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Training High Availability - Ensuring the Resilience of AI Systems

Ref: IHT256
10 people max.
$6,600 HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$180/day onsite · +$540 with certification exam
5 days
remote

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Learning objectives

  • Master High Availability architectures to deploy AI models in production
  • Develop professional skills in clustering and load balancing tailored to AI workloads
  • Design failover and redundancy strategies for business-critical enterprises
  • Implement real-time monitoring tools for critical AI systems
  • Optimize the resilience of Deep Learning infrastructures in continuous training environments
  • Integrate Prompt Engineering into secure high availability environments

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 1High Availability Fundamentals: Redundant Architectures and Basic Principles (Kubernetes, Docker)

Discover the essential concepts of high availability applied to AI systems, explore active-passive and active-active architectures through practical workshops on Kubernetes, configure Docker clusters to simulate resilient AI deployments, analyze real cases of avoided failures, produce a resilience diagram as a deliverable, integrate open-source tools for immediate enterprise implementation.

Module 2High Availability Load Balancing: Load Distribution for AI Models (HAProxy, NGINX)

Dive into load balancing techniques for Deep Learning workloads, install and configure HAProxy and NGINX remotely, test traffic distribution on simulated AI APIs, measure performance with tools like Prometheus, resolve overload scenarios through guided exercises, generate benchmark reports, apply these skills to professional certifying projects.

Module 3High Availability Failover and Clustering: Automatic Failover Mechanisms (Keepalived, Corosync)

Master failover protocols for critical AI environments, deploy Keepalived and Corosync on virtual clusters, simulate network and server failures with automated scripts, verify Deep Learning service continuity, analyze logs to optimize recovery times, produce a clustering plan as a concrete deliverable, strengthen your high availability skills for the enterprise.

Module 4High Availability Monitoring and Alerting: Proactive AI Surveillance (Prometheus, Grafana)

Implement advanced monitoring for High Availability in AI, configure Prometheus and Grafana for real-time dashboards, integrate Slack alerts on critical metrics like CPU and model latency, test thresholds on real Prompt Engineering cases, automate responses via Python scripts, export custom visualizations, acquire professional practices for optimal resilience.

Module 5Advanced High Availability Optimization: Scaling and Security for AI in Production (Terraform, Vault)

Optimize High Availability deployments with Terraform for IaC, secure AI clusters via HashiCorp Vault, horizontally scale Deep Learning services under load, integrate chaos engineering tests with Chaos Monkey, review best practices in collaborative workshops, finalize a capstone project with a complete report, certify your high availability skills for the enterprise.

Evaluation method

  • Daily interactive quizzes on High Availability concepts
  • Practical projects evaluated by experts (simulated AI clusters)
  • Final certifying exam with real business cases

Learning method

  • Alternating theory and 70% hands-on practice on real environments
  • Case studies from leading companies in high availability AI
  • Individualized pedagogical support in live remote format
  • Access to e-learning platform for 6 months post-training

Methods, materials and delivery

The Training High Availability - Ensuring the Resilience of AI Systems 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 High Availability - Ensuring the Resilience of AI Systems 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 High Availability - Ensuring the Resilience of AI Systems 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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