Reliability — Patterns

The Reliability pillar focuses on system availability, performance, disaster recovery, and scalability, so your solutions withstand failures and scale with demand. These patterns turn the pillar’s design principles into concrete, reviewable practices: what to look for in a solution, what good looks like, and the anti-patterns that undermine it.

These patterns put the Reliability pillar’s design principles into practice. Read them alongside the Reliability pillar for the full guidance behind each one.

  • Distribute workload through bulkification — process in batches so a spike in volume doesn’t exhaust governor limits.
  • Assume everything fails — design for the failure of every dependency, not just the ones you expect.
  • Build self-recovering systems — recover automatically from transient failures rather than requiring manual intervention.
  • Design for business requirements first — ground availability and recovery targets in business impact, not arbitrary uptime figures.
  • Validate recovery through drills — prove your disaster-recovery procedures work before you need them.

Each category pairs patterns (what good looks like) with anti-patterns (what to avoid), organized so you can review a solution area by area. Start from the reliability outcome you need:

  • Setting or defending availability and latency targets? Begin with Availability and Performance to ground SLOs in business impact before choosing an architecture.
  • Protecting against data loss or regional failure? Use Disaster Recovery to align backup, failover, and business-continuity procedures to your RPO/RTO.
  • Handling growth or spiky load? Use Scalability to bulkify workloads and stay within governor limits as volume rises.
  • Operating agents in production? Use Agentic Patterns for fallback chains, timeout handling, and agent health monitoring.

Reliability-specific patterns for agentic systems including fallback strategies, timeout handling, and agent health monitoring.

Patterns for high availability, performance optimization, caching, and load management.

Patterns for backup strategies, data recovery, business continuity, and failover procedures.

Patterns for horizontal and vertical scaling, governor limit management, and handling growth.