Many cybersecurity teams are drinking from multiple firehoses without solutions in place to deal with the onslaught of data. And with 70 percent of companies experiencing over one hundred attacks each day, it’s not slowing down. Teams are overwhelmed with data from multiple sources and formats with continuous requests to pull in more and more.
While 2020 and 2021 were significant years for us, we’ve entered this year ready to give more to our users! We’re delighted to share we have raised $142 million in a Series D funding round! So what does that mean for you exactly? Over the past few months, our team has been working hard to build custom mapping for metrics, an advanced tracing UI, and more into our platform. The world is our oyster, and we can’t wait for you to see what else we have planned!
When I talk with Splunk customers, their challenges sometimes sound like trying to find a needle in a stack of needles. Feel the same way? The answers you need are out there, hidden in your data. Our job is to help you find them. Securing your networks, keeping them up and running and maximizing efficiency are key priorities. You also face the challenges of speeding up development and driving innovation to stay competitive.
You may have previously heard about OpenTelemetry (also known as OTel) if you have looked into improved ways of standardising different data types. In this article, we’ll delve into the key things you need to know about OpenTelemetry and how this unified standard may become the future of how logs, metrics, events and traces are all handled.
As organisations increasingly send their logs to one service, their metrics to another and their traces to a third location, they remain unable to gain a unified view across all of their data types. This is because as multiple tools are used to achieve similar goals for different data types the issue of tool sprawl quickly arises.
In the late 1960s, there was a rock band called Ten Years After and I liked the name the first I heard about them. I wanted to use "Splunk and the Financial Services Industry: Ten Years After" as the title of this blog entry, but it’s been more than ten years since I wrote the first Splunk Blogs entry on Splunk and the Financial Services Industry. As you can tell, a lot has changed since then and more than a decade is an internet lifetime in technology.
Here at Grafana Labs, we’re always looking for ways to provide our customers with a choice of platforms where they can run Grafana Enterprise Logs (GEL). As part of that mission, we’re pleased to announce that we’ve added Red Hat OpenShift 4.x support to GEL. GEL, as you may know, is a leading enterprise logs solution.
In this tutorial, we will go through a working example of a NestJS application auto-instrumented with OpenTelemetry. In our example we will use a simple application that outputs “Hello World!” when we call it in the browser. We will instrument this application with OpenTelemetry’s Node.js client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.
