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Perstack 0.0.1 is released 🎉

Observing

Every Perstack execution produces a complete audit trail. Use events and checkpoints to monitor, debug, and verify Expert behavior.

Event stream

perstack run outputs JSON events to stdout:

npx perstack run my-expert "query" | tee execution.jsonl

Each line is a JSON object:

{"type":"startRun","timestamp":1234567890,"runId":"abc123",...} {"type":"startGeneration","timestamp":1234567891,...} {"type":"finishGeneration","timestamp":1234567892,...} {"type":"finishStep","timestamp":1234567893,...} {"type":"finishRun","timestamp":1234567894,...}

Event types

EventWhen
startRunRun begins
startGeneration / finishGenerationLLM call lifecycle
finishStepStep completes
finishRunRun ends
errorRunError occurs

For the full event schema and state machine, see Runtime.

Filtering events

Use jq to extract specific information:

# Errors only npx perstack run my-expert "query" | jq 'select(.type == "errorRun")' # Token usage per step npx perstack run my-expert "query" | jq 'select(.type == "finishGeneration") | {step, usage}' # Final result npx perstack run my-expert "query" | jq 'select(.type == "finishRun")'

Checkpoints

Checkpoints are saved to perstack/jobs/{jobId}/runs/{runId}/ in the workspace. Each checkpoint contains complete state — message history, usage, Expert info — enabling replay and forensic analysis.

See Runtime for the full directory structure.

Integrating with monitoring

CloudWatch (AWS)

npx perstack run my-expert "query" 2>&1 | \ while read line; do echo "$line" | aws logs put-log-events ... done

Or use ECS/Fargate log drivers to capture stdout automatically.

Custom integration

import { run } from "@perstack/runtime" await run(params, { eventListener: (event) => { // Send to your monitoring system metrics.increment(`perstack.${event.type}`) if (event.type === "errorRun") { alerting.notify(event) } if (event.type === "finishRun") { metrics.gauge("perstack.tokens", event.totalUsage.totalTokens) } } })

Auditing checklist

For compliance and security audits:

  • All runs produce event logs
  • Checkpoints retained for required period
  • Token usage tracked per Expert/run
  • Errors monitored and alerted
  • Event logs correlated with platform audit logs

What’s next