Resilience Analysis Framework

A repeatable standard to assess applications and guide strategies for preventing, mitigating, and recovering from failures.

🔹 Why Use This Framework?

• Apply a repeatable standard to assess resilience.
• Guide recovery-oriented strategies for preventing, mitigating, and recovering from failures.
• Build both preventative and corrective controls.
• Ensure observability aligns with resilience strategy.

🔹 Desired Resilience Properties

• Fault Isolation → Prevent cascading failures.
• Sufficient Capacity → Scale workloads under load.
• Timely Output → Meet SLA response times.
• Correct Output → Ensure accurate results.
• Redundancy → Replication, failover, backups.

graph TD
  A[Resilient System] --> B[Fault Isolation]
  A --> C[Sufficient Capacity]
  A --> D[Timely Output]
  A --> E[Correct Output]
  A --> F[Redundancy]

Action: Validate all systems against these five core properties.

🔹 Categories of Failure (SEEMS)

1. Single Points of Failure → No redundancy.
2. Excessive Load → Not enough capacity/resources.
3. Excessive Latency → Requests not completing on time.
4. Misconfiguration & Bugs → Incorrect execution.
5. Shared Fate → Violated fault isolation (e.g., noisy neighbors).

flowchart TD
  S[Failures] --> SPoF[Single Point of Failure]
  S --> EL[Excessive Load]
  S --> LAT[Excessive Latency]
  S --> BUG[Misconfig & Bugs]
  S --> SF[Shared Fate]

Action: Map each workload against SEEMS → design mitigation for each category.

🔹 Analysis Maturity

• Beginning → Component-level checks only.
• Application → End-to-end workload analysis.
• Advanced → Full user journey evaluation.

flowchart LR
  B[Beginning: Component-level] --> A[Application: Workload-level] --> ADV[Advanced: User Journey]

Action: Mature resilience testing from components → to workloads → to user journeys.

🔹 What Are We Analyzing?

• End-to-end workload architectures (e.g., mobile in-app purchase flow).
• Includes API gateways, databases, event-driven services, and external dependencies.

Action: Always test user-visible flows, not just infrastructure pieces.

🔹 Common Components to Assess

• Code & Config → CI/CD, IaC, deployment pipelines.
• Infrastructure → Compute, network, storage.
• Data Stores → Databases, replication, caching.
• External Dependencies → APIs, SaaS, partner systems.

Action: Maintain a resilience checklist for each category.

🔹 Resilience Trade-offs

• Cost & Effort → More resilience costs more.
• Complexity → Multi-region = harder to manage.
• Operational Burden → More monitoring, DR drills.
• Consistency & Latency → Trade-offs in distributed systems.

graph TD
  A[High Impact & High Likelihood] -->|Action| FIX[Fix Immediately]
  B[High Impact & Low Likelihood] -->|Action| BACK[Backups & Runbooks]
  C[Low Impact & High Likelihood] -->|Action| AUTO[Automate Recovery]
  D[Low Impact & Low Likelihood] -->|Action| MON[Monitor & Accept Risk]

Action: Weigh designs based on likelihood × impact. Use a risk matrix to prioritize investments.

🔹 Failure Mode Observability

flowchart LR
  L[Leading Indicators] --> WARN[Early Warning: Queue Depth, CPU, Latency]
  G[Lagging Indicators] --> ISSUE[Customer Visible: Downtime, Errors]

Action: Instrument for both — catch failures before users see them.

🔹 Failure Mode Mitigations

• Preventative → Capacity planning, failover, chaos testing.
• Corrective → Incident response, runbooks, rollback, hotfix.

flowchart TD
  F[Failure Mode] --> P[Preventative]
  F --> C[Corrective]

Action: Pair each failure mode with preventative + corrective controls.

🔹 Continuous Improvement

• Operationalize → Schedule resilience reviews and DR tests.
• Test → Regular chaos drills and synthetic failure injection.
• Learn → Post-incident reviews, update playbooks.

flowchart LR
  O[Operationalize] --> T[Test: Chaos Drills]
  T --> L[Learn & Improve]
  L --> O

Action: Treat resilience as an iterative lifecycle, not one-time design.

🔹 Key Takeaways

• Resilience = prevent, mitigate, recover.
• The framework goes beyond traditional architecture → more holistic analysis.
• Build a toolbox:
  • Identify failure modes
  • Create observability
  • Define mitigations
• Continuous improvement is essential.

Action: Embed this framework into project reviews, DR planning, and system design docs.