The more data you have, the harder it becomes to read through it, let alone identify trends or crucial patterns. Couple that with a shortage of time, and the ability not only to visualize but also to communicate with your data becomes paramount.

IT and security teams have several products they use and in turn, have many admins. Some have wide privileges, while others have focused responsibilities for the various tools and touch points in an IT and security data path. Not all admins are members of all tools. But they are all typically part of a larger group bound by an email alias (aka a distribution list).

The emergence of cloud computing. Arguably the biggest change in technology in decades, cloud computing changed how technology would now develop and how businesses and organizations would operate. Indeed, the enormous popularity of cloud services is due precisely to that: you can get different models depending on your operational needs. To properly utilize these cloud service models, you should understand the differences in their functional capabilities and the ideal use cases for each model.

An analyst’s process often involves searching through a given set of data many times, refining the question and analytics performed each time. Cribl Search was originally designed to be stateless – executing each search from the original dataset provider(s) with every execution. However, a new feature has been introduced to allow searching into previous cached results, accelerating the analyst process for certain types of iterative search development.

As environments have become more complex and digital user expectations are at an all-time high, organizations are under more pressure than ever to keep their digital systems secure and reliable. At Splunk, we’ve been hard at work building features that help ITOps and engineering teams thrive amid digital disruptions and build resilient systems.

Wherever end-user success is critical to a business, your website’s functionality needs diligent testing. Therefore web application monitoring is required for many organizations. Conducting web application monitoring can also offer a whole host of additional advantages to organizations. For example, tracking user interactions and behaviors within the web application aids your organization in understanding how users engage with your application.

Rules are excellent when you know precisely what you want to match, typically based on experience. Yet rules only let you observe what you have learned to look for. This is where artificial intelligence (AI) and machine learning (ML) contribute significantly to observability – detecting errors and early warning signs that were previously unobservable. LM Envision supports metric and log anomaly detection. This blog discusses how LM Envision Log Anomalies uncovers previously unknown anomalies.

Data is born at the edge, and the traditional approach is to collect it, then ingest it into one or more systems of analysis — or at least as much as you can afford to. And now the deep dive analysis begins. This might be the perfect solution for some datasets, but what about all the other data being collected on the edge? All the logs, metrics, and state information you seldom (if ever) retrieve?

What do you get when you combine the full power of the network with market-leading security and observability solutions? More customer value and an amazing partner ecosystem. It’s official! Today, with the closing of the acquisition, Splunk became part of Cisco. We’re looking forward to this exciting new chapter of our journey together – and it couldn’t have come at a better time.