Observability Engineering with OpenTelemetry Corporate Training
Learn to instrument services and build OpenTelemetry pipelines in live guided labs with expert instructors.
Edstellar, a corporate training company, delivers corporate training that helps your team build production-ready observability with OpenTelemetry. Your team will develop the skills to instrument services, correlate signals, and control telemetry cost through guided, instructor-led practice.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an observability-ready engineering team
EDSTELLAR OBSERVABILITY ENGINEERING CAPABILITY MODEL
Assess telemetry maturity
Skill checks map your team's observability coverage, tooling, and incident habits.
Align OTel standards
Teams align on OpenTelemetry SDKs, semantic conventions, and Collector patterns.
Practice pipeline builds
Guided labs instrument services and build Collector pipelines end to end.
Measure signal quality
Reviews score span coverage, correlation, and alert signal against targets.
Scale observability
Cohorts extend pipelines, sampling, and governance across services.
Need more than one program?Get a group quote
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Program Overview: What is Observability Engineering with OpenTelemetry?
Observability Engineering with OpenTelemetry is Edstellar's instructor-led technical program for backend engineers, SREs, and platform teams instrumenting cloud-native applications. Participants learn OpenTelemetry SDKs, collector pipelines and exporters, distributed tracing, signal correlation, and telemetry governance. The program turns instrumentation from scattered libraries into one coherent observability pipeline.
Training is hands-on from the first module. Participants instrument live services with OpenTelemetry SDKs, then build collector pipelines that route traces, metrics, and logs to real backends in guided labs. Instructors coach the team through context propagation, tail-based sampling, and cost-aware telemetry design, reviewing every pipeline with direct feedback. The program closes with a capstone where each team ships a complete end-to-end observability build.
Without deliberate telemetry, teams get metric noise, orphaned traces, and spiralling ingestion bills that nobody trusts. This program teaches your engineers to instrument once with the OpenTelemetry standard, correlate signals across services, and govern cost with sampling. Debugging becomes a trace you can follow instead of a mystery you guess at.
The capstone leaves the team with a production-shaped observability pipeline: services auto-instrumented with the OpenTelemetry SDKs, collector pipelines fanning traces, metrics, and logs into backends, tail-based sampling that holds ingestion costs in check, and correlated views that show one request end to end. Your engineers walk out owning a reference implementation they can extend to every service they own.
Teams start with signal fundamentals and OpenTelemetry architecture, then move through SDK instrumentation, Collector pipelines, and distributed tracing. Later modules unify logs and metrics with traces, then tackle sampling, cost, and governance. The 5.5-hour capstone asks each cohort to ship a full observability pipeline for a multi-service system and defend its reliability and cost story.
What's Included in this Workshop for Your Enterprise Teams
- 1
Guided OpenTelemetry labs
Hands-on instrumentation practice
- 2
Collector pipeline builds
Configure receivers, processors, exporters
- 3
Trace correlation exercises
Link logs, metrics, and traces
- 4
Cost optimization drills
Tune sampling and retention to cut spend
- 5
Capstone build
Ship a full observability pipeline
- Instructor-led delivery, virtual or onsite
- Hybrid batches scheduled around your team
- Live guided labs in every module
- Course materials and lab guides included
- Assessment with feedback after labs
- Post-training support for rollout questions
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
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Observability Engineering with OpenTelemetry Course Topics and Program Outline
A tailored 29-hour, seven-module workshop: one learning journey from observability foundations to a capstone pipeline build. Sessions mix live instruction with guided labs your teams run.
Built by Edstellar with observability practitioners
Built by engineers who run OpenTelemetry pipelines in production, shaped around your stack and use cases.
Skill checks baseline your team's observability maturity, telemetry tooling, and incident response habits before training begins.
Live instruction covers observability foundations, the three signals, and OpenTelemetry architecture across 3 focused hours.
Guided labs build instrumentation, Collector pipelines, and tracing skill across 12.5 hours of supervised practice.
Your team ships a production-style observability pipeline in 5.5 capstone hours, reviewed for reliability and cost control.
From your first OpenTelemetry span to a capstone observability build, every technique is practiced in guided labs.
