new-monitoring-feature

name	new-monitoring-feature
description	Add a new monitoring target / layer to SkyWalking OAP. Orients you to the OAL / MAL / LAL / SpanListener / SegmentListener extension points, the UI template + submodule touchpoints, the docs set that must move together, and the cross-cutting traps that don't live in any one skill.

Adding a New Monitoring Feature / Layer

SkyWalking monitoring for a new target (a new Layer — mobile OS, gateway, DB, language runtime, …) is composed from the same set of reusable extension points. This skill is the index: which extension point fits which signal, where its contract lives, which docs must be updated together, and which harness-wide traps the extension-specific docs don't cover.

There is one skill per narrow concern. This one is the wiring map.

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Working posture

• Default scope for a new monitoring feature is narrow. For most new monitoring targets, traces are re-used as-is — you do not write or modify a trace analyzer. Metrics and log extensions via OTLP (MAL + LAL) are the common shape. OTLP / Zipkin span-based metrics analysis (SpanListener) already exists and only needs a new implementation if your feature introduces genuinely new semantic-convention attributes to extract (e.g. gen_ai.*, mcp.* for the GenAI layer). Do not touch CommonAnalysisListener / RPCAnalysisListener / SegmentAnalysisListener unless the OAP core protocol gains a new SpanLayer enum value — details in §2.
• If you find yourself editing more than this skill suggests, stop and confirm. Scope creep on trace analysis, span-layer mapping, receiver handlers, or protobuf/proto contracts is a strong signal the framing is wrong. Ask the developer before committing that direction.
• Verify every new feature locally before pushing to CI. Compile + checkstyle + license-eye are minimums, but they only tell you the code builds — they do not tell you the new MAL rule compiles its closures at startup, the LAL layer:auto dispatch works, the OTLP payload shape matches the MAL labels, the UI template renders against real data, or the layer shows up in swctl service ly <LAYER>. Run the new e2e case end-to-end locally against a live OAP (see run-e2e skill) and fire every verify step with swctl by hand at least once. Pushing to CI without a local green run wastes shared CI cycles and slow-loops review.

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0. Register the Layer — the feature's entry point

A Layer is how OAP slices services / instances / endpoints by data source. Every new feature needs a new Layer enum value. The UI, storage partitioning, menu navigation, and OAL aggregation all key off it.

Only one place to edit — oap-server/server-core/src/main/java/org/apache/skywalking/oap/server/core/analysis/Layer.java. Add a new enum constant with a unique id and normal flag. Ids are never reused; pick the next integer. Examples: IOS(47, true), APISIX(27, true), VIRTUAL_DATABASE(11, false) for inferred/non-real services.

UI template folders are auto-discovered: UITemplateInitializer.UI_TEMPLATE_FOLDER is computed from Layer.values() + "custom" at class-init time. Drop a ui-initialized-templates/<layer-name-lowercased>/ folder on disk and the initializer picks it up on the next boot. Missing folders are silently skipped. There is no allowlist to append to.

Component ID lookup in Java code: IDs declared in component-libraries.yml are loaded at runtime into ComponentLibraryCatalogService's componentName2Id map — they are not exposed as Java enum constants. To look up by name in listener code, inject the catalog service and resolve once at construction:

IComponentLibraryCatalogService catalog = moduleManager.find(CoreModule.NAME)
    .provider().getService(IComponentLibraryCatalogService.class);
int myComponentId = catalog.getComponentId("My-Component-Name");

Cache as an int field; runtime comparisons are then plain componentId == myComponentId. Trap: there is a ComponentsDefine class under skywalking-trace-receiver-plugin/src/test/java/.../mock/ComponentsDefine.java — it is a test-only mock holding five hand-picked constants (Tomcat, Dubbo, RocketMQ, MongoDB). Do not import or extend it from production code.

Emit the layer from every source object your feature produces:

service.setLayer(Layer.<YOUR_LAYER>);
serviceInstance.setServiceLayer(Layer.<YOUR_LAYER>);
endpoint.setServiceLayer(Layer.<YOUR_LAYER>);

Downstream (the core OAL, service ly <LAYER> swctl query, topology filters, UI root dashboard's layer selector) all work off this single enum value.

