In this blog post, we will discuss the experiments we did to find the best hashing method for Metrictank data distribution.

If money makes the world go round, then technology is becoming its engine. Financial services, in particular, have widely adopted big data technologies and analytics to inform better investment decisions. The past decade has seen the rise of digital investment platforms. Financial institutions — facing increasing competition, regulatory constraints and customer needs — are seeking ways to leverage technology to gain efficiency and competitive advantage.

We’ve had an eventful year here at Grafana Labs. As 2019 comes to a close, here’s a look back. Here’s to an equally exciting 2020!

As 2019 comes to a close, we’re looking back at the 10 most-read blog posts of the year. (We’re not including the also-popular release posts in this list.) Here’s another chance to check them out in case you missed them the first time around.

At KubeCon San Diego, I presented an updated and revised version of my talk “Blazin’ Fast PromQL”. In this blog post I’ll give you a brief write up of the talk and steps to reproduce the results yourself.

Great dashboards answer a limited set of related questions. If you try to answer too many questions in a single dashboard, it can become overly complex. As a consequence, a single dashboard often can’t tell the whole story. So you end up navigating between several, and it can be quite inefficient to search for a particular dashboard every time you need it. Luckily, there are some hacks for navigating between dashboards.

Grafana annotations are great! They clearly mark the occurrence of an event to help operators and devs correlate events with metrics. You may not be aware of this, but Grafana can automatically annotate graphs by querying Loki. Here’s a look at how to use this feature. Loki queries can be used to automatically generate annotations on Grafana dashboards since 6.4.0. For every log line that is returned from a query, the text is automatically displayed as an annotation at the appropriate time.

Data visualization is an essential concept in the field of data science. So much so that whenever you want to analyze any set of data, you must always incorporate data visualization. Regardless, the majority of people still do not have a proper understanding of this concept and how to implement it. Therefore, in this article, we define data visualization and examine ten website applications for performing it.