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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Starlette Is Adding Native OpenTelemetry Tracing. Here's What That Means for Your APM.

If you run Starlette or FastAPI in production with an APM tool, you should keep an eye on PR. It adds native OpenTelemetry HTTP server spans directly into the framework. No external instrumentor, no monkeypatching. Just spans emitted from the router itself. At Scout Monitoring, we instrument Starlette and FastAPI through our Python agent. A change like this touches how every APM tool in the Python ecosystem works with these frameworks, ours included.

Making Machine Data Easier to Onboard, Prepare and Trust with AI-Powered Data Management

Every investigation, detection, dashboard, and AI-assisted workflow depends on one thing: data that teams can trust. But as environments grow more distributed, the data behind those experiences gets harder to manage. New applications, cloud services, security tools, infrastructure, and network devices constantly generate machine data, and each new source can introduce new formats, missing fields, inconsistent mappings, and pipeline changes that require expert attention.

Why You Shouldn't Vibe Code Your Monitoring Tool

Vibe coding made building software feel almost too accessible. You describe what you want, an AI assistant scaffolds it, and a few hours later, something is running. So, it was only a matter of time before developers started asking the obvious question: why should I pay for a monitoring tool when I can just build my own? In all fairness, the DIY instinct is a healthy one. But monitoring is one of the last corners you’d want to cut.

Trace AWS Lambda durable functions with Datadog

AWS Lambda durable functions let you build long-running, multi-step workflows for use cases such as payment processing, order fulfillment, and AI workflows with human approval. A single durable execution can pause for a wait or callback, retry failed work, and resume in a fresh Lambda invocation without losing its state. The strong resilience provided by durable executions, however, creates an observability challenge because each invocation produces its own telemetry data.

Centralize human and agentic work with Datadog Work Management

Teams often track operational work across spreadsheets, Slack threads, Jira tickets, and whatever system generated the original alert or signal. This fragmentation makes it difficult to maintain a consistent record of what needs attention, who or what is addressing the issue, and what has already happened. As AI agents take on more responsibility for investigations, triage, and code changes, the number of handoffs grows, making ownership, status, and history even harder to preserve.

Two ways to measure the cumulative impact of experiments

Mature experimentation programs eventually have to report the cumulative impact of their shipped changes. The request might come as an ROI story for leadership, a revenue update for finance, or a gut check on the quarter’s progress. The tempting shortcut is to sum the observed lift from each winning experiment and report the total. That naive sum almost always overstates the truth because of a statistical artifact called the winner’s curse.

Olly says Hi: Scheduled tasks now report to Slack and email

An agent that only speaks when spoken to is a tool you have to remember to use. Olly has run on a schedule for a while now, working a saved prompt hourly, daily, weekly, or monthly and writing its findings into a chat with its own run history. Those scheduled tasks are now wired into the Coralogix Notification Center, so Olly delivers that output itself, allowing Olly to reach out to Slack or email, out of the box.

From retrieval to agents: 5 takeaways on production architecture for AI agents

How context engineering creates production-ready agentic AI What if the AI strategy you spent the past year building is already being measured by a completely different set of rules? I recently joined Amy Machado, senior research manager at IDC and Jim Malone, senior contributing editor at CIO Marketing Services, for a webinar where we explored how buyer expectations, architectural requirements, and evaluation criteria are shifting as enterprises move from search-driven experiences to agentic AI.

7 Data Integrity Practices Vlaximux Limited Recommends for Platforms Managing High Message Volumes

The assumption that integrity problems are primarily a storage or architecture problem is one of the most expensive misconceptions in platform operations. Vlaximux Limited addresses this directly. Storage and architecture matter - but the majority of integrity failures at high message volumes are operational failures: inconsistent write patterns, missing validation logic, race conditions that only surface under load, and monitoring gaps that allow silent data corruption to compound over weeks before it is detected.

Best Azure monitoring tools: Compare the leading solutions

Microsoft Azure has become one of the most widely adopted cloud platforms for running business applications, databases, containers, analytics workloads, and enterprise services. Modern Azure environments now extend far beyond virtual machines, encompassing services such as Azure Kubernetes Service (AKS), Azure SQL Database, Azure Functions, storage accounts, networking services, and serverless applications.