L9 Techniques for Building Reliable Systems | Designing Data-Intensive Applications скачать в хорошем качестве

L9 Techniques for Building Reliable Systems | Designing Data-Intensive Applications

In Module 1 – Lecture 9: Techniques for Building Reliable Systems, we dive into the engineering principles that separate fragile systems from production-grade architectures. Reliability isn’t accidental — it’s designed. In this lecture, you’ll learn the core techniques used by high-performing engineering teams to build systems that remain stable under failure, scale gracefully, and recover intelligently. We cover: 🔹 Monitoring and Observability — Understanding what your system is actually doing in real time 🔹 Graceful Degradation — Designing systems that partially function instead of completely collapsing 🔹 Fail-Fast vs Fail-Safe Architectures — When to stop immediately vs when to preserve continuity 🔹 Redundancy Strategies — Eliminating single points of failure 🔹 Isolation and Sandboxing — Preventing failures from cascading across services 🔹 Culture of Reliability (SRE Mindset) — Why reliability is as much cultural as technical 🔹 Synthesis: Reliability Is Layered — How these techniques combine into a resilient architecture This lecture is essential for: • Backend engineers • AI system builders • Distributed systems designers • DevOps & SRE professionals • Founders building scalable products If you're building AI agents, distributed systems, or large-scale applications, understanding reliability is non-negotiable. Because in production, failure is not an exception — it’s a certainty. The question is: Did you design for it?