Operations | Monitoring | ITSM | DevOps | Cloud

Observability first emerged as a focal point of interest in the DevOps community in the 2017 time frame. Aware that business was demanding highly adaptable digital environments, DevOps professionals realised that high adaptability required a new approach to IT architecture. Whereas historically, digital stacks were monolithic or, at best, coarsely grained, the new stacks would have to be highly modular, dynamic, ephemeral at the component level, and spread over multiple cloud-based services.

With the rapid adoption of cloud, distributed systems and microservices are standard, resulting in increasingly complex environments. Once straightforward troubleshooting workflows have become chaotic, frustrating, and time-consuming. When something breaks, multiple teams are called to the table to prove they’re “not it”; each with their singular view of the problem.

What do the gauges on your car, the jumbotron at a stadium, and Splunk Observability Cloud all have in common? They all show you the important information to know how something is performing. We all know what to look for in the first two examples.

Empty spaces, what are we searching for? Abandon queries, but do you know the score? On and on, Does anybody know what we are looking for? … Inspired by “The Show Must Go On”, Queen. Since we launched Cribl Search back in late 2022, we’ve been hard at work on adding features and functionality that continue to empower data engineers to do more with their data without needing to collect it first.

At Cribl, we give the people what they want. And what they want is to keep their data close to their sources and destinations. The less data has to travel, the better — lower latency and fewer security risks. This commitment to data locality is even more pronounced among our valued customers in the EMEA region, who are enthusiastically embracing cloud-first strategies.

Organizations saw a 243% ROI and $1.2 million in savings over three years In today’s complex and distributed IT environments, traditional monitoring falls short. Legacy tools often provide limited visibility across an organization’s tech stack and often at a high cost, resulting in selective monitoring. Many companies are therefore realizing the need for true, affordable end-to-end observability, which eliminates blind spots and improves visibility across their ecosystem.

Shorten your time to insights by creating aggregations, visualizations, and alerts directly from Discover with ES|QL.

Simply put, value stream management (VSM) is the practice of measuring and improving the flow of business value created by an organization’s software delivery efforts.By monitoring the software delivery life cycle end-to-end, organizations can better identify processes that add value and eliminate those that create waste to optimize the flow of work. Ultimately, this enables teams to move away from activities that don’t directly contribute to customer value and focus more on those that do.

Terry Mulligan, is a Splunk consultant with Discovered Intelligence (and Notre Dame’s biggest fan)— a data intelligence services and solutions provider that specializes in data observability and security platforms. He shares what Cribl has brought to the table for his organization and his clients, and how it’s changed their processes and the role of the Splunk data engineer.