The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
Logging has been around since programming began. We use logs to debug issues and understand how software works at the code level. After logging and debuggers, profilers are a dev’s best friend when writing code and may run in production with limits to reduce overhead. As we distributed architectures — making systems more complex — centralized log aggregation was soon necessary. At that point, we had to analyze this data. Hence, log analytics technologies were born.
The advancement of technology has brought with it the increased adoption of complex IT systems. Every company operates and maintains a gigantic amount of data that is essential to run their business. The server capacity required to handle this amount of data is huge, and the centralized servers are almost kept off-site in remote locations. Server virtualization technologies have also gained popularity since it helps to address data storage limitations and data security concerns.
Many organizations aspire to become true, high-functioning DevOps shops, but it can be hard to know where you stand. According to DevOps Research and Assessment, or DORA, you can prioritize just four metrics to measure the effectiveness of your DevOps organization—two to measure speed, and two to measure stability.
