DevOps Foundations: Monitoring and Observability

2h 2mIntermediate2023-12-20

Authors

Ibukun Itimi

DevOps and Observability Engineer

Course details

Monitoring is a key practice area of modern operations. Even as we innovate and evolve our processes, there is still a fundamental need to understand and measure the reliability and performance of our infrastructure and products. In this course, explore techniques and tools for monitoring from a DevOps mindset. Instructor Ibukunoluwa Itimi covers all the functional areas of monitoring (synthetic, real user, system, app, and more) that compose an application stack and describe best practices around implementing, analyzing, and using monitoring.

Skills covered

Software AdministrationDevOps FoundationsServer AdministrationDevOpsFoundationsNetwork AdministrationNetwork and System Administration

Concepts

0. Introduction

01 - Measure, detect, and respond
02 - What you need to know

1. Introduction to Monitoring and Observability

03 - Overview of monitoring and observability
04 - Importance of observability in building applications
05 - Pillars of observability
06 - Observability architecture

2. Metrics and Monitoring

07 - Metric types
08 - Analyzing metrics
09 - Choosing the right metric
10 - Metrics in action using Mimir and Grafana Cloud

3. Tracing and Distributed Systems

11 - Concepts of tracing and distributed systems
12 - Tracing in action using Tempo and Grafana Cloud

4. Logging and Log Management

13 - Concepts of logging and log management
14 - Best practices for logging
15 - Log collection and application
16 - Log monitoring in action using Loki and Grafana Cloud

5. Events

17 - Collecting system events
18 - Event analysis and correlation

6. Monitoring Techniques

19 - Application performance monitoring
20 - Synthetics monitoring
21 - Infrastructure monitoring
22 - Product monitoring
23 - Other monitoring techniques

7. Utilizing Observability Signals

24 - Dashboards and visualization
25 - Monitoring and alerting
26 - SLIs, SLOs, SLAs
27 - Incident management
28 - Machine learning and observability

Conclusion

29 - Choosing your observability stack
30 - Measuring the success of your observability
31 - Implementing observability in your organization