Operations | Monitoring | ITSM | DevOps | Cloud

See how you can ensure trust across the data life cycle in February’s episode of This Month in Datadog. Join us for a spotlight of Datadog Data Observability, which enables you to detect data quality and pipeline issues early, as well as remediate those issues with end-to-end lineage. Plus, we cover: Protecting agentic AI applications from real-time threats with Datadog AI Guard Staying up to date and reducing steps to collaborate with five new Incident Management releases Releasing software with confidence using Datadog Feature Flags.

SREs are famously skeptical of AI — so how do you convince them to trust agents in production? In this episode of Grafana’s Big Tent, Tom Wilkie talks with Spiros Xanthos (Resolve AI), Manoj Acharya (Grafana Labs), and Cyril Tovena (Grafana Assistant team) about agent-first observability. They unpack knowledge graphs, LLM reasoning, autonomous debugging, pricing models, and the “Claude Code moment” for observability. Is autonomous production ops closer than we think?

SolarWinds Evangelist Chrystal Taylor introduces the new routing insights feature in Observability Self-Hosted 2026.1. This first phase enhancement enriches routing table information with detailed context, including forwarding interface names, VRF data, next hop IPs, and timestamps. The update unifies BGP, OSPF, and EIGRP neighbors in a single dashboard, providing visibility into peer identity, flap counts, health status, and admin states.

In this video, SolarWinds Evangelist Chrystal Taylor introduces server configuration comparisons, a new feature in Observability Self-Hosted 2026.1 and Server Configuration Monitor 2026.1. The key highlight is the ability to compare server configurations side by side, enabling users to identify differences in configuration files between nodes or against a defined ideal state. This new functionality aims to help users monitor configuration drift.

SolarWinds Evangelist Chrystal Taylor demonstrates the new cloud entity support features in Observability Self-Hosted version 2026.1. The update adds monitoring capabilities for MySQL and PostgreSQL databases on Google Cloud Platform, GCP load balancers, Azure functions, AWS Elastic Kubernetes Service, and AWS Lambda functions. She provides a guided walkthrough of the dashboard interface, showing how users can monitor various metrics including database performance, network traffic, latency, function execution counts, system usage, and costs across different cloud platforms.

Every error tells a story — and Uptrace helps you see the full picture. In this tutorial, you’ll learn how to use Uptrace to capture errors, logs, stacktraces, and request context in a single observability platform. See how errors automatically link to traces, understand exactly what happened, and debug issues faster with rich attributes, user data, and performance impact. What you’ll learn: Understand not just *what broke*, but *who it affected and why* — and fix problems with confidence using Uptrace.

Learn how to use *Uptrace* to measure what truly matters in your applications using percentiles, heatmaps, and histograms—then turn that data into dashboards that answer questions before they’re even asked. In this tutorial, you’ll discover how to: Whether you’re setting up observability for the first time or replacing expensive monitoring tools, this guide shows how Uptrace helps you understand performance, reliability, and user experience — all in one place.

Stop guessing where requests slow down. With Uptrace, you can follow any request across your entire system and instantly see performance bottlenecks, errors, and latency sources. This video covers: Build real observability, not just dashboards.

Learn how to monitor application metrics, track errors, and configure real-time alert notifications in Uptrace. In this step-by-step tutorial, you will: Perfect for developers, DevOps engineers, and teams looking for simple, powerful observability.

What does observability look like when you’re responsible for customers at scale? In this episode of Heartbeat Behind the Metrics, Muraleedharan Sadhasivam, Head of Customer Success, talks about his 15-year journey at ManageEngine and the perspective you only get from being close to customers every day. He shares why custom dashboards matter so much, and why AppLogs is a feature he wishes more users explored to complete the MELT story. From querying logs to turning them into alerts and dashboards, he explains how real insights start when data is brought together.

Try it open source on your system. Learn how tools can make gathering and making sense of observability data instant and painless with co-founder Peter Zaitsev.

This conversation with Grafana Labs engineers, Mat Ryer, Cyril Tovena and Sven Großmann, dives deep into the engineering behind Grafana Assistant, exploring how agentic AI is transforming the observability landscape. From hackathon origins to sophisticated backend agents, the team shares candid lessons on building, scaling, and refining AI tools for engineers.

On release days, we wear teal, y'all! Check out the fun and exciting new features from Cribl releases on a monthly (:fingers-crossed:) basis. Here's what's new in Cribl 4.16.

Learn how autonomous agents are using real-time observability telemetry data to diagnose, fix and verify their own work.