feat(vllm): add vLLM integration #14732

PROFeNoM · 2025-09-30T12:08:48Z

Description

This PR adds a new Datadog tracing integration for vLLM, targeting the V1 engine exclusively. V0 is deprecated and being removed from vLLM (see vLLM Q3 2025 Roadmap), so we're building for the future.

Request Flow and Instrumentation Points

The integration traces requests at the engine level rather than wrapping high-level APIs. This gives us a single integration point for all operations (completion, chat, embedding, classification) with complete access to internal engine metadata and enables profiling the engine process.

Here's how a request flows through vLLM V1 and where we instrument:

1. Engine Initialization (once per engine)

User creates vllm.LLM() or AsyncLLM() or LLMEngine()
    ↓
LLMEngine.__init__() / AsyncLLM.__init__()
    → WRAPPED: traced_engine_init()
        • Forces log_stats=True (needed for output tokens and latency metrics)
        • Captures model name from engine.model_config.model
        • Injects it into output_processor._dd_model_name for later retrieval
    ↓
Engine ready to process requests

2. Request Submission (per request)

User calls llm.generate() / llm.chat() / llm.embed() / etc.
    ↓
Internal flow reaches Processor.process_inputs(trace_headers=...)
    → WRAPPED: traced_processor_process_inputs()
        • Extracts active Datadog trace context from current span/context
        • Injects Datadog headers into trace_headers dict
        • trace_headers propagate through engine automatically
    ↓
Request flows through engine (prefill → decode → completion)

3. Output Processing (when request finishes)

Engine completes request → OutputProcessor.process_outputs(engine_core_outputs)
    → WRAPPED: traced_output_processor_process_outputs()
        • BEFORE calling original:
            - Loop through engine_core_outputs
            - For finished requests: capture req_state data from instance.request_states
              (prompt, params, stats, arrival_time, trace_headers)
        • Call original function (removes req_state from memory)
        • AFTER original returns:
            - Create Datadog span with extracted parent context from trace_headers
            - Tag span with LLMObs metadata (model, tokens, parameters)
            - Extract output_tokens from stats (now updated by original function)
            - Set latency metrics from stats (queue, prefill, decode, TTFT, inference)
            - Finish span
    ↓
Span sent to Datadog with complete request/response data

The key insight is that OutputProcessor.process_outputs has everything we need in one place: request metadata from req_state, output data from engine_core_output, and parent context from trace_headers. We wrap three specific points because each serves a distinct purpose: __init__ for setup, process_inputs for context injection, and process_outputs for span creation.

Version Support

This integration requires vLLM >= 0.10.2 for V1 engine support. Version 0.10.2 includes vLLM PR #20372 which added the trace_headers parameter that we rely on for trace context propagation through the engine.

We don't support V0 at all. It's deprecated and being removed from vLLM. Even if we had supported v0.10.1 and earlier, we'd have to drop it in the next major tracer release anyway, so there's no point building and maintaining for a dead engine.

The integration includes a version check that gracefully skips instrumentation on older versions with a warning log, just in case a customer uses vLLM <= 0.10.1. The instrumentation would otherwise make their application raise an error because of the trace header injection.

Metadata Captured

The following metadata is captured:

Request: prompt, input tokens, sampling parameters (temperature, top_p, max_tokens, seed, etc.)
Response: output text, output tokens, finish reason, cached tokens
Latency metrics: TTFT, queue time, prefill time, decode time, inference time
- These mirror what vLLM captures in its OpenTelemetry do_tracing function for symmetry
Model: name, provider, LoRA adapter (if used)
Embeddings: dimension, count

For chat requests where vLLM doesn't preserve the prompt string (only token IDs), we decode the token IDs back to text using the model's tokenizer to ensure input_messages are correctly captured.

Testing

Tests run on GPU hardware using the new gpu:a10-amd64 runner tag in GitLab CI (internal docs: GPU Runners). These cannot be run locally on our Macs. We need actual GPU hardware. During dev and testing, I ssh'ed into a g6.8xlarge EC2 instance.

Tests:

Unit tests validate LLMObs event generation for all operation types: completion, chat, embedding, classification, scoring, rewards
Integration test validates RAG scenario with parent-child span relationships and context propagation across async engines

The tests converge on the same instrumentation points (as shown in the request flow), so while we could add more operation combinations, the current coverage should be solid for a first release.

Test infrastructure notes:
Runners take ~5-10 minutes to start on the CI, making test iterations slow. I've added module-scoped fixtures cache LLM instances to reduce overall test time; however, caching adds memory pressure, hence, I increased Kubernetes memory allocation to 12 Gi to handle it

On the EC2 engine, tests run in ~1 mn.

Risks

V1 maturity: V1 is production-ready for most workloads but still evolving toward vLLM 1.0. The engine architecture is stabilizing, but future V1 changes may require integration updates. Our instrumentation points (process_inputs and process_outputs) are core to V1's design and unlikely to change significantly.

No V0 support: Customers still on V0 won't get tracing. However, V0 is deprecated and most production deployments have already migrated (V0 doesn't even support pooling models anymore).

Version requirement: Requiring 0.10.2+ may exclude some users, but 0.10.2 is the current latest release and the trace header propagation mechanism is essential to a simple, maintainable design tbh.

High span burst at startup in RAG scenarios: RAG applications that process large document collections can generate significant span volumes during initial indexing. For example, indexing 1000 document chunks creates 1000 vllm.request embedding spans. This is expected behavior (each embedding request to the engine is traced), but may impact:

Trace readability: Parent traces can become cluttered with dozens of embedding child spans
Ingestion costs: More spans = more data sent to Datadog

We could add an integration-specific config like DD_VLLM_TRACE_EMBEDDINGS=false to selectively disable embedding span creation. However, for now, I believe we should monitor customer feedback and add operation-specific filtering in a follow-up if needed, rather than straight-up over-engineer a solution to a problem that may or may not exist.

Additional Notes

Code Architecture

patch.py: Main entry point, wraps vLLM engine methods, as per usual
extractors.py: Extracts request/response data from vLLM structures
utils.py: Span creation, context injection, metrics utilities
llmobs/_integrations/vllm.py: LLMObs-specific tagging and event building, as per usual

github-actions · 2025-09-30T12:09:25Z

CODEOWNERS have been resolved as:

.riot/requirements/2043c14.txt                                          @DataDog/apm-python
.riot/requirements/460aab7.txt                                          @DataDog/apm-python
.riot/requirements/494e77a.txt                                          @DataDog/apm-python
ddtrace/contrib/internal/vllm/__init__.py                               @DataDog/ml-observability
ddtrace/contrib/internal/vllm/extractors.py                             @DataDog/ml-observability
ddtrace/contrib/internal/vllm/patch.py                                  @DataDog/ml-observability
ddtrace/contrib/internal/vllm/utils.py                                  @DataDog/ml-observability
ddtrace/llmobs/_integrations/vllm.py                                    @DataDog/ml-observability
docker-compose.gpu.yml                                                  @DataDog/apm-core-python
releasenotes/notes/add-vllm-integration-b93a517daeb45f61.yaml           @DataDog/apm-python
tests/contrib/vllm/__init__.py                                          @DataDog/ml-observability
tests/contrib/vllm/_utils.py                                            @DataDog/ml-observability
tests/contrib/vllm/api_app.py                                           @DataDog/ml-observability
tests/contrib/vllm/conftest.py                                          @DataDog/ml-observability
tests/contrib/vllm/test_api_app.py                                      @DataDog/ml-observability
tests/contrib/vllm/test_vllm_llmobs.py                                  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_api_app.test_rag_parent_child.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_basic.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_chat.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_classify.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_embed.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_reward.json  @DataDog/ml-observability
tests/snapshots/tests.contrib.vllm.test_vllm_llmobs.test_llmobs_score.json  @DataDog/ml-observability
.github/CODEOWNERS                                                      @DataDog/python-guild @DataDog/apm-core-python
.gitlab/testrunner.yml                                                  @DataDog/python-guild @DataDog/apm-core-python
.gitlab/tests.yml                                                       @DataDog/python-guild @DataDog/apm-core-python
ddtrace/_monkey.py                                                      @DataDog/apm-core-python
ddtrace/contrib/integration_registry/registry.yaml                      @DataDog/apm-core-python @DataDog/apm-idm-python
ddtrace/llmobs/_constants.py                                            @DataDog/ml-observability
ddtrace/llmobs/_integrations/base.py                                    @DataDog/ml-observability
ddtrace/settings/_config.py                                             @DataDog/apm-core-python
docs/integrations.rst                                                   @DataDog/python-guild
docs/spelling_wordlist.txt                                              @DataDog/python-guild
riotfile.py                                                             @DataDog/apm-python
scripts/ddtest                                                          @DataDog/apm-core-python
scripts/gen_gitlab_config.py                                            @DataDog/apm-core-python
supported_versions_output.json                                          @DataDog/apm-core-python
supported_versions_table.csv                                            @DataDog/apm-core-python
tests/llmobs/suitespec.yml                                              @DataDog/ml-observability

github-actions · 2025-09-30T12:34:35Z

Bootstrap import analysis

Comparison of import times between this PR and base.

