# Which Problems Are Solved
With current provided telemetry it's difficult to predict when a
projection handler is under increased load until it's too late and
causes downstream issues. Importantly, projection updating is in the
critical path for many login flows and increased latency there can
result in system downtime for users.
# How the Problems Are Solved
This PR adds three new prometheus-style metrics:
1. **projection_events_processed** (_labels: projection, success_) -
This metric gives us a counter of the number of events processed per
projection update run and whether they we're processed without error. A
high number of events being processed can let us know how busy a
particular projection handler is.
2. **projection_handle_timer** _(labels: projection)_ - This is the time
it takes to process a projection update given a batch of events - time
to take the current_states lock, query for new events, reduce,
update_the projection, and update current_states.
3. **projection_state_latency** _(labels: projection)_ - This is the
time from the last event processed in the current_states table for a
given projection. It tells us how old was the last event you processed?
Or, how far behind are you running for this projection? Higher latencies
could mean high load or stalled projection handling.
# Additional Changes
I also had to initialize the global otel metrics provider (`metrics.M`)
in the `setup` step additionally to `start` since projection handlers
are initialized at setup. The initialization checks if a metrics
provider is already set (in case of `start-from-setup` or
`start-from-init` to prevent overwriting, which causes the otel metrics
provider to stop working.
# Additional Context
## Example Dashboards
---------
Co-authored-by: Silvan <27845747+adlerhurst@users.noreply.github.com>
Co-authored-by: Livio Spring <livio.a@gmail.com>
# Which Problems Are Solved
The service name is hardcoded in the metrics code. Making the service
name to be configurable helps when running multiple instances of
Zitadel.
The defaults remain unchanged, the service name will be defaulted to
ZITADEL.
# How the Problems Are Solved
Add a config option to override the name in defaults.yaml and pass it
down to the corresponding metrics or tracing module (google or otel)
# Additional Changes
NA
# Additional Context
NA
# Which Problems Are Solved
There were multiple issues in the OpenTelemetry (OTEL) implementation
and usage for tracing and metrics, which lead to high cardinality and
potential memory leaks:
- wrongly initiated tracing interceptors
- high cardinality in traces:
- HTTP/1.1 endpoints containing host names
- HTTP/1.1 endpoints containing object IDs like userID (e.g.
`/management/v1/users/2352839823/`)
- high amount of traces from internal processes (spooler)
- high cardinality in metrics endpoint:
- GRPC entries containing host names
- notification metrics containing instanceIDs and error messages
# How the Problems Are Solved
- Properly initialize the interceptors once and update them to use the
grpc stats handler (unary interceptors were deprecated).
- Remove host names from HTTP/1.1 span names and use path as default.
- Set / overwrite the uri for spans on the grpc-gateway with the uri
pattern (`/management/v1/users/{user_id}`). This is used for spans in
traces and metric entries.
- Created a new sampler which will only sample spans in the following
cases:
- remote was already sampled
- remote was not sampled, root span is of kind `Server` and based on
fraction set in the runtime configuration
- This will prevent having a lot of spans from the spooler back ground
jobs if they were not started by a client call querying an object (e.g.
UserByID).
- Filter out host names and alike from OTEL generated metrics (using a
`view`).
- Removed instance and error messages from notification metrics.
# Additional Changes
Fixed the middleware handling for serving Console. Telemetry and
instance selection are only used for the environment.json, but not on
statically served files.
# Additional Context
- closes#8096
- relates to #9074
- back ports to at least 2.66.x, 2.67.x and 2.68.x
# Which Problems Are Solved
To have more insight on the performance, CPU and memory usage of
ZITADEL, we want to enable profiling.
# How the Problems Are Solved
- Allow profiling by configuration.
- Provide Google Cloud Profiler as first implementation
# Additional Changes
None.
# Additional Context
There were possible memory leaks reported:
https://discord.com/channels/927474939156643850/1273210227918897152
Co-authored-by: Silvan <silvan.reusser@gmail.com>
# Which Problems Are Solved
The v2beta services are stable but not GA.
# How the Problems Are Solved
The v2beta services are copied to v2. The corresponding v1 and v2beta
services are deprecated.
# Additional Context
Closes#7236
---------
Co-authored-by: Elio Bischof <elio@zitadel.com>
chore(fmt): run gci on complete project
Fix global import formatting in go code by running the `gci` command. This allows us to just use the command directly, instead of fixing the import order manually for the linter, on each PR.
Co-authored-by: Elio Bischof <elio@zitadel.com>
