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8b87ca50d46d273b868ef98b33fb053750e8d59a
4
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
   
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8b87ca50d4 |
feat(telemetry): auto detect google attributes (#12694)
# Which Problems Are Solved We run multiple deployments (regions) under a single GCP project. Within these deployments we scale containers. Currently all metrics target the same time series in GCP, regardless or region or container. All metics ended up in `generic_node` and Cloud Monitoring rejects the duplicate and out-of-order points. This can be fixed by setting vendor specific attributes such as `faas.name` (K_SERVICE), `faas.version` (K_REVISION), `faas.instance` (instance id from the metadata server), and `cloud.region` (metadata instance/region). # How the Problems Are Solved Use `go.opentelemetry.io/contrib/detectors/gcp` to auto-detect values as mentioned above. A new `Instrumentation.Detectors` config entry is added, which accepts and array of enum for detecotrs. At the moment only Google is accepted, other entries from [contrib](https://github.com/open-telemetry/opentelemetry-go-contrib/tree/main/detectors) can be added if deemed usefull. I've considered using `autodetect` contrib package, identifiers and constructor, but this pulls in the full AWS SDK, increasing zitadel's binary size by 50MiB. By default detection is switched off, as it relies on unauthenticated link-local calls that are insecure anywhere outside of the infrastructure it targets. It also prevents breaking existing deployments that rely on detection being off already. (May break existing trace and logging pipelines). # Additional Changes - none # Additional Context - (internal only): https://github.com/caos/infra/pull/1813 --------- Co-authored-by: Copilot Autofix powered by AI <[email protected]> Co-authored-by: Claude Opus 5 <[email protected]> |
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997aa607c4 |
feat(telemetry): unify request details (#11509)
# Which Problems Are Solved
In the "new" structured logging, request details were added in different
middlewares, such as request, instance and user IDs. This meant the the
upstream request logging middleware did not have access to metadata that
got added later, resulting in incomplete logs. Furthermore it was not
possible to correlate an API error response to log output.
# How the Problems Are Solved
A mutable request details object is added to the context early on. When
the api authz function run, the instance and user IDs are added to this
object as they become available. Every logline emitted after this
(time-wise) will then all contain these details under the `request` log
group.
<details>
<summary>example output in JSON</summary>
```json
{
"time": "2026-03-13T19:21:20.890428806Z",
"level": "INFO",
"source": {
"function": "github.com/zitadel/zitadel/internal/api/grpc/server/connect_middleware.LogHandler.func1.1",
"file": "/workspaces/zitadel/internal/api/grpc/server/connect_middleware/log_interceptor.go",
"line": 34
},
"msg": "request served",
"request": {
"id": "d6q67c04vtjmi77cbbpg",
"instance_host": "localhost:8080",
"instance_id": "362349751439458307",
"user_id": "362349751440048131"
},
"TraceID": "a9e0fee3522224f3583bbdcda737f4b4",
"SpanID": "a563056eee36920a",
"stream": "request",
"version": "2026-03-13T19:20:59Z",
"protocol": "connect",
"service": "zitadel.user.v2.UserService",
"http_method": "POST",
"path": "/zitadel.user.v2.UserService/ListUsers",
"code": "code_0",
"duration": 12254350
}
```
</details>
Request IDs are now also returned with a response header or metadata.
Depending on the protocol:
- HTTP calls always return the request ID as header, regardless of
status
- gRPC calls always return the request ID as header, even if there was
an error
- connect RPC calls returns the request ID as header on success, trailer
in case of error. This is because header must be set on the response
object, which is nil in case of error. When there is an error, metadata
can be added which are then sent as trailers.
# Additional Changes
- Use the existing call duration middleware for both request ID and
logging for a consistent request start timestamp in all layers.
- Upgrade sloggcp for some fixes (notably TraceID)
- Modify the NoCache middleware so it uses `SetHeaders` instead of
`SendHeaders`. The latter prevented any other handler from setting
headers, including the new request ID middleware.
