In case you missed it, this webinar includes code walkthroughs that help you to add observability to your pipelines (using a free Honeycomb account!) so that you and your team can speed up your deployments to prod. This is also a risk-free way to get started with observability if your team isn’t quite yet ready to change your production apps.
During my office hours, I frequently get asked for practical tips on getting started with observability. Often it’s from folks on teams who are already practicing continuous delivery (or trying to get there) and are interested in more advanced practices like progressive delivery. They know observability can help—but as individual contributors—they don’t sign the checks, so they feel powerless to help get their team started with observability.
Starting today, Honeycomb’s Management API is generally available to all Honeycomb users. The Honeycomb Management API is a set of endpoints that lets you programmatically set up, configure, and delete queries, datasets, derived columns, and more. With this release, you can now manage Honeycomb with configuration as code either directly via API or with third-party tools, like Terraform, using the community-contributed Honeycomb provider.
Over the last few months, Honeycomb’s platform team migrated to a new iteration of our ingest pipeline for customer events. Our migration to this newer architecture did not go too smoothly, as can be attested by our status page since February. There were also many near-incidents where we got paged and reacted quickly enough to avoid major issues. We’ve decided to write a full overview of all the challenges we had encountered, which you can can download.
A year ago, we wrote about our experiences as early adopters of Graviton2, and how we were able to see 30% price-performance improvements on one dogfood workload from switching to the arm64 architecture. In those initial experiments, we validated running 20% fewer shepherd ingest workers, using the m6g instance type, which cost 10% less per instance compared to c5 instances.
The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to observability data. For another, most customers have to lean on a hodgepodge of tools that might blend open source and proprietary, require extensive onboarding as team members have to learn which tools are used for what, and have a steep learning curve in general.
Recently, we added a new derived column function to Honeycomb, INGEST_TIMESTAMP(), which can help customers debug event latency and/or inaccurate timestamps. A meaningful minority of the events sent to Honeycomb are already old when they arrive, and a very special few claim to have been sent from the future. Has this happened to you? Let’s do an experiment.
Last week, we announced that Refinery, our platform-agnostic sampling solution, is generally available. But it’s always better to see it for yourself. Follow the steps in this HoneyByte to see how Refinery works by running it locally.
Today, we announced that Refinery is now generally available. With Refinery, it’s now easy to highlight the critical debugging data you need and to stop paying for the rest. Refinery is a sampling solution that lets you control resource costs at scale without sacrificing data fidelity. Support for Refinery is now also included in Honeycomb Enterprise plans.
Are you looking for a better way to troubleshoot, debug, and really see and understand what weird behavior is happening in production? Service-level objectives (SLOs) and observability can help you do all that—but they require collecting and storing the right data. If we’re naive with our telemetry strategy, we spend a lot of money on storing data without seeing adequate return on investment in the form of insights.
