You may have heard of test data management (TDM). It’s part of the software delivery process – some would say a crucial part, involving the creation, management, and maintenance of environments for software development and testing. By provisioning fresh, production-like data, it allows developers to test their proposed changes early, thoroughly, and repeatedly with the right test data, when they need it and where they need it.

We recently sat down with James Phillips, CIO at Rev.io, to talk about test data management (TDM) and the growing attention it’s getting from the C-suite. It’s been prompted by the recognition that provisioning test and development environments with realistic production-like data improves the quality of code being developed, reduces errors, and deliver new features to customers faster.

Today we’re happy to announce our new VictoriaMetrics Anomaly Detection solution, which harnesses machine learning to make database alerts more relevant, accurate and actionable for enterprise customers. VictoriaMetrics Anomaly Detection lightens the load on overworked data engineers, focusing their scarce resources on the alerts that matter most to their organization.

Today, many companies generate and store huge amounts of data. To give you an idea, decades ago, the size of the Internet was measured in Terabytes (TB) and now it is measured in Zettabytes (ZB). Relational databases were designed to meet the storage and information management needs of the time. Today we have a new scenario where social networks, IoT devices and Edge Computing generate millions of unstructured and highly variable data.