# Additional Context
Follow up on demo of:
- https://github.com/zitadel/zitadel/pull/11159
- https://github.com/zitadel/zitadel/pull/11435
- backport to v4
---------
Co-authored-by: Copilot <[email protected]>
Co-authored-by: muhlemmer <[email protected]>
Co-authored-by: Copilot Autofix powered by AI <[email protected]>
Co-authored-by: Marco A. <[email protected]>
|
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11dbb1b277 |
feat(logging): add streams (#11435)
# Which Problems Are Solved Streams allow differentiating logs produced by different components of Zitadel. # How the Problems Are Solved The `backend/v3/instrumentation/logging` package now exposes convenience function for setting and getting a logger from the context. As well as high-level functions to emit log records at various levels. When constructing a new logger a "stream" needs to be specified: - **runtime**: General runtime logs, such as startup and shutdown messages. Default for logs that do not belong to the other categories. - **request**: Logs for incoming API and HTTP requests. - **event_handler**: Logs for event handling in projections. - **queue**: Logs for the job queue processing. - **event_pusher**: Logs for event pushing to the database. Disabled by default, contains sensitive information. Each line from the returned logger contains a `stream` field as well as a `version` field with the current Zitadel version. ## Runtime config Streams can be enabled by passing an array of stream names in the runtime config. Because some log streams may contain sensitive data (especially events), it is now also possible to mask values by their key. # Additional Changes - Wrap `slogctx` in the `logging` package. (Except API error converter packages, because of import cycle) - Add some docs to `logging` package so other devs understand how to add logging to Zitadel - Add `logging.OnError` and `logging.WithError` helper functions with `Panic()` and `Fatal()` methods, to preserve current calls in the `cmd` packages. - Add instance context extractor. - Only output request details in the request info log. Request ID remains propagated through context. - Moved middleware functionality into protocol specific packages. - Removed setting of URI to context in metric middleware. There were ony setters and no getters. (Unused value) - Reuse a single statusWriter in the middleware package for middlewares that need to know the response status. # Additional Context - Closes #11333 - Closes #11331 - Partly #11330 --------- Co-authored-by: Silvan <[email protected]> |
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Tim MöhlmannandGitHub
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eb22b58756 |
feat(telemetry): improved instrumentation for observability (#11159)
# Which Problems Are Solved Zitadel did not provide easy correlation between errors, logs, traces and metrics. The configuration for those instrumentations was also not consistent, with some supporting different exporters then others. Implementation and parsing of config was also spaghettified over multiple packages, with awkward parsing and inconsistent naming of options. # How the Problems Are Solved All telemetry is now merged under the name "instrumentation". Why? 1. We thought it was a good idea in the past to call the milestone exporter `Telemtry` in the runtime config. Calling this `TelemetryV2` looks weird. 2. Not everything is a meter and not everything is sent (tele...). 3. It's also [defined](https://opentelemetry.io/docs/concepts/instrumentation/) as such by the OTEL documentation. ## New features - Adds structured, context based logging with trace-ID awareness - Static log fields are added to the context, such as service and request path - Static log fields are injected in each logline emitted by the application - Structured logs can also be send to an otel exporter - Structured logs can be printed to StdErr in text and JSON format - Error sinks make sure every error is logged at the correct level: - Warnings for client side errors (HTTP 400 range, Invalid request etc) - Error for server side errors (Internal server errors) - Metrics can now also be send to a OTEL collector. (previously they could only be scraped from `/debug/metrics` with prometheus) ## Exporters This change adds all the exporters supported by OTEL upstream and some google specific exporters for our cloud deployment. - StdOut / StdErr: all instrumentations - OTEL gRPC / HTTP: all instrumentations - Google: all instrumentations except logging - Prometheus (pull-based): only metrics The exception is profiling, which only supports the google exporting due to lack of support by OTEL upstream. ## Configuration and structure - All instrumentation is moved into the new `backend/v3/instrumentation` package. It reuses configuration types, so both code and runtime configuration are easier to understand. - The `internal/telemetry` packages are removed. - Instrumentation is started with a single function and a proper shutdown function is now provided. - Legacy configuration is still parsed from the runtime config, as long as the new configuration is disabled. This allows backporting this feature to v4 without breaking existing configurations. # Additional Changes - Devcontainer: set `$PATH` variable so installed go binaries can be run individually, without NX. - NX: install GCI tool to fix imports # Additional Context - Closes https://github.com/zitadel/zitadel/issues/8408 - Closes https://github.com/zitadel/zitadel/issues/6664 - Backport to v4 |