Operations | Monitoring | ITSM | DevOps | Cloud

Datadog App Builder is a low-code tool for creating internal apps, making use of a drag-and-drop interface that allows engineering teams to troubleshoot issues, optimize operations, and enable self-service while connecting directly to their Datadog data and permissions. Now, with conversational AI, teams can go from idea to working prototype even faster.

As organizations grow, engineering leaders often need to drive cross-team initiatives such as reducing cloud spend, upgrading runtimes, or strengthening security controls. Tracking this work can quickly become fragmented across spreadsheets, dashboards, and status meetings. Progress is hard to measure, accountability is unclear, and the impact of each effort can be difficult to demonstrate.

Today, many DevOps and security teams operate in a world of complex, hybrid, or multi-vendor environments. As more teams look to avoid lock-in by adopting open standards, OpenTelemetry (OTel) is quickly gaining adoption as the primary open source method for DevOps and security teams to instrument and aggregate their telemetry data. However, OTel alone may lack the advanced processing functions, native volume control rules, and hybrid environment support that large organizations need.

As major incidents like AWS’s October 2025 outage illustrate, modern systems are immensely interconnected. A failure in one can lead to a cascade of downstream problems. In this case, issues with DNS resolution for DynamoDB led to widespread disruptions with other AWS services and, subsequently, thousands of applications and services that rely on that infrastructure.

Building automated workflows that adapt to real-world complexity can be a challenge. As systems scale and scenarios multiply, teams often end up hardcoding endless logic branches just to handle every potential outcome. That’s why we’re introducing Datadog Agent Builder, a powerful new tool that lets you create custom AI agents that are fully hosted by Datadog.

Over the past three decades, Ruby has assumed a pivotal role in the modern web stack and become a fixture in the tool kits of countless DevOps and platform teams. Today, it is a driving force in contemporary application development, testing, automation, and CI/CD. For this blog post, we used data from our always-on continuous profiling of more than 3,000 real-world services from hundreds of organizations to track trends in Ruby usage and performance.

Backstage is a popular open source framework for building internal developer portals (IDPs) used by organizations to aggregate service metadata and create a single source of truth for their software developers. However, data stored in the Backstage Software Catalog can quickly become siloed and inaccessible from monitoring tools such as Datadog.

Cloud object storage powers a wide range of workloads, from AI training datasets to customer-facing media libraries. As your data grows into the petabyte scale, managing storage costs and ensuring reliability requires fine-grained visibility. You need answers to questions like: Which specific teams, services, workloads, or datasets are driving spend? Which data is cold and should be archived? What fixes will have the biggest impact on cost and performance?

Ensuring digital services remain accessible, reliable, and secure is a high priority for any organization operating at scale. For the Department of Veterans Affairs (VA), this focus is central to its mission of providing quality care to veterans, their families, and caregivers. Often described as “the largest IT shop in the United States,” the VA manages 2.7 million pieces of equipment across a vast network of interconnected systems.

Modern engineering teams face competing priorities. Developers are expected to deliver new features faster than ever, but users expect rock-solid reliability with every release. Shipping quickly can feel like you’re gambling with user trust. If you move too fast, you risk outages, but if you move too slowly, innovation stalls.