Observability on Google Cloud Corporate Training
Instrument, monitor, and debug Google Cloud services with production-grade observability practices.
This instructor-led program builds your team's ability to instrument services, build dashboards, trace requests, and run SLO-driven alerting on Google Cloud, with hands-on labs in every module.
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 a production-ready observability team
The Edstellar OBSERVABILITY Capability Model
Assess observability maturity
Skill checks map your team's telemetry coverage, dashboards, and alerting baseline.
Set shared standards
One shared playbook for instrumentation, dashboards, and alert policies.
Practice in guided labs
Labs cover metrics, logging, tracing, profiling, and SLO design.
Measure the lift
Lab reviews benchmark each engineer's observability capability growth.
Scale across teams
One standard rolls out across services, projects, and teams.
Need more than one program?Get a group quote
Trusted as a Leading Corporate Training Provider by
Program Overview: What is Observability on Google Cloud?
Observability on Google Cloud is Edstellar's instructor-led technical program for cloud engineers and SRE teams operating workloads on Google Cloud. Participants learn Cloud Monitoring metrics and dashboards, structured logging and log analytics, Cloud Trace and Cloud Profiler, plus alerting with SLOs and error budgets. The program builds complete visibility into Google Cloud applications.
Training is hands-on from the first module. Participants build custom Cloud Monitoring dashboards over live GCP projects, run structured logging queries in Log Analytics, and trace real requests with Cloud Trace in guided labs. Instructors coach the team through alerting policies, SLO burn alerts, and profiler-driven optimisation, reviewing every build with direct feedback. The program closes with a capstone where each team ships a full production observability build.
Cloud teams often drown in disconnected GCP console tabs: metrics here, logs there, traces somewhere else entirely. This program teaches your engineers to unify signals with the Google Cloud operations suite, set SLOs that actually reflect user experience, and profile before they optimise. Firefighting gives way to evidence-led reliability.
The capstone is a production observability build on a real GCP project: custom dashboards tracking golden signals, log-based metrics with Log Analytics views, distributed traces wired through Cloud Trace, Cloud Profiler snapshots of hot paths, and alert policies that protect error budgets. Your team keeps this reference architecture, tuned and documented, as the template for every workload they run on Google Cloud.
Six modules and 24 hours: observability foundations, metrics and dashboards, structured logging, distributed tracing and profiling, alerting with SLOs and error budgets, and a capstone production build. Every module pairs concepts with a guided lab in Google Cloud, so each technique is practiced. It closes with a capstone where the team instruments a sample app, builds its dashboards and alerts, and handles a simulated incident.
What's Included in this Workshop for Your Enterprise Teams
- 1
Observability Foundations on Google Cloud
Set up workspaces and connect your first workload.
- 2
Metrics and Custom Dashboards
Build dashboards and uptime checks from live metrics.
- 3
Structured Logging and Log Analytics
Query and route logs for real troubleshooting.
- 4
Distributed Tracing and Profiling
Trace requests and profile hotspots end to end.
- 5
Alerting, SLOs and Error Budgets
Set SLOs and run an incident response drill.
- 6
Capstone: Production Observability Build
Ship a full observability setup and defend it.
- Instructor-led live virtual, onsite, or hybrid delivery
- 24 hours across six modules with guided labs
- Labs run in your Google Cloud projects
- Dashboard, alert, and query templates included
- Cohorts of 8 to 20 engineers recommended
- Post-program Q&A support for rollout
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
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Observability on Google Cloud Course Topics and Program Outline
A tailored 24-hour, six-module workshop: one learning journey from observability foundations to a capstone production build with a simulated incident drill.
Built by Edstellar with observability and SRE practitioners
Built by practitioners who run observability for production Google Cloud workloads, shaped around your stack and use cases.
We map your current telemetry coverage, dashboards, and alerting gaps so every lab targets what your teams actually run.
Instructor-led sessions cover Cloud Monitoring, Logging, Trace, and Profiler with live demos in real Google Cloud projects.
You instrument services, build dashboards, write MQL queries, and tune alerts in guided labs across 24 hours of instruction.
Teams deliver a production-grade observability setup for a sample app, including a simulated incident drill and instructor review.
From workspace setup to a capstone production 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.
