo CD
  • Set up monitoring, logging and alerting with Prometheus and Grafana from the first day
  • Use AI-assisted runbooks to triage alerts and propose fixes for a human to approve
  • Plan and test version upgrades on a schedule so clusters never fall behind support
Works well with

Often used together

HelmArgo CDPrometheusTerraform
Services

Where it fits in our work

Containers and orchestrationContainers and Kubernetes sized for your team, not for a giantLearn more »Infrastructure as codeEvery server, network and permission defined in code you ownLearn more »After launchInfrastructure that keeps getting cheaper, faster and safer after launchLearn more »
From the blog

Related articles

AI · November 2, 2026CI/CD for Models and PromptsEvaluation gates, model registries, canary releases and rollback: applying CI/CD discipline to prompts and models in LLM applications.AI · September 7, 2026GPU Nodes on Kubernetes Without Wasting MoneyNode pools, MIG, time-slicing, scale to zero and spot instances: practical ways to keep Kubernetes GPU costs under control for AI workloads.AI · August 27, 2026vLLM vs Ollama vs TGI: Choosing an Inference ServerHow vLLM, Ollama and Hugging Face TGI differ in throughput, hardware support and operations, and which one fits your workload.
Questions

Kubernetes: frequently asked

Do we need Kubernetes?

Only if the operational benefits outweigh the effort. For a small number of services, Amazon ECS, Cloud Run or a well-managed VM is often simpler; we recommend what fits.

Managed Kubernetes or self-managed?

Managed services such as EKS, GKE and AKS take the control plane off your hands and suit most teams. Self-managed makes sense on your own hardware or with special requirements.

Running Kubernetes, or deciding whether to? Tell us what you have; the first consultation is free.

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