The last ten years have seen a massive change in how IT operations and development enable business success. From virtualization and cloud computing to continuous delivery, continuous integration, and rapid application development, IT has never been more complex or more critical to creating competitive advantage. To support increasingly Web-Scale IT operations and wide-scale cloud adoption, applications now operate as services.

In the new world of rapid releases, continuous change, and increasingly high user expectations, more organizations are embracing DevOps. One of the primary drivers for adopting DevOps is speed — particularly the reduction of risk at speed. As DevOps seeks to reduce risk and deliver insight at an increasingly faster pace, new tools have emerged in the monitoring space. But these tools alone will not deliver us into the low-risk world of DevOps — not without new and updated thinking.

The exponential growth of machine generated data in recent years has created the need for solutions purpose-built to handle extremely high-frequency telemetry data. This has driven increasingly more organizations to adopt time series databases and address the unique challenges around ingesting, analyzing, and storing massive amounts of time-series data.