timeseries [6/6] RUM-13949 Add end-to-end timeseries verification tests with CSV fixtures#3436
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timeseries RUM-13949 Add end-to-end timeseries verification tests with CSV fixtures
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## tvaleev/feature/RUM-13949/timeseries-rum-session-wiring #3436 +/- ##
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Introduces the core primitives for the timeseries data pipeline: `Timeseries` interface (with `@NoOpImplementation`), `DataPoint`, `Buffer`, `DeltaCompression`, `Pipeline`, `EventWriter`, `JsonSerializer` interface, `DataPointsReader` interface, `VitalReaderWrapper`, and the generic `RumSessionScopeTimeseries` per-session collector. Also adds detekt safe-call allowlist entries for the new APIs. ### What does this PR do? Adds the foundational building blocks shared by all timeseries metric types: the `Timeseries` lifecycle interface, immutable `DataPoint`, the `Buffer`/`DeltaCompression`/`Pipeline` data-processing chain, the `EventWriter` flush boundary, `JsonSerializer` interface, `DataPointsReader`/`VitalReaderWrapper` for OS-metric abstraction, and `RumSessionScopeTimeseries` — the generic per-session scheduler that drives sampling, batching, and writing for any metric type. ### Motivation Establishes the shared infrastructure that CPU and memory collectors will extend, keeping primitive types and pipeline logic isolated so they can be reviewed without metric-specific details. ### Additional Notes Unit tests cover all primitives. `DataPointForgeryFactory` and the `Configurator` registration are included so subsequent commits can write tests against generated `DataPoint` values. `RumSessionTypeExt` session-type mappings are added here (used by both CPU and memory serializers in later commits).
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- Switch `RumSessionScopeTimeseries` from owning a per-session executor to accepting a shared `ScheduledExecutorService` (no creation, no shutdown). - Add `RumSessionScopeTimeseriesFactory` so reviewers can see how `RumSessionScopeTimeseries` is instantiated. - Wire timeseries `start`/`stop` lifecycle into `RumSessionScope` (`startTimeseries`/`stopTimeseries` called from `renewSession`/`stopSession`). - Remove 3 unused entries added to `detekt_custom_safe_calls.yml` in this branch.
### What does this PR do? Adds `CpuDatapointReader`, which reads CPU-usage metrics from the existing `CpuVitalReader` vital and wraps them as `DataPoint` values; and `CpuEventSerializer`, which converts a batch of CPU `DataPoint`s into a `RumTimeseriesCpuEvent` JSON object ready for ingestion. ### Motivation Implements CPU metric collection as the first concrete timeseries type, exercising the pipeline infrastructure introduced in the previous commit. ### Additional Notes `CpuDatapointReader` normalises the raw MHz value to a 0–100 percent scale and clamps it with `coerceIn`. `CpuEventSerializer` maps `RumSessionType` to `RumTimeseriesCpuEvent.Session.Type` via the `toTimeseriesCpuSessionType()` extension. Both classes are fully covered by unit tests.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…ions Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds `MemoryEventSerializer`, which converts a batch of memory `DataPoint`s (heap + native RSS) into a `RumTimeseriesMemoryEvent` JSON object. Introduces `TimeseriesConfiguration` as the public `@ExperimentalRumApi` configuration class (sampling intervals, batch size, background collection flag). Completes the pipeline with `RumSessionScopeTimeseriesFactory`, which wires CPU and memory readers, serializers, and the `TimeseriesConfiguration` together to create fully configured `RumSessionScopeTimeseries` instances for each new session. Completes the two metric types and provides the factory needed to tie the pipeline to the RUM session lifecycle. `MemoryEventSerializer` reports both heap and native RSS in bytes, normalised to a 0–100 percent scale using device `maxMemory`. `RumSessionScopeTimeseriesFactory` creates one pipeline per metric type and dispatches them through the same `Timeseries.Factory` interface. `TimeseriesConfiguration` exposes sampling interval, batch size, and a background-collection flag with sensible defaults.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds `enableTimeseries()`/`disableTimeseries()` builder methods on `RumConfiguration.Builder`. Wires the `Timeseries.Factory` through `RumFeature` → `DatadogRumMonitor` → `RumApplicationScope` → `RumSessionScope`, so that a new `RumSessionScopeTimeseries` collector is created and started for each sampled session and stopped on session end or SDK teardown. Also enables timeseries in the Kotlin sample app. Connects the standalone pipeline and public configuration API to the existing RUM session lifecycle, completing the end-to-end data flow from configuration through to event emission. Existing scope and monitor test scaffolding is updated to pass `timeseriesFactory = null` / a mock factory where required. The `RumFeature.onStop()` ordering test verifies the writer is still live when the final flush fires.
…ctivityManager cast Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
MemoryInfo() and getMemoryInfo() are listed in knownThrowingCalls as they can throw RuntimeException on broken Android implementations. Extract to readTotalRamBytes() with a safe RuntimeException catch and WARN log, falling back to 0. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
### What does this PR do? Adds a self-contained end-to-end test suite for the timeseries pipeline using CSV-driven input fixtures and golden JSON files, without any real Android API dependencies. Includes `CSVReader`, `CsvTimeseries` (a synchronous, executor-free test double mirroring `RumSessionScopeTimeseriesFactory`), `TimeseriesEndToEndTest`, and the accompanying CSV input and expected JSON fixture files. ### Motivation Provides regression coverage that the full memory and CPU batch outputs match the expected wire format exactly, catching any serialization regressions independently of mock-heavy unit tests. ### Additional Notes Fixtures use a fixed 10-sample / 2-batch scenario. Numeric comparisons use a small relative tolerance for floating-point memory_percent values.
- DataPoint(timestamp→timestampNs), onSessionStart/Stop, remove unsafe ?. call Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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timeseries RUM-13949 Add end-to-end timeseries verification tests with CSV fixturestimeseries [6/6] RUM-13949 Add end-to-end timeseries verification tests with CSV fixtures
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What does this PR do?
Adds a self-contained end-to-end test suite for the timeseries pipeline using CSV-driven input fixtures and golden JSON files, without any real Android API dependencies. Includes
CSVReader,CsvTimeseries(a synchronous, executor-free test double mirroringRumSessionScopeTimeseriesFactory),TimeseriesEndToEndTest, and the accompanying CSV input and expected JSON fixture files.Motivation
Provides regression coverage that the full memory and CPU batch outputs match the expected wire format exactly, catching any serialization regressions independently of mock-heavy unit tests.
Review checklist (to be filled by reviewers)