Set up a Cloud Monitoring workspace, enable APIs, and connect a sample workload.
learna)The three pillars: metrics, logs, traces
b)Cloud Monitoring workspace setup
c)Enabling APIs and agent installation
d)Navigating the Cloud Console observability views
Build a service dashboard with MQL charts and uptime checks.
practicea)Built-in vs custom metrics
b)Writing MQL queries for analysis
c)Building dashboards for services
d)Uptime checks and synthetic monitoring
Ship structured logs, create sinks, and build log-based metrics.
practicea)Structured vs unstructured logs
b)Cloud Logging routing and sinks
c)Log-based metrics
d)Log Analytics queries for troubleshooting
Instrument a multi-service app and analyze latency with traces and profiles.
practicea)Trace context and span propagation
b)Instrumenting services with Cloud Trace
c)Reading latency breakdowns
d)Continuous profiling with Cloud Profiler
Define SLOs, wire burn-rate alerts, and run an incident drill.
applya)Alert policies and notification channels
b)Defining SLIs and SLOs
c)Error budgets and burn-rate alerts
d)Incident response workflows
Deliver a production-grade observability setup and defend it in review.
applya)End-to-end instrumentation of a sample app
b)Dashboards, alerts, and SLOs for the app
c)Simulated incident: detect and debug
d)Instructor review and standards checklist
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 reviewed by the instructor.
Set up observability on Google Cloud
Enable Monitoring, Logging, Trace, and Profiler in your projects and connect workloads with agents and instrumentation.
Query metrics and build dashboards
Use MQL and the Cloud Console to analyze metrics and build dashboards that surface service health.
Design structured logging
Emit structured logs, route them with sinks, and derive log-based metrics for searchable, useful telemetry.
Trace and profile distributed services
Propagate trace context across services and use Cloud Profiler to find latency and resource hotspots.
Define SLOs and error budgets
Turn user journeys into SLIs and SLOs, and use error budgets to guide release and reliability decisions.
Build reliable alerting
Write alert policies with the right signals and notification channels to cut noise and page the right people.
Run incident response with telemetry
Detect, triage, and debug production incidents using dashboards, traces, and logs in a simulated drill.
Teams that Benefit from this Observability on Google Cloud Group Training
This group training is built for engineering teams that run services on Google Cloud and need reliable observability. The content adapts to each cohort's services and telemetry stack, so every group practices the workflows it owns.
Standardize observability across every service
Platform teams define the telemetry standards, dashboards, and alerting defaults that every product team inherits.
Workflow friction
- Inconsistent logging formats across teams
- Dashboard sprawl with no ownership
- Alert fatigue from noisy policies
How the program helps
- Consistent instrumentation standards across services
- Reusable dashboards for every team
- Faster onboarding of new services
Practice use cases
- Custom metrics design
- Dashboard templates
- Alert policy tuning
Run reliable services with SLOs that matter
SRE and DevOps engineers turn raw telemetry into SLOs, error budgets, and alerting that actually reflects user experience.
Workflow friction
- SLOs defined without data
- Alerts firing on the wrong signals
- Slow root-cause analysis
How the program helps
- SLOs tied to real user journeys
- Error budgets that guide releases
- Incident workflows with clear telemetry
Practice use cases
- SLO and error budgets
- Incident response drills
- Trace-based debugging
Instrument code teams own and operate
Developers learn to emit structured logs, traces, and metrics from their services so production issues surface fast.
Workflow friction
- Blind spots in service behavior
- Logs that are hard to search
- Slow incident triage
How the program helps
- Production issues caught earlier
- Faster debugging with distributed traces
- Better release confidence
Practice use cases
- Structured logging
- Trace instrumentation
- Latency analysis
Gate releases with telemetry-driven checks
QA and release engineers use observability data to validate deployments, catch regressions, and approve rollouts.
Workflow friction
- Release checks based on gut feel
- Regressions found by customers
- Slow rollback decisions
How the program helps
- Deployment validation with live metrics
- Regression detection in staging
- Data-backed release decisions
Practice use cases
- Deployment monitoring
- Canary analysis
- Release dashboards
Cohorts train as a cross-functional workforce, with each small group aligned on shared telemetry standards and incident workflows.
Prerequisites: This program benefits platform engineers, SREs, DevOps engineers, and developers who build or operate services on Google Cloud. Familiarity with cloud concepts helps but is not required, and no prior observability tooling experience is needed. Labs adapt to each cohort's projects and telemetry stack.
