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feat(intel): publish E13/E14/E15 intelligence seams to OSS core
Publish the generic, tier-neutral OSS intelligence base so downstream
consumers resolve it on public main (publish-before-consume):
- pkg/scheduler: E13 recurring-evaluation seam (OSS registers no jobs → no-op)
- pkg/signalsources: prometheus/tempo queriers, registry, metric/trace shapes
- pkg/storage: ModelStore lifecycle (E14) over the base Provider
- pkg/core: typed signal seam (SignalLearner/Detector/Observation/TypedVerdict)
- pkg/agent: brain seam (E15 per-type) + analyze metric/trace query tools
- cmd, config, services wiring; fake-metrics script, helm + docs
All exported funcs covered by *_test.go; go vet + go build clean.
Copy file name to clipboardExpand all lines: examples/docker-compose/README.md
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@@ -9,6 +9,7 @@ spun up alongside Versus + Redis.
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|[file/](./file/)| versus + redis | Quickest start; tail a local log file |
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|[loki/](./loki/)| versus + redis + **loki** + **grafana**| Test the `loki` source against a real Loki |
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|[metrics/](./metrics/)| versus + redis + **prometheus** + **pushgateway**| OSS metric/trace **correlation**: `query_metrics`/`query_traces` analyze tools pull host-pushed series during an AI investigation (incident triggered via a `file` log source). All fake data comes from the `scripts/` generators. The standing `prometheus`/`traces`*source* is Enterprise. |
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|[elasticsearch/](./elasticsearch/)| versus + redis + **elasticsearch** + **kibana**| Test the `elasticsearch` source against a real ES |
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|[cloudwatch/](./cloudwatch/)| versus + redis | Test the `cloudwatchlogs` source against your AWS account |
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|[graylog/](./graylog/)| versus + redis + **graylog** + mongodb + opensearch | Test the `graylog` source against a real Graylog |
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