Operations | Monitoring | ITSM | DevOps | Cloud

It’s been a while since the last update on “What’s New” series, so I will try and keep it short yet informative. Stay tuned for upcoming content on anomaly detection.

We recently sat down with James Phillips, Senior IT Leader, to talk about test data management (TDM) and the growing attention it’s getting from the senior IT leaders. 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.

We are excited to announce the release of SSIS components Data Flow Components version 4.0, an update that delivers expanded compatibility with the latest development tools and database platforms. Version 4.0 introduces full support for Visual Studio 2026 and Visual Studio 2026 Insiders, ensuring developers can seamlessly adopt Microsoft’s newest IDE while continuing to work with familiar workflows.

In PostgreSQL, the EXPLAIN ANALYZE statement gives you a detailed report of what actually happens when you execute a query. This kind of information is important for troubleshooting slow queries, but using EXPLAIN ANALYZE to collect this data is often challenging in a production environment. Datadog Database Monitoring now supports automatic collection of EXPLAIN ANALYZE plans for PostgreSQL, enabling you to easily capture execution details that help you troubleshoot slow queries.

Tempo 2.10 has arrived, delivering TraceQL enhancements, improved cardinality management for the metrics-generator, vParquet5, and more. You can continue reading and check out the video below to learn more about these and other new features. The Tempo 2.10 release notes and changelog provide more in-depth details and include all of the changes that came with this release.

DataReader and DataSet are two significant data access models that can greatly impact the performance, scalability, and responsiveness of your.NET application. The connected model, powered by DataReader, keeps a live connection open and streams data forward-only to maximize speed and minimize memory usage. The disconnected model, implemented through DataSet, takes the opposite approach. It loads data into memory so you can edit and reuse it without constant database interaction.