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Training Karpenter - Optimize AWS Kubernetes Clusters

Ref: PNO799
10 people max.
5250€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master the installation of Karpenter to scale EKS nodes in enterprise settings
  • Develop custom NodePools and intelligent provisioning policies
  • Optimize CPU/memory allocation with automatic workload consolidation
  • Implement monitoring and debugging of Karpenter in production
  • Integrate Karpenter into CI/CD pipelines for certified deployments
  • Design scalable architectures that reduce professional cloud costs

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Karpenter Fundamentals: Installation and Initial Configuration (Helm, EKS IAM, manifests)

Quick installation of Karpenter via Helm on an existing EKS cluster, configuration of IAM roles and AWS providers, creation of initial basic NodePools, manual provisioning tests of Spot and On-Demand nodes, practical exercises on a simulated enterprise workload, validation of logs and metrics to confirm successful deployment, obtaining a cluster ready for professional autoscaling.

Module 2Advanced Karpenter NodePools: Customization and Reactive Scaling (taints, labels, hardware requirements)

Definition of advanced NodePools with taints, labels, and specific CPU/memory constraints, implementation of scaling based on real-time pod requests, exercises on concrete cases like stateful and stateless applications, simulation of load spikes to test responsiveness, adjustment of parameters for optimal resource allocation, production of reusable manifests for your enterprise projects.

Module 3Karpenter Consolidation: Cost Optimization and Densification (disruption budgets, drift detection)

Activation of consolidation policies to merge under-utilized pods, configuration of disruption budgets to minimize interruptions, live detection and correction of node drift, practical workshops on reducing idle nodes wasting cloud budgets, analysis of AWS cost impacts with integrated calculator, creation of quantified optimization plans applicable immediately in professional production.

Module 4Karpenter Monitoring: Monitoring and Alerting (Prometheus, Grafana, CloudWatch logs)

Integration of Karpenter metrics with Prometheus and Grafana for custom dashboards, setup of alerts on provisioning failures and abnormal costs, in-depth exploration of logs via CloudWatch and kubectl logs, debugging exercises on real error scenarios like exhausted quotas or unavailable instance types, development of proactive alert rules, export of reports for certifying enterprise audits.

Module 5Advanced Karpenter Integration: CI/CD and Production (GitOps, ArgoCD, high availability)

Integration of Karpenter with ArgoCD for automated GitOps, securing high availability with multiple providers, end-to-end tests on a simulated production cluster, integration into Jenkins or GitHub Actions pipelines, code review on the optimized ongoing project, delivery of ready-to-use templates and rollout plan for your professional environments, final evaluation of acquired skills.

Evaluation method

  • Technical MCQ on Karpenter and Kubernetes at the end of the training
  • Practical evaluation via an autoscaled ongoing project
  • Oral defense of the optimizations performed in front of the expert trainer

Learning method

  • Sessions led by a certified active DevOps trainer
  • Hands-on exercises on real EKS clusters and enterprise cases
  • Progressive ongoing project with individualized code review
  • Complete digital course materials and open-source resources

Methods, materials and delivery

The Training Karpenter - Optimize AWS Kubernetes Clusters program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Karpenter - Optimize AWS Kubernetes Clusters program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Karpenter - Optimize AWS Kubernetes Clusters program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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