Container packaging
Define reproducible images, non-root execution where practical, dependency handling and externalized configuration.
Docker & Kubernetes Containerization
Docker & Kubernetes Containerization
Package and operate applications in containers where portability, deployment consistency or workload orchestration justifies the added platform responsibility.
Inside the delivery
From application dependencies to an operable workload
Separate stateless processes from persistent data and identify network, storage and startup dependencies. The flow below shows the main delivery stages and the evidence produced at each step.
- 01
Runtime assessment
Separate stateless processes from persistent data and identify network, storage and startup dependencies.
Output
Workload and dependency map
- 02
Image and registry
Build versioned images with external configuration, a defined base-image update policy and registry access controls.
Output
Dockerfiles and image build instructions
- 03
Workload configuration
Define probes, resource requests, secrets access and rollout settings for the chosen runtime.
Output
Deployment manifests and configuration notes
- 04
Recovery rehearsal
Exercise failed probes, restarts and rollback; document backup and restore responsibilities for persistent data.
Output
Recovery evidence and cluster ownership runbook
Controls across the workflow
- Image provenance
- Runtime permissions
- Resource limits
- Upgrade ownership
Decisions that shape the scope
- Do we need Kubernetes to use containers?
- No. A managed container runtime may be sufficient. Kubernetes is justified when scheduling, networking or platform requirements outweigh its upgrade and operational overhead.
- What needs to be available before delivery?
- Application dependencies, persistent stores, traffic patterns, registry access and the team responsible for cluster operations.
Before you commit
Is this the right engagement?
- What we need from you
- Application dependencies, runtime requirements, stateful services, traffic profiles and existing platform ownership.
- How you accept the work
- Build a reproducible image and test probes, resource limits, restarts, configuration and rollback under representative load.
- Scope & alternatives
- No. A managed container runtime may be sufficient. Kubernetes is justified when scheduling, networking or platform requirements outweigh its upgrade and operational overhead.
Capabilities
Engineering scope and deliverables
Select the work that addresses your constraint. Responsibilities and acceptance criteria are agreed before delivery.
Workload orchestration
Configure scheduling, health probes and resource requests with clear treatment of persistent state and service dependencies.
Platform handover
Document deployment, diagnostic and recovery procedures alongside responsibility for cluster upgrades and security maintenance.
Integrations
Selected for your environment
Tools are chosen around your existing systems, access requirements and operating constraints.
Microsoft Azure
AWS
Docker
Kubernetes
GitHub Actions
Terraform and infrastructure tooling
Frequently asked questions
Questions to resolve before starting
01Do we need Kubernetes to use containers?
Do we need Kubernetes to use containers?
No. A managed container runtime may be sufficient. Kubernetes is justified when scheduling, networking or platform requirements outweigh its upgrade and operational overhead.
02What should we prepare for the first technical discussion?
What should we prepare for the first technical discussion?
Application dependencies, persistent stores, traffic patterns, registry access and the team responsible for cluster operations.
03What evidence is available at handover?
What evidence is available at handover?
The agreed delivery includes recovery evidence and cluster ownership runbook. Exercise failed probes, restarts and rollback; document backup and restore responsibilities for persistent data.
04How is the engagement estimated?
How is the engagement estimated?
We review the available inputs before estimating: Application dependencies, persistent stores, traffic patterns, registry access and the team responsible for cluster operations. The proposal identifies dependencies, review milestones and excluded work; the scope determines the schedule.
Start a conversation
Discuss your next technical step
Share your current situation and the constraint you need to resolve. We will use the discovery inputs above to define a practical scope for Docker & Kubernetes Containerization.