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1. Pick the right extension point

Signal you want to process	Extension point	Register via
SkyWalking native trace segments (from language agents)	AnalysisListener (TraceSegmentListener / EntryAnalysisListener / ExitAnalysisListener / LocalAnalysisListener / FirstAnalysisListener) + factory in agent-analyzer	META-INF/services/org.apache.skywalking.oap.server.analyzer.provider.trace.parser.listener.AnalysisListenerFactory
OTLP / Zipkin trace spans (OTel SDKs, Istio, Envoy, iOS/Android, …)	SpanListener in core.trace	META-INF/services/org.apache.skywalking.oap.server.core.trace.SpanListener
OTel metrics (Prometheus scrape, Envoy stats, Istio, …)	MAL rules — otel-rules/<namespace>/*.yaml	Append the rule path to enabledOtelMetricsRules in application.yml
Logs (OTLP, SkyWalking native, Fluent Bit, Envoy ALS)	LAL rules — lal/<rule>.yaml	Append to SW_LOG_LAL_FILES (env) or lalFiles (YAML) under log-analyzer
Pre-computed meter / custom meter (custom agent protocol, meter receiver)	MAL meter-analyzer-config/*.yaml	Append to meter-analyzer-config entries
Aggregation from Source entities (service, instance, endpoint, relation)	OAL rules — oal/*.oal	Already loaded by OAL grammar; just add lines

All five DSLs (OAL, MAL, LAL, Hierarchy + SpanListener SPI) compile via ANTLR4 + Javassist at startup. Source-of-truth details are in:

• docs/en/concepts-and-designs/oal.md
• docs/en/concepts-and-designs/mal.md
• docs/en/concepts-and-designs/lal.md
• docs/en/concepts-and-designs/scope-definitions.md
• oap-server/analyzer/meter-analyzer/CLAUDE.md — MAL compiler internals
• oap-server/analyzer/log-analyzer/CLAUDE.md — LAL compiler internals

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2. Trace ingestion — two parallel pipelines

SkyWalking OAP ingests traces through two distinct entry points. Pick based on source.

Before writing any trace extension — ask "do I actually need one?"

For most new layers you do not touch trace analysis at all. Segments (native or OTLP) flow through the existing pipeline, RPCAnalysisListener.parseExit produces the outbound ServiceRelation edges, the backend-side agent produces the inbound metrics via its own parseEntry, and the new-layer Service / Instance / Endpoint entities come from MAL + LAL, not from trace analysis. This is how browser (Layer.BROWSER), iOS (Layer.IOS), mobile mini-programs (Layer.WECHAT_MINI_PROGRAM / Layer.ALIPAY_MINI_PROGRAM), and most scraped-metric layers work.

Extend trace analysis only when the feature genuinely needs per-span interpretation that the existing pipeline cannot express:

• A new SpanLayer — OAP core protobuf has a new SpanLayer enum value that callers of identifyServiceLayer / identifyRemoteServiceLayer must dispatch on. That means touching CommonAnalysisListener / RPCAnalysisListener.
• A genuinely new signal class not covered by existing listeners — e.g. the GenAI work added GenAISpanListener for LLM / MCP instrumentation because OTLP spans carry semantic-convention attributes (gen_ai.*, mcp.*) that no prior listener extracted. That is rare.

Anti-pattern we've been bitten by: using a componentId mapping in CommonAnalysisListener to assign a client-side layer to exit-only segments. This does not produce inbound metrics anyway (no entry spans → no service_cpm / endpoint_cpm from OAL), and it is orthogonal to the Service entity layer (which MAL / LAL sets). Mirror the browser pattern instead: ship Layer + component-libraries.yml + MAL + LAL + dashboards, and leave the listener chain alone.

2.1 SkyWalking native segments — AnalysisListener

Source protocol: apm-protocol/apm-network/src/main/proto/language-agent/Tracing.proto (TraceSegmentObject).

Receiver: oap-server/server-receiver-plugin/skywalking-trace-receiver-plugin. After wire decoding, segments are handed to SegmentParserServiceImpl which fans out to registered AnalysisListenerFactory implementations.

Extension: implement one or more of

• FirstAnalysisListener — per-segment, before per-span phase
• EntryAnalysisListener — per-entry-span
• ExitAnalysisListener — per-exit-span
• LocalAnalysisListener — per-local-span
• TraceSegmentListener — whole-segment, after per-span phase

Register the factory in META-INF/services/org.apache.skywalking.oap.server.analyzer.provider.trace.parser.listener.AnalysisListenerFactory. Existing examples: RPCAnalysisListener, MultiScopesAnalysisListener, SegmentAnalysisListener in oap-server/analyzer/agent-analyzer/src/main/java/.../trace/parser/listener/.

