We are thrilled that Elastic has been recognized as a Leader and a Fast Mover in the 2021 GigaOm Radar Report for Cloud Observability. GigaOm Radar reports offer a forward-looking view of the market and are designed to help IT decision makers evaluate solutions with an eye to the future. Their analysts consider not just where the solutions are today, but also how the market is evolving and where the solutions are headed relative to that trend.

Last week, we announced that Refinery, our platform-agnostic sampling solution, is generally available. But it’s always better to see it for yourself. Follow the steps in this HoneyByte to see how Refinery works by running it locally.

Over a year ago we decided to invest heavily in Application Observability, understanding the modern observability platform must unite logs, metrics, and traces in one analytics layer to better serve reliability use cases. We have also advocated a modern trend to acquire tracing data via open source industry standards like OpenTelemetry without vendor lock-in.

Before we start, please take a moment to appreciate what day it is. IoT, or Internet of Things, has been a buzzword for longer than usual. Buzzwords usually have two common properties, and then their paths fork. I like thinking about buzzwords and about the useful aspects of what they mean. The most recent public example focuses on another buzzword currently in its hype phase: observability.

Digital transformation is accelerating at a staggering pace. Consider these statistics. In December 2019, Splunk partner Zoom had 10 million monthly active users. By the end of last year, that number was estimated to be closer to 300 million. It was part of an explosion of technological growth replicated across many industries and businesses in 2020. As Splunk CEO Doug Merritt said.

IT teams live in dynamic environments and continuous integration/continuous delivery has been on high demand. In the dynamic environment, DevOps and underlying technologies such as containers and microservices, continue to grow more dynamic, and complex. Now, just like DevOps, observability has become a part of the software development life cycle.

What precisely are the requirements of a DevOps practitioner, as opposed to an SRE, legacy developer, or operations manager? And do those specific requirements require a different approach to monitoring?

Amidst the nonstop pace of work to constantly evolve today’s digital business, we can forget to take a moment out to think about how it is that we’re doing that work. A new series of ‘coffee break’ webinars aim to provide that opportunity by pausing to look at the ways humans can best work with observability data. In particular, Coffee Break with Helen Beal looks at improving the work done by different types of software engineers that leverage artificial intelligence.

This is the second in a series of blog posts exploring the role that intelligent observability plays in the day-to-day life of smart teams. In this post, meet our clever ITOps engineer, James, as he reduces noise and distraction using intelligent observability.

I drive a 2005 Ford diesel pickup truck. Most of the time my truck runs great. But occasionally an orange light on the dashboard will flicker on to alert me that something is wrong. Unfortunately, there’s no information about what is wrong and why. My truck has a monitoring solution, but not an observability solution. In many cases, IT has the same problem as my truck.