How to instrument your charm with tracing telemetry

This howto has been incorporated in the tempo docs.

In order to instrument a charm with tracing telemetry, you will need to:

Set up a model with cos-lite:

juju add-model clite
juju deploy cos-lite --trust

See more: Charmhub | cos-lite

Deploy tempo:

juju deploy tempo-k8s

See more: Charmhub | tempo-k8s

Integrate tempo with cos-lite:

jhack imatrix fill

See more: jhack, GitHub | jhack > imatrix > fill

Alternatively, you can integrate manually by:

juju integrate tempo:logging loki:logging
juju integrate tempo:ingress traefik:ingress
juju integrate grafana:grafana-source tempo:grafana-source
juju integrate prometheus:metrics-endpoint, tempo:metrics-endpoint
juju integrate grafana:grafana-dashboard, tempo:grafana-dashboard
juju integrate traefik:tracing, tempo:tracing
juju integrate prometheus:tracing, tempo:tracing

At some point there will be an overlay bundle to deploy cos-lite + tempo and integrate them; see this PR to follow the progress on the overlay.

At this point you should have a working cos-lite plus tempo deployment; something like this:

Fetch the charm_tracing and the tracing libs:

charmcraft fetch-lib charms.tempo-k8s.v1.charm_tracing
charmcraft fetch-lib charms.tempo-k8s.v2.tracing

See more: charmcraft fetch-lib, Charmhub | tempo-k8s > Libraries > charm-tracing, Charmhub | tempo-k8s > Libraries > tracing

Add opentelemetry exporter dependency used by charm_tracing to your requirements.txt:

opentelemetry-exporter-otlp-proto-http>=1.21.0

Add an integration with tempo:

# in charmcraft.yaml
provides:
  tracing:
    interface: tracing
    limit: 1

See more: File charmcraft.yaml > provides

Instrument your charm code:

# in /your/charm/project/src/charm.py
from charms.tempo_k8s.v1.charm_tracing import trace_charm
from charms.tempo_k8s.v2.tracing import TracingEndpointRequirer

@trace_charm(tracing_endpoint="tracing_endpoint")
class MyCharm(CharmBase):
    def __init__(self, *args):
        super().__init__(*args)
        # add a provider wrapper for the tracing endpoint
        self.tracing = TracingEndpointRequirer(self, protocols=["otlp_http"])

    @property
    def tracing_endpoint(self) -> Optional[str]:
        """Tempo endpoint for charm tracing."""
        if self.tracing.is_ready():
            return self.tracing.get_endpoint("otlp_http")
        return None

By default, the traces generated by this charm will be tagged with service name equal to the class name of the charm, so "MyCharm" in this case. You override this default by passing service_name="foo" to trace_charm.

Pack, deploy, and integrate your charm with cos-lite:

charmcraft pack
juju deploy ./my-charm-operator_ubuntu-20.04-amd64.charm mycharm \
  $(yq eval '.resources | to_entries | map(select(.value.upstream-source != null) | "--resource " + .key + "=" + .value.upstream-source) | join(" ")' charmcraft.yaml)
juju integrate mycharm:tracing tempo-k8s:tracing

cos-lite is a kubernetes bundle. tempo is a Kubernetes charm.

See more: charmcraft pack, Juju | juju deploy, Juju | juju integrate

View the traces for the charm.

Open the Grafana dashboard in a browser (see here for more detailed instructions).

Next, navigate to the traces for your charm:

go to Explore and select the Tempo datasource.
pick the service_name you gave to MyCharm above (the default is the application name) to see the traces for that charm
click on a trace ID to visualize it. For example, this is the trace for an update-status event on the Tempo charm itself:

Mapping events to traces with jhack tail

jhack tail supports a -t option to show the trace IDs associated with a charm execution:

This means that you can tail a charm, grab the trace id from tail, put it in the grafana dashboard query and get to the trace in no time.

Last updated 3 months ago.

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