Email address

Password

Email address

Enter a valid email address

Free Software Telemetry Course

Software Telemetry and Observability

Beginner level 3.0 learning hrs

In this free software telemetry course, you'll learn to follow a slow request across several services. Enroll to see how you can use a trace and related logs to narrow down where the request spent its time.

Stand out with an industry-recognized certificate

Start learning

10,000+ certificates claimed, get yours today!

Get noticed by top recruiters

Share on professional channels

Globally recognised

Land your dream job

Skills you will gain

Observability

Metrics & Monitoring

Distributed Tracing

Log Management

OpenTelemetry

Prometheus & Grafana

+6 More

Key Highlights

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

About this course

When a request slows down, this free software telemetry course shows you how to decide which signals to check first. A Grafana dashboard can show when response times changed. A distributed trace follows one request across services, and related logs give you more context about what happened along the way. If you're new to supporting software in production, the course gives you a way to connect those clues before you investigate a possible cause.

The software observability lessons also explain what happens before data reaches a dashboard. You'll see how the OpenTelemetry Collector receives, processes, and exports signals, and why a team might sample traces or limit how long it keeps data. Then you'll consider what to do with those signals. Service level objectives give you a target to monitor, and the alerting lessons help you think through which changes are worth bringing to an on-call team's attention.

Stand out with an industry-recognized certificate

Start learning

10,000+ certificates claimed, get yours today!

Get noticed by top recruiters

Share on professional channels

Globally recognised

Land your dream job

Course outline

Understanding Telemetry Fundamentals and Observability

In this module, you'll learn the definition and purpose of telemetry, how it differs from monitoring and observability, the three pillars of metrics, logs, and traces, data flow through instrumentation and collectors, push versus pull collection models, and key open telemetry standards and tools.

Building the Metrics and Monitoring Foundation

In this module, you'll learn metric types including counters, gauges, and histograms, time-series data fundamentals, metric naming and labeling conventions, the Prometheus data model, aggregation and downsampling, and building dashboards with Grafana.

Capturing and Managing Log Data

In this module, you'll learn structured versus unstructured logging, log levels and schema design, centralized log aggregation with the ELK/EFK stack, parsing and indexing log data, correlating logs with metrics and traces, and log retention policies.

Implementing Distributed Tracing

In this module, you'll learn the anatomy of a trace, span and trace context propagation, instrumenting services with OpenTelemetry, sampling strategies, visualizing traces, and using trace data for root cause analysis in microservices.

Designing Telemetry Pipelines and Architecture

In this module, you'll learn telemetry pipeline architecture, the OpenTelemetry Collector's receivers, processors, and exporters, time-series database selection, scaling telemetry infrastructure, data retention and cost management, and securing sensitive telemetry data.

Establishing SLOs, Alerting, and Incident Response

In this module, you'll learn how to define SLIs, SLOs, and SLAs, use error budgets for decision-making, design effective alerts, reduce alert fatigue, run on-call workflows, and conduct blameless postmortems after incidents.

Applying Intelligent Analysis and Anomaly Detection

In this module, you'll learn to baseline normal system behavior, detect anomalies across metrics and logs, apply AI-assisted pattern recognition and automated root cause suggestions, understand AIOps practices, and validate automated findings with human oversight.

From Telemetry Maturity to Enterprise Observability Strategy

In this module, you'll learn to assess telemetry maturity, run a gap analysis, build an observability roadmap, establish governance and tooling standards, manage costs at scale, and measure the business value of observability.

Get access to the complete curriculum once you enroll in the course

View Full Course

Software Telemetry and Observability

3.0 Hours

Beginner

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

Trusted by 10 Million+ Learners globally

4.6

4.89

4.94

4.7

Frequently Asked Questions

Where do I start if I'm new to software observability?

Start with how software produces telemetry and how collectors receive it. That foundation helps you follow the later lessons on tracking changes in a system and investigating a slow request.

When would I use a counter, gauge, or histogram in Prometheus?

A counter tracks a running total, a gauge captures a value that can rise or fall, and a histogram groups observations into ranges. The metrics lessons explain how Prometheus represents these measurements.

What makes structured logs easier to search?

Structured logs store details in consistent fields, which makes them easier to parse and index. The logging module connects those choices to searching records in a centralized logging system.

How does a distributed trace link work across services?

The tracing module shows how services pass along the context that identifies a request. That context lets you connect spans, which record individual operations, and see where the request spent time.

What do receivers, processors, and exporters do in the OpenTelemetry Collector?

A receiver brings telemetry into the collector, a processor handles it along the way, and an exporter sends it to a destination. The course uses these parts to explain how a telemetry pipeline is organized.

Why might a team sample its traces?

Sampling means keeping a selection of traces for analysis. The tracing lessons introduce sampling strategies so you can understand the trade-off between the amount of data collected and the detail available.

How do service level objectives and error budgets fit together?

A service level objective sets a performance or reliability target. The error budget expresses how much the service can fall short while staying within that target, giving teams a basis for decisions.

What comes after an alert reaches the on-call team?

The course covers on-call workflows for handling incidents and blameless postmortems for reviewing them. The review helps teams examine what happened and what they can improve after the incident.

How does the course approach automated anomaly detection?

You first study how to establish a baseline for normal behavior in metrics and logs. Then you see how AI can suggest patterns or possible causes and why a person reviews those suggestions.

Where can I go next if my team already collects telemetry?

The final module introduces a maturity assessment and gap analysis. You can use those concepts to identify where your team's collection or tooling falls short and put improvements in an observability roadmap.