{"data":{"kind":"file","path":"README.md","version_id":"zmpfu96r3kxhzr7296388a57","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":2490,"modified_at":"2026-08-26T13:18:14.825000","content_hash":"124d5252be84ad0804f1dd1b00c41fa49928ca2e1c4bb19490ce18491551b873"},"entries":[],"content":"# Microservices Orchestration Simulator\n\nA verifiers environment that evaluates LLM reasoning about microservices orchestration in distributed systems.\n\n## Overview\n\nThis environment presents realistic microservices architecture scenarios requiring the model to:\n\n- **Design service topologies** with proper dependency graphs and communication patterns\n- **Implement failure recovery** strategies including circuit breakers, retries, and fallbacks\n- **Optimize resource allocation** across heterogeneous service clusters\n- **Reason about latency propagation** in multi-hop service chains\n- **Debug orchestration issues** from logs, metrics, and trace data\n- **Evaluate trade-offs** between consistency, availability, and partition tolerance\n\n## Task Types\n\n### 1. Topology Design\nGiven a set of business requirements, design a microservices topology with:\n- Service boundaries and responsibilities\n- Communication patterns (sync/async, pub/sub, event-driven)\n- Data ownership and consistency models\n\n### 2. Failure Scenario Analysis\nGiven a system state with failing services, determine:\n- Root cause from logs and metrics\n- Blast radius of the failure\n- Correct recovery strategy (circuit breaker, bulkhead, retry with backoff)\n\n### 3. Load Balancing Optimization\nGiven traffic patterns and service capacities, compute:\n- Optimal routing weights\n- Auto-scaling thresholds\n- Queue depth and backpressure policies\n\n### 4. Latency Chain Analysis\nGiven a service dependency graph with per-hop latencies:\n- Calculate end-to-end P50/P95/P99 latencies\n- Identify bottleneck services\n- Propose optimization strategies\n\n### 5. Orchestration Workflow Design\nGiven a business process, design:\n- Saga pattern implementation\n- Compensation logic for partial failures\n- Idempotency guarantees\n\n## Evaluation\n\n- **Correctness**: Are the proposed solutions technically sound?\n- **Completeness**: Are failure modes and edge cases addressed?\n- **Efficiency**: Are resource allocations and routing decisions optimal?\n- **Robustness**: Do solutions handle partial failures gracefully?\n\n## Scoring\n\nEach task has multi-dimensional scoring:\n- `topology_score`: correctness of service graph design\n- `failure_handling_score`: quality of failure recovery strategies\n- `optimization_score`: efficiency of resource/routing decisions\n- `reasoning_score`: quality of explanation and trade-off analysis\n\n## Usage\n\n```python\nimport verifiers as vf\nenv = vf.load_environment(\"microservices-orchestration-simulator\")\n```\n","encoding":"utf-8","truncated":false,"total_bytes":2490},"status":null}