From legacy Azure infrastructure to a Kubernetes platform

Private, instructor-led training for DevOps and integration engineers who need to move Azure-hosted services onto a shared Kubernetes platform.

Your team already knows how each service runs. A shared platform needs consistent release processes, clear access rules, and resource controls for services with different needs.

LearnKube connects those requirements to Kubernetes through a sample integration service. Your engineers will practice repeatable releases, dependency access, and diagnosis within a shared cluster.

Discuss your team's training

Learning in practice

Hands-on learning and the skills engineers take back to work.

Preview: course-wide figures are not yet available.

Hands-on learning
60%
Of instruction time spent on labs and challenges.
Troubleshooting confidence
86%
Of respondents report greater confidence diagnosing Kubernetes problems.
Relevant to your work
92%
Of respondents say the course addressed their engineering responsibilities.
Skills put into practice
95%
Of respondents applied their new skills at work within 90 days.

Make the shared platform usable for service teams

Deploy an integration service by defining workloads, configuration, and release templates, so another engineer can repeat the deployment.
Preserve service boundaries by applying access rules, network policies, and resource controls, so shared infrastructure supports each service's requirements.
Diagnose failed integrations by tracing DNS, endpoints, and credentials, so engineers distinguish application problems from platform restrictions.
Define the self-service boundary by documenting permitted changes and escalation paths, so service teams know what they can operate independently.

Replace service-specific procedures with shared patterns

Azure-hosted services can depend on different deployment scripts, identities, and infrastructure configuration. A shared Kubernetes platform uses common APIs for workloads, but each service keeps its own dependencies. Engineers need to separate application configuration from the platform tools that handle traffic, access, and capacity.

A namespace groups resources, but it does not automatically isolate their traffic. I want teams to prove permitted connections and API actions before they treat shared infrastructure as a secure replacement for their existing service boundaries.
— Daniele Polencic, LearnKube founder and Kubernetes instructor

Current task or requirement	New concept or decision	Practice
Release a custom service	Deployments and Helm releases	Repeat a service release
Separate integration workloads	Namespaces and network policies	Diagnose a blocked dependency
Supply service credentials	Secrets and workload identity	Trace credential delivery
Share infrastructure capacity	Resource requests and limits	Inspect resource pressure

Your team is not alone in platform standardization

Parloa's platform initiative includes a transition from legacy Azure infrastructure to a standardized Kubernetes-based platform. Its integration services need security, isolation, resource management, reusable pipelines, and self-service capabilities.

For a transition like this, engineers need shared deployment patterns that retain service-specific requirements. We recommend a four-day workshop with particular attention to release configuration, service boundaries, and dependency diagnosis.

A recommended four-day workshop for integration teams

This proposed agenda focuses on one integration service. Each day introduces a platform responsibility for the service team to learn.

Day 1

Turn a service into a Kubernetes workload

We show how container configuration relates to Pods, Deployments, Services, and probes. You will compare release behavior and see how readiness affects traffic during updates.

Hands-on exercises

Deploy a sample integration service with its runtime configuration.
Introduce a release that fails readiness and restore the previous version.

Day 2

Build repeatable release configuration

You will compare Helm and Kustomize for shared deployment patterns. We explain cluster architecture, reconciliation, and where service configuration ends and platform components begin.

Hands-on exercises

Create a reusable Helm chart with environment-specific values.
Simulate a node failure and inspect how the service recovers.

Day 3

Connect services across boundaries

We explain DNS, Services, ingress, and network policies along the application's traffic path. You will discuss service mesh use cases and placement controls for shared nodes.

Hands-on exercises

Trace a request from ingress through the integration service to a dependency.
Diagnose a network policy that blocks required communication.

Day 4

Manage state, demand, and access

You will connect secrets, persistent storage, and autoscaling to service requirements. We explain authentication and RBAC as the basis for application-team access.

Hands-on exercises

Configure credentials and persistent data for the integration service.
Apply load and inspect autoscaling behavior alongside resource limits.

Your integration services, Azure dependencies, and platform-support responsibilities can shape the agenda. Get in touch to tailor the workshop to your shared Kubernetes platform adoption.

Turn platform rules into understandable decisions

If an engineer thinks a namespace blocks all cross-team traffic, the instructor can show how connections between namespaces behave. The team can then apply a network policy and discuss the separate role of RBAC.

The instructor Salman was very knowledgable and engaged, and made sure to cover specific topics that were relevant to our expectations from what we would learn from the course.
— Isaac, GIS Developer at EIFER.

Start with one integration service

Tell us how your Azure services run, which capabilities the Kubernetes platform will provide, and who will support each layer. We will recommend exercises around your release and access requirements.

Discuss your team's training