Chaos engineering + monitoring, part 2: for starters

Oh man, did I get ahead of myself in my last post! I started chatting tools, and I realize now that I really should have been talking more about why I’m using Sensu and Gremlin. But it didn’t occur to me until last year at Monitorama. John Allspaw gave the keynote talk (Taking Human Performance Seriously). While you can watch the talk here, I’ll highlight a few points...


Streaming live data is the heart of observability

As a security engineer working on the core team at Humio, I focus on making Humio a powerful part of the security stack for our customers. I have a passion for cybersecurity, and like a lot of our customers, I love breaking stuff in the most unexpected ways so I can fix them. For security, much of the power of Humio comes from its ability to ingest live streaming data and make it immediately available to update alerts, visualizations, and perform queries.


Why Do I Need an O11y platform?

Welcome to the beginning of our observability journey. It can be challenging to keep up with new philosophies and vocabulary when our day jobs so rarely incorporate them. Then suddenly, someone in your organization hears that observability (or, O11y, if you will) is important and we have to figure it out — fast. So why do we really need an observability platform?


3 cool tech tapas we found at Cisco Live Europe

I love traveling to Barcelona for conferences. Between Gaudi’s architecture and tech architectures, there’s really not much more I can ask for. Walking into Cisco Live!, the first thing I encountered was the huge indoor fountain called the “Rain Wall”, which was built to raise awareness and celebrate Cisco’s Corporate Social Responsibility program.


Building a Modern Observability Stack with Garland, Corelight, and Humio

In its most basic form, data travels across the internet in packets — each carrying a maximum of 1,500 bytes — until they reach a pre-determined destination. As packets arrive, the network receiving the data assembles the packets like a puzzle, recreating the message. Today, data transmission involves unprecedented volumes of data at increasing speeds.


A Step Towards Observability with Lambda Destinations

If we are to loosely extrapolate the well-known Chinese proverb, “a journey of a thousand miles starts with a single step”, we can build the story of how AWS Lambda Functions has matured on its journey to an ideal serverless solution. The absolute optimization of serverless, where all known barriers are overcome, may still be far, but AWS has been industriously taking the steps to this goal. One of the latest being AWS Lambda Destinations.


Using Honeycomb to remember to delete a feature flag

Feature flags are great and serve us in so many ways. However, we do not love long-lived feature flags. They lead to more complicated code, and when we inevitably default them to be true for all our users, they lead to unused sections of code. In other words, tech debt. How do we stay on top of this? Find out how Honeycomb’s trigger alerts proactively tell you to go ahead and clean up that feature flag tech debt!


Getting At The Good Stuff: How To Sample Traces in Honeycomb

(This is the first post by our new head of Customer Success, Irving.) Sampling is a must for applications at scale; it’s a technique for reducing the burden on your infrastructure and telemetry systems by only keeping data on a statistical sample of requests rather than 100% of requests. Large systems may produce large volumes of similar requests which can be de-duplicated.