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.
Learning objectives
- Master OpenTelemetry to instrument distributed applications in certified professional training.
- Develop skills in tracing with Jaeger and Zipkin to diagnose latencies in production.
- Design trace pipelines for scalable enterprises, optimizing observability.
- Implement trace-log-metrics correlations in Kubernetes environments.
- Optimize microservices performance via expert distributed tracing analysis.
- Deploy serverless and hybrid tracing solutions for DevOps teams.
- Certify distributed tracing skills to accelerate enterprise career.
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.
Program
Module 1Advanced Fundamentals of Distributed Tracing: OpenTelemetry and Jaeger Protocols (Expert Instrumentation)
Dive into OpenTelemetry protocols to export traces to Jaeger, install collectors and agents in Java and Node.js applications, perform practical exercises on parent-child spans, configure adaptive samplings to reduce overhead, analyze real-time trace topologies, produce initial latency diagnostic reports, integrate with Prometheus for metrics-traces correlations in scalable microservices environments.
Module 2Distributed Tracing Tools: Zipkin, Tempo, and Elasticsearch (Advanced Integrations)
Explore Zipkin for trace storage in Cassandra, deploy Grafana Tempo for ultra-fast queries without indexing, integrate Elasticsearch for full-text searches on traces, practice auto-instrumentation with Python and Go SDKs, simulate bottleneck detection scenarios via service graphs, generate Loki dashboards to visualize distributed flows, test collector resilience under high load, deliver production-ready configurations for DevOps teams.
Module 3Distributed Tracing in Kubernetes: Operators and Sidecars (Native Observability)
Deploy OpenTelemetry Operator for auto-instrumentation of pods, configure tracing sidecars with Istio and Linkerd, trace service mesh traffic with Envoy proxies, analyze Lambda cold starts via AWS X-Ray, practice distributed queries on EKS/AKS clusters, optimize baggage propagation for business contexts, generate service latency heatmaps, integrate Jaeger into Grafana for proactive alerts, produce playbooks for diagnosing complex incidents.
Module 4Advanced Correlations in Distributed Tracing: Logs, Metrics, Profiling (Full Observability)
Link traces to Fluentd logs and VictoriaMetrics metrics via traceID, implement continuous profiling with Pixie and Parca, use eBPF for kernel-level tracing without overhead, practice ML-based anomaly detection on Jaeger traces, analyze dynamic dependencies in GitOps CI/CD, configure tracing SLOs for SRE golden signals, test chaos engineering scenarios with Litmus, deliver full-stack observability architectures ready for enterprise scalability.
Module 5Optimization and Securing Distributed Tracing: Production Hardening (Real Cases)
Harden tracing pipelines with TLS encryption and fine-grained RBAC, optimize storage costs via intelligent retention policies, integrate tracing into GitHub Actions for dev observability, practice forensic analysis on real incidents like Netflix outages, deploy multi-tenant tracing for SaaS, measure ROI via quantified MTTR reduction, finalize capstone project with certified portfolio, receive post-training coaching for enterprise implementation.
Evaluation method
- Advanced quizzes on tracing protocols and tools with expert scoring.
- Real case studies: diagnosing microservices failures in time-limited scenarios.
- Final project: deploying a certified Kubernetes tracing pipeline.
Learning method
- 70% hands-on practice time on real Kubernetes and cloud labs.
- Real-world cases inspired by Fortune 500 outages for professional immersion.
- Unlimited OpenTelemetry resources support post-training for 6 months.
- Qualiopi certification validating expert DevOps skills.
Methods, materials and delivery
The Training Distributed Tracing - Diagnosing Microservices Failures 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 Distributed Tracing - Diagnosing Microservices Failures 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 Distributed Tracing - Diagnosing Microservices Failures 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
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
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.
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.
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.
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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