Kubernetes where you need it
Platform choice starts with your applications, data requirements and your team's ability to operate it. We work with Kubernetes on your own infrastructure, in the cloud and in hybrid architectures.
On your own infrastructure
VMware vSphere Kubernetes Service (VKS), Red Hat OpenShift and Rancher. We support architecture definition, implementation and integration with networking, storage, identity and operational services.
In the cloud
Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS) and Google Kubernetes Engine (GKE). We design the environment and its integration with cloud services, defining what the provider manages and what your organisation must operate.
When several environments coexist
We define common deployment, access and observability criteria. We assess each application's dependencies before moving it: using Kubernetes does not make every platform interchangeable without adaptation.
Implementation and migration with a clear plan
You may need a new platform, to evolve an existing one or to move applications between distributions and providers. We begin by reviewing workloads, versions, dependencies and continuity requirements.
- Assessment and architecture. Current state, target platform and action priorities.
- Implementation and integration. Configure clusters, networking, storage, identity and shared components.
- Application migration. Review manifests, persistent data, operators and integrations, with testing before the change.
- Production rollout. Intervention plan, checks and rollback procedure agreed with your team.
The scope includes the documentation and knowledge transfer defined for the project. Change windows and acceptance criteria are tailored to each environment.
Operations begin with design
A platform needs maintenance after its first deployment. We include operations in the project so your team has procedures and visibility over the service.
- Monitoring and observability: metrics, logs and alerts to detect and analyse incidents.
- Backup and recovery: application and data protection, with restoration tests within the agreed scope.
- Updates and maintenance: compatibility reviews, planning and validation of changes.
- Security and access: roles, permissions, secrets management and network controls tailored to the environment.
- Automation: repeatable deployments and versioned configuration with CI/CD and GitOps where appropriate.
Support coverage and responsibilities are explicitly agreed. Not every team needs the same support model.
Platform Engineering and DevOps within the project
These are not separate from Kubernetes: they are part of the project when development teams need consistent platform access. We agree what to automate and who will operate each component.
- Repeatable environments: version-controlled configuration and deployment templates.
- Application delivery: integration of CI/CD, GitOps and controls agreed with the team.
- Platform services: catalogue, permissions and procedures for requesting and maintaining environments.
Deliverables are defined for each project: repositories and templates, delivery workflows, operational documentation and knowledge transfer. You can also consult the existing Platform Engineering and DevOps description; its URL is preserved.
A platform for development and AI
We connect Kubernetes with Platform Engineering and DevOps to standardise environments and simplify cloud-native application deployment. The same approach prepares services for data and AI teams.
Service catalogues your team can request
Instead of configuring every environment from scratch, we can build a catalogue with services such as:
- AI development environments, with tools and access to authorised resources, including GPUs when needed.
- Model APIs, to integrate inference into applications with quotas and metrics.
- Assistants using your own documentation, connected to defined sources and permissions.
- Agent workspaces, with controlled access to tools and integrations.
Each service is designed with identity, permissions, capacity, observability and maintenance actions. We start from the available infrastructure and prioritise an initial catalogue that can grow in stages. Implementation and dependencies are validated for each platform.
This capability connects with Private AI and infrastructure and with Nuxia Data. EstrategIA Nux helps decide which capabilities the business needs; the platform enables their deployment and operation.
Let's start with your situation
Tell us which platform you use, where it runs and what you need: implementation, migration, operational troubleshooting or AI services. We review your starting point and define the next step together.