In recent years, monoliths have lost favor as microservices increased in popularity. Conventional wisdom says that microservices, and distributed systems in general, are hard to operate: There are often too many dependencies and tunables, multiple moving parts, and operational complexity.
Entity extraction is, in the context of search, the process of figuring out which fields a query should target, as opposed to always hitting all fields. The reason we may want to involve entity extraction in search is to improve precision. For example: how do we tell that, when the user typed in Apple iPhone, the intent was to run company:Apple AND product:iPhone? And not bring back phone stickers in the shape of an apple?
In a hyper-connected world, the threat landscape is undoubtedly evolving. Ensuring the security of your enterprise networks on a daily basis is essential to protect your business, no matter how big (or small) it is. According to SophosLabs’ 2019 threat report, one dangerous ransomware called SamSam cost companies $6.5 million ($10K to $50K per ransom).
We have been working on a new panel and component architecture for the last half year (or more), and it’s finally starting to bear fruit in terms of new visualizations and capabilities.
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.
