Honeycomb makes room for metrics as observability space grows and thrives

Honeycomb Metrics

With a recent update to its product, debugger for live production systems Honeycomb has finally submitted to sprinkling metrics over its event-based approach. 

Honeycomb Metrics is a still-in-beta addition to the platform that allows it to receive metrics data directly. Given that the company is known for not caring too much about metrics — mainly because time series data “bundles everything about system state over a given period of time into one number and that number can’t be decomposed back into its individual event parts” — this step is quite notable.

However, it might also be necessary in order to win some more established businesses over, given that not all systems can be fitted with the instrumentation needed to procure the events that are Honeycomb’s measure of choice. Opening the platform up for aggregated measures, therefore, makes it more of an option for everyone looking after very mixed estates of cloud native, serverless, and legacy tech.

Company CEO Christine Yen explained the move in a blog post, noting that aggregated measures can still serve as warning signals. “For a majority of use cases, it makes sense to use events for understanding the code you write and use metrics for understanding constraints that impact how your code runs.”

According to Yen, focusing on events only made it hard for customers to get metrics into Honeycomb, which meant they’d have to run more tools on the side and switch between them in case of production issues. This, however, didn’t fit with the company’s idea of observability — which entails that all debugging data should be in one place to get answers quickly in case of an issue. Adding Honeycomb Metrics helps to make that vision more of a reality and supplements event-based debugging.

Other than that, Honeycomb looked into ways of supporting its users in the creation and use of queries. Results include a Query Data API, which allows operation teams to programmatically create and run Honeycomb queries. This addition is especially helpful in automating workflows, and lets teams feed Honeycomb data into other visualisation tools.

The platform also includes a reworked version of the Query Builder, which offers proposals for automatically filling in field values, and a function to compare query results over two time ranges.

Honeycomb’s reworked offering will surely help it stay relevant, as new players emerge in the observability space. Just a couple of days ago, self-defined Kubernetes troubleshooting company Komodor announced a $21 million Series A funding round. 

Komodor generated excitement in March 2021 with the promise of a platform designed to support teams in tracking changes across the Kubernetes stack, to simplify the identification of unhealthy services as well as the cause of that state. The newly secured funding should help the one-year-old company drive feature development and finance a team to market the product.