292 updates from Datadog and Grafana Labs in the last 30 days. We read them all so you don't have to.
Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
Grafana Labs helps users get the most out of Grafana, enabling them to take control of their unified monitoring and avoid vendor lock in and the spiraling costs of closed solutions.
Datadog positions itself as a comprehensive monitoring platform designed to help IT, development, and operations teams derive actionable insights from large-scale application data, emphasizing integration and built-in analytics. Grafana Labs focuses on empowering users with open-source tools to create unified monitoring experiences, prioritizing flexibility, vendor independence, and cost control. While Datadog offers a closed, all-in-one solution with proprietary data collection and analysis, Grafana emphasizes open-source customization and interoperability with external data sources, appealing to users seeking avoid vendor lock-in and tailored monitoring setups.
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Weekly updates per vendor, last 12 weeks.
Page-type activity over the last 30 days. Brighter cells = more updates.
DatadogGrafana LabsDatadog focused heavily on its DASH2026 event, announcing a broad suite of AI-driven capabilities including the Bits AI Agent Suite for automated workflows, Bits Code for automated remediation, and AI Guard for agent security. Their updates emphasize autonomous operations and unified observability across the development lifecycle. In contrast, Grafana Labs released targeted product enhancements, including upgraded Assistant Investigations for auto-remediation, AI Observability for monitoring agent execution flows, and new frontend observability tools. While Datadog's activity centered on large-scale platform expansions and ecosystem partnerships, Grafana Labs focused on specific feature updates for k6 synthetic monitoring, dashboard granularity, and integration improvements for MongoDB and Kubernetes.
Last updates we detected for each vendor.
Datadog amplified a post by Eugene Kovnatsky discussing the unique observability challenges faced by live media streaming services during sudden traffic spikes, such as those occurring during a World Cup match.
Datadog shared insights on the massive scale of live media infrastructure required to support major global sporting events with billions of viewers.
Datadog shared a personal story from Namit D'Cruz about the challenges and rewards of building the company's enterprise business in India from scratch.
Datadog shared a case study demonstrating how AccuWeather used Datadog Data Observability to reduce false alarms by 50% and cut incident response times from 90 minutes to just minutes.
Datadog is hosting a live recap of its flagship #DASH2026 conference on June 25th. The session will cover how modern teams use AI to transform software building, operations, and security.
Grafana Labs provides documentation explaining how to create, manage, and visualize data using Grafana dashboards. The guide covers data source integration, panel customization, and sharing capabilities for various monitoring needs.
Grafana Labs released version 5.24.0 of the Grafana Operator to fix a medium-severity path traversal and privilege escalation vulnerability. The update includes a workaround using ValidatingAdmissionPolicy to secure Kubernetes service accou
Grafana Labs is removing filters from the resource permissions list in Grafana Cloud. This change ensures that administrators can see a complete list of all users and teams with access to a resource, providing full visibility into permissio
Grafana Labs has made section-level variables for rows and tabs generally available. This feature allows users to apply independent filters to specific rows or tabs within a single dashboard, enabling more granular control over multi-servic
Grafana Labs showcases how DataSnipper utilized Grafana Cloud to scale observability during its transition from a desktop-first product to a SaaS platform. The migration enabled the SRE team to unify metrics, logs, and traces, significantly
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