Use when: the data arrives on the SW native wire (language agents — Java, Python, Go, Node.js, .NET, PHP, Lua, etc.).

2.2 OTLP / Zipkin spans — SpanListener

Source protocol: OTLP proto (opentelemetry/proto/trace/v1/trace.proto) or Zipkin v2 JSON.

Receiver: oap-server/server-receiver-plugin/otel-receiver-plugin/src/main/java/.../otlp/OpenTelemetryTraceHandler.java (OTLP) and oap-server/server-receiver-plugin/zipkin-receiver-plugin/.../ITZipkinTraceCollector (Zipkin). After decoding, spans are iterated and passed to every registered SpanListener through SpanListenerManager.

Extension: implement org.apache.skywalking.oap.server.core.trace.SpanListener:

public interface SpanListener {
    String[] requiredModules();
    void init(ModuleManager moduleManager);
    SpanListenerResult onOTLPSpan(OTLPSpanReader span, Map<String,String> resourceAttributes,
                                  String scopeName, String scopeVersion);
}

Register in META-INF/services/org.apache.skywalking.oap.server.core.trace.SpanListener. Reference implementations:

• oap-server/analyzer/ios-analyzer/src/main/java/.../IOSHTTPSpanListener.java — OTel Swift URLSession → OAL (Service / ServiceInstance / Endpoint)
• oap-server/analyzer/ios-analyzer/src/main/java/.../IOSMetricKitSpanListener.java — OTel Swift MetricKit → MAL samples via OpenTelemetryMetricRequestProcessor.toMeter
• oap-server/analyzer/gen-ai-analyzer/src/main/java/.../GenAISpanListener.java — LLM / MCP instrumentation

Return SpanListenerResult.builder().shouldPersist(false).build() to prevent a span being stored as a trace (useful for e.g. 24-hour aggregate spans that are not meaningful as traces).

When both native and OTLP should feed the same metric, write your extension against the downstream scope (Service / ServiceInstance / Endpoint + OAL) and emit those entities from both a SegmentListener and a SpanListener. The OAL layer is protocol-agnostic.

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3. Metrics — MAL / OAL rules

3.1 OAL (for entities already produced by core sources)

oap-server/server-starter/src/main/resources/oal/core.oal already defines the standard service_cpm, service_resp_time, service_sla, endpoint_cpm, etc. — keyed off the Service, ServiceInstance, Endpoint source scopes. If your new layer emits those entities with the right Layer, you get the core metrics for free.

Who emits those entities matters. service_cpm / service_resp_time / service_sla / endpoint_cpm / endpoint_resp_time come from RPCAnalysisListener.parseEntry → callingIn.toService() / toEndpoint(). That only fires on inbound entry spans. Client-side / edge layers (browser, iOS, mini-programs) only emit exit spans, so these OAL metrics do not populate under those layers — their Service entities are produced by MAL / LAL, and their dashboards use MAL metrics (meter_<layer>_*) for load / latency, not service_cpm / service_resp_time. Don't wire dashboards to OAL-derived metrics that the layer never produces.

Additional OAL rules go in the same file. OAL grammar: oap-server/oal-grammar/src/main/antlr4/OALParser.g4. Syntax and examples: docs/en/concepts-and-designs/oal.md.

3.2 MAL (for meter / metric samples)

File location: oap-server/server-starter/src/main/resources/otel-rules/<namespace>/*.yaml (OTel scrape) or meter-analyzer-config/*.yaml (SW native meter).

Registration (MANDATORY): append the rule path to the default in oap-server/server-starter/src/main/resources/application.yml:

receiver-otel:
  default:
    enabledOtelMetricsRules: ${SW_OTEL_RECEIVER_ENABLED_OTEL_METRICS_RULES:"...,<your-namespace>/*"}

If you skip this, the rule isn't loaded in the default starter and downstream converters.forEach(...) is a silent no-op — samples just disappear.

Also update test/e2e-v2/cases/storage/expected/config-dump.yml. This e2e diffs /debugging/config/dump output against a static file; every default-value change in application.yml must mirror here or the storage e2e fails.

