The service sampling ratio - in case different than the default 100% - is now easily available in Helios for each service and API impacted.

In addition to automatically tracing E2E flows that include handling message queues such as Kafka or Amazon SQS - Helios now provides observability & monitoring over queue latency of the messages handled.

The service dashboard now also offers insight into the top APIs of the service, grouped by:

The API dashboard in Helios now also displays a few new metrics on the top right, calculated based on instrumented data during that time range and in the specific environment:

The service map in Helios, which is constructed automatically based on distributed tracing data reported by the application, now also highlights the interactions with the highest call frequency (pink), error rate (red), and average call duration (teal).

It's now possible to visualize and apply observability & monitoring to Temporal.io workflows & activities instrumented with the Helios SDK.

We've added the options to sort the list of APIs (incoming operations) each service has by the following properties - based on the instrumented data and OpenTelemetry spans:

We’ve added a new widget to the label dashboard: the most frequent operations that match the label's conditions.

After some time during which our service map was made available as a beta feature, we're excited to announce that it is now generally available

The Helios Slack Community is now live and users are welcome to join!