Autoscaling
The number of instances of a service and the size of the cluster adjust to the load, based on standard or application-specific metrics.
Expertise · Kubernetes
Kubernetes Consulting: Reliable, Operable Cloud-Native Platforms
Kubernetes orchestrates containerized applications when running them requires structured management of deployments and resources. Our teams set it up and operate it for the products they build or take over, including AI services, when the complexity is justified.
Understanding the technology
Kubernetes in your project.
Kubernetes orchestrates containerized applications: scheduling, deployment and maintaining a declared state. It provides mechanisms to organize services and their resources, but requires specific operational capabilities. We consider it when the application’s needs justify that complexity.
The benefits for your product
Why choose Kubernetes?
Self-healing
A failing container is restarted, a lost instance is replaced; health probes take anything that stops responding out of the traffic.
Service discovery
Internal DNS and load balancing simplify communication between services.
Zero-downtime updates
Rolling deployments, rollbacks and blue/green or canary strategies limit the risk of each production release.
Resource control
CPU and memory requests and limits, priorities and workload placement prevent one service from penalizing another.
Portability
Kubernetes runs on AWS (EKS), Microsoft Azure (AKS), GCP (GKE) or on premises.
What we cover
The work we take on.
Deployment
Describe services, configurations and update strategies.
Availability
Organize probes, resources and recovery mechanisms.
Operations
Track logs, metrics and access while keeping the cluster’s complexity under control.
Our Kubernetes expertise
The Kubernetes ecosystem we master.
Kubernetes core
Pods, Services, Deployments, ConfigMaps and Secrets; Helm and Kustomize to describe deployments, GitOps with Argo CD.
Networking & ingress
CNI plugins (Calico, Flannel), ingress controllers (NGINX, Traefik, HAProxy) with TLS and routing, network policies; service mesh (Istio, Linkerd) when the context justifies it.
Storage & data
Persistent Volumes and CSI drivers, StatefulSets, database operators (PostgreSQL, MySQL, MongoDB).
Observability
Prometheus, Grafana and Alertmanager for metrics, EFK for logs, Jaeger and OpenTelemetry for tracing.
Kubernetes relies on well-built images; see our Docker expertise.
Kubernetes and AI
Hosting and operating AI services.
AI services have specific load profiles: long-running model calls, batch document indexing jobs, and sometimes self-hosted models that require dedicated resources. Kubernetes makes it possible to separate these workloads, size them and track their consumption, provided the product justifies a cluster.
Our teams add what production requires: model provider secrets, resource limits, monitoring of response times and costs. See our AI solutions for business.
In the field
From technology to real-world use.
For a set of services that are already containerized, we define deployments, configurations and health checks. Resources and update strategies are tuned to the applications’ behavior. Recovery tests verify that a restart or instance replacement does not compromise data or operations in progress.
The choices that matter
The choices to examine before building.
A cluster does not remove dependencies on a database, storage or an external service. We review maintenance responsibilities, access, observability and costs. A simpler platform may be preferable if the product does not need this orchestration and the team will not maintain it.
From work to deliverables
Delivered work your team can take over.
The scope of the engagement specifies the components to build or take over and the acceptance criteria. We prepare what is needed to understand the changes, verify them and continue the work. Cluster setup, application migration or long-term operations within a dedicated team: the format follows the need.
- Versioned configurations
- Documented delivery pipeline
- Monitoring and operating procedures
Frequently asked questions
Kubernetes: your questions.
What is Kubernetes and why use it?
Kubernetes is an open-source container orchestrator that automates the deployment, scaling and recovery of applications. It suits architectures made up of several services that need to stay available.
Is Kubernetes right for our application?
Not always. It is justified when several services need to be deployed, scaled and kept available, and a team will be responsible for operating it. For a simple application, a lighter managed platform is often preferable.
What is the difference between Kubernetes and Docker Swarm?
Kubernetes is more feature-rich and has a large ecosystem. Docker Swarm is simpler and built into Docker, suited to modest deployments.
Is Kubernetes complex to manage?
Yes, the learning curve is real. Managed offerings (EKS, AKS, GKE), GitOps with Argo CD and tools such as Helm or Kustomize reduce this complexity, without removing the need for ongoing operations.
How much does Kubernetes cost?
The cost depends on the control plane (often billed in managed offerings), compute nodes, storage and operations time. Right-sizing, autoscaling and discounted instances help keep it under control.
Can you run databases on Kubernetes?
Yes, with StatefulSets, persistent volumes and dedicated operators that automate deployment, backup and scaling. A database managed by the cloud provider is often simpler to operate.
What are the security best practices?
RBAC and least privilege, network policies, Pod Security Standards, image scanning, secret encryption, regular updates and audit logs.
How do you monitor applications on Kubernetes?
Prometheus and Grafana for metrics, a centralized logging stack, Jaeger or OpenTelemetry for tracing, and targeted alerts with Alertmanager.
Can AI services be deployed on Kubernetes?
Yes. We separate services that call models from batch jobs, set their resources and monitor response times and costs, as part of taking an AI service to production.
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the initial scope of work with your team.