Summary

The average import time from this PR is: 236 ± 1 ms.

The average import time from base is: 240 ± 3 ms.

The import time difference between this PR and base is: -3.9 ± 0.1 ms.

Import time breakdown

The following import paths have shrunk:

ddtrace.auto 2.215 ms (0.94%)

ddtrace.bootstrap.sitecustomize 1.490 ms (0.63%)

ddtrace.bootstrap.preload 1.490 ms (0.63%)

ddtrace.internal.remoteconfig.client 0.691 ms (0.29%)

ddtrace 0.725 ms (0.31%)

ddtrace.internal._unpatched 0.071 ms (0.03%)

subprocess 0.041 ms (0.02%)

contextlib 0.041 ms (0.02%)

json 0.029 ms (0.01%)

json.decoder 0.029 ms (0.01%)

re 0.029 ms (0.01%)

enum 0.029 ms (0.01%)

types 0.029 ms (0.01%)

pr-commenter · 2025-09-30T13:02:31Z

Performance SLOs

Comparing candidate alex/feat/vllm (3db04ff) with baseline main (57b137d)

📈 Performance Regressions (3 suites)

📈 iast_aspects - 40/40

✅ re_expand_aspect

Time: ✅ 32.417µs (SLO: <40.000µs 📉 -19.0%) vs baseline: +2.1%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.7%

✅ re_expand_noaspect

Time: ✅ 28.966µs (SLO: <40.000µs 📉 -27.6%) vs baseline: +1.4%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.8%

✅ re_findall_aspect

Time: ✅ 2.901µs (SLO: <10.000µs 📉 -71.0%) vs baseline: -0.9%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.9%

✅ re_findall_noaspect

Time: ✅ 1.412µs (SLO: <10.000µs 📉 -85.9%) vs baseline: -1.3%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_finditer_aspect

Time: ✅ 4.408µs (SLO: <10.000µs 📉 -55.9%) vs baseline: -0.6%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_finditer_noaspect

Time: ✅ 1.415µs (SLO: <10.000µs 📉 -85.8%) vs baseline: -0.6%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +5.0%

✅ re_fullmatch_aspect

Time: ✅ 2.661µs (SLO: <10.000µs 📉 -73.4%) vs baseline: -0.8%

Memory: ✅ 37.749MB (SLO: <39.000MB -3.2%) vs baseline: +5.0%

✅ re_fullmatch_noaspect

Time: ✅ 1.295µs (SLO: <10.000µs 📉 -87.1%) vs baseline: -0.1%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_group_aspect

Time: ✅ 3.137µs (SLO: <10.000µs 📉 -68.6%) vs baseline: +6.7%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.8%

✅ re_group_noaspect

Time: ✅ 1.607µs (SLO: <10.000µs 📉 -83.9%) vs baseline: +0.2%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +4.7%

✅ re_groups_aspect

Time: ✅ 3.283µs (SLO: <10.000µs 📉 -67.2%) vs baseline: +6.6%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_groups_noaspect

Time: ✅ 1.690µs (SLO: <10.000µs 📉 -83.1%) vs baseline: -0.4%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +4.6%

✅ re_match_aspect

Time: ✅ 3.199µs (SLO: <10.000µs 📉 -68.0%) vs baseline: 📈 +18.1%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +5.0%

✅ re_match_noaspect

Time: ✅ 1.303µs (SLO: <10.000µs 📉 -87.0%) vs baseline: -0.1%

Memory: ✅ 37.591MB (SLO: <39.000MB -3.6%) vs baseline: +4.5%

✅ re_search_aspect

Time: ✅ 2.552µs (SLO: <10.000µs 📉 -74.5%) vs baseline: -0.1%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_search_noaspect

Time: ✅ 1.203µs (SLO: <10.000µs 📉 -88.0%) vs baseline: ~same

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.7%

✅ re_sub_aspect

Time: ✅ 3.572µs (SLO: <10.000µs 📉 -64.3%) vs baseline: +4.8%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.6%

✅ re_sub_noaspect

Time: ✅ 1.539µs (SLO: <10.000µs 📉 -84.6%) vs baseline: -0.5%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ re_subn_aspect

Time: ✅ 3.683µs (SLO: <10.000µs 📉 -63.2%) vs baseline: +0.3%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +5.2%

✅ re_subn_noaspect

Time: ✅ 1.616µs (SLO: <10.000µs 📉 -83.8%) vs baseline: +0.3%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +5.0%

📈 iastaspects - 118/118

✅ add_aspect

Time: ✅ 0.404µs (SLO: <10.000µs 📉 -96.0%) vs baseline: -0.8%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +4.0%

✅ add_inplace_aspect

Time: ✅ 0.408µs (SLO: <10.000µs 📉 -95.9%) vs baseline: +0.5%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ add_inplace_noaspect

Time: ✅ 0.318µs (SLO: <10.000µs 📉 -96.8%) vs baseline: -0.6%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ add_noaspect

Time: ✅ 0.278µs (SLO: <10.000µs 📉 -97.2%) vs baseline: -0.8%

Memory: ✅ 37.572MB (SLO: <39.000MB -3.7%) vs baseline: +4.6%

✅ bytearray_aspect

Time: ✅ 1.358µs (SLO: <10.000µs 📉 -86.4%) vs baseline: +2.1%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.8%

✅ bytearray_extend_aspect

Time: ✅ 1.517µs (SLO: <10.000µs 📉 -84.8%) vs baseline: +0.6%

Memory: ✅ 37.788MB (SLO: <39.000MB -3.1%) vs baseline: +4.0%

✅ bytearray_extend_noaspect

Time: ✅ 0.616µs (SLO: <10.000µs 📉 -93.8%) vs baseline: +0.4%

Memory: ✅ 38.004MB (SLO: <39.000MB -2.6%) vs baseline: +5.1%

✅ bytearray_noaspect

Time: ✅ 0.484µs (SLO: <10.000µs 📉 -95.2%) vs baseline: +0.6%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +3.5%

✅ bytes_aspect

Time: ✅ 1.521µs (SLO: <10.000µs 📉 -84.8%) vs baseline: 📈 +17.2%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +3.9%

✅ bytes_noaspect

Time: ✅ 0.494µs (SLO: <10.000µs 📉 -95.1%) vs baseline: +1.4%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ bytesio_aspect

Time: ✅ 1.372µs (SLO: <10.000µs 📉 -86.3%) vs baseline: ~same

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.0%

✅ bytesio_noaspect

Time: ✅ 0.502µs (SLO: <10.000µs 📉 -95.0%) vs baseline: +0.3%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +3.8%

✅ capitalize_aspect

Time: ✅ 0.732µs (SLO: <10.000µs 📉 -92.7%) vs baseline: -1.3%

Memory: ✅ 37.847MB (SLO: <39.000MB -3.0%) vs baseline: +4.1%

✅ capitalize_noaspect

Time: ✅ 0.435µs (SLO: <10.000µs 📉 -95.7%) vs baseline: +0.4%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ casefold_aspect

Time: ✅ 0.734µs (SLO: <10.000µs 📉 -92.7%) vs baseline: -1.1%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.7%

✅ casefold_noaspect

Time: ✅ 0.372µs (SLO: <10.000µs 📉 -96.3%) vs baseline: +1.0%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.8%

✅ decode_aspect

Time: ✅ 0.721µs (SLO: <10.000µs 📉 -92.8%) vs baseline: -0.4%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +3.8%

✅ decode_noaspect

Time: ✅ 0.423µs (SLO: <10.000µs 📉 -95.8%) vs baseline: +1.6%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +3.8%

✅ encode_aspect

Time: ✅ 0.712µs (SLO: <10.000µs 📉 -92.9%) vs baseline: +0.7%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.7%

✅ encode_noaspect

Time: ✅ 0.403µs (SLO: <10.000µs 📉 -96.0%) vs baseline: ~same

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.8%

✅ format_aspect

Time: ✅ 3.366µs (SLO: <10.000µs 📉 -66.3%) vs baseline: +0.3%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.2%

✅ format_map_aspect

Time: ✅ 3.609µs (SLO: <10.000µs 📉 -63.9%) vs baseline: -0.8%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +3.5%

✅ format_map_noaspect

Time: ✅ 0.781µs (SLO: <10.000µs 📉 -92.2%) vs baseline: +1.0%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ format_noaspect

Time: ✅ 0.594µs (SLO: <10.000µs 📉 -94.1%) vs baseline: -0.5%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +4.0%

✅ index_aspect

Time: ✅ 0.361µs (SLO: <10.000µs 📉 -96.4%) vs baseline: +1.5%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.0%

✅ index_noaspect

Time: ✅ 0.278µs (SLO: <10.000µs 📉 -97.2%) vs baseline: ~same

Memory: ✅ 37.591MB (SLO: <39.000MB -3.6%) vs baseline: +3.6%

✅ join_aspect

Time: ✅ 1.370µs (SLO: <10.000µs 📉 -86.3%) vs baseline: -0.7%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ join_noaspect

