For the majority of the first year that we worked on the Loki project, the questions and feedback seemed to come from people who were familiar with Prometheus. After all, Loki is like Prometheus – but for logs! Recently, however, we are seeing more people trying out Loki who have no Prometheus experience, and many are coming from systems with much different strategies for working with logs.

The days of logging as a mere troubleshooting mechanism are past gone. Nowadays, log management is a must. In today’s post, we’ll present you with a list of 11 log management solutions worth checking out. Let’s dig in. The first tool in our list is Splunk, which is a comprehensive utility very well-known by sysadmins. It’s available as a downloadable tool for Linux, Windows, and macOS X. A cloud version also exists, as well as a free version with limited capabilities.

At Logz.io, our team has the opportunity to partner with many cutting edge technology companies and products from different trades. Many have a crucial mission and help save lives worldwide. In the fight against the novel coronavirus, telehealth is one such sector. It compels us to do all we can to support these organizations by improving application accessibility and performance for users who need it. One of our customers epitomizes this—Tyto Care. Tyto Care is a healthcare pioneer.

In modern digital environments, logs are present everywhere. From networking devices, servers, and databases, to operating systems, cloud-based services, and applications, every component produces some form of digital records of events. These records or logs provide an audit trail for Security Information Event Management (SIEM) and help in performance monitoring of servers and applications.

We are offering a variety of on-demand Elastic training courses for free — featuring 11 titles that span observability, security, and Elastic Stack administration. If you haven’t tried one of our self-paced courses yet, now is the perfect time to find out why so many people have shifted their learning preference from in-class to online. Our on-demand courses provide the same immersive learning experience found in the classroom, but delivered in a convenient, remote environment.

Managing a network more effectively has been something our customers have been asking us about for many years, but it has become an increasingly important topic as working from home becomes the new normal across the globe. In this blog series, I thought I’d present a few analytical techniques that we have seen our customers deploy on their network data to: Better understand their network and Develop baselines for network behaviour and detect anomalies.

A difficult question we come across with many customers is ‘what does normal look like for my network?’. There are many reasons why monitoring for changes in network behaviour is important, with some great examples in this article - such as flagging potential security risks or predicting potential outages.

When working with observability data, a good portion of it comes in as time series data — things like CPU or memory utilization, network transfer, even application trace data. And the Elastic Stack offers powerful tools within Kibana for time series analysis, including TSVB (formerly Time Series Visual Builder). In this blog post, I’m going to attempt to demystify rates in TSVB by walking through three different types: positive rates, rate of change, and event rates.

Elasticsearch allows you to store, search, and analyze large amounts of structured and unstructured data. This speed, scale, and flexibility makes the Elastic Stack a powerful solution for a wide variety of use cases, like system observability, security (threat hunting and prevention), enterprise search, and more. Because of this flexibility, effectively architecting your deployment’s data storage for scale is incredibly important.