Operations | Monitoring | ITSM | DevOps | Cloud

In today’s digital world, the performance of websites and apps has a direct effect on sales, customer satisfaction, and brand reputation. Synthetic performance monitoring provides the proactive intelligence needed to ensure your application is always performing optimally. By simulating real user interactions from global locations before issues affect actual users, you transform from reactive problem-solving to proactive performance excellence.

Modern IT operations live in constant flux. New tools appear, workloads shift to the cloud, architectures fragment, and every device, application, and user brings its own update rhythm. In this state of constant motion, reliability isn’t a static condition; it’s a dynamic discipline. For years, organizations have relied on observability and monitoring to keep systems running. But those tools only tell half the story.

Stop letting tool sprawl drain your engineering resources. Discover how unified automation platforms eliminate configuration drift, close security gaps, and accelerate delivery by consolidating your fragmented DevOps stack.

Is it GitOps or DevOps? Stop choosing between them. Learn how DevOps culture and GitOps workflows work together to automate Kubernetes, eliminate drift, and accelerate software delivery.

Stop choosing between Heroku's simplicity and Kubernetes' power. Learn how to deploy to EKS, GKE, or AKS with a PaaS-like experience—zero YAML required, full control retained.

Microsoft just added Anthropic’s Claude models to Microsoft Foundry. Instead of reading the press release, I ran a mini-benchmark to see how Claude Opus, Sonnet, and Haiku actually perform with real Python tasks and stdin/stdout workflows. The results will surprise you. Opus was the most complete, Haiku the fastest (and chattiest), and instruction-following was the weak point across the board. If you’re thinking about using Claude in production, read this first.

If it feels like your GitHub notifications are a targeted DDoS attack on your brain, you aren't imagining it. Data from GitHub's Octoverse 2025 report shows an average of 43.2 million pull requests merged every month, a 23% jump from just a year ago. This surge in activity coincides with the widespread adoption of AI tools to write code. The temptation to just click "Approve" on a well-formatted AI-written pull request is higher than ever.

You’ve used wildcard certificates for years. It made your life easier. Once a year you’d renew your wildcard certificate, and copy it around to all the servers. It was way too complicated and expensive to get a unique certificate for every system. But now certificate lifetimes are shrinking to 47 days by 2029 and it’s not going to work anymore. You need to automate your certificates. Soon.

One key takeaway from AWS re:Invent 2025 was that a clear gap has emerged between teams still experimenting with AI and those seeing measurable value at scale. In two sessions, PagerDuty customers joined us onstage to explain how they’ve scaled pilots into successful AI operations.