Application delivery platforms
Namespaced workloads, ingress, services, configuration, secrets, autoscaling, policies, deployment standards, and developer workflows.
Built with Kubernetes
Kubernetes only when orchestration value exceeds platform complexity.
Automiq designs Kubernetes delivery for organizations whose workload count, portability, scaling, policy, or platform standards justify a cluster—and recommends simpler container hosting when they do not.
Kubernetes versions, cloud distributions, add-ons, APIs, and support windows change; the current target platform and supported component lifecycle govern delivery.
Product outcome
Existing systems
Data & constraints
Kubernetes
Fit-for-purpose design
Production controls
Owned handover
- Architecture choice
- Fit-first
- The platform must earn its place against alternatives
- Supported interfaces
- Current
- Versions, regions, APIs, and policies are verified during delivery
- Production behavior
- Operable
- Security, quality, cost, failures, and recovery remain visible
- Handover objective
- Portable
- Agreed code, access, decisions, tests, and runbooks transfer
What we build
Production systems Automiq can build with Kubernetes.
The technology supports a business or product outcome; it is not the outcome by itself.
AI and worker platforms
APIs, queues, background workers, scheduled jobs, model services, resource classes, and observable batch or online workloads.
Cluster modernization and reliability
Audit, upgrade, simplify, secure, standardize, monitor, recover, and document existing Kubernetes environments.
Best-fit use cases
When Kubernetes is a credible choice.
Fit follows workload, data, team, procurement, delivery stage, and operating responsibility—not a preferred agency stack.
Many container workloads need shared orchestration
Teams benefit from consistent deployment, networking, policy, scaling, and operational conventions.
Platform portability has a concrete reason
Cloud, region, customer, or workload requirements justify a common orchestration API and its costs.
A capable platform owner exists
The organization can own clusters, add-ons, security, upgrades, incidents, capacity, and developer experience.
When not to use it
- A handful of services can run reliably on a managed container platform.
- No team has time or skill to own cluster and add-on lifecycle.
- Kubernetes is being adopted as a status signal instead of solving a measured platform problem.
Architecture pattern
How Kubernetes fits into a complete production system.
The diagram exposes the surrounding application, data, control, and operating layers that a logo wall usually hides.
- Stage 01
Platform boundary
- Cluster, environment, and namespace model
- Identity, network, policy, and secrets
- Supported distribution and add-on lifecycle
- Stage 02
Workload delivery
- Images, manifests, and deployment templates
- Services, ingress, jobs, and configuration
- Resource requests, limits, health, and scaling
- Stage 03
State & dependencies
- Managed databases and queues where appropriate
- Storage classes and backup boundaries
- External APIs, DNS, and certificates
- Stage 04
Operations
- Metrics, logs, traces, events, and alerts
- Upgrade, capacity, cost, incident, and recovery
- Developer documentation and platform handover
Integration options
Connect through explicit interfaces and ownership boundaries.
Integration choices are evaluated for identity, source ownership, data contracts, failure behavior, supported APIs, and long-term operations.
Managed Kubernetes service
Use a supported cloud control plane while retaining ownership of nodes, workloads, add-ons, security, cost, and upgrades as applicable.
CI/CD or GitOps workflow
Connect versioned workload definitions, policy checks, environments, approvals, progressive delivery, and rollback.
External managed data services
Keep databases, queues, storage, and identity outside the cluster where managed reliability and ownership are stronger.
Production controls
Security, cost, quality, and handover are part of the implementation.
Controls scale with failure consequence, data sensitivity, usage, and the people responsible after release.
Security and access
Least-privilege workload identity, network policy, secret handling, admission controls, image policy, tenant boundaries, and audit.
Performance and cost
Requests, limits, autoscaling, node pools, scheduling, utilization, storage, egress, observability volume, and idle platform overhead.
Testing, observability, and handover
Manifest and policy tests, deployment probes, platform telemetry, upgrade rehearsal, recovery exercises, capacity reviews, and runbooks.
Deployment models
Ways Kubernetes can fit the operating environment.
Current vendor support, region, procurement, identity, team capability, and recovery objectives determine the final route.
Managed cloud Kubernetes
Useful when cloud integrations and supported control-plane operations fit procurement, region, and platform skills.
Shared internal platform
Useful when multiple teams need governed self-service delivery and a dedicated platform function owns it.
Special-purpose cluster
Useful for a bounded AI, edge, regulated, or customer environment when isolation and workload needs justify dedicated operations.
Regional platform context
Kubernetes availability and terminology must match the market.
Vendor features, hosting locations, commercial terms, legal entities, supported interfaces, and model or service availability can differ by country and region.
