* fix(mcp): honor an explicit null on toolset update, cover MCP lifecycle e2e PUT /v1/mcp/toolset dumped its payload with exclude_none, so a field sent as null looked exactly like one the caller left out and the stored value survived. An admin could not clear a toolset's description: the save reported success and the old text came straight back. It now dumps with exclude_unset, so absent keeps and null clears, which is what PUT /v1/mcp/server already did. A null tools list clears the selection to empty, and a null toolset_name is ignored because a toolset always has a name. Adds create, read, partial-update, clear and delete e2e coverage for MCP servers and toolsets, with every read-back polled on every replica so an edit that lands on one replica and not another fails the test, plus an enforcement test proving a key granted a toolset lists exactly that toolset's tools against the real Datadog upstream. * fix(e2e): refuse a read-back that no replica serves A read-back over an empty replica mapping satisfied every predicate and returned as if it had converged, so it would have asserted nothing and passed. No wiring can produce that today, since the replica list always falls back to at least one URL, but a helper whose whole job is proving a write reached every replica should not have a shape that passes vacuously. * fix(mcp): keep a null tools list a no-op on toolset update Treating a null tools list as a clear meant an existing client that sends tools=null during a partial update, meaning "leave the selection alone", silently lost every tool the toolset grants. That is a permission surface, so the quiet version of it is the worst version. A toolset always has a tool list, the same way it always has a name, so a null on either is now a no-op. Emptying the selection is an explicit [], which cannot be confused with a field the caller left out, and which is what the dashboard already sends. * fix(e2e): keep MCP admin routes on the data plane /v1/mcp/* is a lazily mounted feature, so a gateway registers it on the first matching request, which happens after the startup route trim that drops management endpoints. Routing it to the control plane therefore sent every MCP call to the one backend process: the new lifecycle read-backs proved a single process rather than every replica, and mcp_client's await_registered barrier waited on a registry that does not serve the tools/list call it guards, so the existing MCP suites polled a gateway that had not synced yet until poll_timeout Verified against a two-gateway split stack (backend on 4001, gateways on 4010 and 4011, one postgres): both gateways answer /v1/mcp/server and /v1/mcp/toolset, and each served 6 server reads and 7 toolset reads over the run * fix(e2e): grant the toolset by the tool's own name, not the wire name tools/list serves a tool as <prefix><tool_name>, but a toolset grants by the tool's own name: resolve_toolset_permissions reads toolset.tools[].tool_name straight through, and the prefix is added on the way out. The test built the toolset from the names tools/list reported, so the grant matched nothing, the scoped key listed no tools, and await_tools ran out its whole poll_timeout before failing Measure the prefix off search_datadog_logs, whose own name is known, rather than guessing it from the alias, since the proxy can be configured to prefix with a short server id instead. The expectation compared against tools/list stays in wire names; only what the toolset stores crosses back * test(mcp): build immutable lifecycle updates and replica results * test: validate opaque stream IDs and hide log-reader credentials * test: isolate auto-router scenarios and clean partial setup * test: honor Datadog search rate-limit reset headers * test: share the Datadog read-back deadline across retries * test: preserve captured MCP toolset update fields |
||
|---|---|---|
| .. | ||
| __init__.py | ||
| collector.py | ||
| guardrail.yaml | ||
| llm_claude_code_compat.yaml | ||
| llm_conversational.yaml | ||
| llm_nonconversational.yaml | ||
| logging.yaml | ||
| mcp.yaml | ||
| mgmt.yaml | ||
| other.yaml | ||
| quota_management.yaml | ||
| README.md | ||
| registry.py | ||
| reliability.yaml | ||
| schema.py | ||
| test_collector.py | ||
e2e coverage registry
This directory is the denominator for e2e test coverage: the set of behaviors we
want covered, one row per behavior, checked into the repo so coverage is a number we
can track instead of a guess. It implements the plan in the "E2E Coverage Tracking"
note; the naming grammar lives in tests/e2e/CLAUDE.md.
The model
A cell is one customer-noticeable behavior a single e2e test can assert pass/fail
on, for example llm.chat_completions.bedrock_converse.tool_use.stream.works. Cells are
grouped module > feature > test, with LLM cells split into Core LLMs and
Non-Core LLMs for dashboarding. Each cell carries a tier (P0/P1/P2), a source, and a
fail_before_fix flag.
The rows live in per-prefix YAML files (llm_*.yaml, mgmt.yaml, mcp.yaml,
reliability.yaml, quota_management.yaml, logging.yaml, guardrail.yaml,
other.yaml) and validate against
the discriminated union in schema.py, so an LLM row cannot carry a guardrail field and
vice versa. llm rows with subject_endpoint of chat_completions, messages, or
responses roll up to Core LLMs; all other LLM endpoints roll up to Non-Core LLMs.
