[FEATURE] Chaos/Resiliency Evaluation of Agents

[vinayakarannil]

Problem Statement

When evaluating AI agents in production environments, developers currently lack systematic approaches to assess operational resilience under failure conditions. This creates several critical gaps.

• Untested failure modes: Agents are deployed without understanding how they handle tool failures, resource constraints, degraded inputs, or coordination issues
• Production incidents: Agents fail unpredictably when dependent services experience degradation, leading to customer experience issues
• Limited observability: No standardized way to measure agent robustness, retry strategies, fallback behaviors, or graceful degradation
• Evaluation blind spot: Traditional evaluation focuses on functional correctness under normal conditions but ignores operational resilience
  .
  I would like Strands to support chaos/resiliency testing as a core capability (may be as an additional library)

Proposed Solution

Add a chaos testing library that enables systematic injection of failures during agent execution:

1. Failure injection framework: Tool-agnostic interception layer that wraps tool calls to inject controlled failures without modifying agent core logic
2. Failure categories: Support for tool failures, resource constraints, input degradation, output corruption, and multi-agent coordination failures
3. Declarative configuration: Define chaos experiments through configuration files specifying failure types, injection rates, and conditions
4. Resiliency metrics: Built-in evaluators to measure retry strategies, fallback effectiveness, error handling, and graceful degradation
5. Framework compatibility: Support agents built with any framework (LangChain, AutoGPT, CrewAI, custom implementations)

Use Case

• Pre-production validation: Test agent resilience before deployment by simulating API timeouts, rate limits, and service degradation
• Resiliency benchmarking: Measure and compare agent robustness across different implementations or configurations
• Failure mode discovery: Identify weak points in agent error handling and recovery logic
• Production readiness: Validate that agents can handle real-world infrastructure failures gracefully

Alternatives Solutions

No response

Additional Context

No response