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 Grafana Tempo - Mastering Distributed Tracing training are: Knowledge of Docker, Kubernetes, Prometheus, and OpenTelemetry tracing basics. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Grafana Tempo - Mastering Distributed Tracing training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Grafana Tempo - Mastering Distributed T... | 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.

Configure your training

Response within 24hNo commitment100% free

8 spots remaining for the next session

FormatParticipantsDateDetails

Which format do you prefer?

Methods, approaches, and teaching resources

The Training Grafana Tempo - Mastering Distributed Tracing 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 Grafana Tempo - Mastering Distributed Tracing 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 Grafana Tempo - Mastering Distributed Tracing 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 access terms and deadlines

Training objectives

Master the installation and configuration of Grafana Tempo for professional environments

Develop skills in instrumenting traces with OpenTelemetry

Analyze distributed traces to quickly diagnose incidents in enterprise settings

Integrate Grafana Tempo with Loki and Prometheus for complete observability

Optimize Tempo performance in scalable production environments

Implement certified dashboards to monitor critical applications

Training program

Module 1Grafana Tempo Fundamentals: Installation and Initial Configuration (Docker, Helm, Storage)

In-depth discovery of Grafana Tempo through quick installation with Docker Compose and Helm on Kubernetes, configuration of storage backends such as S3 or MinIO, first sends of simulated traces from a Node.js application, practical exercises to validate connectivity, creation of a realistic test environment with instrumented trace generation, and initial diagnosis of system health metrics.

Module 2Grafana Tempo Instrumentation: Generating Traces with OpenTelemetry (SDKs Java, Python, JS)

Hands-on with OpenTelemetry SDKs to instrument microservices applications in Java, Python, and JavaScript, adding custom spans and distributed contexts, configuring exporters to Tempo, exercises on a red-thread e-commerce project with traces propagated via HTTP and gRPC, validation of received traces in the Tempo interface, and optimization of attributes for efficient searching.

Module 3Grafana Tempo Analysis: Advanced Queries and Trace Exploration (Query Language, Service Graph)

Interactive exploration of traces via the Grafana interface with TraceQL queries, filtering by tags, latency, and errors, building service graphs to visualize dependencies, practical cases on debugging real incidents like slow queries or memory leaks, collaborative exercises for root cause analysis, and exporting reports for ops teams, enhancing immediate diagnostic skills.

Module 4Grafana Tempo Integrations: Coupling with Loki Logs and Prometheus Metrics (Unified Dashboards)

Seamless connection of Tempo to Loki to correlate traces and logs, integration with Prometheus for enriched metrics, creation of unified Grafana dashboards showing traces, logs, and metrics at a glance, practical workshops on a simulated Kubernetes cluster with Jaeger migration to Tempo, configuration of alerts based on anomalous traces, and end-to-end tests for full-stack enterprise observability.

Module 5Advanced Grafana Tempo: Scaling, Optimization, and Production Deployments (HA, Queriers)

High-availability deployment of Tempo in microservices mode on Kubernetes with automatic scaling of queriers and ingesters, performance tuning to ingest millions of spans per second, storage cost optimization via compaction and retention policies, case studies on major incidents resolved by Tempo, final project with certified dashboard deliverable, and action plan for secure production integration.

Evaluation method

Multiple-choice quiz to validate learning outcomes at the end of the training
Continuous assessment through practical exercises on a red-thread project
Presentation of a personalized Grafana Tempo dashboard to the trainer

Learning method

Courses led by an active SRE expert trainer
Practical exercises on real enterprise cases with Kubernetes clusters
Progressive red-thread project for an observable application
Complete course materials and OpenTelemetry resources provided to each participant