Observability
Metrics, logs and traces that help teams understand cluster and application behavior.
Kubernetes practice / Munich
Operate Kubernetes responsibly for research-led technology in Munich.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together. In Munich, this connects directly to governed data flows for mobility, research and regulated services.
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 Munich
German organizations frequently combine exacting operational standards, established enterprise systems and European governance requirements with pressure to modernize delivery.
Munich teams often combine physical products, specialist research and long-lived enterprise platforms. Successful modernization creates safe interfaces between those worlds and evidence for every important change.
Automotive, advanced manufacturing, insurance, aerospace and deep technology demand traceability across both software and physical systems.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together.
- Workload boundary
- Digital platforms aligned with industrial and product lifecycles
- Cluster control
- Governed data flows for mobility, research and regulated services
- Day-two operation
- Repeatable delivery with strong verification and rollback paths
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 governed data flows for mobility, research and regulated services.
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 Munich?
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 governed data flows for mobility, research and regulated services.
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 Munich.
Start with governed data flows for mobility, research and regulated services and the technical or organizational boundary that makes it difficult today.