Recent changes and improvements to Dash0

Every dataset now supports three roles: Viewer, Editor, and Maintainer. Viewers can explore all data and build non-intrusive assets like dashboards and views. Editors extend that by creating new check rules and synthetic checks. Maintainers hold the keys to telemetry-impacting settings - from spam filters to semantic convention versioning.

The result is flexibility with clarity. You can give broad access to non-critical datasets without worrying about accidental changes in production. And because roles are transparent, it’s always clear who has which level of control.

This is a major step toward balancing collaboration with protection, ensuring that Dash0 grows safely alongside your organization.

Read more

Starting with release 0.86.0 of the Dash0 operator, it now has full support for Google GKE Autopilot. Dash0 is now a GKE Autopilot partner, and the Dash0 operator can run as a privileged workload in Autopilot clusters.

Enable the Dash0 operator's autopilot mode by deploying the operator into your GKE Autopilot cluster with operator.gke.autopilot.enabled=trueCopy, and benefit from out-of-the-box telemetry collection that just works.

For more information, refer to the operator's documentation.

You can now bind any dashboard variable to any kind of filter in your queries, supercharging your custom dashboards and bringing a new level of dynamic control to all your observability views.

This update removes the previous limitation of variable usage only within specific query languages. We've introduced a flexible binding mechanism that allows you to map any existing dashboard variable to filters across all supported data sources. Be it logs, metrics, or traces.

We've introduced the ability to hide the main (top-most) chart in various explorers. Hiding these charts gives you more screen real estate to display more entries (e.g., more logs in the logs explorer).

​​What’s New

We’ve added the ability to sort list and table legends for various chart types in dashboards.Additionally, we’ve also added the ability to sort the grids of both gauge and stats charts, along with the ability to also sort the slices of the pie chart.

Sorting is available for the following chart types:

• Time series chart
• Stat charts
• Gauge charts
• Time series table
• Pie chart
• Logs table
• Geographical map

In addition to the above, we’ve also taken the chance of streamlining where the sorting controls live: they now appear consistently in the right sidebar of the Panel Edit screen.

It is also possible to directly sort a table by directly clicking on the column header whilst editing the panel

Having to set up OpenTelemetry SDKs in your applications is a hassle. Wouldn't it be so much nicer if telemetry collection just worked automatically for your production workloads? Enter the Dash0 operator: Not only does it take care of setting up and configuring the OpenTelemetry collector for you, it also makes sure your applications send telemetry to the collector (and thus to Dash0), so you have end-to-end visibility into what is going on in your Kubernetes clusters.

The operator already supports automatic instrumentation for a few other runtimes, and now .NET joins the party. Starting with release 0.83.0 of the Dash0 operator, it will instrument .NET workloads for sending traces, metrics and logs automatically to Dash0.

We are excited to announce that Dash0 now supports Exponential Histograms — the next-generation histogram format introduced by OpenTelemetry.

Dash0 has already been ingesting and storing exponential histograms from OpenTelemetry sources, but until now these metrics could only be listed in the UI. With this update, exponential histograms can be queried and visualized, allowing you to explore, graph, and analyze these metrics alongside regular histograms.

Unlike regular histograms with fixed bucket boundaries, exponential histograms use dynamically scaled buckets that automatically adjust to the magnitude of recorded values. This allows Dash0 to:

• Efficiently represent metrics with high dynamic ranges (for example, latency from microseconds to seconds).
• Maintain higher precision without excessive memory usage.
• Provide smoother and more accurate visualization for metrics such as latency, request duration, or payload sizes.

Dash0 ingests and stores OpenTelemetry exponential histograms in their native form, translating them into native histogram representation for querying and visualization in the UI. This ensures full compatibility with OpenTelemetry data while preserving the precision and scale of the original metrics.

This update allows you to use any of the standard Prometheus histogram functions — such as histogram_quantile() — with full precision and scale preserved from the original OpenTelemetry data.

What’s New

✅ Synthetic Check Sharing: Synthetic Checks can now be shared just like dashboards, views, and check rules - with edit permissions.

✅ Check Rule Sharing: Check Rules, previously unsharable, can now be granted to Teams or individual users with edit permissions.

👥 Consistent Collaboration: Every observability asset now follows the same model. Share once with a Team, and everyone gets the right access level.

🔎 Visibility Built-In: See exactly which assets are shared with which Teams and users, directly from Team and User settings.

Why It Matters

This release closes the loop on Access Control in Dash0. You can now manage sharing across all key observability assets with the same, simple model - giving teams the flexibility to collaborate while keeping management clear and oversight consistent.

Many Dash0 users have asked for the ability to show lists of logs in Dashboards. And now you can:

The Log Table widget allows you to visualize, filter and analyze your logs along all the other data in a Dashboard.

What’s New

Panels can now be opened and viewed directly in TV mode (sometimes referred to "kiosk" mode) similarly to what is possible already with entire dashboards.

Also, we took the chance to make it clearer when you're in TV Mode, and how you can get out of it.