Most modern web apps end up sprouting some subset of tasks that happen in the “background”, i.e., when a user is not directly waiting on the request from a server to finish. These types of tasks range across all kinds of use cases – processing media, generating aggregate statistics for later view in the front end, and syncing data to 3rd party providers are just a few of many examples.
Democratizing data is one of our key product goals, and we share a similar approach to content. With over half a million words, our Sumo Logic documentation set is a substantial amount of information to provide to our users on the various ways you can collect logs and metrics, query that information, and turn it into meaningful visualizations. But the real trick is making sure that people can find what they need quickly.
Logging your virtual machines (VMs) is important, but what’s even more important is logging the hypervisors that run them. Hypervisors generate extremely useful data about the operation of your virtual machines and the environments that they run in. While VMs provide some information about their state, details such as VM performance, changes in state, errors, and security can only be found through hypervisor logs.
In the midst of all the turmoil and debate around Open Distro for Elasticsearch, Elastic continues to produce, and last week announced both a new major release of the Elastic Stack — version 6.7 (and also the first release candidate for 7.0!). As usual, I’ve put together a brief overview of the main features introduced. One change I’ve applied this time is adding a comment for each feature detailing what license it falls under.
I recently gave a talk at DigitalOcean Tide in Bangalore on “Grafana and the DigitalOcean Marketplace.” The DO Marketplace lets you launch a range of open source software, including Grafana, with just a few clicks. This post is not about the marketplace – I’m going to talk about how we automated the building of the images.
Being inside a company that lives and breathes logging, observability and DevOps intelligence, sometimes it takes a moment to step back and explain what we do to friends, family and others. The simplest way we explain what LogDNA solves for companies with IT systems and software is similar to a blackbox on a plane that keeps a record of the flight data and the cockpit voice recorder.
One of the major projects we’re working on for Metrictank – our large scale Graphite solution – is the meta tags feature, which we started last year and are targeting to release in a few months. A lot of people don’t realize this, but Graphite has had tag support for more than a year. Our mission with Metrictank is to provide a more scalable version of Graphite, so introducing meta tags was a logical next step.
Spring has finally sprung! I realize that was a groaner, but new features are no joke – using them will simplify your troubleshooting process and open up time for all the cool tasks you want to do. Besides parsing logs, of course.
Whether or not you’re familiar with time-series data, it has a significant impact on your life – and your business. If you aren’t using it, you’re missing out. If you are using it, you may not be getting the most out of it. First things first, let’s define time-series data. Simply stated, it’s any series of data points recorded with accompanying time stamps, usually as a sequence recorded at equally spaced intervals.