Engineer to SRE-ready practitioner
Skills progress from foundational instrumentation to advanced incident response, with each level backed by guided lab hours.
One program that grows with engineering careers, from observability basics to confident production practice.
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 team's calendar. Every mode includes live instruction and the same guided labs in Google Cloud.
Hybrid Training
A blend of live virtual sessions and onsite labs, scheduled in flexible batches around delivery cycles.
- Live instruction with guided cloud labs
- Flexible batch scheduling across weeks
- Onsite capstone sessions available
- Shared dashboard and alert templates
Onsite Training
The instructor and labs come to your office, with teams working in their own projects and war-room sessions for the capstone.
- Instructor in the room for every module
- War-room style capstone build
- Uses your projects and conventions
- Ideal for platform and SRE cohorts
Live Virtual Training
Fully remote delivery with live demos, screen-shared labs, and breakout reviews, scheduled across your time zones.
- Live demos in real cloud projects
- Screen-shared guided labs
- Breakout reviews with the instructor
- Works across time zones
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, Google Cloud footprint, and preferred dates. You receive a tailored proposal with batch options and commercial terms.
Yes. A training advisor walks through your observability maturity, tooling, and goals so the program is scoped to your stack.
Yes. It runs as instructor-led live virtual training with hands-on labs in your own Google Cloud projects and shared screens.
Yes. Onsite delivery is available for teams that want the instructor and labs in the room, scheduled around your calendar.
The standard program runs 24 hours across six modules, typically delivered in focused batches over two to three weeks.
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.
Observability on Google Cloud follows core Google Cloud skills so your team knows the services it is watching. OpenTelemetry then makes instrumentation portable, and SRE, which Google helped define, turns the signals into reliability targets.
Why Choose Edstellar as Your Observability on Google Cloud Corporate Training Provider
When comparing providers, Edstellar is the training partner teams choose for cloud-native expertise and hands-on, production-grade labs.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
The program adapts to your Google Cloud services and telemetry standards, so labs mirror the stack your teams operate every day.
Proven Methodology
A learn, practice, apply arc moves your teams from observability concepts to a reviewed capstone build in 24 hours.
Practice-Based Learning
Every module includes guided hands-on labs in real Google Cloud projects, from dashboards to a simulated incident drill.
Expert Trainers
Sessions are led by practitioners who run observability for production cloud workloads and teach from that experience.
Global Scale
Cohorts run across regions and time zones with consistent content, so distributed platform teams learn the same standards.
Measurable Outcomes
Lab reviews and the capstone checklist show exactly how each engineer's observability skills progressed.
Develop Google Cloud Observability With Actionable Signals and Incident Evidence
Edstellar connects Google Cloud monitoring tools with the questions operators need to answer. Participants build metrics dashboards, structure logs, and investigate traces and profiles before defining SLOs and alerts. The final setup is reviewed through incident practice, emphasizing connected evidence, meaningful service objectives, and a clear rationale for alerting choices.
- Step 01
Consult
We explore Google Cloud service responsibilities and current telemetry challenges to identify gaps in dashboards, structured logging, latency diagnosis, SLOs, and alert interpretation.
- Step 02
Plan
We establish monitoring foundations before metrics and logging, then develop distributed tracing, profiling, and error-budget alerting ahead of the integrated observability review.
- Step 03
Align
We align Google Cloud observability expertise with SRE, platform, DevOps, and developer roles, adapting practice to the cohort's projects, cloud familiarity, and telemetry arrangements.
- Step 04
Customize
Sample services, structured events, and latency scenarios reflect relevant application patterns, enabling tailored dashboards and incident exercises without exposing confidential operational logs.
- Step 05
Execute
Participants build dashboards, route logs, inspect traces and profiles, and rehearse SLO incidents, receiving feedback on signal coverage, latency explanations, and alert usefulness.
- Step 06
Evaluate
We assess the observability setup for coherent metrics, logs, and traces, justified service objectives, and incident evidence demonstrating that alerts support a reasoned investigation.
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 on Google Cloud 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 on Google Cloud Training for Your Team
Share your team size, Google Cloud services, observability maturity, and timelines to receive a tailored training plan and group quote.