Naming: keep attribute scope in the metric name. If a metric reads from foo.bar.foreground.exit_count, call it foo_foreground_exit_count, not foo_exit_count. When two attributes (foreground vs background, ingress vs egress) share a theme, keep them as separate distinguishable metrics — don't flatten.

3.3 Histogram pitfalls (both OAL and MAL)

• Per-bucket counts, not cumulative. histogram_percentile accumulates internally. Feeding cumulative counts doubles the accumulator and shifts percentiles up. Each observation contributes 1 to exactly one le bucket.
• le label scale. SampleFamily.histogram() rescales le by defaultHistogramBucketUnit.toMillis(1) (default SECONDS ⇒ ×1000). If your raw labels are already in ms, use SampleFamilyBuilder.newBuilder(samples).defaultHistogramBucketUnit(TimeUnit.MILLISECONDS).build().
• Overflow bucket. MAL parses le="Infinity" as Double.POSITIVE_INFINITY → stored as Long.MAX_VALUE. If a percentile lands there, the UI renders ≈ 9.2 × 10¹⁸. Prefer a finite sentinel (e.g., 30 s for hang/launch) so outliers remain visible without crashing the chart.
• NamingControl — every service / serviceInstance / endpoint label that ends up as an entity key must go through namingControl.formatServiceName() / formatInstanceName() / formatEndpointName(). Raw resource attributes (long git-SHA build metadata, path-style endpoints) will otherwise exceed storage limits.

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4. Logs — LAL

File location: oap-server/server-starter/src/main/resources/lal/<feature>.yaml.

Registration: append to SW_LOG_LAL_FILES env var, or log-analyzer.default.lalFiles in application.yml.

Grammar: oap-server/analyzer/log-analyzer/src/main/antlr4/LALParser.g4. The compiler docs are thorough: oap-server/analyzer/log-analyzer/CLAUDE.md — covers:

• filter { … } block with parsed.*, tag(), sourceAttribute(), log.*, def locals, extractor {}, metrics {}, sink {}
• layer: auto mode (script decides layer from source attrs)
• inputType / outputType SPI (LALSourceTypeProvider) to bind typed proto to parsed.*
• Test harness at oap-server/analyzer/log-analyzer/src/test/resources/scripts/lal/test-lal/oap-cases/ — ship YAML + .data.yaml pair; LALScriptExecutionTest picks them up automatically.

layer: auto gotcha: the extractor's layer "X" assignment must propagate to LogMetadata.layer (not just the output builder) — FilterSpec.doSink reads metadata to decide drop/route. The current codegen (LALBlockCodegen.generateFieldToOutput) handles this correctly; if you extend codegen, preserve that invariant.

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5. UI — templates, submodule, and menu

5.1 Dashboard templates

JSON files under oap-server/server-starter/src/main/resources/ui-initialized-templates/<feature>/. Conventional fileset:

• <feature>-root.json — ServiceList widget, layered service index.
• <feature>-service.json — per-service dashboard, usually a Tab with Overview / Instance / Endpoint / Log sub-tabs.
• <feature>-instance.json — per-instance dashboard.
• <feature>-endpoint.json — per-endpoint dashboard.
• Menu link in oap-server/server-starter/src/main/resources/ui-initialized-templates/menu.yaml.

Collaborate with the developer on dashboard design. Dashboard layout and metric selection are product decisions, not derivable from the MAL rules alone. Before authoring the JSON, check in with the developer on: which metric goes on which panel, which percentiles / aggregations to show, what's on the root list vs. per-service vs. per-instance vs. per-endpoint pages, what stays in the Overview tab vs. a sub-tab, widget sizes / ordering, and whether Trace / Log tabs belong at all (depends on whether the feature emits traces and logs). Then manually set up the feature against a live OAP — emit a few real OTLP payloads, open each dashboard in the UI, confirm every widget renders non-empty, and walk the drill-down from root → service → instance → endpoint. Only after that eyes-on pass is the dashboard ready to ship.

