Every system has an Achilles' heel—the one component whose failure makes all your other redundancy meaningless. Here's how to find yours.
High availability isn't about preventing failures—it's about surviving them. Learn how to design systems that keep running when components inevitably break.
Why databases need copies of themselves, the trade-offs between speed and safety, and what happens when the primary fails.
Your system can't be everywhere at once—but it needs to survive as if it could. Geographic redundancy is the art of choosing which impossible problem you'd rather solve.
Distributed systems are hard because you can never know the truth—whether a message arrived, if a node is dead or slow, or what time it actually is. Understanding this fundamental uncertainty is the first step to building reliable systems.
Why distributed systems face an impossible choice during network failures—and how that choice shapes everything from your bank's database to DNS.
Every distributed system must choose its lie. Strong consistency pretends writes are instant. Eventual consistency pretends everyone agrees. Understanding this trade-off is the key to building systems that stay available when networks fail.
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