Time: ✅ 0.492µs (SLO: <10.000µs 📉 -95.1%) vs baseline: +0.5%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.7%

✅ ljust_aspect

Time: ✅ 2.562µs (SLO: <20.000µs 📉 -87.2%) vs baseline: +2.0%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.8%

✅ ljust_noaspect

Time: ✅ 0.413µs (SLO: <10.000µs 📉 -95.9%) vs baseline: +2.5%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.6%

✅ lower_aspect

Time: ✅ 2.187µs (SLO: <10.000µs 📉 -78.1%) vs baseline: -0.4%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.7%

✅ lower_noaspect

Time: ✅ 0.369µs (SLO: <10.000µs 📉 -96.3%) vs baseline: -0.6%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +4.2%

✅ lstrip_aspect

Time: ✅ 2.224µs (SLO: <20.000µs 📉 -88.9%) vs baseline: +0.7%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ lstrip_noaspect

Time: ✅ 0.381µs (SLO: <10.000µs 📉 -96.2%) vs baseline: -0.5%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +3.9%

✅ modulo_aspect

Time: ✅ 1.004µs (SLO: <10.000µs 📉 -90.0%) vs baseline: +0.7%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +3.6%

✅ modulo_aspect_for_bytearray_bytearray

Time: ✅ 1.537µs (SLO: <10.000µs 📉 -84.6%) vs baseline: ~same

Memory: ✅ 38.004MB (SLO: <39.000MB -2.6%) vs baseline: +4.8%

✅ modulo_aspect_for_bytes

Time: ✅ 0.986µs (SLO: <10.000µs 📉 -90.1%) vs baseline: ~same

Memory: ✅ 37.768MB (SLO: <39.000MB -3.2%) vs baseline: +4.2%

✅ modulo_aspect_for_bytes_bytearray

Time: ✅ 1.239µs (SLO: <10.000µs 📉 -87.6%) vs baseline: +0.4%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +4.6%

✅ modulo_noaspect

Time: ✅ 0.629µs (SLO: <10.000µs 📉 -93.7%) vs baseline: ~same

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +3.8%

✅ replace_aspect

Time: ✅ 4.876µs (SLO: <10.000µs 📉 -51.2%) vs baseline: +0.7%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +3.7%

✅ replace_noaspect

Time: ✅ 0.461µs (SLO: <10.000µs 📉 -95.4%) vs baseline: ~same

Memory: ✅ 37.749MB (SLO: <39.000MB -3.2%) vs baseline: +4.0%

✅ repr_aspect

Time: ✅ 0.910µs (SLO: <10.000µs 📉 -90.9%) vs baseline: ~same

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.0%

✅ repr_noaspect

Time: ✅ 0.422µs (SLO: <10.000µs 📉 -95.8%) vs baseline: +0.7%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +5.0%

✅ rstrip_aspect

Time: ✅ 1.926µs (SLO: <20.000µs 📉 -90.4%) vs baseline: +0.5%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.8%

✅ rstrip_noaspect

Time: ✅ 0.380µs (SLO: <10.000µs 📉 -96.2%) vs baseline: +0.7%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.8%

✅ slice_aspect

Time: ✅ 0.497µs (SLO: <10.000µs 📉 -95.0%) vs baseline: -0.3%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +4.0%

✅ slice_noaspect

Time: ✅ 0.447µs (SLO: <10.000µs 📉 -95.5%) vs baseline: ~same

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ stringio_aspect

Time: ✅ 1.573µs (SLO: <10.000µs 📉 -84.3%) vs baseline: +0.6%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.6%

✅ stringio_noaspect

Time: ✅ 0.730µs (SLO: <10.000µs 📉 -92.7%) vs baseline: +1.0%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ strip_aspect

Time: ✅ 2.204µs (SLO: <20.000µs 📉 -89.0%) vs baseline: +0.3%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ strip_noaspect

Time: ✅ 0.387µs (SLO: <10.000µs 📉 -96.1%) vs baseline: +1.8%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +3.8%

✅ swapcase_aspect

Time: ✅ 2.415µs (SLO: <10.000µs 📉 -75.8%) vs baseline: ~same

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.8%

✅ swapcase_noaspect

Time: ✅ 0.535µs (SLO: <10.000µs 📉 -94.7%) vs baseline: -1.3%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +3.9%

✅ title_aspect

Time: ✅ 2.322µs (SLO: <10.000µs 📉 -76.8%) vs baseline: -0.6%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +3.7%

✅ title_noaspect

Time: ✅ 0.503µs (SLO: <10.000µs 📉 -95.0%) vs baseline: +0.2%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +3.8%

✅ translate_aspect

Time: ✅ 3.249µs (SLO: <10.000µs 📉 -67.5%) vs baseline: +0.9%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.7%

✅ translate_noaspect

Time: ✅ 1.041µs (SLO: <10.000µs 📉 -89.6%) vs baseline: +0.6%

Memory: ✅ 37.591MB (SLO: <39.000MB -3.6%) vs baseline: +3.6%

✅ upper_aspect

Time: ✅ 2.201µs (SLO: <10.000µs 📉 -78.0%) vs baseline: +0.4%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +3.8%

✅ upper_noaspect

Time: ✅ 0.372µs (SLO: <10.000µs 📉 -96.3%) vs baseline: -0.3%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +3.7%

📈 iastaspectsospath - 24/24

✅ ospathbasename_aspect

Time: ✅ 4.189µs (SLO: <10.000µs 📉 -58.1%) vs baseline: +1.1%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.7%

✅ ospathbasename_noaspect

Time: ✅ 1.072µs (SLO: <10.000µs 📉 -89.3%) vs baseline: ~same

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.9%

✅ ospathjoin_aspect

Time: ✅ 6.124µs (SLO: <10.000µs 📉 -38.8%) vs baseline: +0.7%

Memory: ✅ 37.591MB (SLO: <39.000MB -3.6%) vs baseline: +4.5%

✅ ospathjoin_noaspect

Time: ✅ 2.289µs (SLO: <10.000µs 📉 -77.1%) vs baseline: -0.8%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +5.3%

✅ ospathnormcase_aspect

Time: ✅ 3.418µs (SLO: <10.000µs 📉 -65.8%) vs baseline: -1.5%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +4.6%

✅ ospathnormcase_noaspect

Time: ✅ 0.569µs (SLO: <10.000µs 📉 -94.3%) vs baseline: +0.6%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.7%

✅ ospathsplit_aspect

Time: ✅ 4.718µs (SLO: <10.000µs 📉 -52.8%) vs baseline: -0.5%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ ospathsplit_noaspect

Time: ✅ 1.587µs (SLO: <10.000µs 📉 -84.1%) vs baseline: +0.4%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +4.7%

✅ ospathsplitdrive_aspect

Time: ✅ 3.625µs (SLO: <10.000µs 📉 -63.8%) vs baseline: -0.5%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ ospathsplitdrive_noaspect

Time: ✅ 0.692µs (SLO: <10.000µs 📉 -93.1%) vs baseline: +0.5%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.7%

✅ ospathsplitext_aspect

Time: ✅ 5.142µs (SLO: <10.000µs 📉 -48.6%) vs baseline: 📈 +14.5%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.8%

✅ ospathsplitext_noaspect

Time: ✅ 1.378µs (SLO: <10.000µs 📉 -86.2%) vs baseline: -1.0%

Memory: ✅ 37.631MB (SLO: <39.000MB -3.5%) vs baseline: +4.9%

🟡 Near SLO Breach (4 suites)