Details that always bite:

• Tab chrome eats ~4 rows. Set outer Tab.h = content_max_y + 4 or you get an inner scrollbar on top of the page scrollbar.
• Widget heights consistent. Use h=15 per row for Line / Bar widgets to match mesh / general peer templates. Don't mix h=12 / h=15 / h=24 across a feature's dashboards.
• List widgets (ServiceList / InstanceList / EndpointList) render two pieces per cell:
  • expressions → the aggregated summary number (right side). Required. Wrap raw metrics in avg(...) / sum(...). Omitting it leaves the column empty.
  • subExpressions → the sparkline trend (left side). Optional, falls back to expressions if absent.
  • metricConfig pairs 1-to-1 with expressions (not subExpressions). Use for label (column header) and unit.
  • Compound columns via MQE addition: avg(metric_a + metric_b) in expressions, metric_a + metric_b in subExpressions.
  • Normal widgets with multiple expressions on one chart — always give a human label per expression in metricConfig, otherwise legend renders raw metric names.

5.2 Hot-reload (edits to shipped templates take effect on restart)

UITemplateInitializer normally uses addIfNotExist (keyed on JSON id), so on a plain restart your edits to shipped templates are ignored — the seeded copy in storage wins. For dev / extension work, set the environment variable and restart:

SW_UI_TEMPLATE_FORCE_RELOAD=true
# then restart OAP — shipped templates overwrite the seeded copies via addOrReplace.
# Hard-refresh the browser (Cmd+Shift+R) because the booster UI caches config in memory.

This is a dev / extension knob only — read directly from the OS environment, not wired through application.yml. Unset or false preserves the default production behavior where operators' UI edits persist across restarts.

5.3 New top-level menu group (e.g. "Mobile", "Gateway")

New child entries only need template JSON + menu.yaml. A new top-level group needs submodule work in skywalking-ui (git submodule at skywalking-ui/):

1. skywalking-ui/src/assets/icons/<name>.svg — menu icon.
2. skywalking-ui/src/locales/lang/menus/{en,es,zh}.ts — i18n labels (<name>, <name>_desc, <name>_<child>, <name>_<child>_desc). Missing i18n falls back to raw keys on screen.
3. Commit those upstream in apache/skywalking-booster-ui, bump the submodule pointer here.
4. Rebuild with -Pui,dist (not -Pbackend,dist) and make docker.ui, otherwise the new assets aren't in the image. See package skill.

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6. Docs set — everything that moves together

File	What to add
docs/en/setup/backend/<feature>-monitoring.md	User-facing setup guide. Required SDK / collector, required env vars, sample OTLP payload, metrics / log tags list.
docs/menu.yml	Add the guide to the docs navigation tree.
docs/en/security/README.md	Client-side monitoring: mobile / browser / mini-program endpoints accept data from the public internet without auth by default. Add a rate-limit + abuse-protection note. Agent-side monitoring over private VPC usually doesn't need this.
docs/en/changes/changes.md	Per-release changelog. Add under #### OAP Server for features/bug-fixes, #### UI if the submodule bumps, #### Documentation if new guides.
docs/en/swip/SWIP-<N>.md	Design doc for non-trivial features; keep reconciled with final code after review.
docs/en/swip/readme.md	Move SWIP from "Proposed" to "Accepted" once merged.

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7. E2E test

Folder: test/e2e-v2/cases/<feature>/. See run-e2e skill for harness basics (setup / trigger / verify phases, template functions, expected-file authoring via contains).

Feature-specific extras:

1. Docker-compose: extend ../../script/docker-compose/base-compose.yml oap + storage. Set SW_OTEL_RECEIVER_ENABLED_HANDLERS, SW_LOG_LAL_FILES, and any feature-specific env. Don't list default rules here — rely on application.yml so the config-dump test stays consistent.
2. Register in CI: add an entry under the e2e matrix in .github/workflows/skywalking.yaml.
3. OTLP data hygiene:
   • spanId is exactly 16 hex chars; traceId is exactly 32. Protobuf-JSON decodes them as base64; other lengths return HTTP 400.
   • Setup-step curl loops must fail loudly: curl -sS -f --retry 30 --retry-delay 5 --retry-connrefused --retry-all-errors --max-time 10 ... + set -e. The pattern for …; do curl && break || sleep 5; done silently succeeds when every attempt connection-refused (the final sleep returns 0) because OAP takes ~50 s to start in CI.
4. Verify each case by hand before pushing and use a published simulator image where the upstream SDK has one. See run-e2e skill §6–§9 for verify-query triage, expected-file authoring, and the list of expected-file traps (YAML quoting on colons, nested contains fragility, timeUnixNano: "0", setup-step curl loops that swallow failure).
5. Config dump: when you modify any application.yml default (rule list, handler list, ...), also update test/e2e-v2/cases/storage/expected/config-dump.yml.

