# Runbook: Runtime Reachability Facts (Zastava → Signals)

## Goal
Stream runtime symbol evidence from Zastava Observer to Signals in NDJSON batches that align with the runtime/static union schema, stay deterministic, and are replayable.

## Endpoints
- Signals structured ingest: `POST /signals/runtime-facts`
- Signals NDJSON ingest: `POST /signals/runtime-facts/ndjson`
  - Headers: `Content-Encoding: gzip` (optional), `Content-Type: application/x-ndjson`
  - Query/header metadata: `callgraphId` (required), `scanId|imageDigest|component+version`, optional `source`

## NDJSON event shape (one per line)
```json
{
  "symbolId": "pkg:python/django.views:View.as_view",
  "codeId": "buildid-abc123",
  "purl": "pkg:pypi/django@4.2.7",
  "loaderBase": "0x7f23c01000",
  "processId": 214,
  "processName": "uwsgi",
  "containerId": "c123",
  "socketAddress": "10.0.0.5:8443",
  "hitCount": 3,
  "observedAt": "2025-11-26T12:00:00Z",
  "metadata": { "pid": "214" }
}
```

Required: `symbolId`, `hitCount`; `callgraphId` is provided via query/header metadata. Optional fields shown for correlation.

## Batch rules
- NDJSON MUST NOT be empty; empty streams are rejected.
- Compress with gzip when large; maintain stable line ordering.
- Use UTC timestamps (ISO-8601 `observedAt`).
- Avoid PII; redact process/user info before send.

## CAS alignment
- When runtime trace bundles are produced, store under `cas://runtime_traces/<hh>/<sha>.tar.zst` and include `meta.json` with analysisId.
- Pass the same `analysisId` in `X-Analysis-Id` (if present) when uploading union bundles so replay manifests can link graphs+traces.

## Errors & remediation
- `400 callgraphId is required` → set `callgraphId` header/query.
- `400 runtime fact stream was empty` → ensure NDJSON has events.
- `400 Subject must include scanId/imageDigest/component+version` → populate subject metadata.

## Determinism checklist
- Stable ordering of NDJSON lines.
- No host-dependent paths; only IDs/digests.
- Fixed gzip level if used (suggest 6) to aid reproducibility.

## Zastava Observer setup (runtime sampler)
- **Sampling mode:** deterministic EntryTrace sampler; default 1:1 (no drop) for pilot. Enable rate/CPU guard: `Sampler:MaxEventsPerSecond` (default 500), `Sampler:MaxCpuPercent` (default 35). When rates are exceeded, emit `sampler.dropped` counters with drop reason `rate_limit`/`cpu_guard`.
- **Symbol capture:** enable build-id collection (`SymbolCapture:CollectBuildIds=true`) and loader base addresses (`SymbolCapture:EmitLoaderBase=true`) to match static graphs.
- **Batching:** buffer up to 1,000 events or 2s, whichever comes first (`Ingest:BatchSize`, `Ingest:FlushIntervalMs`). Batches are sorted by `observedAt` before send to keep deterministic order.
- **Transport:** NDJSON POST to Signals `/signals/runtime-facts/ndjson` with headers `X-Callgraph-Id`, optional `X-Analysis-Id`. Set `Content-Encoding: gzip` when batches exceed 64 KiB.
- **CAS traces (optional):** if EntryTrace raw traces are persisted, package as `cas://runtime_traces/<hh>/<sha>.tar.zst` with `meta.json` containing `analysisId`, `nodeCount`, `edgeCount`, `traceVersion`. Include the CAS URI in `metadata.casUri` on each NDJSON event.
- **Security/offline:** disable egress by default; allowlist only the Signals host. TLS must be enabled; supply client certs per platform runbook if required. No PID/user names are emitted—only digests/IDs.

### Example appsettings (Observer)
```json
{
  "Sampler": {
    "MaxEventsPerSecond": 500,
    "MaxCpuPercent": 35
  },
  "SymbolCapture": {
    "CollectBuildIds": true,
    "EmitLoaderBase": true
  },
  "Ingest": {
    "BatchSize": 1000,
    "FlushIntervalMs": 2000,
    "Endpoint": "https://signals.local/signals/runtime-facts/ndjson",
    "Headers": {
      "X-Callgraph-Id": "cg-123"
    }
  }
}
```

### Operational steps
1) Enable EntryTrace sampler in Zastava Observer with the config above; verify `sampler.dropped` stays at 0 during pilot.
2) Run a 5-minute capture and send NDJSON to a staging Signals instance using the smoke test; confirm 202 and CAS pointers recorded.
3) Correlate runtime facts to static graphs by callgraphId in Signals; ensure counts match sampler totals.
4) Promote config to prod/offline bundle; freeze config hashes for replay.

## Smoke test
```bash
cat events.ndjson | gzip -c | \
  curl -X POST "https://signals.local/signals/runtime-facts/ndjson?callgraphId=cg-123&component=web&version=1.0.0" \
       -H "Content-Type: application/x-ndjson" \
       -H "Content-Encoding: gzip" \
       --data-binary @-
```
Expect 202 Accepted with SubjectKey in response; Signals will recompute reachability and emit `signals.fact.updated@v1`.