Operations | Monitoring | ITSM | DevOps | Cloud

Modern systems generate huge volumes of time series data. Advances in hardware and edge instrumentation enable sensors and applications to capture new values every second—or faster—which makes high-frequency measurement easy and affordable. When applied effectively, this steady flow of data reveals early warning signs, highlights subtle performance shifts, and helps teams understand how systems behave in real-time.

Today, we’re excited to announce our expanded partnership with Amazon, bringing together the power of Amazon Kiro, Amazon Q Developer, and Harness SaaS on AWS to revolutionize how your team builds, troubleshoots, secures, and deploys software. This collaboration is designed to deliver a seamless, intelligent, and scalable software delivery experience for all AWS customers.

In 2026, digital performance is more critical than ever. Users expect web applications to load instantly, respond flawlessly, and support complex interactions without delay. For DevOps teams, this means browser monitoring is no longer optional—it’s a foundational capability for ensuring availability, speed, and reliability across modern web experiences.

Looking for reliable Heroku monitoring in 2026? Start with the metrics that matter, pair Heroku’s built-ins with the right add-ons, and add alerts that catch issues before users do.

We are on the ground with AWS and announcing innovations that give customers more powerful AI agents for incident management. These new and improved integrations bring PagerDuty context into the AWS ecosystem for faster resolution and more connected data across the business. And, with our new competency, we take this a step further by codifying these best practices into our joint customers’ day-to-day operations. Announced today, here are some of the highlights.

Ten years ago, Datadog was a single-product company focused on breaking down the silos between dev and ops. As the shift towards the cloud accelerated and organizations transitioned to the new DevOps model, we set out to develop an observability platform that would enable these teams to safely scale faster and answer the essential questions about their services: are they available, secure, compliant, performant, and cost-efficient?

Running Kubernetes at scale almost always means paying for more compute than you need. To protect reliability, platform and application teams typically overprovision nodes early in development and keep scaling up as they add features and workloads. They are often reluctant to move to smaller or different instance types without a clear picture of how those changes will affect performance or availability. The result is a fleet of underutilized nodes that silently inflate your cloud bill.

For many engineering teams, an incident is a chaotic, all-hands-on-deck event. Once the incident is resolved, everyone returns to their regular work and the valuable lessons from the incident are often lost. The result is a cycle of repeated failures and engineer burnout, where incidents are something to be survived, not learned from. At Cortex, our mission is to help engineering organizations build a culture of continuous improvement.

Somewhere along the line, enterprises convinced themselves that buying the right “knowledge management platform” would finally fix all of the chaos. Once the tool went in, engineers would magically find the right troubleshooting steps, documentation would stay current, and institutional knowledge would move cleanly across teams without anyone having to chase it down.

When technology slows, everything does. Guests wait to check in. Travelers queue at kiosks. Shoppers refresh the page, hoping the payment goes through. Every second of downtime costs companies millions and frustrates millions more. LogicMonitor and Catchpoint have been solving that problem from different sides: one focused on the systems and infrastructure that keep businesses running, the other on the experiences and performance that users actually feel.