🟡 djangosimple - 30/30

✅ appsec

Time: ✅ 20.478ms (SLO: <22.300ms -8.2%) vs baseline: -0.1%

Memory: ✅ 65.333MB (SLO: <67.000MB -2.5%) vs baseline: +4.5%

✅ exception-replay-enabled

Time: ✅ 1.351ms (SLO: <1.450ms -6.8%) vs baseline: -0.7%

Memory: ✅ 64.489MB (SLO: <67.000MB -3.7%) vs baseline: +4.9%

✅ iast

Time: ✅ 20.563ms (SLO: <22.250ms -7.6%) vs baseline: +0.2%

Memory: ✅ 65.274MB (SLO: <67.000MB -2.6%) vs baseline: +4.4%

✅ profiler

Time: ✅ 15.266ms (SLO: <16.550ms -7.8%) vs baseline: -0.2%

Memory: ✅ 53.669MB (SLO: <54.500MB 🟡 -1.5%) vs baseline: +4.6%

✅ resource-renaming

Time: ✅ 20.623ms (SLO: <21.750ms -5.2%) vs baseline: ~same

Memory: ✅ 65.477MB (SLO: <67.000MB -2.3%) vs baseline: +4.9%

✅ span-code-origin

Time: ✅ 26.213ms (SLO: <28.200ms -7.0%) vs baseline: ~same

Memory: ✅ 67.541MB (SLO: <69.500MB -2.8%) vs baseline: +4.9%

✅ tracer

Time: ✅ 20.488ms (SLO: <21.750ms -5.8%) vs baseline: ~same

Memory: ✅ 65.303MB (SLO: <67.000MB -2.5%) vs baseline: +4.6%

✅ tracer-and-profiler

Time: ✅ 22.027ms (SLO: <23.500ms -6.3%) vs baseline: -0.2%

Memory: ✅ 66.689MB (SLO: <67.500MB 🟡 -1.2%) vs baseline: +5.0%

✅ tracer-dont-create-db-spans

Time: ✅ 19.325ms (SLO: <21.500ms 📉 -10.1%) vs baseline: -0.5%

Memory: ✅ 65.327MB (SLO: <66.000MB 🟡 -1.0%) vs baseline: +4.6%

✅ tracer-minimal

Time: ✅ 16.603ms (SLO: <17.500ms -5.1%) vs baseline: -0.4%

Memory: ✅ 65.352MB (SLO: <66.000MB 🟡 -1.0%) vs baseline: +4.7%

✅ tracer-native

Time: ✅ 20.458ms (SLO: <21.750ms -5.9%) vs baseline: -0.3%

Memory: ✅ 71.347MB (SLO: <72.500MB 🟡 -1.6%) vs baseline: +4.8%

✅ tracer-no-caches

Time: ✅ 18.479ms (SLO: <19.650ms -6.0%) vs baseline: +0.2%

Memory: ✅ 65.284MB (SLO: <67.000MB -2.6%) vs baseline: +4.5%

✅ tracer-no-databases

Time: ✅ 18.841ms (SLO: <20.100ms -6.3%) vs baseline: ~same

Memory: ✅ 65.274MB (SLO: <67.000MB -2.6%) vs baseline: +4.8%

✅ tracer-no-middleware

Time: ✅ 20.225ms (SLO: <21.500ms -5.9%) vs baseline: +0.4%

Memory: ✅ 65.287MB (SLO: <67.000MB -2.6%) vs baseline: +4.6%

✅ tracer-no-templates

Time: ✅ 20.377ms (SLO: <22.000ms -7.4%) vs baseline: +0.3%

Memory: ✅ 65.323MB (SLO: <67.000MB -2.5%) vs baseline: +4.6%

🟡 errortrackingdjangosimple - 6/6

✅ errortracking-enabled-all

Time: ✅ 18.025ms (SLO: <19.850ms -9.2%) vs baseline: -0.4%

Memory: ✅ 65.330MB (SLO: <66.500MB 🟡 -1.8%) vs baseline: +4.9%

✅ errortracking-enabled-user

Time: ✅ 18.389ms (SLO: <19.400ms -5.2%) vs baseline: +1.4%

Memory: ✅ 65.294MB (SLO: <66.500MB 🟡 -1.8%) vs baseline: +4.8%

✅ tracer-enabled

Time: ✅ 18.030ms (SLO: <19.450ms -7.3%) vs baseline: ~same

Memory: ✅ 65.333MB (SLO: <66.500MB 🟡 -1.8%) vs baseline: +4.9%

🟡 flasksimple - 18/18

✅ appsec-get

Time: ✅ 4.587ms (SLO: <4.750ms -3.4%) vs baseline: +0.3%

Memory: ✅ 61.991MB (SLO: <65.000MB -4.6%) vs baseline: +4.9%

✅ appsec-post

Time: ✅ 6.565ms (SLO: <6.750ms -2.7%) vs baseline: -0.3%

Memory: ✅ 61.853MB (SLO: <65.000MB -4.8%) vs baseline: +4.6%

✅ appsec-telemetry

Time: ✅ 4.576ms (SLO: <4.750ms -3.7%) vs baseline: -0.5%

Memory: ✅ 62.049MB (SLO: <65.000MB -4.5%) vs baseline: +5.1%

✅ debugger

Time: ✅ 1.855ms (SLO: <2.000ms -7.2%) vs baseline: -0.2%

Memory: ✅ 45.338MB (SLO: <47.000MB -3.5%) vs baseline: +4.7%

✅ iast-get

Time: ✅ 1.863ms (SLO: <2.000ms -6.9%) vs baseline: ~same

Memory: ✅ 42.369MB (SLO: <49.000MB 📉 -13.5%) vs baseline: +5.0%

✅ profiler

Time: ✅ 1.915ms (SLO: <2.100ms -8.8%) vs baseline: +0.2%

Memory: ✅ 46.419MB (SLO: <47.000MB 🟡 -1.2%) vs baseline: +4.6%

✅ resource-renaming

Time: ✅ 3.379ms (SLO: <3.650ms -7.4%) vs baseline: -0.2%

Memory: ✅ 52.219MB (SLO: <53.500MB -2.4%) vs baseline: +4.9%

✅ tracer

Time: ✅ 3.372ms (SLO: <3.650ms -7.6%) vs baseline: -0.2%

Memory: ✅ 52.258MB (SLO: <53.500MB -2.3%) vs baseline: +4.9%

✅ tracer-native

Time: ✅ 3.367ms (SLO: <3.650ms -7.8%) vs baseline: -0.2%

Memory: ✅ 58.233MB (SLO: <60.000MB -2.9%) vs baseline: +4.7%

🟡 otelspan - 22/22

✅ add-event

Time: ✅ 45.216ms (SLO: <47.150ms -4.1%) vs baseline: -0.4%

Memory: ✅ 45.229MB (SLO: <47.000MB -3.8%) vs baseline: +4.7%

✅ add-metrics

Time: ✅ 319.113ms (SLO: <344.800ms -7.4%) vs baseline: -0.2%

Memory: ✅ 551.838MB (SLO: <562.000MB 🟡 -1.8%) vs baseline: +4.7%

✅ add-tags

Time: ✅ 290.429ms (SLO: <314.000ms -7.5%) vs baseline: ~same

Memory: ✅ 554.144MB (SLO: <563.500MB 🟡 -1.7%) vs baseline: +4.8%

✅ get-context

Time: ✅ 83.893ms (SLO: <92.350ms -9.2%) vs baseline: ~same

Memory: ✅ 40.366MB (SLO: <46.500MB 📉 -13.2%) vs baseline: +4.9%

✅ is-recording

Time: ✅ 42.892ms (SLO: <44.500ms -3.6%) vs baseline: -0.2%

Memory: ✅ 44.596MB (SLO: <47.500MB -6.1%) vs baseline: +4.8%

✅ record-exception

Time: ✅ 61.781ms (SLO: <67.650ms -8.7%) vs baseline: ~same

Memory: ✅ 40.627MB (SLO: <47.000MB 📉 -13.6%) vs baseline: +4.7%

✅ set-status

Time: ✅ 48.822ms (SLO: <50.400ms -3.1%) vs baseline: +0.1%

Memory: ✅ 44.620MB (SLO: <47.000MB -5.1%) vs baseline: +4.8%

✅ start

Time: ✅ 42.337ms (SLO: <43.450ms -2.6%) vs baseline: +0.2%

Memory: ✅ 44.646MB (SLO: <47.000MB -5.0%) vs baseline: +5.0%

✅ start-finish

Time: ✅ 84.983ms (SLO: <88.000ms -3.4%) vs baseline: +0.3%

Memory: ✅ 34.603MB (SLO: <46.500MB 📉 -25.6%) vs baseline: +4.9%

✅ start-finish-telemetry

Time: ✅ 86.659ms (SLO: <89.000ms -2.6%) vs baseline: +0.2%

Memory: ✅ 34.564MB (SLO: <46.500MB 📉 -25.7%) vs baseline: +4.7%

✅ update-name

Time: ✅ 44.241ms (SLO: <45.150ms -2.0%) vs baseline: +0.5%

Memory: ✅ 44.955MB (SLO: <47.000MB -4.4%) vs baseline: +4.8%

⚠️ Unstable Tests (1 suite)

⚠️

coreapiscenario - 10/10 (1 unstable)

⚠️ context_with_data_listeners

Time: ⚠️ 13.233µs (SLO: <20.000µs 📉 -33.8%) vs baseline: -0.6%

Memory: ✅ 32.126MB (SLO: <33.500MB -4.1%) vs baseline: +5.0%

✅ context_with_data_no_listeners

Time: ✅ 3.348µs (SLO: <10.000µs 📉 -66.5%) vs baseline: +1.1%

Memory: ✅ 31.850MB (SLO: <33.500MB -4.9%) vs baseline: +4.2%

✅ get_item_exists

Time: ✅ 0.581µs (SLO: <10.000µs 📉 -94.2%) vs baseline: +0.5%

Memory: ✅ 32.126MB (SLO: <33.500MB -4.1%) vs baseline: +5.6%

✅ get_item_missing

Time: ✅ 0.635µs (SLO: <10.000µs 📉 -93.6%) vs baseline: ~same

Memory: ✅ 32.047MB (SLO: <33.500MB -4.3%) vs baseline: +4.8%

✅ set_item

Time: ✅ 24.174µs (SLO: <30.000µs 📉 -19.4%) vs baseline: -0.4%

Memory: ✅ 31.929MB (SLO: <33.500MB -4.7%) vs baseline: +4.4%

✅ All Tests Passing (16 suites)

