We all have been there! Getting the largest metrics plan available, turning on real-time monitoring, and…. You know what happens next… BIG BILL! With the explosion of telemetry from microservices, containers, and cloud stacks, engineering teams often have to choose between data and budget. To help our Splunk champions, we are introducing Archive Metrics to make storing data up to ten times cheaper.

During the early periods of cloud computing, most organizations used single-location data centers. These single-location data centers often faced higher risks of downtime and service disruption due to localized disasters or hardware failures. As a solution to these problems, cloud services like AWS introduced the concept of availability zones. This introduction was an important milestone in the evolution of cloud computing, as it facilitated high availability through geographic distribution.

To buy or to build... that is the question businesses must ask when deciding to buy off-the-shelf software or create custom software to satisfy their business needs. Deciding whether to buy off-the-shelf software or create custom software is a lot like choosing between a ready-made meal and cooking a meal from scratch. It's a big decision for any business (or hungry person). Let's imagine we're planning dinner...

Splunk gives you amazing tools to analyze system data and make business-critical decisions, react to issues, and even proactively address future problems. And since it is so good at those things, it’s not surprising that there are myriad tools to help you reflexively analyze your own Splunk deployment.

Data analysis is crucial in today's businesses and organizations. With the increasing amount of data being created at 328.77 million terabytes of data per day, and them being readily available to most businesses, having efficient tools that can help analyze and interpret this data effectively is essential. In this article, we will discuss the top 9 best data analysis tools currently used in the market today.

Time series data is becoming more prevalent across many industries. Indeed, it is no longer limited to financial data. As the need to handle time-stamped data increases, the demand for specialized databases to handle this type of data has also grown. The solution: Time series databases. In this introduction guide, we'll explain all the basics you need to know about time series databases, including what they are, how they work and are applied, and some of their benefits.