The most complete hands-on observability training for DevOps and SRE engineers — metrics, logs, and traces from first principles to production. Master Prometheus, Grafana, OpenTelemetry, ELK, Jaeger, Datadog, and Dynatrace on real Kubernetes clusters. Every session is a live demo in a real lab environment — not slides, not theory. You watch the instructor instrument, observe, and debug it; then you do the same.
By the end of this observability engineering course, you'll have shipped 18 production-grade artefacts and demonstrated you can:
Instrument and monitor distributed systems end-to-end — metrics, logs, and traces collected from real microservices running on Kubernetes.
Write production-grade PromQL — instant and range vectors, aggregations, recording rules, and multi-window burn-rate alerts with Alertmanager.
Build Grafana dashboards that combine Prometheus metrics, Loki logs, and Tempo traces in unified panels — the complete Prometheus Grafana monitoring stack.
Instrument applications with OpenTelemetry — auto and manual instrumentation in Python, Java, or Go; route telemetry through an OTel Collector pipeline.
Operate the ELK stack — ship structured logs from Kubernetes pods, apply Logstash pipelines, and query with KQL in Kibana Discover and Lens.
Trace requests across microservices with Jaeger — understand trace propagation, sampling strategies, and flame-graph debugging for latency outliers.
Deploy Prometheus Operator on Kubernetes — ServiceMonitors, PrometheusRules, kube-state-metrics, and node exporters for full-cluster observability.
Define and operate SLOs — latency, availability, and correctness SLIs; error budget policies; Pyrra and Sloth for automated burn-rate alerting.
Pass the final observability exam — 3 hours, online, open-book, scenario-based — and earn a verifiable cloud native observability certification.
Rajesh Kumar has 20 years operating distributed systems at PayPay, ServiceNow, Adobe, and Intuit — he built observability stacks before most vendors existed. He teaches what he ran, not what he read.
You deploy Prometheus, Grafana, OpenTelemetry Collector, and Jaeger on your own AWS/GCP/Azure cluster. When the cohort ends, your observability stack stays up — and the skill goes with you.
Every Prometheus, Grafana, and OpenTelemetry session is a live instructor demo in a working lab. You see alert pipelines fire, traces appear in Jaeger, and dashboards update in real time — then you build the same setup yourself.
Every tool ends with a graded capstone. By the end of this hands-on observability course you have 18 GitHub-public artefacts that prove you can instrument, monitor, and debug production systems — not just describe them.
Every cohort is capped at 10 learners by design. That's how the instructor still answers your real Prometheus, Grafana, and OpenTelemetry production questions in week 4 — not just the rehearsed ones from week 1.
Need a custom corporate cohort for your team? Talk to us →
This observability engineering course is purpose-built as both an observability training for DevOps engineers and an observability certification for SRE practitioners. It covers the full stack — metrics, logs, and traces — with every major open-source and commercial observability tool. Each module is a live demonstration inside a real Kubernetes lab. You see it instrumented, scraped, visualised, and alerted end-to-end before you build the same setup yourself.
Get the PDF syllabus with every tool, sub-topic, assignment brief, capstone spec and reading list.
Download syllabusEvery module in this hands-on observability course ends with a graded capstone you ship to GitHub. By the end you have a portfolio of real observability artefacts — not toy examples — built on actual Kubernetes clusters in AWS, GCP, or Azure.
Instrument three microservices (Python, Go, Java) with OTel SDK; route traces, metrics, and logs through an OTel Collector DaemonSet to Prometheus, Loki, and Jaeger simultaneously.
Deploy Prometheus Operator, add ServiceMonitors for two apps, implement multi-window burn-rate alerting with Sloth-generated recording rules — Prometheus Certified Associate (PCA) prep level.
Build a Grafana dashboard linking Prometheus metrics, Loki logs, and Tempo traces via exemplars; provision it as a Kubernetes ConfigMap with zero manual clicks. Grafana Alerting fires to Slack on SLO breach.
Deploy Fluent Bit DaemonSet → Elasticsearch → Kibana on Kubernetes; apply a 30-day ILM policy; build a Kibana Lens dashboard and detection rule that fires on a 5xx spike.
Debug a latency regression across a four-service app using Jaeger flame graphs and span filters; identify the slow database query; document the root-cause analysis as a structured postmortem.
Configure Datadog APM on a Kubernetes workload; run the same incident across Datadog and the open-source Prometheus/Grafana/Jaeger stack; document detection latency, toil, and cost trade-offs.
Deploy Dynatrace OneAgent on a Kubernetes cluster; trigger a memory leak; validate Davis AI detects, clusters, and root-causes the problem automatically without manual alert configuration.
Define SLOs for a three-tier app; implement burn-rate alerts; run a Chaos Mesh pod-kill exercise; measure the SLO impact live; write a postmortem with root-cause analysis driven entirely by your observability data.
Every tool is taught with a live demo in a real Kubernetes lab — not a slide.
The MASTER-OBS observability exam is intentionally not a memorisation contest. Open-book, scenario-driven, and proctored online — it tests whether you can instrument, debug, and operate distributed systems using the tools you spent five weeks building with. It mirrors what engineers actually face during on-call: given metrics, logs, and traces, find the problem and fix it.
