71e9a56cfd
- Implemented `run-scanner-ci.sh` to build and run tests for the Scanner solution with a warmed NuGet cache. - Created `excititor-vex-traces.json` dashboard for monitoring Excititor VEX observations. - Added Docker Compose configuration for the OTLP span sink in `docker-compose.spansink.yml`. - Configured OpenTelemetry collector in `otel-spansink.yaml` to receive and process traces. - Developed `run-spansink.sh` script to run the OTLP span sink for Excititor traces. - Introduced `FileSystemRiskBundleObjectStore` for storing risk bundle artifacts in the filesystem. - Built `RiskBundleBuilder` for creating risk bundles with associated metadata and providers. - Established `RiskBundleJob` to execute the risk bundle creation and storage process. - Defined models for risk bundle inputs, entries, and manifests in `RiskBundleModels.cs`. - Implemented signing functionality for risk bundle manifests with `HmacRiskBundleManifestSigner`. - Created unit tests for `RiskBundleBuilder`, `RiskBundleJob`, and signing functionality to ensure correctness. - Added filesystem artifact reader tests to validate manifest parsing and artifact listing. - Included test manifests for egress scenarios in the task runner tests. - Developed timeline query service tests to verify tenant and event ID handling.
26 lines
1.4 KiB
Markdown
26 lines
1.4 KiB
Markdown
# Advisory AI CI Runner Harness (DEVOPS-AIAI-31-001)
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Purpose: deterministic, offline-friendly CI harness for Advisory AI service/worker. Produces warmed-cache restore, build binlog, and TRX outputs for the core test suite so downstream sprints can validate without bespoke pipelines.
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Usage
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- From repo root run: `ops/devops/advisoryai-ci-runner/run-advisoryai-ci.sh`
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- Outputs land in `ops/devops/artifacts/advisoryai-ci/<UTC timestamp>/`:
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- `build.binlog` (solution build)
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- `tests/advisoryai.trx` (VSTest results)
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- `summary.json` (paths + hashes + durations)
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Environment
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- Defaults: `DOTNET_CLI_TELEMETRY_OPTOUT=1`, `DOTNET_SKIP_FIRST_TIME_EXPERIENCE=1`, `NUGET_PACKAGES=$REPO/.nuget/packages`.
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- Sources default to `local-nugets` then the warmed cache; override via `NUGET_SOURCES` (semicolon-separated).
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- No external services required; tests are isolated/local.
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What it does
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1) Warm NuGet cache from `local-nugets/` into `$NUGET_PACKAGES` for air-gap parity.
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2) `dotnet restore` + `dotnet build` on `src/AdvisoryAI/StellaOps.AdvisoryAI.sln` with `/bl`.
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3) Run the AdvisoryAI test project (`__Tests/StellaOps.AdvisoryAI.Tests`) with TRX output; optional `TEST_FILTER` env narrows scope.
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4) Emit `summary.json` with artefact paths and SHA256s for reproducibility.
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Notes
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- Timestamped output folders keep ordering deterministic; consumers should sort lexicographically.
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- Use `TEST_FILTER="Name~Inference"` to target inference/monitoring-specific tests when iterating.
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