Operations | Monitoring | ITSM | DevOps | Cloud

Modern product teams ship features constantly. Every change—whether it’s a new onboarding flow, pricing tweak, or UI adjustment—raises the same question: Did this improve the product? AI has changed the stakes entirely: As release cycles accelerate and code generation scales across every team, the volume of changes has outpaced most teams’ ability to measure their true value.

It’s an all too common scenario: You get paged for some queries timing out, but when you investigate, the database performance looks unchanged. Something must have changed, though. If the database doesn’t look overloaded, where are these timeouts coming from? The answer often lies outside the database itself. Round trip query latency includes every hop between your application and the database, including connection pools, load balancers, and proxies.

Caching is critical to modern apps, helping you serve data more quickly and improve your app’s overall performance. Effective caches can result in better Core Web Vitals (CWV), improved search visibility, and a smoother user experience.

Nutanix is a hyperconverged infrastructure (HCI) platform that combines compute, storage, and virtualization into a single software-defined stack. By collapsing traditional infrastructure tiers into one platform, Nutanix simplifies provisioning and operations for virtualized workloads. Clusters are managed through Prism Central, which provides visibility into health, performance, capacity, and operational activity across hosts and VMs.

As AI-powered products and services become central to how organizations operate, the need for responsible AI governance has never been greater. Customers, partners, and regulators are seeking assurance that AI systems are built, managed, and monitored responsibly and effectively. Datadog is committed to the responsible use of AI, both in how we build our products and in how we help customers observe their AI workloads.

As organizations adopt AI-assisted development and increase their release velocity, they are not only generating more code but also finding more vulnerabilities from static analysis. The traditional remediation workflow of manually triaging issues, creating tickets, and opening individual pull requests (PRs) cannot keep pace. Fixing tens of thousands of vulnerabilities one by one is not a viable remediation strategy.

A host map is a visual representation of your infrastructure that displays hosts and related resources such as clusters, pods, and containers in a single, interactive view. We introduced the Datadog Host Map more than a decade ago to help you “know thy infrastructure” and answer critical questions: Does everything look healthy? Has anything changed? Does the shape of my environment match what I expect?

From point-of-sale (POS) terminals to cloud-based applications and mobile devices, reliable connectivity is critical to business operations. Even brief disruptions can negatively impact user experiences, resulting in failed transactions, delayed application responses, or repeated attempts to reconnect. Juniper Mist is an AI-powered networking platform that provides insight into wireless environments, including access point performance and radio frequency health.

Many organizations rely on Oracle Fusion Cloud Applications to run core business workflows across finance, HR, and supply chain operations. Because these SaaS-based applications run on Oracle Cloud Infrastructure (OCI), engineering teams have limited visibility into their performance. Without direct access to the underlying stack, they often lack the signals needed to detect regressions or investigate degraded user experience.

Kubernetes environments generate a constant stream of signals across clusters, nodes, pods, and workloads. For teams that have standardized on OpenTelemetry (OTel), maintaining ownership of that data is critical. But in practice, many observability platforms require translation into vendor-specific data formats, leading to fragmented product experiences, blank dashboards, and uncertainty about data integrity.