✅ errortrackingflasksqli - 6/6

✅ errortracking-enabled-all

Time: ✅ 2.097ms (SLO: <2.300ms -8.8%) vs baseline: +0.8%

Memory: ✅ 52.121MB (SLO: <53.500MB -2.6%) vs baseline: +4.8%

✅ errortracking-enabled-user

Time: ✅ 2.082ms (SLO: <2.250ms -7.5%) vs baseline: ~same

Memory: ✅ 52.101MB (SLO: <53.500MB -2.6%) vs baseline: +4.8%

✅ tracer-enabled

Time: ✅ 2.092ms (SLO: <2.300ms -9.0%) vs baseline: +0.6%

Memory: ✅ 52.101MB (SLO: <53.500MB -2.6%) vs baseline: +4.9%

✅ flasksqli - 6/6

✅ appsec-enabled

Time: ✅ 3.933ms (SLO: <4.200ms -6.3%) vs baseline: ~same

Memory: ✅ 62.148MB (SLO: <66.000MB -5.8%) vs baseline: +4.7%

✅ iast-enabled

Time: ✅ 2.442ms (SLO: <2.800ms 📉 -12.8%) vs baseline: -0.3%

Memory: ✅ 58.570MB (SLO: <60.000MB -2.4%) vs baseline: +4.9%

✅ tracer-enabled

Time: ✅ 2.072ms (SLO: <2.250ms -7.9%) vs baseline: -0.4%

Memory: ✅ 52.239MB (SLO: <54.500MB -4.1%) vs baseline: +4.7%

✅ httppropagationextract - 60/60

✅ all_styles_all_headers

Time: ✅ 80.819µs (SLO: <100.000µs 📉 -19.2%) vs baseline: ~same

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.1%

✅ b3_headers

Time: ✅ 14.332µs (SLO: <20.000µs 📉 -28.3%) vs baseline: +1.1%

Memory: ✅ 32.165MB (SLO: <33.500MB -4.0%) vs baseline: +4.6%

✅ b3_single_headers

Time: ✅ 13.300µs (SLO: <20.000µs 📉 -33.5%) vs baseline: ~same

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ datadog_tracecontext_tracestate_not_propagated_on_trace_id_no_match

Time: ✅ 63.417µs (SLO: <80.000µs 📉 -20.7%) vs baseline: +0.1%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ datadog_tracecontext_tracestate_propagated_on_trace_id_match

Time: ✅ 65.771µs (SLO: <80.000µs 📉 -17.8%) vs baseline: +0.3%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ empty_headers

Time: ✅ 1.600µs (SLO: <10.000µs 📉 -84.0%) vs baseline: ~same

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.7%

✅ full_t_id_datadog_headers

Time: ✅ 22.614µs (SLO: <30.000µs 📉 -24.6%) vs baseline: -0.2%

Memory: ✅ 32.145MB (SLO: <33.500MB -4.0%) vs baseline: +4.7%

✅ invalid_priority_header

Time: ✅ 6.545µs (SLO: <10.000µs 📉 -34.6%) vs baseline: +0.9%

Memory: ✅ 32.145MB (SLO: <33.500MB -4.0%) vs baseline: +4.7%

✅ invalid_span_id_header

Time: ✅ 6.606µs (SLO: <10.000µs 📉 -33.9%) vs baseline: +0.9%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.8%

✅ invalid_tags_header

Time: ✅ 6.536µs (SLO: <10.000µs 📉 -34.6%) vs baseline: +0.9%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +5.1%

✅ invalid_trace_id_header

Time: ✅ 6.602µs (SLO: <10.000µs 📉 -34.0%) vs baseline: +0.3%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +4.9%

✅ large_header_no_matches

Time: ✅ 27.552µs (SLO: <30.000µs -8.2%) vs baseline: +0.3%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ large_valid_headers_all

Time: ✅ 28.868µs (SLO: <40.000µs 📉 -27.8%) vs baseline: +0.7%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ medium_header_no_matches

Time: ✅ 9.922µs (SLO: <20.000µs 📉 -50.4%) vs baseline: +0.7%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.7%

✅ medium_valid_headers_all

Time: ✅ 11.327µs (SLO: <20.000µs 📉 -43.4%) vs baseline: +1.0%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ none_propagation_style

Time: ✅ 1.702µs (SLO: <10.000µs 📉 -83.0%) vs baseline: ~same

Memory: ✅ 32.145MB (SLO: <33.500MB -4.0%) vs baseline: +4.6%

✅ tracecontext_headers

Time: ✅ 34.334µs (SLO: <40.000µs 📉 -14.2%) vs baseline: +0.6%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +4.8%

✅ valid_headers_all

Time: ✅ 6.531µs (SLO: <10.000µs 📉 -34.7%) vs baseline: +0.1%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +5.1%

✅ valid_headers_basic

Time: ✅ 6.218µs (SLO: <10.000µs 📉 -37.8%) vs baseline: +2.1%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ wsgi_empty_headers

Time: ✅ 1.608µs (SLO: <10.000µs 📉 -83.9%) vs baseline: +0.2%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +5.0%

✅ wsgi_invalid_priority_header

Time: ✅ 6.570µs (SLO: <10.000µs 📉 -34.3%) vs baseline: ~same

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.7%

✅ wsgi_invalid_span_id_header

Time: ✅ 1.596µs (SLO: <10.000µs 📉 -84.0%) vs baseline: -0.4%

Memory: ✅ 32.165MB (SLO: <33.500MB -4.0%) vs baseline: +4.7%

✅ wsgi_invalid_tags_header

Time: ✅ 6.562µs (SLO: <10.000µs 📉 -34.4%) vs baseline: ~same

Memory: ✅ 32.244MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ wsgi_invalid_trace_id_header

Time: ✅ 6.597µs (SLO: <10.000µs 📉 -34.0%) vs baseline: ~same

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.8%

✅ wsgi_large_header_no_matches

Time: ✅ 28.784µs (SLO: <40.000µs 📉 -28.0%) vs baseline: +0.2%

Memory: ✅ 32.145MB (SLO: <33.500MB -4.0%) vs baseline: +4.7%

✅ wsgi_large_valid_headers_all

Time: ✅ 29.800µs (SLO: <40.000µs 📉 -25.5%) vs baseline: -0.4%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +4.9%

✅ wsgi_medium_header_no_matches

Time: ✅ 10.170µs (SLO: <20.000µs 📉 -49.1%) vs baseline: +0.7%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ wsgi_medium_valid_headers_all

Time: ✅ 11.542µs (SLO: <20.000µs 📉 -42.3%) vs baseline: +0.2%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ wsgi_valid_headers_all

Time: ✅ 6.575µs (SLO: <10.000µs 📉 -34.2%) vs baseline: +0.3%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ wsgi_valid_headers_basic

Time: ✅ 6.097µs (SLO: <10.000µs 📉 -39.0%) vs baseline: -0.3%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +4.8%

✅ httppropagationinject - 16/16

✅ ids_only

Time: ✅ 21.702µs (SLO: <30.000µs 📉 -27.7%) vs baseline: -0.5%

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +4.9%

✅ with_all

Time: ✅ 28.985µs (SLO: <40.000µs 📉 -27.5%) vs baseline: ~same

Memory: ✅ 32.224MB (SLO: <33.500MB -3.8%) vs baseline: +5.0%

✅ with_dd_origin

Time: ✅ 25.939µs (SLO: <30.000µs 📉 -13.5%) vs baseline: +2.3%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +5.0%

✅ with_priority_and_origin

Time: ✅ 24.796µs (SLO: <40.000µs 📉 -38.0%) vs baseline: -0.3%

Memory: ✅ 32.165MB (SLO: <33.500MB -4.0%) vs baseline: +4.9%

✅ with_sampling_priority

Time: ✅ 22.286µs (SLO: <30.000µs 📉 -25.7%) vs baseline: +2.8%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.9%

✅ with_tags

Time: ✅ 27.354µs (SLO: <40.000µs 📉 -31.6%) vs baseline: +1.0%

Memory: ✅ 32.204MB (SLO: <33.500MB -3.9%) vs baseline: +5.0%

✅ with_tags_invalid

Time: ✅ 28.484µs (SLO: <40.000µs 📉 -28.8%) vs baseline: -0.4%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +5.0%

✅ with_tags_max_size

Time: ✅ 27.708µs (SLO: <40.000µs 📉 -30.7%) vs baseline: +0.2%

Memory: ✅ 32.185MB (SLO: <33.500MB -3.9%) vs baseline: +4.7%

✅ iastaspectssplit - 12/12

✅ rsplit_aspect

Time: ✅ 1.393µs (SLO: <10.000µs 📉 -86.1%) vs baseline: +0.2%

Memory: ✅ 37.611MB (SLO: <39.000MB -3.6%) vs baseline: +4.6%

✅ rsplit_noaspect

Time: ✅ 0.580µs (SLO: <10.000µs 📉 -94.2%) vs baseline: -0.5%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +5.1%

