Operations | Monitoring | ITSM | DevOps | Cloud

Digital Employee Experience (DEX): why isolated technical metrics are no longer enough

Digital transformation and remote work have made the user’s experience with IT a core operational requirement. Many organizations still measure IT success through traditional metrics such as response time, system availability, and the number of tickets resolved. These indicators, while useful, hide a more complex reality. A server can be 99,9% available and yet an employee may still lose 30 minutes per day due to a slow application or an unstable connection.

WHOIS & RDAP Domain Lookup & Expiry Check

In this video, we’ll walk you through how to set up and configure your Whois and RDAP Domain Lookup & Expiry Checks in Uptime.com. Learn how to monitor and receive alerts before your domain expires, and protect your registration information from unauthorized modifications. We cover step-by-step instructions for setting up checks through the Uptime.com UI and via API.

We Built a Better DNS Propagation Checker. Here's What Makes It Different.

Today we are launching the DNS Spy DNS Propagation Checker. It is free. It works on any domain. It shows you what is happening in more places, in more detail, and faster than the tools you have been using. You can try it right now: dnsspy.io/dns-tools/dns-propagation-checker.

Ameet Talwalkar on Building the AI Research Lab

"We're doing cutting-edge AI, focused on real translational impact: getting our research over the wall and into production." Ameet Talwalkar, Datadog's Chief Scientist, shares what it took to build the AI Research Lab from the ground up — and what makes DAIR different from traditional research teams. At Datadog, research ships. Recent work from the lab includes Toto 2.0, open-weights time series forecasting models ranked on leading benchmarks, and ARFBench, a new benchmark for evaluating AI on real incident data.

Instant Java Client SDK, no spec required!

Learn how to generate a client SDK for a production service when you have no documentation, no OpenAPI spec, and no remaining team knowledge of the original Ruby code. This demo shows you how to capture real production data from a running app and transform it into a functional Java client library in minutes. Visit proxymock.io OR speedscale.com to learn more.

The Case for VM and Container Consolidation in 2026

Two platforms, two teams, two procurement relationships, all doing one job. There’s a reason it ended up this way. There isn’t a reason it has to stay this way. Ask anyone at a typical enterprise why the VM platform and the container platform are separate, and they’ll give you a sensible answer. The VM estate has been there for fifteen years. It runs the workloads the business depends on.

Explore for Spans: One View with Infinite Depth

It’s 20 minutes into a P0 incident, and you have already switched between four different tools, re-authenticated twice, and translated queries across three incompatible syntax languages. The root cause you are searching for. Well, that is still out there somewhere. The reality of investigative latency is that most engineering teams face navigation problems, not data problems. During high-pressure incidents, teams lose cognitive momentum due to context switching between disconnected telemetry silos.

Search Azure Blob data in-place with BYOS for Cribl Lake

See how Bring Your Own Storage (BYOS) in Cribl Lake allows teams to connect directly to Azure Blob Storage and instantly search data in place — without moving, duplicating, or rehydrating telemetry. In this demo, Cribl Product Manager Risk Salsa walks through setup, dataset creation, and how to run fast investigations across your Azure-hosted data using Cribl Search.

AI Might Break Open Source Differently Than You Think

AI coding agents may not replace open source libraries overnight. But Adam Arellano, Field CTO at Harness, thinks models like Mythos could expose a bigger problem: finding bugs, vulnerabilities, and edge cases faster than maintainers can keep up. That might be the real threat to tools and libraries.

Building a Defensible AI Compliance Framework

Organizations have moved past theoretical conversations about AI adoption. Models, agents, and autonomous workflows are entering production environments. Business leaders are optimistic about potential gains in efficiency, decision support, and operational scale. Yet beneath this momentum, compliance and risk teams feel a different pressure.