Regions and residency
Validate which Kubernetes services are available in the required geography, where data and logs move, and which recovery region is permitted.
Localization layer
Design locale, language, dates, time zones, addresses, phone formats, currency, tax, units, accessibility, and right-to-left behavior where the product requires them.
Procurement and operations
Confirm account ownership, billing currency, provider terms, support route, service limits, deprecation policy, release windows, and international team overlap.
Alternatives
Compare Kubernetes with the closest credible options.
The decision guide explains when another model, framework, cloud, platform, or simpler approach may be better.
| Option | Best when | Main tradeoff |
|---|---|---|
| Kubernetes | Workload breadth, platform standards, policy, scaling, or portability justify sustained orchestration ownership. | Powerful control with significant platform and upgrade complexity. |
| Managed container service | Teams need container deployment and scaling without operating a cluster ecosystem. | Lower overhead with fewer orchestration and portability controls. |
| Serverless or application platform | Workloads fit supported limits and product speed matters more than runtime control. | Simplest operations with stronger platform constraints. |
Delivery stages
From architecture evidence to an operable handover.
The method is adapted to the platform and project size. A bounded integration uses lighter ceremony than a cloud migration, but the control points remain.
- 01
Scope & discovery
Map users, workflows, constraints, success measures, and the smallest valuable production milestone.
Outcome: Prioritized scope and delivery plan
- 02
Data & architecture
Audit systems, integrations, data quality, security boundaries, and the architecture the future team can maintain.
Outcome: Architecture and risk register
- 03
Prototype & evaluate
Test the riskiest assumptions against representative data, measurable acceptance criteria, and real user feedback.
Outcome: Evidence-based go or adjust decision
- 04
Build & integrate
Ship in reviewable increments with testing, access controls, observability, documentation, and clear ownership.
Outcome: Production-ready software
- 05
Deploy & hand over
Release progressively, monitor real usage, train operators, and transfer repositories, infrastructure, and runbooks.
Outcome: Controlled launch and clean handover
- 06
Support & grow
Maintain reliability, refine workflows, manage dependencies, and keep shipping as the product and business evolve.
Outcome: A stable platform that keeps improving
Timeline and investment context
Scope follows the production responsibility—not a technology label.
Automiq does not publish a universal duration or price for technology implementation. Discovery identifies a bounded milestone and the risks that shape it.
Platform and tenant depth
Clusters, environments, namespaces, identity, policy, networks, and developer workflows determine setup.
Reliability and lifecycle
Availability, upgrades, backups, capacity, regions, add-ons, incidents, and recovery create ongoing work.
Baseline operating cost
Control plane, nodes, idle capacity, logs, security, support, and platform-team time exist before application traffic.
Third-party platform, model, cloud, hosting, data, support, app-store, and usage charges remain separate unless an engagement agreement explicitly includes them.
Relevant experience
Product context behind the technology decisions.
ATZ CRM supplies founder-led production context for SaaS delivery, workloads, monitoring, support, and reliability decisions. The page does not claim Kubernetes was used without supporting evidence.
Product visual
founded
ATZ CRM
Recruitment · B2B SaaS experience involving AI, Web app, Workflow automation, CRM integrations.
- Recruitment
- B2B SaaS
Related technologies
Continue through the same architecture neighborhood.
Explore adjacent tools without treating every layer as mandatory.
delivery
Docker
Docker application containerization and production delivery
Explore DockerQuestions, answered
Kubernetes development questions, answered
Direct answers about fit, alternatives, architecture, access, operations, ownership, and handover.
Does our product need Kubernetes?
Often not. A managed container or application platform is usually better until workload count, policy, scaling, platform standards, or portability justify continuous cluster ownership.
Can Automiq audit an existing Kubernetes platform?
Yes. The audit can cover workload definitions, identity, network, secrets, images, policies, resources, autoscaling, reliability, observability, cost, upgrades, backups, and ownership.
Should databases run inside Kubernetes?
Sometimes, but managed external databases are often operationally safer for general product teams. The decision follows stateful expertise, recovery, performance, portability, policy, and cost.
Does Automiq claim an official vendor partnership for this technology?
No official vendor partnership or certification is claimed on this page. Automiq is an independent engineering company; any future partner status should be published only with current supporting evidence.
Who owns the application and handover materials?
Ownership is finalized in the engagement agreement. The intended custom-build model hands over the agreed source code, configuration, infrastructure access, architecture decisions, tests, documentation, and operating runbooks. Third-party platforms retain ownership of their own services.
Talk to the engineering team
Discuss a Kubernetes requirement with the engineering team.
Bring the product, workflow, current stack, constraints, and expected operating model. We will help determine whether this technology is the right fit and define the first useful milestone.