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8. Pre-submit checklist

Run in order; each has a dedicated skill:

1. compile — ./mvnw clean flatten:flatten install javadoc:javadoc -B -q -Pall -Dmaven.test.skip -Dcheckstyle.skip -Dgpg.skip. Javadoc [ERROR] ... error: must be fixed; [ERROR] ... warning: is noise.
2. Tests: ./mvnw -pl oap-server/analyzer/log-analyzer -am test -Dtest=LALScriptExecutionTest for LAL changes, equivalent for MAL, OAL unit tests where the rule lives.
3. license — license-eye header check (Apache 2.0 headers). If the UI submodule bumped npm deps, also license-eye dependency resolve --summary ./dist-material/release-docs/LICENSE.tpl and commit the LICENSE diff.
4. package — full make docker (or dist-rebuild + make docker.oap / make docker.ui). Don't trust docker.oap alone to pick up code changes; the dist tarball is a file-level prereq.
5. run-e2e — run the new case end-to-end locally before pushing.
6. gh-pull-request — commit and open PR with the template, attach UI screenshots.

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9. Cross-cutting traps collected from real extensions

Trap	Symptom	Fix
Layer folder named with hyphens	ui-initialized-templates/my-layer/*.json on disk but dashboard empty	Folder must be Layer.name().toLowerCase() (underscores). wechat_mini_program/, not wechat-mini-program/
Extending CommonAnalysisListener for a client-side layer	Added componentId → layer mapping "to get topology for free"; then service_cpm etc. don't populate anyway	Client-side (exit-only) layers don't need trace-analysis changes. Ship Layer + component-libraries.yml + MAL + LAL. See §2 header for when extending trace analysis is actually justified
Dashboards wired to OAL-derived metrics on a client-side layer	Charts stay empty — service_cpm / service_resp_time / endpoint_cpm never populate	Those come from inbound parseEntry, which mini-program / browser / iOS don't emit. Use MAL metrics (meter_<layer>_*) instead
LAL # comment in DSL body	OAP boot fails with extraneous input 'metrics' at the # line	LAL grammar accepts // and /* */ only. No # comments
LAL bare def-var value access — tag 'x': myvar	OAP boot fails with Cannot resolve expression '[myvar]'	LALValueCodegen only treats def-vars as valid when there's a method chain (myvar?.foo). Inline sourceAttribute(...) or tag(...) in the three value-access sites instead of storing to a def, or add a no-op chain like myvar.toString(). Conditions (if (myvar == ...)) go through a different codegen path and DO handle bare def refs
MAL rule file with multi-doc YAML (--- separator)	MALFilterExecutionTest fails with expected a single document; OAP would also fail at startup via Rules.loadRules (calls Yaml.loadAs, single-doc)	Split into one file per top-level expSuffix / filter / metricPrefix combo. Reference each file by name in application.yml (lalFiles, malFiles, enabledOtelMetricsRules)
Histogram bucket bounds in ms with default .histogram() call	Percentile values come out 1000× inflated (P50 = 100000 for a 100 ms request)	MAL's default defaultHistogramBucketUnit = SECONDS multiplies le by 1000 when converting to stored ms. For SDKs that emit ms bounds directly (mini-program, most in-house JS SDKs), use .histogram("le", TimeUnit.MILLISECONDS). TimeUnit is registered in MALCodegenHelper.ENUM_FQCN so rule YAML can reference it
.rate() / .increase() on a DELTA counter / histogram _count	Compute delta-of-delta — nonsense values	OTLP DELTA means each flush is already the per-flush count. MAL's per-minute aggregator sums directly to requests-per-minute. For CUMULATIVE (Prometheus default), use .rate("PT1M") for per-sec or .increase("PT1M") for per-min; they are not equivalent (differ by 60×)
MAL bucket-family name with _histogram suffix	Rule compiles, metric stays empty	PrometheusMetricConverter emits the bucket family as <metric_name> (no suffix), with <metric_name>_count and <metric_name>_sum as the companion families. Reference the bucket family by its bare name in the rule
LAL tag("key") == null check on a missing tag	Check never triggers — LAL's tag() returns empty string "" for absent tags, not null, so conditional abort is a no-op	Guard on both: `tag("key") == null
MAL rule file with expSuffix: service(...) mixing service-scoped and endpoint-scoped rules	Endpoint rules' metrics appear under the service entity (no endpoint_traffic rows created); swctl endpoint ls returns empty. MetricConvert.formatExp:132 appends (exp).expSuffix to every rule, so .endpoint(...) in the rule's expression is followed by .service(...) and the service scope wins.	Follow the APISIX pattern — leave expSuffix: empty and explicitly chain .service(...) / .endpoint(...) on each rule. If every rule in a file is same-scope (e.g. all instance-scoped in *-instance.yaml), expSuffix is still fine