✅ split_aspect

Time: ✅ 1.384µs (SLO: <10.000µs 📉 -86.2%) vs baseline: +0.6%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +5.1%

✅ split_noaspect

Time: ✅ 0.571µs (SLO: <10.000µs 📉 -94.3%) vs baseline: -0.5%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +4.7%

✅ splitlines_aspect

Time: ✅ 1.362µs (SLO: <10.000µs 📉 -86.4%) vs baseline: -1.4%

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +4.8%

✅ splitlines_noaspect

Time: ✅ 0.582µs (SLO: <10.000µs 📉 -94.2%) vs baseline: -0.3%

Memory: ✅ 37.650MB (SLO: <39.000MB -3.5%) vs baseline: +5.0%

✅ iastpropagation - 8/8

✅ no-propagation

Time: ✅ 49.140µs (SLO: <60.000µs 📉 -18.1%) vs baseline: -0.9%

Memory: ✅ 37.729MB (SLO: <39.000MB -3.3%) vs baseline: +4.9%

✅ propagation_enabled

Time: ✅ 180.636µs (SLO: <190.000µs -4.9%) vs baseline: +5.3%

Memory: ✅ 37.670MB (SLO: <39.000MB -3.4%) vs baseline: +4.7%

✅ propagation_enabled_100

Time: ✅ 1.893ms (SLO: <2.300ms 📉 -17.7%) vs baseline: -0.9%

Memory: ✅ 37.690MB (SLO: <39.000MB -3.4%) vs baseline: +4.9%

✅ propagation_enabled_1000

Time: ✅ 32.286ms (SLO: <34.550ms -6.6%) vs baseline: ~same

Memory: ✅ 37.709MB (SLO: <39.000MB -3.3%) vs baseline: +4.9%

✅ otelsdkspan - 24/24

✅ add-event

Time: ✅ 40.449ms (SLO: <42.000ms -3.7%) vs baseline: -0.3%

Memory: ✅ 34.583MB (SLO: <39.000MB 📉 -11.3%) vs baseline: +5.1%

✅ add-link

Time: ✅ 36.503ms (SLO: <38.550ms -5.3%) vs baseline: +0.8%

Memory: ✅ 34.524MB (SLO: <39.000MB 📉 -11.5%) vs baseline: +5.1%

✅ add-metrics

Time: ✅ 219.182ms (SLO: <232.000ms -5.5%) vs baseline: +0.4%

Memory: ✅ 34.544MB (SLO: <39.000MB 📉 -11.4%) vs baseline: +4.9%

✅ add-tags

Time: ✅ 210.915ms (SLO: <221.600ms -4.8%) vs baseline: -0.7%

Memory: ✅ 34.564MB (SLO: <39.000MB 📉 -11.4%) vs baseline: +5.0%

✅ get-context

Time: ✅ 29.159ms (SLO: <31.300ms -6.8%) vs baseline: +0.2%

Memory: ✅ 34.564MB (SLO: <39.000MB 📉 -11.4%) vs baseline: +5.0%

✅ is-recording

Time: ✅ 29.090ms (SLO: <31.000ms -6.2%) vs baseline: ~same

Memory: ✅ 34.524MB (SLO: <39.000MB 📉 -11.5%) vs baseline: +4.8%

✅ record-exception

Time: ✅ 63.217ms (SLO: <65.850ms -4.0%) vs baseline: +0.5%

Memory: ✅ 34.898MB (SLO: <39.000MB 📉 -10.5%) vs baseline: +4.8%

✅ set-status

Time: ✅ 32.018ms (SLO: <34.150ms -6.2%) vs baseline: +0.8%

Memory: ✅ 34.564MB (SLO: <39.000MB 📉 -11.4%) vs baseline: +5.1%

✅ start

Time: ✅ 28.776ms (SLO: <30.150ms -4.6%) vs baseline: ~same

Memory: ✅ 34.524MB (SLO: <39.000MB 📉 -11.5%) vs baseline: +4.9%

✅ start-finish

Time: ✅ 33.955ms (SLO: <35.350ms -3.9%) vs baseline: +0.4%

Memory: ✅ 34.544MB (SLO: <39.000MB 📉 -11.4%) vs baseline: +4.9%

✅ start-finish-telemetry

Time: ✅ 34.105ms (SLO: <35.450ms -3.8%) vs baseline: +0.4%

Memory: ✅ 34.485MB (SLO: <39.000MB 📉 -11.6%) vs baseline: +4.9%

✅ update-name

Time: ✅ 30.985ms (SLO: <33.400ms -7.2%) vs baseline: -0.3%

Memory: ✅ 34.505MB (SLO: <39.000MB 📉 -11.5%) vs baseline: +4.9%

✅ packagespackageforrootmodulemapping - 4/4

✅ cache_off

Time: ✅ 341.107ms (SLO: <354.300ms -3.7%) vs baseline: -0.9%

Memory: ✅ 38.107MB (SLO: <40.000MB -4.7%) vs baseline: +4.5%

✅ cache_on

Time: ✅ 0.383µs (SLO: <10.000µs 📉 -96.2%) vs baseline: -1.1%

Memory: ✅ 36.468MB (SLO: <39.000MB -6.5%) vs baseline: +5.8%

✅ packagesupdateimporteddependencies - 24/24

✅ import_many

Time: ✅ 156.720µs (SLO: <170.000µs -7.8%) vs baseline: +1.4%

Memory: ✅ 36.818MB (SLO: <38.500MB -4.4%) vs baseline: +5.4%

✅ import_many_cached

Time: ✅ 121.983µs (SLO: <130.000µs -6.2%) vs baseline: +0.4%

Memory: ✅ 36.719MB (SLO: <38.500MB -4.6%) vs baseline: +4.6%

✅ import_many_stdlib

Time: ✅ 1.641ms (SLO: <1.750ms -6.2%) vs baseline: +0.5%

Memory: ✅ 36.915MB (SLO: <38.500MB -4.1%) vs baseline: +5.0%

✅ import_many_stdlib_cached

Time: ✅ 0.985ms (SLO: <1.100ms 📉 -10.5%) vs baseline: +0.4%

Memory: ✅ 36.989MB (SLO: <38.500MB -3.9%) vs baseline: +5.1%

✅ import_many_unknown

Time: ✅ 829.896µs (SLO: <890.000µs -6.8%) vs baseline: -0.2%

Memory: ✅ 36.931MB (SLO: <38.500MB -4.1%) vs baseline: +5.4%

✅ import_many_unknown_cached

Time: ✅ 801.371µs (SLO: <870.000µs -7.9%) vs baseline: +1.2%

Memory: ✅ 37.084MB (SLO: <38.500MB -3.7%) vs baseline: +5.7%

✅ import_one

Time: ✅ 19.643µs (SLO: <30.000µs 📉 -34.5%) vs baseline: -0.7%

Memory: ✅ 36.822MB (SLO: <39.000MB -5.6%) vs baseline: +5.5%

✅ import_one_cache

Time: ✅ 6.386µs (SLO: <10.000µs 📉 -36.1%) vs baseline: +0.8%

Memory: ✅ 36.748MB (SLO: <38.500MB -4.5%) vs baseline: +5.2%

✅ import_one_stdlib

Time: ✅ 18.591µs (SLO: <20.000µs -7.0%) vs baseline: -1.1%

Memory: ✅ 36.765MB (SLO: <38.500MB -4.5%) vs baseline: +5.4%

✅ import_one_stdlib_cache

Time: ✅ 6.240µs (SLO: <10.000µs 📉 -37.6%) vs baseline: -1.2%

Memory: ✅ 36.695MB (SLO: <38.500MB -4.7%) vs baseline: +4.6%

✅ import_one_unknown

Time: ✅ 45.591µs (SLO: <50.000µs -8.8%) vs baseline: +0.2%

Memory: ✅ 36.892MB (SLO: <38.500MB -4.2%) vs baseline: +5.0%

✅ import_one_unknown_cache

Time: ✅ 6.258µs (SLO: <10.000µs 📉 -37.4%) vs baseline: -0.7%

Memory: ✅ 36.717MB (SLO: <38.500MB -4.6%) vs baseline: +4.9%

✅ ratelimiter - 12/12

✅ defaults

Time: ✅ 2.353µs (SLO: <10.000µs 📉 -76.5%) vs baseline: +1.0%

Memory: ✅ 31.811MB (SLO: <34.000MB -6.4%) vs baseline: +4.9%

✅ high_rate_limit

Time: ✅ 2.410µs (SLO: <10.000µs 📉 -75.9%) vs baseline: +0.6%

Memory: ✅ 31.713MB (SLO: <34.000MB -6.7%) vs baseline: +4.9%

✅ long_window

Time: ✅ 2.368µs (SLO: <10.000µs 📉 -76.3%) vs baseline: -0.2%

Memory: ✅ 31.674MB (SLO: <34.000MB -6.8%) vs baseline: +4.3%

✅ low_rate_limit

Time: ✅ 2.358µs (SLO: <10.000µs 📉 -76.4%) vs baseline: ~same

