Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training RabbitMQ Expert - Master Advanced Topologies and HA training are: Advanced mastery of RabbitMQ (complex exchanges, durable queues), asynchronous programming in Python/Java/Go, Docker/Kubernetes, Linux sysadmin.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training RabbitMQ Expert - Master Advanced Topologies and HA training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training RabbitMQ Expert - Master Advanced Topol... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training RabbitMQ Expert - Master Advanced Topologies and HA training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training RabbitMQ Expert - Master Advanced Topologies and HA training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training RabbitMQ Expert - Master Advanced Topologies and HA training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Design advanced RabbitMQ topologies for microservices

Optimize performance and scalability with expert tuning

Implement clustering and high availability seamlessly

Develop custom plugins and extensions

Secure exchanges with SSL, ACL, and federation

Diagnose and monitor in real production environments

Integrate RabbitMQ with Kubernetes and hybrid cloud

Training program

Module 1Advanced RabbitMQ Topologies: exchanges, queues, complex bindings

Dive into modeling massive flows, configure topic and headers exchanges on simulated clusters, complete hands-on exercises with dead-letter queues and alternates, produce deliverable schemas for 10k msg/s, test manual sharding, everything to scale your apps without bottlenecks.

Module 2RabbitMQ Performance: tuning, benchmarking, memory optimization

Analyze bottlenecks with Prometheus, tune prefetch and heartbeats on high-load VMs, benchmark 1M msg/min via Go/Python exercises, optimize GC and paging, generate before/after performance reports, apply lazy queues for 50% RAM savings, master explosive throughput.

Module 3RabbitMQ High Availability: mirroring, clustering, failover

Deploy quorum clusters on 3 Docker nodes, configure mirrored queues and arbitration, simulate network failures for HA tests, implement federation and shovels inter-DC, validate zero-downtime with automation scripts, produce production-ready Ansible playbooks, ensure 99.99% critical uptime.

Module 4RabbitMQ Extensions: plugins, HTTP management, custom exchanges

Compile advanced Erlang plugins like MQTT adapter, extend HTTP API with OAuth auth, code custom exchanges in Elixir for AI routing, test on real e-commerce cases, debug rotating logs, deliver open-source modules, transform RabbitMQ into an irresistible custom broker.

Module 5RabbitMQ Security and Monitoring: SSL, ACL, production alerting

Secure with TLS 1.3 and client certs, define granular ACLs for 100 users, integrate Prometheus/Grafana for live dashboards, simulate attacks and mitigate, alert via PagerDuty on latency >500ms, complete Kubernetes capstone project, leave certified and production-autonomous.