Problems / Multi-agent and harness, medium

Harness progress notes

The harness writes progress notes and a checkpoint after every turn to a store with 6 slots.

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Your goals

Success ≥ 95% of tasks, p99 ≤ 90 s.

Test cases

Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 6; 2 of them are hidden until then.

  1. As given. The problem’s own traffic, scheduled failures and seed.
  2. Peak hour. 25% more traffic than the problem states, with the same failures.
  3. A slow dependency. The main data store or model answers twice as slowly for part of the run.
  4. A server dies. One replica of the service with the most replicas is killed for part of the run.

The traffic

30 requests a second for 45 seconds: 100% task (writes).

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic enters here.Calls Agent API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header.–
Agent APIApp serviceLoad balancer forwards to it.Calls Agent harness.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s.3 replicas × 500 slots · timeout 180 s
Agent harnessAgent harnessAgent API calls it.Calls Model, Checkpoint store.A harness is everything around the model in an agent: context management, tools, checkpoints, retries and evaluation.400 slots · 6 steps
ModelLLM endpointAgent harness calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second.2000 streams
Checkpoint storeCheckpoint storeAgent harness calls it.Durable execution saves state after each step so a crash resumes instead of starting over.6 slots

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