The latest version of the Splunk Operator builds upon the release we made last year with a whole host of new features and fixes. We like Kubernetes for Splunk since it allows us to automate away a lot of the Splunk Administrative toil needed to set up and run distributed environments. It also brings a resiliency and ease of scale to our heavy-lifting components like Search Heads and Indexer Clusters.
Picture this: Your on-call engineer gets an alert at 2 AM about a system outage, which requires the entire team to work hours into the night. Even worse, your engineering team has no context of where the issue lies because your systems are too distributed. Solving the problem requires them to have data from resources that live in another timezone and aren’t responsive. All the while, your customers cannot access or interact with your application, which, as you can imagine, is damaging.
Two recent studies conducted by Nucleus Research, focused on how a global telecommunications provider, and multi-line insurance company realized quantified business value through Elastic. The companies that were studied saw great levels of satisfaction from deploying Elastic Cloud. Through their adoption they were able to increase the maturity of their tech stack and circumvent prior limitations in scalability.
This is Part One of a series of blogs around troubleshooting Cribl Stream. Part One will focus on identifying and troubleshooting issues with Sources and Destinations in Stream. I will cover some of the common problems that users face and how you can work through them and find the root cause.
ZScaler delivers a suite of well-regarded products for helping IT securely move from network infrastructure to the cloud, using principles of zero trust. According to their website, they have 5,600+ customers and process 200B+ daily transactions.
Cybersecurity can often seem intimidating for IT teams. After all, things like “threat hunting,” “red teaming,” and “blue teaming” are not used in IT operations. On the other hand, just because these words are terms of art doesn’t mean that they’re activities you don’t do already. You’re probably already using log data as part of your IT operations incident response.
Ah, good question! TL;DR: Trace instead of log. Traces show connection, performance, concurrency, and causality. Logs are the original observability, right? Back in the day, I did all my debugging with `printf.` Sometimes I still write `console.log(“JESS WAS HERE”)` to see that my code ran. That’s instrumentation, technically. What if I emitted a “JESS WAS HERE” span instead? What’s so great about a span in a trace? Yeah, and so do logs in any decent framework.
As we know that many of our users are system administrators, network and software engineers as well as cloud infrastructure leaders who use Linux primarily, we've created a helpful cheat sheet as a reference guide to help you with understanding the most common Linux commands. Feel free to save the sheet below and share it with any team members that you think would appreciate learning some of the most essential commands for Linux.
Greetings Criblers! We’re introducing a new series by the Criblers, for the Criblers called How I Stream! Each month (maybe more frequently–you, too can be featured, share your insights here), we’ll share a quick profile from one of our community GOATS (Greatest of All Time Streamers) sharing use cases and lessons learned. Our first guest goes by Hobbit in the community.
If you’re involved in IT, you’ve likely come across the word “Kubernetes.” It’s a Greek word that means “boat.” It’s one of the most exciting developments in cloud-native hosting in years. Kubernetes has unlocked a new universe of reliability, scalability, and observability, changing how organizations behave and redefining what’s possible. But what exactly is it?