Memory: ✅ 31.811MB (SLO: <34.000MB -6.4%) vs baseline: +4.9%

✅ no_rate_limit

Time: ✅ 0.837µs (SLO: <10.000µs 📉 -91.6%) vs baseline: -0.2%

Memory: ✅ 31.752MB (SLO: <34.000MB -6.6%) vs baseline: +4.8%

✅ short_window

Time: ✅ 2.517µs (SLO: <10.000µs 📉 -74.8%) vs baseline: +1.8%

Memory: ✅ 31.831MB (SLO: <34.000MB -6.4%) vs baseline: +5.1%

✅ recursivecomputation - 8/8

✅ deep

Time: ✅ 309.110ms (SLO: <320.950ms -3.7%) vs baseline: +0.2%

Memory: ✅ 32.932MB (SLO: <34.500MB -4.5%) vs baseline: +5.1%

✅ deep-profiled

Time: ✅ 326.394ms (SLO: <359.150ms -9.1%) vs baseline: -0.2%

Memory: ✅ 37.572MB (SLO: <39.000MB -3.7%) vs baseline: +5.0%

✅ medium

Time: ✅ 7.062ms (SLO: <7.400ms -4.6%) vs baseline: ~same

Memory: ✅ 32.165MB (SLO: <34.000MB -5.4%) vs baseline: +5.2%

✅ shallow

Time: ✅ 0.957ms (SLO: <1.050ms -8.9%) vs baseline: -0.2%

Memory: ✅ 32.086MB (SLO: <34.000MB -5.6%) vs baseline: +5.0%

✅ samplingrules - 8/8

✅ average_match

Time: ✅ 146.852µs (SLO: <290.000µs 📉 -49.4%) vs baseline: -0.9%

Memory: ✅ 32.047MB (SLO: <34.000MB -5.7%) vs baseline: +4.9%

✅ high_match

Time: ✅ 192.491µs (SLO: <480.000µs 📉 -59.9%) vs baseline: -1.1%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +5.2%

✅ low_match

Time: ✅ 99.313µs (SLO: <120.000µs 📉 -17.2%) vs baseline: -0.9%

Memory: ✅ 632.626MB (SLO: <700.000MB -9.6%) vs baseline: +4.9%

✅ very_low_match

Time: ✅ 2.893ms (SLO: <8.500ms 📉 -66.0%) vs baseline: ~same

Memory: ✅ 70.220MB (SLO: <75.000MB -6.4%) vs baseline: +4.7%

✅ sethttpmeta - 32/32

✅ all-disabled

Time: ✅ 10.619µs (SLO: <20.000µs 📉 -46.9%) vs baseline: +0.3%

Memory: ✅ 32.558MB (SLO: <34.000MB -4.2%) vs baseline: +4.9%

✅ all-enabled

Time: ✅ 40.041µs (SLO: <50.000µs 📉 -19.9%) vs baseline: -0.2%

Memory: ✅ 32.558MB (SLO: <34.000MB -4.2%) vs baseline: +4.7%

✅ collectipvariant_exists

Time: ✅ 40.664µs (SLO: <50.000µs 📉 -18.7%) vs baseline: -0.2%

Memory: ✅ 32.598MB (SLO: <34.000MB -4.1%) vs baseline: +4.8%

✅ no-collectipvariant

Time: ✅ 39.801µs (SLO: <50.000µs 📉 -20.4%) vs baseline: -0.4%

Memory: ✅ 32.598MB (SLO: <34.000MB -4.1%) vs baseline: +4.9%

✅ no-useragentvariant

Time: ✅ 39.045µs (SLO: <50.000µs 📉 -21.9%) vs baseline: +0.4%

Memory: ✅ 32.598MB (SLO: <34.000MB -4.1%) vs baseline: +5.0%

✅ obfuscation-no-query

Time: ✅ 40.497µs (SLO: <50.000µs 📉 -19.0%) vs baseline: ~same

Memory: ✅ 32.578MB (SLO: <34.000MB -4.2%) vs baseline: +4.8%

✅ obfuscation-regular-case-explicit-query

Time: ✅ 75.707µs (SLO: <90.000µs 📉 -15.9%) vs baseline: ~same

Memory: ✅ 32.991MB (SLO: <34.000MB -3.0%) vs baseline: +4.9%

✅ obfuscation-regular-case-implicit-query

Time: ✅ 76.274µs (SLO: <90.000µs 📉 -15.3%) vs baseline: ~same

Memory: ✅ 32.991MB (SLO: <34.000MB -3.0%) vs baseline: +4.9%

✅ obfuscation-send-querystring-disabled

Time: ✅ 153.821µs (SLO: <170.000µs -9.5%) vs baseline: -0.2%

Memory: ✅ 33.010MB (SLO: <34.500MB -4.3%) vs baseline: +4.9%

✅ obfuscation-worst-case-explicit-query

Time: ✅ 147.920µs (SLO: <160.000µs -7.5%) vs baseline: ~same

Memory: ✅ 32.991MB (SLO: <34.500MB -4.4%) vs baseline: +4.9%

✅ obfuscation-worst-case-implicit-query

Time: ✅ 154.299µs (SLO: <170.000µs -9.2%) vs baseline: -0.2%

Memory: ✅ 32.971MB (SLO: <34.500MB -4.4%) vs baseline: +4.7%

✅ useragentvariant_exists_1

Time: ✅ 39.281µs (SLO: <50.000µs 📉 -21.4%) vs baseline: -0.3%

Memory: ✅ 32.539MB (SLO: <34.000MB -4.3%) vs baseline: +4.7%

✅ useragentvariant_exists_2

Time: ✅ 40.684µs (SLO: <50.000µs 📉 -18.6%) vs baseline: ~same

Memory: ✅ 32.598MB (SLO: <34.000MB -4.1%) vs baseline: +4.9%

✅ useragentvariant_exists_3

Time: ✅ 40.010µs (SLO: <50.000µs 📉 -20.0%) vs baseline: +0.1%

Memory: ✅ 32.617MB (SLO: <34.000MB -4.1%) vs baseline: +5.1%

✅ useragentvariant_not_exists_1

Time: ✅ 39.505µs (SLO: <50.000µs 📉 -21.0%) vs baseline: +0.2%

Memory: ✅ 32.617MB (SLO: <34.000MB -4.1%) vs baseline: +4.9%

✅ useragentvariant_not_exists_2

Time: ✅ 39.471µs (SLO: <50.000µs 📉 -21.1%) vs baseline: +0.6%

Memory: ✅ 32.558MB (SLO: <34.000MB -4.2%) vs baseline: +4.8%

✅ span - 26/26

✅ add-event

Time: ✅ 24.190ms (SLO: <26.200ms -7.7%) vs baseline: -0.5%

Memory: ✅ 51.550MB (SLO: <53.000MB -2.7%) vs baseline: +4.7%

✅ add-metrics

Time: ✅ 93.565ms (SLO: <98.350ms -4.9%) vs baseline: -1.0%

Memory: ✅ 605.825MB (SLO: <961.000MB 📉 -37.0%) vs baseline: +4.9%

✅ add-tags

Time: ✅ 151.432ms (SLO: <168.550ms 📉 -10.2%) vs baseline: +0.5%

Memory: ✅ 606.036MB (SLO: <962.500MB 📉 -37.0%) vs baseline: +4.9%

✅ get-context

Time: ✅ 22.440ms (SLO: <23.700ms -5.3%) vs baseline: ~same

Memory: ✅ 50.529MB (SLO: <53.000MB -4.7%) vs baseline: +4.9%

✅ is-recording

Time: ✅ 22.675ms (SLO: <23.900ms -5.1%) vs baseline: -0.4%

Memory: ✅ 50.539MB (SLO: <53.000MB -4.6%) vs baseline: +5.0%

✅ record-exception

Time: ✅ 42.251ms (SLO: <44.500ms -5.1%) vs baseline: -0.7%

Memory: ✅ 43.439MB (SLO: <53.000MB 📉 -18.0%) vs baseline: +5.1%

✅ set-status

Time: ✅ 24.348ms (SLO: <26.000ms -6.4%) vs baseline: -0.9%

Memory: ✅ 50.523MB (SLO: <53.000MB -4.7%) vs baseline: +4.9%

✅ start

Time: ✅ 22.239ms (SLO: <23.500ms -5.4%) vs baseline: +0.4%

Memory: ✅ 50.531MB (SLO: <53.000MB -4.7%) vs baseline: +5.0%

✅ start-finish

Time: ✅ 54.110ms (SLO: <55.500ms -2.5%) vs baseline: -0.1%

Memory: ✅ 32.106MB (SLO: <34.000MB -5.6%) vs baseline: +4.9%

✅ start-finish-telemetry

Time: ✅ 54.891ms (SLO: <58.300ms -5.8%) vs baseline: -1.0%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +5.1%

✅ start-finish-traceid128

Time: ✅ 57.317ms (SLO: <60.050ms -4.6%) vs baseline: -0.2%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +5.0%

