Observability
Metrics, logs and traces that help teams understand cluster and application behavior.
Kubernetes practice / Hamilton
Operate Kubernetes responsibly for research-led technology in Hamilton.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together. In Hamilton, this connects directly to integration between research, operational and business systems.
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 Hamilton
New Zealand organizations often need resilient digital services that serve a geographically distributed market while making efficient use of focused engineering teams.
Hamilton's strength in agriculture, science, education and manufacturing creates valuable data across field, laboratory and production settings. Engineering systems should preserve context as that data moves.
Agriculture, food production, machinery, education and logistics create clear opportunities for connected data and maintainable automation.
Kubernetes can provide repeatable compute environments for data and research workloads when scheduling, storage and production handoff are designed together.
- Workload boundary
- Trusted data paths from field and production environments
- Cluster control
- Integration between research, operational and business systems
- Day-two operation
- Practical cloud delivery for focused industrial teams
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
A compact consulting or delivery team can address a defined constraint while transferring decisions and operating knowledge back to New Zealand stakeholders. For Kubernetes, the initial scope should stay anchored to integration between research, operational and business systems.
ConsultingADVISORY
Opinions, reviews, and focused direction.
ExploreStaff AugmentationEMBEDDED
Ongoing capacity in your engineering team.
ExploreOn-Call SupportON-CALL
Incidents, rotations, and production response.
ExploreOutsourcingDELIVERY
Roadmaps with clear delivery ownership.
ExploreSolutionsPROJECT
Plan and deliver a defined technical outcome.
ExploreSupportCARE
Ongoing engineering care and improvement.
ExploreQuestions 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 Hamilton?
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 integration between research, operational and business systems.
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 Hamilton.
Start with integration between research, operational and business systems and the technical or organizational boundary that makes it difficult today.