Operations | Monitoring | ITSM | DevOps | Cloud

APIs power everything. From login flows to checkout systems to internal microservice communication. But as teams scale, so does the confusion around the terminology: HTTP API vs REST API vs Web API. Many articles treat these as interchangeable, but the differences are real, and they affect reliability, performance, caching behavior, authentication flows, and ultimately how you monitor your endpoints.

We’ve all been there. It’s 2 AM, your phone is buzzing with alerts, and you’re suddenly thrust into an incident war room with a dozen other bleary-eyed engineers. The production environment is on fire, customers are affected, and everyone’s trying to piece together what went wrong. But here’s what makes these moments fascinating from a systems perspective – it’s rarely just one person silently fixing the issue in isolation.

Kentik AI Runbooks are machine-readable instructions that codify tribal knowledge into specific diagnostic workflows. By guiding AI Advisor’s reasoning and tool selection, Runbooks turn alerts into actionable, automated investigations, dramatically accelerating MTTR.

Modern organizations generate more data than ever before. Logs, metrics, traces, and events stream from every application and every physical and virtual layer of infrastructure. Hidden inside this telemetry are pieces of sensitive information that security teams do not expect to see. Social Security numbers, account identifiers, medical details, personal contact information, and other forms of PII can appear in unexpected fields and formats. Static tools cannot keep pace with this volume or variability.

For Grafana Labs, 2025 was a year defined by innovation, growth, and the power of our community. We celebrated the release of Grafana 12 at our 10th annual GrafanaCON event, and marked major milestones across open source projects, including Mimir, k6, Beyla, Faro, and Alloy. It was also a year of taking bold steps forward in how teams interact with their systems and data.

After four days of AWS re:Invent—a 65,000-step marathon that included 60,000 attendees spread across five Las Vegas campuses—and navigating the latest installment of this 13-year-old cloud pilgrimage, we’re all a little dehydrated but significantly wiser. The volume of announcements felt less like a single flood and more like a river branching into three powerful currents. Making sense of this massive technological convergence requires zooming out.

For our last episode of 2025, we’re focusing on Datadog releases announced at AWS re:Invent. Join Jeremy to see how you can manage logs at petabyte scale in your infrastructure, eliminate unneeded costs in Amazon S3 buckets, build agentic workflows, and detect credential leaks. Later in the episode, Scott spotlights how you can connect your AI agents to Datadog tools and context with our MCP Server.

We launched agent monitoring earlier this year, allowing our users to instrument LLM usage and tool calls in their applications. However, we only had Agent Monitoring support for Python and JavaScript. We’ve been working on creating an Agent Monitoring SDK for.NET — specifically for Microsoft.Extensions.AI.Abstractions.

Organizations are struggling with rising operational complexity, fragmented tools, and inconsistent security enforcement as Kubernetes becomes the foundation for modern application platforms. As a result of this complexity and fragmentation, platform teams are increasingly burdened by the need to stitch together separate solutions for networking, network security, and observability.

HTTP/1.1 is a text-based protocol where the message framing is mixed with its semantics, making it easy to parse incorrectly. The boundaries between messages are very weak because there is no clear delimiter between them. Thus, HTTP/1.1 parsers are especially vulnerable to request smuggling attacks.