Operations | Monitoring | ITSM | DevOps | Cloud

Monitor Oracle NetSuite performance with Continuous AI's offering in the Datadog Marketplace

Oracle NetSuite is a fully managed business management platform that helps organizations centralize and automate their core business functions, including enterprise resource planning (ERP), customer relationship management (CRM), and e-commerce. NetSuite customers have the flexibility to customize their business processes and operational workflows using SuiteScript, a programming language that provides application-level scripting capabilities.

From data to action: Optimize Core Web Vitals and more with Datadog RUM

Delivering seamless user experiences requires deep visibility into web performance. Core Web Vitals—Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS)—serve as critical benchmarks for assessing site health. However, many teams struggle to turn these metrics into actionable insights that can help resolve performance problems.

Gain key insights into user experiences faster with Datadog Synthetic Monitoring

In today’s fast-paced digital landscape, customers expect seamless and reliable user experiences and have little tolerance for poor performance or downtime. In order to avoid the costs to revenue and reputation that can come from poor customer experiences, organizations across all industries are increasingly prioritizing digital experience monitoring (DEM), the practice of monitoring how end users interact with business-critical applications in order to understand and optimize user journeys.

Leverage Cloudflare logs for cost optimization, troubleshooting, and security

Cloudflare is a content delivery network (CDN) that helps businesses accelerate, protect, and optimize their websites, applications, and APIs. It acts as a reverse proxy, sitting between users and a website’s origin server to provide DDoS protection, web application firewall (WAF), CDN caching, and load balancing.

Spotlight on Reference Tables Add Custom Metadata in Datadog! #Datadog #TMiDD #TechTips

This month we’re putting the spotlight on Reference Tables, which is now generally available and enables teams to add custom metadata to their existing Datadog telemetry. Check out the link in our bio to watch the new episode of This Month in Datadog.

Simplify multi-cloud cost management with FOCUS and Datadog

When your cloud environment spans multiple cloud service providers (CSPs) and SaaS providers, it can be challenging to collect cost and usage data in a way that gives you complete visibility. Each provider formats its data according to a unique billing model, and these inconsistencies can leave you with fragmented information about your total cloud spend.

This Month in Datadog: Reference Tables is generally available, Attacker Clustering, and more

Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. To learn more about Datadog and start a free 14-day trial, visit Cloud Monitoring as a Service | Datadog.

This Month in Datadog - March 2025

On the March episode of This Month in Datadog, Jeremy Garcia (VP of Technical Community and Open Source) covers Attacker Clustering, Auto Test Retries, and new Observability Pipelines features, including keyword dictionaries and several integrations. Later in the episode, Jinwu Liu (Product Manager) spotlights Reference Tables, which is now generally available, and Yash Kumar (Product Lead, Cloud SIEM) shows how these tables can be used to add context to detection rules in Cloud SIEM.

Monitor the performance of queues and topics with Azure Service Bus

Azure Service Bus is a fully managed enterprise message broker that enables asynchronous messaging between distributed applications. It is designed to decouple application components, allowing them to communicate reliably, securely, and at scale. With Datadog’s Azure Service Bus integration, you can.

Enrich your existing Datadog telemetry with custom metadata using Reference Tables

As your applications scale and generate more telemetry, it becomes increasingly difficult to sift through the data and analyze it against cost, business functions, and security measures. Logs, events, and other telemetry on their own may not include enough meaningful context or readable details, leading to slower troubleshooting, inefficient business processes, and higher costs.