Building Resilient Distributed Systems

The Challenge

Building distributed systems that survive failure is hard. Not because the individual concepts are complex, but because failures compose in unexpected ways.

Over the past several years, I've worked on systems processing millions of events per second. Here's what I've learned about keeping things running when everything wants to fall apart.

Circuit Breakers

The circuit breaker pattern is your first line of defense. When a downstream service starts failing, you need to fail fast rather than queueing up requests that will never succeed.

typescript
class CircuitBreaker {
  private failures = 0;
  private lastFailure = 0;
  private state: 'closed' | 'open' | 'half-open' = 'closed';

  async call<T>(fn: () => Promise<T>): Promise<T> {
    if (this.state === 'open') {
      if (Date.now() - this.lastFailure > this.resetTimeout) {
        this.state = 'half-open';
      } else {
        throw new Error('Circuit is open');
      }
    }
    try {
      const result = await fn();
      this.onSuccess();
      return result;
    } catch (error) {
      this.onFailure();
      throw error;
    }
  }
}

Retry with Exponential Backoff

Not all failures are permanent. Transient errors — network blips, momentary overloads — resolve themselves. Retries handle these, but naive retries can amplify problems.

Graceful Degradation

The best systems don't just survive failure; they degrade gracefully. Serve cached data when the database is slow. Show a simplified UI when a microservice is down. Always have a fallback.

Key Takeaways