Delivered as
Delivered as a hybrid program of live instruction and guided labs, scheduled around your team's calendar in flexible batches.
Install the OpenTelemetry SDK and Collector locally, then send your first span through the pipeline.
learna)What observability means: signals versus monitoring
b)The three signals: traces, metrics, and logs
c)OpenTelemetry architecture: APIs, SDKs, and the Collector
d)Spans, resources, and semantic conventions
Instrument a two-service sample application and verify propagated spans in the Collector.
practicea)Automatic versus manual instrumentation
b)SDK setup for common runtimes and frameworks
c)Context propagation across service calls
d)Span attributes, events, and status codes
e)Sampling configuration basics
Configure a Collector pipeline that routes sampled traces to two backends with retry policy.
practicea)Collector architecture: receivers, processors, exporters
b)Head-based and tail-based sampling in the Collector
c)Batching, retries, and memory limiters
d)Exporting to common observability backends
e)Securing the Collector with auth and TLS
Trace a failing request through a Kubernetes lab cluster and isolate the latency source.
practicea)Distributed context propagation with W3C trace context
b)Tracing microservices running on Kubernetes
c)Service mesh integration and span stitching
d)Reading trace waterfalls to isolate latency
e)Debugging broken traces and coverage gaps
Wire structured logs and histograms to traces, then define an SLO with a burn-rate alert.
applya)Metric instruments: counters, histograms, and gauges
b)Structured logging with trace correlation
c)Exemplars linking metrics back to traces
d)Building service-level indicators and objectives
e)Alerting on burn rate and anomalies
Apply tail sampling rules and redaction processors, then measure the volume and cost impact.
applya)Sampling strategies: head, tail, and rule-based
b)Estimating and reducing telemetry volume
c)Retention tiers and storage trade-offs
d)Data governance: PII redaction and access control
e)Cost dashboards and chargeback models
Ship the full pipeline and walk through a simulated incident from alert to root cause.
applya)Scoping the observability target and SLIs
b)Instrumenting every service in the stack
c)Building the Collector pipeline with sampling
d)Correlating signals into one incident view
e)Presenting results: the reliability and cost story
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Seven job-ready outcomes your team will demonstrate by the end of the program. Each competency is practiced in guided labs and proven in the capstone build.
Explain observability signals
Describe traces, metrics, and logs, and how OpenTelemetry standardizes telemetry.
Instrument with OTel SDKs
Add automatic and manual instrumentation with context propagation.
Operate Collector pipelines
Configure receivers, processors, and exporters for reliable routing.
Trace distributed systems
Follow requests across services and Kubernetes to find latency.
Correlate all signals
Link logs and metrics to traces for one incident view.
Define SLOs and alerts
Set service-level objectives and burn-rate alerts that reduce noise.
Control telemetry cost
Apply sampling, retention, and governance to keep spend in check.
Teams that Benefit from this Observability Engineering with OpenTelemetry Group Training
This group training is built for platform and product teams running distributed systems who want unified telemetry without guesswork. Cohorts practice with their own stack patterns, and content adapts to each role's experience so every group trains on the workflows it owns.
Standardize telemetry across every service your platform runs.
Platform engineers build shared Collector pipelines, enforce instrumentation standards, and give every team the same reliable signal.
Workflow friction
- Inconsistent telemetry across services
- Collector misconfigurations at scale
- No shared view during incidents
How the program helps
- Shared Collector pipelines for every team
- Instrumentation standards that scale
- One signal source for incidents
Practice use cases
- Collector pipelines
- SDK standards
- Signal routing
Cut incident response time with correlated signals.
SREs link traces, metrics, and logs into one incident view, define SLOs, and alert on burn rate instead of noise.
Workflow friction
- Alert noise without context
- Blind spots in distributed paths
- Post-incident data gaps
How the program helps
- Faster root cause analysis
- SLOs backed by real signals
- Burn-rate alerting that works
Practice use cases
- SLO definition
- Burn-rate alerts
- Incident drills
Instrument services so every request is traceable.
Backend developers add OpenTelemetry instrumentation to their services, propagate context, and enrich spans with useful attributes.
