Private, instructor-led training for SRE and platform engineers who need to connect service-level symptoms with Kubernetes investigation, recovery, and controlled changes.
A dashboard or objective does not select the next useful action. Client behavior, workload signals, and dependency evidence can disagree, especially during a release or incident.
LearnKube connects the mechanisms behind those observations to an illustrative service objective. Engineers investigate a failure, justify an intervention, and identify the evidence needed to confirm recovery.
Hands-on learning and the skills engineers take back to work.
Preview: course-wide figures are not yet available.
The team already measures reliability, but service-level indicators describe selected user outcomes rather than every Kubernetes condition. Readiness probes influence workload traffic without proving that the service meets those outcomes. Engineers must connect the two levels of evidence before they select a recovery action or decide whether the observed conditions support the next change.
I ask what the user can do again before accepting a recovery report. Green Pods can coexist with failed requests or unusable results, so the service observation must remain visible while the infrastructure explanation is tested.
— Daniele Polencic, LearnKube founder and Kubernetes instructor
| Production question | Mechanism to understand | Practice |
|---|---|---|
| Which user outcome changed? | Service indicators and coverage | Define a representative observation |
| Which mechanism explains it? | Workload and dependency behavior | Compare evidence across layers |
| Is the intervention justified? | Change and recovery criteria | Review a bounded action |
| What prevents recurrence? | Technical incident learning | Record a repeatable check |
Everbridge's production operating responsibilities include Kubernetes and AWS services, SLOs, observability, incident management, release decisions, and recovery rehearsals.
For the Kubernetes decisions within that work, we recommend a four-day workshop connecting service symptoms to mechanisms and evidence. The focus is technical operating capability rather than a complete organizational SRE program.
We use one service and a clearly stated operating objective. Existing organizational policies provide context, while the practical work concerns the evidence behind Kubernetes actions.
Day 1
Explain probes, rollout behavior, and application responses. Establish a service observation that can disagree with otherwise healthy infrastructure status.
Hands-on exercises
Day 2
Connect rendered resources, controller decisions, and architecture to a service symptom. Build an explanation that can be checked rather than selected by familiarity.
Hands-on exercises
Day 3
Examine DNS, routing, policy, placement, and downstream service behavior. Separate application pressure from an inaccessible or saturated dependency.
Hands-on exercises
Day 4
Connect storage, identity, scaling, and access to the service objective. Verify the recovery observation and turn the investigation into a concrete operating improvement.
Hands-on exercises
Your service objectives, incident questions, and operating responsibilities can shape the agenda. Get in touch to tailor the workshop to your team's work.
When an engineer reports healthy resources, the instructor can ask for the user-facing observation that completes the explanation. Asked what he valued in another course, Jim described its teaching format:
Breakup between labs and classroom instruction.
— Jim, SRE at Rebellion Defense.
Tell us which Kubernetes services you operate, which incident or change decisions remain uncertain, and which responsibilities your team owns. We will recommend technical mechanisms and representative operating exercises.