E2E-side authoring traps (log-content YAML quoting, nested contains fragility, timeUnixNano: "0", setup-step curl swallowing failure) live in the run-e2e skill §9. | Missing layer-root template | Menu item lands on empty "no dashboard" view | Layer.vue:41-44 requires a template with isRoot: true; ship a <layer>-root.json (precedent: ios/ios-root.json) | | New layer not selectable in UI / swctl | service ly <LAYER> returns empty | Add the enum in Layer.java with a fresh id; see §0 | | Stale dist in image | make docker.oap succeeds but behavior is old | See package skill; rebuild dist first, then image | | Shipped template edits don't render after restart | Edited JSON on disk, but OAP shows old copy | Set SW_UI_TEMPLATE_FORCE_RELOAD=true (environment variable, not application.yml) and restart; OAP writes addOrReplace. Unset in production so operator UI edits aren't clobbered. | | MAL service-scoped rule fragmented by instance | "Overall app" metric has N series per version | Keep service_instance_id out of service-scoped .sum/.avg. Put instance-scoped metrics in a separate <feature>-instance.yaml with expSuffix: instance(...) — see otel-rules/ios/ pattern. | | Config dump drift | Storage e2e fails after application.yml edit | Mirror the change in test/e2e-v2/cases/storage/expected/config-dump.yml | | LAL layer:auto WARN drop | Every log silently dropped | Codegen must set metadata.layer alongside output builder's layer | | Histogram 1000× off | p50 = 2 000 000 ms | defaultHistogramBucketUnit(MILLISECONDS) on the SampleFamily | | Histogram shifted up | p50 = 5 000 on 500–2500 ms data | Emit per-bucket, not cumulative | | Empty list column | Dashboard instance table has no numbers | Add expressions (not just subExpressions) | | Double scroll | Inner tab scroll + page scroll | Tab.h = content_max + 4 chrome buffer | | Raw metric name in legend | Multiple expressions on one widget | Add parallel metricConfig[].label entries | | spanKind mismatch | Span skipped silently | OTLPSpanReaderImpl.spanKind() returns enum .name() like SPAN_KIND_CLIENT, not CLIENT | | Negative latency | *_sla inflated | Clamp rawLatency < 0 ? 0 : (int) min(Integer.MAX_VALUE, rawLatency) | | SLA too optimistic | Client-side DNS / timeout / connection-refused counted as success | Require a real response code for success: status = code > 0 && code < 400. Do not treat missing (0) as success. | | Silent drop with no rules | converters == null NPE elsewhere | Init to empty list at declaration | | +Inf bucket surfaces as 9.2e18 | UI shows garbage when a sample lands in overflow | Use finite sentinel bucket (e.g. 30 s) | | OTel submodule bump misses UI image | New icons / i18n not visible | Rebuild with -Pui,dist + make docker.ui | | LICENSE drift after submodule bump | CI Dependency licenses fails | license-eye dependency resolve --summary ./dist-material/release-docs/LICENSE.tpl and commit | | Setup-step curl loop swallows failure | e2e passes metrics but fails log verify | curl -f --retry-connrefused --retry-all-errors + set -e | | Verify case flag mismatch | CI fails early on swctl flag unknown to pinned commit | Fire every verify command locally first; bump SW_CTL_COMMIT if needed |

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10. Reference extensions (read their code)

Browse these when you need a template to copy from. Grouped by the kind of data source, because the extension points differ significantly:

SW native trace (language agents) — the "General" layer and friends

Layer.GENERAL is the default layer for services reporting via the SkyWalking native trace protocol (Java / Python / Go / Node.js / .NET / PHP / Lua / Rust agents). It's the richest reference because the native pipeline is where the full topology lives:

• Service → service dependency (topology): derived by MultiScopesAnalysisListener and NetworkAddressAliasMappingListener in oap-server/analyzer/agent-analyzer/src/main/java/.../trace/parser/listener/. Entry/exit spans produce ServiceRelation, ServiceInstanceRelation sources.
• Endpoint → endpoint dependency: RPCAnalysisListener emits EndpointRelation sources from cross-process refs and exit spans. This is unique to the native protocol — OTLP spans don't preserve upstream entry-span metadata the same way, so OTLP-only layers generally lose endpoint-level topology.
• OAL aggregation: oap-server/server-starter/src/main/resources/oal/core.oal — all service_relation_*, service_instance_relation_*, endpoint_relation_* metrics are already defined there; a new native-tracing layer just needs to produce the right sources with the right Layer.

Read order: AnalysisListenerFactory SPI registration → SegmentParserServiceImpl fan-out → individual listeners → OAL rules.

Service-mesh (Istio / Envoy ALS) — topology from proxy-side signals

No agent in the service; Envoy emits HTTP/TCP access logs (ALS) and metrics. Service-to-service topology is reconstructed from ALS request/response pairs.

• oap-server/server-receiver-plugin/envoy-metrics-receiver-plugin/ — ALS receiver + EnvoyAccessLogBuilder persistence (LAL output type).
• otel-rules/istio-*, otel-rules/envoy/* — MAL rules for proxy-emitted OTel metrics.
• lal/envoy-als.yaml — LAL rule that extracts topology-generating fields from ALS.
• Layer: Layer.MESH, plus Layer.MESH_CP (control plane) and Layer.MESH_DP (data plane) for split-plane topology.

Topology parity with native traces: ALS gives you service-level relations; endpoint-level relations are approximate (proxy sees inbound + outbound, not the full call-chain that a native agent observes).

OTLP-only layers (OTel SDKs, iOS/Android, AI gateway, …)

OTLP spans feed a SpanListener. Topology is partial by construction — an OTel Swift SDK on a mobile device only knows about its own outbound requests; there's no upstream caller. So these layers typically produce only Service / ServiceInstance / Endpoint sources (no *Relation) and the Topology view shows isolated islands, by design.

• iOS (Layer.IOS, OTLP traces + MetricKit + LAL diagnostics): oap-server/analyzer/ios-analyzer/ + docs/en/swip/SWIP-11.md.
• Envoy AI Gateway (Layer.ENVOY_AI_GATEWAY, LLM / MCP, OTLP metrics + Zipkin sampled traces + LAL access-log sampling): oap-server/analyzer/gen-ai-analyzer/, otel-rules/envoy-ai-gateway/*, lal/envoy-ai-gateway.yaml.

OTel-metrics-only layers (scraped exporters)

No spans, no logs — just MAL rules converting OTel metric scrapes.

• MySQL / PostgreSQL: otel-rules/mysql/*, otel-rules/postgresql/*.
• Kubernetes: otel-rules/k8s/* — paired with virtual-k8s-service (Layer.K8S_SERVICE) sources for synthetic services.
• AWS: otel-rules/aws-eks/*, otel-rules/aws-s3/*, otel-rules/aws-dynamodb/*.

SW native meter (custom protocol)

No OTel; the agent / plugin sends pre-built meter samples on the SW MeterProtocol.

• Nginx Lua (Layer.NGINX): meter-analyzer-config/nginx-service.yaml, with the Lua agent in apache/skywalking-nginx-lua.
• APISIX (Layer.APISIX): meter-analyzer-config/apisix-service.yaml + LAL trace extraction.

Which to copy from

You're adding	Closest reference
Language agent (new JVM / runtime)	The General / Java layer flow; extend AnalysisListener SPI.
Service mesh / proxy	mesh-* + envoy-* rules; LAL on ALS.
Mobile / browser / mini-program SDK (OTLP)	ios-analyzer (OTLP client-side). Expect no topology relations.
Database / middleware (metrics only)	mysql, postgresql — pure MAL rules.
Cloud service (no agent, just metrics)	aws-eks / aws-s3.
Custom protocol / home-grown telemetry	apisix / nginx — SW native meter.