Enhancements to Honeycomb Telemetry Pipeline Deliver Greater Visibility, Smarter Control, and Lower Costs

In July, we introduced powerful new Honeycomb Telemetry Pipeline features that helped teams take control of their observability data with safe sampling, flexible rehydration, and a visual pipeline builder. Since then, we’ve built on that foundation. Today, we’re introducing the latest enhancements to Honeycomb Telemetry Pipeline, which give teams deeper visibility into pipeline health, more efficient access to archived telemetry data, and reduced operational complexity.

According to recent Gartner research on telemetry pipelines, organizations are increasingly adopting purpose-built pipeline tools to manage the growing scale, cost, and complexity of observability data. Honeycomb was cited among the vendors driving this shift, reflecting our continued focus on helping teams improve efficiency and control.

With the introduction of Pipeline Health (beta), Enhance Indexing (GA), and Refinery 3.0, Honeycomb gives teams new ways to see how telemetry flows through their systems and quickly rehydrate the specific data they need.

Pipeline Health (beta): real-time insight into your pipeline

Even when telemetry pipelines are configured correctly, teams often lack a clear way to confirm that data is flowing as expected. In many cases, they rely on fragile dashboards or manual checks that fail if data has not yet started streaming through the system.

Now available in Pipeline Builder, the new Pipeline Health tab fixes that. It provides real-time operational metrics across the entire pipeline infrastructure. Teams can see at a glance whether data is flowing as expected, with charts showing incoming data volumes at each stage and breakdowns by destination.

What makes Pipeline Health particularly powerful is that a pipeline's operational telemetry flows into a dedicated Honeycomb environment at no additional cost. This means teams aren't limited to pre-built dashboards. They can query their operational telemetry just like any other Honeycomb data, define SLOs on pipeline performance, and investigate pipeline issues using Canvas.

Pipeline Health also displays the effective configuration currently running on OpenTelemetry Collectors and Refinery nodes, making it easy to verify deployments and troubleshoot configuration drift. It gives observability teams a real-time window into how their telemetry infrastructure is performing, enabling engineers to verify their pipelines are configured correctly, confirm data is flowing as intended, and troubleshoot issues when they arise.

Enhance Indexing (GA): faster, smarter data rehydration

Rehydrating telemetry data from cold storage such as Amazon S3 can be time-consuming and expensive. Many tools require a complete retrieval of archived data, which can take hours and result in significant costs from ingesting unnecessary information.

With Honeycomb's Enhance, you can rehydrate data in minutes or even seconds, and target a more precise slice of your archived telemetry. Enhance Indexing, now GA, makes rehydration even more efficient. Rather than rehydrating entire date ranges and then filtering within Honeycomb, teams can specify index values upfront. For example, "Only rehydrate files containing spans or logs with trace_id X" or "service_name Y."

Enhance by default indexes three fields: trace_id, session_id, and service_name. Teams can also define custom indexes for any fields that reflect their specific workflows, such as customer IDs, API endpoints, or error codes. When initiating a rehydration, Honeycomb displays an estimate of how many events will be ingested, allowing teams to verify they're retrieving the right scope of data before proceeding.

Enhance Indexing lets teams sample aggressively to manage daily costs while maintaining confidence that they can retrieve critical data quickly at any time without wasted spend.

Refinery 3.0

Refinery is Honeycomb's tail-based sampling proxy. It helps teams reduce their observability costs by intelligently routing only the most important telemetry data to Honeycomb.

Trace-aware tail-based sampling requires holding trace data in memory while waiting to make sampling decisions. It needs to handle sudden volume spikes with little time to scale, and do all of this as efficiently as possible, since teams use sampling primarily for cost control.

The recent release of Refinery 3.0 focused on making Refinery dramatically more efficient. When we upgraded Honeycomb's internal Refinery cluster, the results were significant:

• 70% lower CPU usage
• 60% lower memory consumption
• 50% fewer nodes required to manage the same volume of telemetry

Customers deploying Refinery 3.0 are reporting similar infrastructure reductions. Multiple customers have halved their Refinery deployments, reducing memory allocations, CPU requirements, and instance counts by 50% or more while maintaining performance. As one customer put it: "We continue to be amazed at how effective this update is."

These efficiency gains translate directly to lower infrastructure costs for running Refinery, while providing more headroom to handle traffic spikes smoothly as systems scale.

If you want to learn more about how we did it, check out the announcement blog.

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Together, Pipeline Health, Enhance Indexing, and Refinery 3.0 form a stronger foundation for efficient, reliable observability. Honeycomb Telemetry Pipeline now helps teams build smarter, more transparent pipelines that remain stable and cost-effective as systems grow.

As Gartner's analysis highlights, organizations are recognizing the need for telemetry pipelines that balance cost and control. Honeycomb continues to lead in delivering these capabilities through products that make observability faster, leaner, and easier to trust.

Honeycomb Telemetry Pipeline is available to all Honeycomb Enterprise customers. Don’t have an account yet? Talk to sales today.