the course
Design systems that remain reliable — even when everything fails.
Failure is inevitable in modern IT systems.
Yet most teams don’t design for it.
The result?
Incidents escalate, recovery slows down, and systems become harder to control.
This reliability engineering training shows you how to design, validate and operate reliable systems — with practical patterns and real-world trade-offs.
For engineers, architects and IT professionals responsible for system reliability.
If you design, build or operate systems that need to stay available under pressure, this training is for you.
It is especially relevant if you:
Available as a 2-day classroom training (on-site or virtual via Teams/Zoom) and as a self-paced e-learning.
The e-learning consists of 90+ short videos with a total duration of approximately 5–6 hours.
No specific prerequisites are required.
A basic understanding of IT concepts is recommended. If you are new to IT, we advise starting with our IT Fundamentals training.
Reliability By Default
Course Agenda
0. Architecture in Practice
1. Scope, Mindset & Shared Language
2. Software Resilience & Designing for Failure
3. High Availability Architecture
4. Safe Change & Delivery Reliability
5. Data Reliability & State Management
6. Resilience Validation & Chaos Engineering
7. System Intelligence & Observability
8. Adoption, Governance & Reliability Maturity
Learn how modern system design is driven by trade-offs, simplicity (KISS) and continuous change. Understand why architecture is never static and how reliability is influenced by design decisions from day one.
Build a solid foundation in reliability engineering, including SLI, SLO and error budgets. Learn how SRE principles and reliability economics shape system design and operational decisions.
Design systems that handle failure gracefully using patterns like retries, backoff, circuit breakers and bulkheads. Prevent cascading failures with loose coupling, backpressure and cell-based architecture.
Understand high availability beyond infrastructure, including availability zones, multi-region design and failover strategies. Learn how to control blast radius and design for predictable recovery.
Implement reliable delivery with GitOps, Infrastructure as Code and progressive delivery strategies like canary and blue-green deployments. Use guardrails, feature flags and automated policies to reduce risk.
Master data consistency, replication and recovery strategies. Explore CAP and PACELC, eventual consistency, and how to prevent data corruption in distributed systems.
Validate system behavior under stress using resilience testing and chaos engineering. Learn how to define steady state, test failure scenarios and safely experiment in production.
Move beyond monitoring with observability, tracing and system intelligence. Apply SRE concepts like the four golden signals and use data-driven insights for better decision making.
Scale reliability across teams using platform engineering, policy-as-code and governance models. Learn how to implement reliability guardrails, maturity models and continuous improvement loops.
This reliability engineering training helps you design systems that remain stable under real-world conditions.
Available through preferred suppliers and procurement channels.
Design a training that fits your IT landscape, standards and organization
• Combine proven content with your specific architecture and technologies
• Increase relevance and adoption with organization-specific examples
• Build custom classroom training for teams, engineers, management and architects
• Create tailored e-learning aligned with your internal guidelines
• Integrate learning into your intranet or LMS environment
• Deliver training in your branding and corporate identity
Understand how network and security converge in modern cloud environments
Learn the fundamentals of SASE architecture and cloud-native security
• Explore SD-WAN, CASB and Zero Trust concepts in context
• Understand identity-driven and policy-based access control
• Learn how networking evolves from MPLS to software-defined architectures
• Recognize modern challenges such as remote work, cloud adoption and complexity
Apply SASE principles to scalable and distributed systems
