Logz.io Debuts Multiple Tracing Accounts and Jaeger Architecture Visualization

Logz.io has pressed hard to align our tracing and metrics analytics capabilities over the past year. And as our technology advances, so does our service. We are announcing Multiple Tracing Accounts with Logz.io Distributed Tracing, aligning it with our logging and metrics tools.

Complementing multiple data sources for metrics and logs, Logz users can segment their data according to sources and teams for better organization. You may want to separate between staging and production data or between teams in branches of the larger organization. 

Filtering Tracing Data Sources

Your main account’s allotment of spans can be divided between these multiple tracing accounts. Further, each separate source can be limited to a certain number of those spans, allocating by priority or need.

Set up your new data source (account), then modify access permissions to sources on the Manage Accounts page.

When entering the Tracing section of the Logz.io UI, you can choose a tracing data source from a drop-down list.  

Your dash will then display the stats and spans for that data origin. At the moment, there is no option for an aggregated view of multiple sources, but that option is available in the Kibana UI for logging. Simply select the relevant sources there and you will be able to view the relevant spans.

Just note, to see data from a new source, you might need to allow some time for the new data source/account to initiate. 

Jaeger System Architecture Visualization

We are also announcing the general release of our Jaeger System Architecture Feature. This visualization creates a point graph of all your spans. The diagram adds another dimension to the visualization of traces. In our deployment, traces are identified by number and labeled by junction through which they pass before coming to Logz.io.

This architecture visualization shows a simple traffic pattern between services, but does’t necessarily mark traffic endpoints., While it shows you individual traces went from point A to B and point B to point C, it doesn’t indicate if there were any traces that traveled the A-to-B-to-C path. 

This graph shows how microservices communicate with each other, and in what order. You can see an example here of the Jaeger system architecture here:

We would like to thank our incredible team of developers and engineers for making this happen. But most of all, we want to thank our customers for their feedback. Their requests and use of the Jaeger UI in Logz.io Distributed Tracing has made us quick to enact changes that our community needs. 

We look forward to sharing more news with you soon, both for Logz.io Distributed Tracing and open source news in the Jaeger and OpenTelemetry communities.