✅ start-traceid128

Time: ✅ 22.468ms (SLO: <24.600ms -8.7%) vs baseline: -0.7%

Memory: ✅ 50.504MB (SLO: <53.000MB -4.7%) vs baseline: +4.7%

✅ update-name

Time: ✅ 23.315ms (SLO: <24.100ms -3.3%) vs baseline: +0.1%

Memory: ✅ 51.169MB (SLO: <53.000MB -3.5%) vs baseline: +4.9%

✅ telemetryaddmetric - 30/30

✅ 1-count-metric-1-times

Time: ✅ 3.225µs (SLO: <20.000µs 📉 -83.9%) vs baseline: +2.5%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +4.7%

✅ 1-count-metrics-100-times

Time: ✅ 213.201µs (SLO: <250.000µs 📉 -14.7%) vs baseline: -0.3%

Memory: ✅ 32.067MB (SLO: <34.000MB -5.7%) vs baseline: +4.5%

✅ 1-distribution-metric-1-times

Time: ✅ 2.922µs (SLO: <20.000µs 📉 -85.4%) vs baseline: -1.6%

Memory: ✅ 32.145MB (SLO: <34.000MB -5.5%) vs baseline: +5.0%

✅ 1-distribution-metrics-100-times

Time: ✅ 191.456µs (SLO: <220.000µs 📉 -13.0%) vs baseline: +0.6%

Memory: ✅ 32.106MB (SLO: <34.000MB -5.6%) vs baseline: +4.6%

✅ 1-gauge-metric-1-times

Time: ✅ 2.066µs (SLO: <20.000µs 📉 -89.7%) vs baseline: -3.0%

Memory: ✅ 32.027MB (SLO: <34.000MB -5.8%) vs baseline: +4.7%

✅ 1-gauge-metrics-100-times

Time: ✅ 124.373µs (SLO: <150.000µs 📉 -17.1%) vs baseline: -0.4%

Memory: ✅ 32.086MB (SLO: <34.000MB -5.6%) vs baseline: +4.6%

✅ 1-rate-metric-1-times

Time: ✅ 3.100µs (SLO: <20.000µs 📉 -84.5%) vs baseline: -2.1%

Memory: ✅ 32.204MB (SLO: <34.000MB -5.3%) vs baseline: +5.0%

✅ 1-rate-metrics-100-times

Time: ✅ 212.790µs (SLO: <250.000µs 📉 -14.9%) vs baseline: +0.6%

Memory: ✅ 32.027MB (SLO: <34.000MB -5.8%) vs baseline: +4.3%

✅ 100-count-metrics-100-times

Time: ✅ 21.591ms (SLO: <23.500ms -8.1%) vs baseline: -0.6%

Memory: ✅ 32.106MB (SLO: <34.000MB -5.6%) vs baseline: +4.8%

✅ 100-distribution-metrics-100-times

Time: ✅ 2.012ms (SLO: <2.250ms 📉 -10.6%) vs baseline: +1.6%

Memory: ✅ 32.067MB (SLO: <34.000MB -5.7%) vs baseline: +4.6%

✅ 100-gauge-metrics-100-times

Time: ✅ 1.279ms (SLO: <1.550ms 📉 -17.5%) vs baseline: -2.1%

Memory: ✅ 32.086MB (SLO: <34.000MB -5.6%) vs baseline: +4.7%

✅ 100-rate-metrics-100-times

Time: ✅ 2.200ms (SLO: <2.550ms 📉 -13.7%) vs baseline: -0.7%

Memory: ✅ 32.067MB (SLO: <34.000MB -5.7%) vs baseline: +4.7%

✅ flush-1-metric

Time: ✅ 4.226µs (SLO: <20.000µs 📉 -78.9%) vs baseline: +3.0%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +4.7%

✅ flush-100-metrics

Time: ✅ 180.617µs (SLO: <250.000µs 📉 -27.8%) vs baseline: -1.0%

Memory: ✅ 32.126MB (SLO: <34.000MB -5.5%) vs baseline: +4.7%

✅ flush-1000-metrics

Time: ✅ 2.212ms (SLO: <2.500ms 📉 -11.5%) vs baseline: +1.1%

Memory: ✅ 32.853MB (SLO: <34.500MB -4.8%) vs baseline: +4.7%

✅ tracer - 6/6

✅ large

Time: ✅ 30.368ms (SLO: <32.950ms -7.8%) vs baseline: +0.5%

Memory: ✅ 33.187MB (SLO: <34.500MB -3.8%) vs baseline: +4.5%

✅ medium

Time: ✅ 2.958ms (SLO: <3.200ms -7.6%) vs baseline: +0.6%

Memory: ✅ 31.831MB (SLO: <34.000MB -6.4%) vs baseline: +4.1%

✅ small

Time: ✅ 336.886µs (SLO: <370.000µs -8.9%) vs baseline: +0.8%

Memory: ✅ 31.595MB (SLO: <34.000MB -7.1%) vs baseline: +3.0%

ℹ️ Scenarios Missing SLO Configuration (9 scenarios)

The following scenarios exist in candidate data but have no SLO thresholds configured:

coreapiscenario-core_dispatch_listeners
coreapiscenario-core_dispatch_no_listeners
coreapiscenario-core_dispatch_with_results_listeners
coreapiscenario-core_dispatch_with_results_no_listeners
djangosimple-baseline
errortrackingdjangosimple-baseline
errortrackingflasksqli-baseline
flasksimple-baseline
flasksqli-baseline

brettlangdon · 2025-10-02T18:01:58Z

@PROFeNoM probably worth updating the codeowners file as well to make llmobs the owner of this integration, will help require less people to review it (after the codeowners change is merged)

PROFeNoM self-assigned this Sep 30, 2025

PROFeNoM force-pushed the alex/feat/vllm branch 4 times, most recently from bf30414 to 0af046e Compare September 30, 2025 14:00

PROFeNoM added integrations Tracing Distributed Tracing CI MLObs ML Observability (LLMObs) labels Oct 2, 2025

PROFeNoM force-pushed the alex/feat/vllm branch 3 times, most recently from 5627244 to 494f936 Compare October 2, 2025 13:09

PROFeNoM marked this pull request as ready for review October 2, 2025 13:58

PROFeNoM requested review from a team as code owners October 2, 2025 13:58

PROFeNoM requested review from juanjux, vlad-scherbich and wconti27 October 2, 2025 13:58

PROFeNoM force-pushed the alex/feat/vllm branch 3 times, most recently from d970650 to 2c22b68 Compare October 2, 2025 14:20

PROFeNoM force-pushed the alex/feat/vllm branch 2 times, most recently from 23026f8 to e64073f Compare October 6, 2025 13:17

PROFeNoM force-pushed the alex/feat/vllm branch from e64073f to 46d0ac8 Compare October 6, 2025 13:25

PROFeNoM added 6 commits October 7, 2025 09:24

feat(vllm): add vLLM integration

f7c9df0

Rework the integration for 0.10.2+ V1 engine support only

622b42b

chore: Update the CODEOWNERS file

d25fdc8

chore: Update registry.yaml

90fc73c

migrate latency metrics to span events

5d7cdf9

lint

3db04ff

PROFeNoM force-pushed the alex/feat/vllm branch from 46d0ac8 to 3db04ff Compare October 7, 2025 07:25

feat(vllm): add vLLM integration #14732

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Description

Request Flow and Instrumentation Points

Version Support

Metadata Captured

Testing

Risks

Additional Notes

Code Architecture

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Bootstrap import analysis

Summary

Import time breakdown

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Performance SLOs

✅ re_expand_aspect

✅ re_expand_noaspect

✅ re_findall_aspect

✅ re_findall_noaspect

✅ re_finditer_aspect

✅ re_finditer_noaspect

✅ re_fullmatch_aspect

✅ re_fullmatch_noaspect

✅ re_group_aspect

✅ re_group_noaspect

✅ re_groups_aspect

✅ re_groups_noaspect

✅ re_match_aspect

✅ re_match_noaspect

✅ re_search_aspect

✅ re_search_noaspect

✅ re_sub_aspect

✅ re_sub_noaspect

✅ re_subn_aspect

✅ re_subn_noaspect

✅ add_aspect

✅ add_inplace_aspect

✅ add_inplace_noaspect

✅ add_noaspect

✅ bytearray_aspect

✅ bytearray_extend_aspect

✅ bytearray_extend_noaspect

✅ bytearray_noaspect

✅ bytes_aspect

✅ bytes_noaspect

✅ bytesio_aspect

✅ bytesio_noaspect

✅ capitalize_aspect

✅ capitalize_noaspect

✅ casefold_aspect

✅ casefold_noaspect

✅ decode_aspect

✅ decode_noaspect

✅ encode_aspect

✅ encode_noaspect

✅ format_aspect

✅ format_map_aspect

✅ format_map_noaspect

✅ format_noaspect

✅ index_aspect

✅ index_noaspect

✅ join_aspect

✅ join_noaspect

✅ ljust_aspect

✅ ljust_noaspect

✅ lower_aspect

✅ lower_noaspect

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