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Reliability Testing & Continuous Verification

The training presents, with detailed explanations and realistic examples, the motivations, objectives, practices, techniques, and tools for implementing and optimizing continuous verification and open observability. Hands-on labs provide participants with the opportunity to practice key techniques, including automation of software verification, automated observability, AI-based Quality Gates implementation, performance testing, end-to-end testing, and chaos engineering.

Day 1 : Foundations of Testing and Observability

  • Performance Testing foundation
  • Performance Quality Gate 
  • Chaos Engineering foundation
  • Performance tests on individual microservices and APIs: Open Telemetry, k6, Grafana 
  • Stress tests and use the results for capacity planning: k6, Grafana 
  • Comprehensive load testing framework: k6, Harness

Day 2 : AI-powered Open Observability

  • Open Observability Foundation
  • Pipeline-driven Unified Reliability Testing
  • Agile & AI-driven Test Management (Squash)
  • Design and execute complex chaos experiments: failure flags.
  • Test Management with Squash
  • AI-SQUARE platform: Performance Quality Gate Verification & Root Cause Analysis

Day 3 : Compliance and Holistic AI-powered Observability

  • Continuous Compliance (Kosli)
  • DevOps Change Management (SNOW)
  • AI-Powered Functional Quality Gates Verification Automation
  • Compliance verification and management with Kosli
  • DevOps Change Management with SNOW.
  • AI-SQUARE holistic Observability: Models, Knowledge Graph and Orchestration

This course is available online and onsite and fully customizable to your needs.
*The course is also available in French.

Theory

Practical Labs

Learning outcomes:

This training allows you to understand and practice industrial techniques and practices to implement Unified Reliability Testing for complex systems covering Performance testing, Chaos Engineering, Open Observability and AI-powered Quality Gates verification. It will enable your teams to implement and optimize software verification and observability through advanced AI-powered techniques and practices.

Your profile and prerequisites:

  • DevOps, SRE, System Infra engineers
  • Staging Decision Makers
  • Quality – Operation – Processes Managers

With knowledge of

  • DevOps and Software Testing
  • Software & System Engineering 
  • Container & Cloud Engineering

Learning outcomes:

You will learn how to effectively apply SRE hard and soft skills in your work and architecture.

  1. Understand what SRE is, why it is important and learn how it can be applied in practise with the Digital Highway for Software Delivery.
  2. Learn how to understand the inner working of your application in production through applying SLO engineering principles and Observability.
  3. Learn how to continuously deliver software into production and how to embrace the shift right paradigm through Continuous Verification and Rollbacks 3.

Your profile and prerequisites:

  • Software engineers 
  • DevOps engineers
  • System engineers
  • ML Architects

With knowledge of

  • Software Engineering skills (OOP, Scripting, ad ac code,…)
  • System Engineering skills (OS, Network, Deployment, Security, Monitoring,…)
  • Advantageous: Performance Analysis, Release Engineering, APM/Infra Monitoring Distributed/ Reliable Architect Design