Operations | Monitoring | ITSM | DevOps | Cloud

September 2021

Understanding Lambda Sleep Cycles With CONCURRENCY

It started with a simple question: Why did one query take 10 seconds, while another almost identical query took 5? At Honeycomb, we use AWS Lambda to accelerate our query processing. It mostly works well, but it can be hard to understand and led us to wonder: What was really going on inside this box called Lambda? These questions kicked off the development of CONCURRENCY, a new aggregate in the Query Builder that lets us look at how many spans are active at once.

Observability: The 5-Year Retrospective

Two years ago, I wrote a long retrospective of observability for its third anniversary. It includes a history of instrumentation and telemetry, a detailed explanation of the technical spec, and why the whole “three pillars” thing is nonsense. At the time, it’s what was needed to steer conversations away from silly rabbit holes about data types and back to what matters: how we understand our systems.

How Refinery Helps With Sampling Complex Event Data

Sampling is the practice of extracting a subset of data from a dataset to make conclusions about that larger dataset. It’s far from a perfect solution, but when it’s implemented with Refinery, Honeycomb’s trace-aware sampling proxy, sampling can help you manage very high volumes of complex event data.

Metrics now generally available in Honeycomb

Starting today, Honeycomb Metrics is now generally available to all Enterprise customers. You’ve adopted our event-based observability practices, in part to overcome the debugging roadblocks you hit when using custom metrics to identify application issues. But metrics do still provide value at the systems level. Now, you can easily see and use your metrics data alongside your event data in Honeycomb—all in one interface.

An Introduction to Distributed Tracing

There’s no strict definition of a distributed system. But generally speaking, if you have reached a point where you’re running more than five interdependent services at once, that means you’re running a distributed system. It also means you are more than likely experiencing difficulties when troubleshooting using traditional debugging tools. Unfortunately, pulling up multiple tools, each built for a monolithic world, doesn’t help pinpoint the problem.