LLM endpoint, route, and capability values are typed in schema.py, so new taxonomy
values require an explicit schema change. logging and guardrail are two id-prefixes
that roll up into the single Logging & Guardrails dashboard module.
A test declares what it covers with a marker:
@pytest.mark.covers("llm.chat_completions.openai.tool_use.stream.works")
def test_openai_streaming_tool_calls(self) -> None:
...
The number
collector.py diffs the registry against those markers and reports coverage per module.
It is static: a collect-only pass reads the markers, so it runs no test and needs no live
proxy. Whether a covered cell currently passes or fails is a separate, live concern.
A skipped test asserts nothing, so its markers do not count. A cell is covered only when
at least one test pytest would actually run declares it; a cell claimed by both a live
test and a skipped one stays covered. Skip state comes from pytest's own evaluator, so
skip and skipif resolve exactly as they do in the e2e run, which also means a
skipif on an absent credential makes that cell uncovered in the environments where the
test cannot run. Cells left uncovered this way are listed under the headline (and counted
by litellm_e2e_coverage_skipped_markers) so an unskipped-pending gap is visible rather
than inflating the number. The one skip the collector cannot see is pytest.skip()
called from inside a test body, since it does not exist until the test runs.
cd tests/e2e && PYTHONPATH=. python -m coverage_registry.collector
Use --format loki after the e2e pytest run in the same Kubernetes job/pod to print
structured stdout lines for Loki:
cd tests/e2e && PYTHONPATH=. python -m coverage_registry.collector --format loki --strict
This emits exactly one COVERAGE_TOTAL line and one COVERAGE_MODULE line per module
in MODULE_ORDER, in that order. Loki uses log-safe module= labels from
LOKI_MODULE_LABELS (core_llms, management_ui, etc.) so existing JSON and
Prometheus consumers keep their human-readable module names unchanged.
The headline is overall coverage. The collector also lists markers that point at ids not in the registry, so a typo or an unenumerated behavior surfaces instead of being silently dropped.
Use strict mode in CI once existing draft markers are reconciled:
cd tests/e2e && PYTHONPATH=. python -m coverage_registry.collector --strict
Strict mode exits non-zero on @pytest.mark.covers(...) ids that are not checked into
the registry. Add --fail-on-collection-errors when the job should also fail on pytest
collection errors.
Provider x feature matrix: customer-run Bedrock combinations
The provider and feature combinations customers actually run get explicit cells, expanded
here as incidents surface new ones. The current Bedrock set, seeded from a customer's
production shape (regional us.anthropic.* inference-profile ids over both chat routes,
provider response headers for AWS-side correlation, and the Test Connection probe for a
responses-mode Bedrock Mantle deployment):
| Cell | Feature | Covering test |
|---|---|---|
llm.chat_completions.bedrock_converse.basic.nonstream.works |
regional us. id, Converse |
llm_translation/test_chat_completions_regression_e2e.py |
llm.chat_completions.bedrock_converse.basic.stream.works |
regional us. id, Converse stream |
llm_translation/test_chat_completions_regression_e2e.py |
llm.chat_completions.bedrock_invoke.basic.nonstream.works |
regional us. id, Invoke |
llm_translation/test_bedrock_provider_matrix_e2e.py |
llm.chat_completions.bedrock_invoke.basic.stream.works |
regional us. id, Invoke stream |
llm_translation/test_bedrock_provider_matrix_e2e.py |
llm.chat_completions.bedrock_converse.response_headers.nonstream.works |
llm_provider-* headers |
llm_translation/test_bedrock_provider_matrix_e2e.py |
llm.chat_completions.bedrock_converse.response_headers.stream.works |
llm_provider-* headers, stream |
llm_translation/test_bedrock_provider_matrix_e2e.py |
mgmt.model.test_connection.happy_path |
Test Connection, Bedrock Mantle | management/test_model_test_connection_e2e.py |
Status: this is a draft for review
The cells were enumerated from the codebase and the tiers are a first proposal. Known things to settle before treating the set as final:
- tiers are proposed, not signed off; 125 P0 is a lot to prove fail-before-fix, so P0 may want tightening
- a few cells need a support check or a prune (for example
llm.embeddings.anthropic.*andreliability.perf.throughput.under_slo) - auth is covered in two places (
other.auth.*and the mgmt authz assertions); the boundary needs a decision, and the auth cluster may deserve promotion to its own module - the P2 "niche" cells each stand in for a large tail of integrations/providers by design, so the denominator is deliberately P0-weighted rather than a full inventory