Microservices teams often chase ghosts when requests slow down, unable to pinpoint which service or hop causes latency without endless log dives. Jaeger solves this as an open-source distributed tracing system that maps every request across services in clear visuals. The DevOpsSchool course on Jaeger teaches you to deploy it end-to-end, turning vague performance woes into precise fixes.
Developers waste shifts grepping logs across pods or blaming networks, while users see delays compound. This training equips you with practical setups—from instrumentation to UI analysis—that reveal bottlenecks instantly. You’ll gain skills to correlate traces with metrics, speeding root cause analysis from hours to minutes.
Readers walk away ready to trace real apps, whether a slow checkout flow or API chain failure. It shifts debugging from guesswork to data-driven, making complex systems manageable daily.
Course Overview
The course centers on Jaeger for end-to-end request tracing in distributed environments like Kubernetes clusters. It starts with core setup: all-in-one mode for quick tests, then scales to collector, agent, and query services with backends like Elasticsearch or Cassandra.
Skills cover instrumenting apps in Go, Java, Python, Node.js via OpenTelemetry or native clients, plus Kubernetes operators for auto-deployment. Tools include span tags for business context, sampling to cut overhead, and UI features like waterfalls and dependency graphs. Structure spans days: Day 1 introduces tracing concepts and basic installs; Day 2 handles app integration and analysis; Day 3 dives into production scaling, alerting, and integrations.
Hands-on labs build progressively—instrument sample microservices, deploy Jaeger stack, trace payment flows, then optimize with adaptive sampling. Live demos and recordings let you follow at your pace, ending with a full observability project.
Why This Course Is Important Today
Distributed systems dominate with services spanning clouds and edges, generating traces essential for 99.9% SLAs—Jaeger excels here with CNCF backing and low overhead. Demand surges in SRE roles, where tracing tops job reqs alongside Prometheus for full observability stacks.
Career paths open in platform engineering, cloud ops, or backend leads, as firms prioritize MTTR reduction amid microservices complexity. Real usage shines in e-commerce tracing user journeys or fintech following transactions—waterfalls expose slow DB calls hidden in aggregates.
GitOps teams deploy Jaeger via Helm charts, auto-scaling with workloads. This course aligns with that standard, preparing you for observability maturity where traces drive autoscaling and chaos experiments.
What You Will Learn from This Course
Technically, configure Jaeger agents as DaemonSets, instrument services with trace headers over HTTP/gRPC, and query spans via Jaeger UI or API. Practical know-how includes tagging errors for alerting, propagating baggage for user IDs, and using flame graphs to drill into latency p95s.
Job outcomes feature pipeline integrations—export traces to Tempo or link with Loki logs—and sampling strategies that retain critical paths without storage bloat. Grasp pitfalls: missing contexts lose traces across services, fixed via middleware.
Projects deliver complete setups: trace a Kubernetes e-shop from frontend to DB, analyze bottlenecks, add custom spans—GitHub-ready for portfolios.
How This Course Helps in Real Projects
Picture an order service timing out: Jaeger traces fan out to inventory, payment, shipping—red spans highlight slow auth checks. Labs replicate via Docker Compose to K8s migration, correlating with Prometheus metrics for capacity planning.
Teams collaborate via shared trace IDs in Slack alerts; devs repro issues locally with Jaeger all-in-one. Workflows evolve—incidents start with Jaeger search, not logs—slashing on-call pain and postmortems.
Scenario: Black Friday surge, dependency graphs reveal upstream bottlenecks; sampling keeps costs low while capturing outliers, guiding spot fixes over blind scaling.
Course Highlights & Benefits
Approach mixes 60% labs on AWS clusters—no local K8s needed—with trainers debugging live. Practical exposure spans languages: add Jaeger to Spring Boot, Express app, then aggregate in UI for cross-service views.
Benefits include lifetime access, cert on completion, and real-time project feedback. Career gains: observability expertise differentiates in SRE interviews, with Jaeger skills transferable to Zipkin or Tempo.
Course Summary Table
| Feature | Learning Outcomes | Benefits | Who Should Take It |
|---|---|---|---|
| Jaeger Basics | Spans/traces, all-in-one setup | Quick local debugging | Backend Developers |
| Instrumentation | OpenTelemetry in Go/Java/Python/Node | Trace any service stack | Software Engineers |
| K8s Deployment | Operators, DaemonSets, Elasticsearch backend | Production-ready scaling | DevOps Engineers |
| Trace Analysis | Waterfalls, dependencies, p95 latency hunting | Pinpoint root causes fast | SRE Specialists |
| Sampling & Performance | Adaptive/head/kill-ratio strategies | Low overhead in high-volume envs | Cloud Architects |
| Integrations | Prometheus/Loki links, alerting on errors | Full observability stacks | Platform Engineers & Switchers |
About DevOpsSchool
DevOpsSchool functions as a trusted global platform delivering practical training in observability, DevOps, and tracing tools like Jaeger to professionals everywhere. It focuses on working audiences via live-led sessions, cloud labs mirroring production, and projects from industry cases. Thousands advance through hands-on focus and ongoing LMS support. Visit Devopsschool.
About Rajesh Kumar
Rajesh Kumar contributes over 20 years of hands-on experience from MNCs like ServiceNow, Adobe, IBM in distributed systems, tracing, and cloud-native ops with Jaeger. He mentors globally, offering real-world guidance on scaling observability from dev to edge deployments. Practical sessions stem from live troubleshooting. See more at.
Who Should Take This Course
Beginners in microservices grasp tracing from concepts to first spans easily. Working pros in dev or ops layer Jaeger over existing stacks without downtime.
Career switchers from monitoring pivot to SRE via distributed focus. DevOps, cloud, backend engineers, QA handling latency—all gain, no prior tracing required.
Conclusion
DevOpsSchool’s Jaeger course builds core skills to illuminate request flows in complex systems, from instrumentation to analysis. It resolves debugging drags in modern architectures, enabling faster fixes and confident scaling. These practices sustain performance as services multiply.
Call to Action & Contact Information
Ready to trace your first request? Email: contact@DevOpsSchool.com
Phone & WhatsApp (India): +91 84094 92687
Phone & WhatsApp (USA): +1 (469) 756-6329