Observability
Metrics, logs and traces that help teams understand cluster and application behavior.
Kubernetes practice / Berlin
Operate Kubernetes responsibly for research-led technology in Berlin.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together. In Berlin, this connects directly to platform paths that let product teams scale without repeated setup.
What this practice covers
What Kubernetes covers
Kubernetes work spans platform architecture and the operational details that determine whether workloads remain understandable in production.
Kubernetes priorities in Berlin
German organizations frequently combine exacting operational standards, established enterprise systems and European governance requirements with pressure to modernize delivery.
Berlin's startup, digital, healthcare, creative and mobility ecosystems reward fast learning. Sustainable growth depends on turning that learning into repeatable platforms and clear operational practices.
Digital technology, healthcare, mobility, media, energy technology and modern manufacturing each create different paths from experiment to production.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together.
- Workload boundary
- Platform paths that let product teams scale without repeated setup
- Cluster control
- Data and AI evaluation suited to health and digital products
- Day-two operation
- Reliability practices that mature alongside growing services
What that gives your team
- Workload-fit clusters
- Repeatable delivery
- Operational confidence
Cluster architecture
Networking, control-plane, node and tenancy choices for the workload mix.
Workload migration
A staged path for packaging, deployment and validation.
GitOps delivery
Desired-state workflows with reviewable changes and recovery options.
Security and policy
Identity, secrets, admission and workload boundaries made explicit.
Data on Kubernetes
Database and storage concerns addressed with operational context.
How it works
How Kubernetes work moves
Reliable Kubernetes work joins platform design with the application and operating practices around it.
01
Inventory
Map workloads, dependencies, traffic, storage and team ownership.
02
Design
Choose cluster and workload patterns that fit the reliability and delivery needs.
03
Migrate
Move representative workloads with observable checkpoints and rollback options.
Engagement models
Choose how we work together
Engagements can isolate risk in a defined workstream, support an internal platform group or provide accountable delivery around a larger German transformation programme. For Kubernetes, the initial scope should stay anchored to platform paths that let product teams scale without repeated setup.
ConsultingADVISORY
Opinions, reviews, and focused direction.
ExploreStaff AugmentationEMBEDDED
Ongoing capacity in your engineering team.
On-Call SupportON-CALL
Incidents, rotations, and production response.
OutsourcingDELIVERY
Roadmaps with clear delivery ownership.
SolutionsPROJECT
Plan and deliver a defined technical outcome.
SupportCARE
Ongoing engineering care and improvement.
Questions answered
Kubernetes questions, answered
A short set of practical questions to clarify the first conversation.
How should research and experimentation workflows shape Kubernetes work in Berlin?
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together. Scope should begin with the systems, owners and evidence connected to platform paths that let product teams scale without repeated setup.
Do you work with existing Kubernetes clusters?
Yes. The first step is understanding the current workloads, constraints and ownership before deciding whether to tune, migrate or redesign.
Does Kubernetes work include application changes?
It can include packaging, configuration and delivery changes needed to operate the workload, with boundaries agreed for the engagement.
Can Kubernetes include database workloads?
The existing CloudNativePG service provides evidence for PostgreSQL on Kubernetes; database-specific scope remains explicit.
Is Kubernetes On-Call Support currently offered?
No public On-Call route is currently offered. The category contains a draft model record only until coverage evidence exists.
Next step
Clarify the next Kubernetes improvement in Berlin.
Start with platform paths that let product teams scale without repeated setup and the technical or organizational boundary that makes it difficult today.