In a real on-call shift you look things up. The exam mirrors that. We test the skill that actually matters — composing what you know into a working solution under time pressure. Memorising flag syntax wouldn't make you a better engineer.
Clear the exam and you'll be issued the MASTER-OBS digital certificate within 5 working days, with a verifiable credential ID on our public registry.
Rajesh is a working practitioner with 20 years across DevOps, SRE and Security, and an early-bird operator in MLOps and AIOps — he was already running model-deployment and telemetry-driven incident pipelines years before either term became industry vocabulary. He has held principal engineering and architect roles at PayPay, SoftwareAG, ServiceNow (Netherlands), JDA Software, Intuit, Adobe, IBM/Emptoris, Ness, MindTree and Accenture. He has personally trained engineers at JPMorgan Chase, Wells Fargo, Bank of America, Verizon, Nokia, World Bank, GE Healthcare, VMware, Citrix, Oracle, Qualcomm, Ericsson, Splunk, New Relic, Datadog, Airbus, AstraZeneca, Bosch, Mercedes-Benz, Vodafone, Deloitte, EY, Capgemini, Infosys, Cognizant, HCL, Wipro and dozens more. He teaches what he runs — not what he reads.
Every MASTER-OBS observability certification is issued with a unique credential ID, a tamper-proof QR code, and a verification URL on devopsschool.com/certificates. Add it to LinkedIn in one click alongside your 8 GitHub capstone projects.
Every plan includes the full curriculum, recorded sessions, and access to our learner community.
Need an invoice for your employer? Request a corporate quote → · Taxes (GST) where applicable are billed in addition to the listed price.
Not slides. Not a 500-seat MOOC. Not a temporary sandbox. Three things make this the best observability certification programme for working engineers — then compare line-by-line.
Every session is the instructor screen-sharing a real working lab and building the thing in front of you — then you build it yourself. No PowerPoint, no "imagine if…".
We guide you through provisioning a free-tier AWS / Azure / GCP environment on day one — the same skill you'll use at work. A temporary sandbox login disappears the day the cohort ends. Your own lab doesn't.
Cohorts are capped at 10 by design. The instructor still knows your name in week 4 — and still has time to debug the weird production thing you brought from work.
| What matters | YouTube + blogs | Generic online course | Boot camp | DevOpsSchool MASTER-OBS |
|---|---|---|---|---|
| Teaching method | You piece it together yourself | Pre-recorded talking-head + slides | Mix of slides & some labs | Live demos in a real lab — every session |
| Cohort size | 1 (you, alone) | Hundreds to thousands | 30–60 per batch | 10 by design — instructor knows your name |
| Lab environment | None | Throwaway sandbox | Shared sandbox login | Your own AWS/Azure/GCP, guided setup |
| Per-tool structure | Ad-hoc | Inconsistent across modules | Theme-based, varies wildly | 5 hrs · 2 assignments · 1 capstone for every tool |
| Final assessment | None | Multiple-choice quiz | Mini-project | 3-hour open-book scenario exam |
| Portfolio at the end | What you built solo | 1–2 generic toy projects | 1 capstone | 1 capstone per tool — GitHub-public |
| Instructor pedigree | Mixed (creator-economy) | Mixed (often academic) | Recent-grad TAs common | Rajesh Kumar — 20 yrs, ex-PayPay/ServiceNow/Adobe |
| Cohort start cadence | N/A — pure self-pace | Self-paced only | Quarterly windows | New cohort every 1st of the month |
| Post-program support | None | Drip-fed retention emails | 30–90 day Slack | Lifetime forum + alumni community |
| LMS bundled | No | This one course only | This program only | 1 year full LMS — 20+ courses, 50+ tools |
| Refund posture | N/A | Vendor-specific, often none after start | Usually none after week 1 | 100% within 15 days if we cancel |
| Total cost (full program) | Free, slow | ₹15K – ₹50K per single course | ₹80K – ₹3L+ | ₹34,999 · LMS + lifetime forum included |
Still on the fence? Talk to an advisor → — they'll tell you straight if MASTER-OBS fits your goal.
Questions from DevOps engineers, SRE practitioners, and beginners starting their observability journey. Don't see yours? Ask us directly →
kube-prometheus-stack via Helm on your existing Kubernetes cluster. (2) Connect Grafana and import standard dashboards for your services. (3) Add an OpenTelemetry Collector as the vendor-neutral telemetry pipeline — it ingests traces, metrics, and logs and routes to Prometheus, Loki, and Tempo. (4) Instrument one service with the OTel SDK to emit custom spans. This is exactly what the Prometheus Grafana OpenTelemetry course at DevOpsSchool covers in live demos — with graded assignments for every step.Talk to an advisor — they'll tell you straight whether this fits your goal.
Talk to advisorNext cohort starts 1st of next month. Only 3 of 10 seats remaining. Drop your details and we'll send the full observability training syllabus + book a free 20-min consult to map this cert to your Prometheus, Grafana, or OpenTelemetry goal.