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Training LiteLLM - Optimizing LLM Proxies in Production

Ref: VVW978
10 people max.
5500€ 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 LiteLLM to unify calls to over 100 LLM providers in enterprise
  • Develop professional skills in intelligent routing and load balancing
  • Design scalable LLM pipelines with caching, fallbacks and observability
  • Implement advanced security and certifying production monitoring
  • Optimize API costs and performance for critical applications
  • Deploy LiteLLM in Kubernetes and hybrid cloud environments
  • Acquire an internal certification validating your LLM proxy skills

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LiteLLM Fundamentals: Installation, Basic Configuration and First Tests (Python, Docker)

Discover rapid LiteLLM installation via pip or Docker, configure API keys for OpenAI, Anthropic and Hugging Face, test first unified calls with streaming and JSON mode enabled, complete practical exercises on complex prompts, generate initial logs and metrics to validate integration, while exploring OpenAI-like compatibility that simplifies migrations.

Module 2Advanced LiteLLM Routing: Multi-Providers, Fallbacks and Litellm Routing (YAML, Python SDK)

Dive into LiteLLM's intelligent routing with custom YAML rules, implement automatic fallbacks between providers for high availability, test weighted load balancing on real cases like enterprise chatbots, develop Python scripts for dynamic routes based on cost or latency, analyze impacts on resilience, and produce architecture diagrams for your projects.

Module 3LiteLLM Performance: Caching, Batching and Cost Optimization (Redis, async)

Optimize LiteLLM with Redis caching to reduce API calls by 50%, configure asynchronous batching to handle 100+ simultaneous requests, measure latency and cost gains on production-like workloads, implement per-provider budgets and custom hooks, perform before/after benchmarks, and integrate these techniques into CI/CD pipelines for immediate scalability.

Module 4LiteLLM Security and Observability: Guards, Logging and Monitoring (Prometheus, Sentry)

Strengthen LiteLLM with security guards against prompt injections, configure JWT authentication and per-user rate limiting, deploy Prometheus and Grafana for real-time LLM metrics dashboards, integrate Sentry for error tracing, test simulated attack scenarios, generate GDPR compliance reports, and secure deployments for sensitive environments.

Module 5Production LiteLLM Deployment: Kubernetes, Helm and Enterprise Use Cases (EKS, GKE)

Deploy LiteLLM in Kubernetes clusters via custom Helm charts, scale horizontally on EKS or GKE with autoscaling, integrate with gateways like Kong or Istio, migrate legacy applications to this unified proxy, analyze a real enterprise case reducing LLM costs by 40%, finalize with a deliverable capstone project and Q&A session for your specific challenges.

Evaluation method

  • Daily technical quizzes on LiteLLM and practical cases
  • Final project: deployment of a complete LLM proxy in Kubernetes
  • Qualiopi certifying attestation validating advanced skills

Learning method

  • 70% hands-on practice with dedicated machines and real datasets
  • Enterprise use cases drawn from Fortune 500 productions
  • Individual pedagogical support in small groups of max 10
  • Unlimited access to replays and labs post-training

Methods, materials and delivery

The Training LiteLLM - Optimizing LLM Proxies in Production 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 LiteLLM - Optimizing LLM Proxies in Production 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 LiteLLM - Optimizing LLM Proxies in Production 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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