Operations | Monitoring | ITSM | DevOps | Cloud

At Datadog, we want our developers to become better at using AI tools with the end goal of building quality software, faster, that generates real value. This includes not only the products and features that our customers use, but also the internal tools that help keep our workflows running smoothly behind the scenes.

The World Cup may be the most-watched event in media history — so what does it look like from inside the network? We dug into ISP traffic data to reveal how Fox Sports peaks during US games, why second halves usually win, and how traffic flows shift for entire nations like Brazil and Iran when their team takes the field.

Summary: Q2 was about giving teams more leverage with less overhead. Between April and June 2026, releases across Telegraf, InfluxDB 3, and InfluxDB 3 Explorer focused on reducing manual work and putting more control directly in their hands as they scale. Telegraf Enterprise reached general availability, giving teams a centralized way to manage, monitor, and support tens of thousands of Telegraf agents.

How do we keep our Sonicwall certificates up to date as certificate lifetimes get shorter? We’re already at 200 day certs with 100 then 47 day certificates coming soon. A certificate you used to touch once every year now needs replacing up to twelve times a year. Doing this by hand is out of the question, no one has the time. Even if they did, the frequent updates is just asking for mistakes. Luckily, this can be automated using the SonicOS API.

For the last two years, enterprise AI strategy has largely focused on one thing: adoption. Organizations encouraged employees to experiment with ChatGPT, Claude, Copilot, Gemini, and dozens of emerging AI tools in the hope that productivity gains would naturally follow. CIOs approved pilots, departments launched AI task forces, and leaders pushed teams to integrate AI into everyday work as quickly as possible. But the enterprise AI conversation is beginning to change.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s Rundeck/RBA 6.0 recently announced in GA builds towards this vision.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how AI Orchestrations builds towards this vision. “We should automate this.” Sound familiar? For many operations teams, that sentence never becomes action. Building event orchestration rules demands deep platform expertise, time no one has, and the ability to spot which patterns in your data actually matter.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey toward autonomous operations. Read on to learn about the PagerDuty agent app in GitHub (Early Access) and how it builds toward this vision. How many tabs do you have open right now? And how many more do you open the moment an incident hits? Context switching during incident response is one of the most persistent sources of toil in engineering.

The Agile software development lifecycle was designed to surface problems early, with short sprints, iterative testing, and continuous integration built on the premise that faster feedback loops produce better software. AI coding tools have changed the velocity equation across every phase of that loop, but the phases designed to catch failures are struggling to keep up because build speed and validation capacity have not accelerated at the same rate, and the gap between them is widening with every sprint.

Norsk Tipping is Norway’s state-owned gaming operator, running 2,500 to 3,000 production releases a year across iOS, Android, web and backend systems. Like every regulated organisation at scale, the platform team has to hold two things in tension: maintain strict deployment controls that stand up to audit, and keep the path to production open so that 100 engineers can ship safely.