With Elastic 7.9, the Elastic Agent and Fleet were released, along with a new way to structure indices and data streams in Elasticsearch for time series data. In this blog post, we'll give an overview of the Elastic data stream naming scheme and how it works. This is the first in a series of blog posts around the Elastic data stream naming scheme.

Monitoring COVID-19 metrics has become essential as the Coronavirus pandemic continues to impact countries across the globe. Mitigating virus impact and spread requires ongoing tracking of metrics such as cases and fatalities. This is what the InfluxDB COVID-19 Monitoring Template does.

In the first and second part of the blog series, we discussed the importance of correlation analysis in root cause analysis in general and in the context of promotional marketing. In a similar vein, in this blog we walk through how to leverage correlation analysis to address challenges in the telecom space.

AI and analytics are playing critical roles in driving innovation among many businesses riding the digital transformation wave during this pandemic. Many business leaders realize that people are not wired to think exponentially, but incrementally in a linear world, unable to see the ripple effects of their actions. The pandemic has highlighted the enormous impact this has on the quality of decisions made, especially in the context of business.

When investigating a complex system—or learning about it for the first time—you need to explore metrics, traces, logs, and other kinds of data. But as you navigate across different views of your data in dashboards, alert notifications, flame graphs, and so on, it can be hard to keep track of what you have already seen. When a potential issue comes up and time is tight, the last thing you need is to spend time remembering a crucial graph or finding the right browser tab.

Signed search keys in Elastic App Search give you more control over a user's search experience. You can tailor the experience to show results you know are more relevant to the specific user while also controlling what data the user can see and search over.

With the speed of change in artificial intelligence (AI) and big data, podcasts are an excellent way to stay up-to-date on recent developments, new innovations, and gain exposure to experts’ personal opinions, regardless if they can be proven scientifically. Great examples of the thought-provoking topics that are perfect for a podcast’s longer-form, conversational format include the road to AGI, AI ethics and safety, and the technology’s overall impact on society.

Last month we announced InfluxDB IOx (pronounced: eye-ox), a new Rust and Apache Arrow based core for InfluxDB. While InfluxDB IOx is a columnar database built on top of object storage, that’s only part of its role. In addition to query functionality, one of the big goals of InfluxDB IOx is to help manage the data lifecycle for time series data. This post will cover the design for how InfluxDB IOx plans to manage that data lifecycle.

Now that you’ve read through Top 5 Hurdles for Flux Beginners and Resources for Learning to Use Flux, you’re well on your way to being an advanced Flux user. This post includes some of the top hurdles for intermediate Flux users as well as solutions.

Are you new to InfluxDB v2.0 and Flux? Are you intimidated by learning a new time series scripting and query language? Perhaps you’re an InfluxDB v1.x user and you’re familiar with InfluxQL, and you’re unconvinced that learning Flux is worth your while? This two-part blog series aims to demonstrate the power of Flux and walk you through solutions to the top hurdles for both new and old InfluxDB users.