Workflow friction
- Uninstrumented legacy services
- Broken context propagation
- Sparse span attributes
How the program helps
- Traceable requests end to end
- Context propagation that works
- Richer spans for debugging
Practice use cases
- Manual instrumentation
- Context propagation
- Span enrichment
Control telemetry cost while keeping full visibility.
DevOps teams tune sampling, retention, and exporters so telemetry stays affordable as traffic grows.
Workflow friction
- Exploding telemetry bills
- Over-retained low-value data
- Exporter sprawl
How the program helps
- Telemetry spend under control
- Sampling tuned to traffic
- Retention tiers that fit
Practice use cases
- Sampling rules
- Cost dashboards
- Retention tiers
Cohorts train as a cross-functional workforce, with each small group aligned on shared observability standards.
Prerequisites: This program benefits platform engineers, SREs, backend developers, and DevOps practitioners who run or support distributed systems. Familiarity with one programming language and basic cloud concepts helps but is not required. No prior OpenTelemetry experience is needed, and every module adapts to your team's stack and context.
Platform Engineer to Observability Engineer
Tracks how engineers move from basic signal literacy to advanced pipeline ownership across the program's learning phases.
A program that grows with platform and SRE careers, from first telemetry signals to confident production observability.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the delivery mode that fits your teams: hybrid, onsite, or live virtual. Every mode is instructor-led with hands-on labs in each module.
Hybrid Training
Instructor-led sessions mix onsite and virtual delivery with guided labs throughout. Teams keep momentum between sessions with shared lab guides and recordings.
- Live instruction across onsite and virtual sessions
- Guided labs in every module
- Shared lab guides and session recordings
- Flexible batches around your calendar
Onsite Training
Instructors deliver at your office with labs on your network. Onsite batches suit platform-wide rollouts and teams that learn best together in one room.
- Instructor-led sessions at your office
- Labs running on your network
- Team exercises tuned to your stack
- Rollout support after the program
Live Virtual Training
Live virtual sessions on Zoom or Teams pair instruction with guided labs. Breakout rooms keep small groups productive, and recordings support review after each session.
- Live instruction on Zoom or Teams
- Guided labs with breakout rooms
- Recordings for review after sessions
- Same curriculum as onsite delivery
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, timelines, and delivery preference, and we will send a detailed per-group quote with batch options for your cohort.
Yes. A short discovery call maps your observability goals, stack, and skill gaps so the training plan fits your teams before you commit.
Yes. Live virtual sessions run on Zoom or Teams with guided labs, the same as onsite. Many teams choose a hybrid mix across batches.
Yes. Instructors travel for onsite delivery and labs can run on your network. Onsite works well for platform-wide rollouts.
The program runs 29 hours across 7 modules, typically delivered in flexible batches. We shape the schedule around your team's calendar.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
OpenTelemetry builds on infrastructure monitoring, adding traces and application signals your team cannot get from host metrics alone. SRE then uses that data for service levels, and AI observability applies it to LLM systems.
Why Choose Edstellar as Your Observability Engineering with OpenTelemetry Corporate Training Provider
When comparing providers, Edstellar is the training partner teams choose for observability expertise and 5+ years of corporate delivery. Every engagement is tailored to your stack, led by expert trainers, and measured for outcomes your teams can see in production.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Every cohort's labs, pipelines, and sampling rules are tuned to your stack, backends, and telemetry standards.
Proven Methodology
A diagnose-to-scale path moves teams from telemetry assessment to measurable observability maturity across cohorts.
Practice-Based Learning
Guided labs in every module let engineers instrument services and debug traces with expert support.
Expert Trainers
Practitioners who run OpenTelemetry pipelines in production lead every session, matched to your domain.
Global Scale
One consistent curriculum rolls out across regions and time zones, with delivery matched to each cohort.
Measurable Outcomes
Skill checks and the assessed capstone prove pipeline quality, correlation coverage, and cost control.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Observability Engineering with OpenTelemetry Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Observability Engineering with OpenTelemetry Training for Your Team
Share your team size, observability goals, and timelines to receive a tailored training plan and quote. Book a discovery call to check availability for your cohorts.