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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Dash 2020: Guide to Datadog’s newest announcements
2020-08-11 · via Datadog | The Monitor blog

Today, at Dash 2020, we unveiled new products and features on the Datadog platform that provide engineering teams with even deeper visibility into their distributed applications and infrastructure. With these additions, Datadog further streamlines every step of your release cycle, from shift-left testing in your CI/CD pipelines to profiling your code in production. We also launched the Datadog mobile app to make on-call easier, Cloud Security Posture Management for enhanced cloud security, and the Marketplace as a collaboration platform for our Partners. Get more details about these developments—and everything else we announced at Dash—in this comprehensive roundup.

Incident Management

Incidents

With Datadog Incident Management, your teams can now use Datadog to easily create incidents and track them from notification to resolution and postmortem. The new Incidents UI provides a central place for reporting and monitoring the status of all your incidents. Tag each incident with important information like severity, customer impact, incident commander, and affected environments. An incident’s timeline automatically reflects any new information or status changes, and anybody can add additional markdown or interactive graphs from inside Datadog. Incidents also works seamlessly with other new features, including our mobile app, which allows on-call engineers to triage alerts on the go, as well as our enhanced Notebooks, which now supports live, multi-user editing for collaborative post-incident reviews. Read our blog post here for more information about how Datadog can help improve your incident response workflow.

Drill down to ongoing SEV-1 and SEV-2 incidents in Datadog Incident Management

Mobile application

The Datadog mobile app is here! Available for both iOS and Android devices, the app provides on-call engineers with instant access to your Datadog dashboards and alerts from anywhere. Now, when you get paged by one of your integrated on-call services like PagerDuty or OpsGenie, the notification contains a link to the relevant in-app Datadog alert, where you’ll see a summary of recent environment activity along with interactive metric graphs for immediate context. For metric correlations and a better view of the health of your services, you can access mobile-native versions of all your dashboards. You can also view related events around the alert to get a fuller picture of why it was triggered, making it easy to quickly triage the problem’s severity and decide your next course of action—all without needing to hop on your laptop.

The Datadog mobile app provides full access to your monitors, making the on-call experience more seamless.

Datadog Cloud SIEM and Cloud Security Posture Management

Datadog Cloud SIEM: Investigation dashboards

With Datadog Cloud SIEM, you can detect potential security issues and threats to your environment in real time. To help you more effectively investigate these issues and the context in which they arise, we are introducing out-of-the-box investigation dashboards for Cloud SIEM. These dashboards visualize security trends in your environment broken down by key entities, such as IP addresses and users. They also include correlated observability data for richer context, such as HTTP activity tied to an IP or user. Use these dashboards to review your security posture at a glance. If you notice an anomaly, like several Security Signals related to a single IP, you can easily filter the dashboard to drill down further into that entity’s behavior.

Use our out-of-the-box investigation dashboards to visualize security trends and review potential issues.

Datadog Cloud SIEM: Threat intelligence enrichment

We are adding threat intelligence enrichment to Datadog Cloud SIEM. Threat intelligence provides valuable external context to ingested log events so you can more quickly triage Security Signals. Threat intelligence identifies whether specific log attributes (e.g., IPs, file hashes, URLs, etc.) may be malicious or benign and provides an associated rationale. For example, if Datadog detects that an IP address associated with a potential attack has also been observed exploiting a known vulnerability, Datadog will flag the resulting Security Signal as malicious so you can prioritize this investigation. Conversely, if the IP is known to be benign, it is likely a scanner gathering intelligence (e.g., shodan.io), and any associated Security Signal can be safely ignored, reducing alert fatigue. Datadog maintains and updates threat intelligence feeds curated by trusted providers, so logs are enriched with up-to-date and accurate context.

Cloud Security Posture Management

Back in April, we announced Datadog Cloud SIEM, which lets you detect and track security threats across your infrastructure in real-time, giving development, operations, and security teams the insights they need to secure your environment. Now, with the release of Datadog Cloud Security Posture Management (CSPM), we are helping you to continuously monitor production environments for misconfigurations and maintain compliance with rigorous industry standards and frameworks, such as PCI DSS, SOC 2, or CIS. It automatically watches the state of key cloud resources, such as your security groups, storage buckets, and load balancers, in order to detect potential misconfigurations and compliance violations across every level of your stack. The Datadog Agent now checks the local configuration of your servers, containers, and Kubernetes clusters. The Agent also actively monitors the filesystem of containerized environments to provide a production-ready file integrity monitoring (FIM) solution. Finally, with custom detection and compliance rules, users can expand the scope of their out-of-the-box detection capabilities without needing to learn a proprietary query language. Read our blog post here.

APM & UX monitoring

Continuous Profiler

Datadog Continuous Profiler allows you to analyze your application’s performance in production—down to single lines of code and with minimal overhead. Continuous Profiler collects multiple types of profiles (CPU, memory allocation, concurrent locks, I/O, and more) across your entire stack. Inspecting these profiles helps you identify and optimize the most resource-consuming methods in your application, allowing you to reduce end-user latency and cloud provider costs. It also automatically performs heuristic code analysis and shares actionable insights for performance improvements, so anyone on your team can quickly address main problem areas. Whether you’re releasing a new version, investigating an outage, or troubleshooting slow requests, Continuous Profiler helps you debug code-level performance issues across any scope, from a single request to a fleet of applications. Learn more about Continuous Profiler in our blog post.

Synthetic CI/CD Testing

Datadog Synthetic tests are both robust and easy to create, which saves your team time and prevents alert fatigue. With Synthetic CI/CD Testing, you’re able to integrate your existing, production-level synthetic tests into your CI/CD pipeline in order to prevent bad merges, to automate rollbacks, and to run tests alongside canary deployments. This shift-left approach to testing can be achieved with both our flexible API endpoints and CLI, so you can seamlessly incorporate synthetic tests into the tooling you’ve already set up. Read our blog post to learn more about Synthetic CI/CD Testing.

Error Tracking

Errors can be difficult to troubleshoot without meaningful context. Datadog Error Tracking intelligently groups errors into issues, so you can easily understand when an error started, which versions of your code are impacted, and what may have caused it. Error Tracking uses source maps to unminify your frontend JavaScript code, reducing mean time to resolution by showing you which lines to investigate. Error Tracking is included with Datadog Real User Monitoring, so there is no need to install an SDK or modify your code. Read more about Error Tracking here.

Mobile Real User Monitoring

Like web and backend developers, mobile developers need real-time visibility into application performance and user experience. But mobile applications run at the edge of your infrastructure, making it more challenging to see the full picture. Datadog Mobile RUM helps mobile developers navigate this complexity and deploy applications with confidence. With Mobile RUM, you can analyze usage information across any app version, OS, or device—and get end-to-end visibility for investigating errors and crashes. Because Mobile RUM is tightly integrated with Datadog APM, teams can quickly understand if an issue originated at the level of the application, backend server, or network, and get the insights they need to improve their users’ mobile experience. Read more about Mobile RUM here.

Datadog APM Live Search allows you to search 100 percent of ingested traces by any tag on any span over the last 15 minutes. Traces are streamed live as users navigate your website or mobile application, giving you complete access to user requests during an outage or performance investigation. Filter down to traces matching infrastructure, application, or custom tags and watch real-time analytics for requests, errors, and latency percentiles as you deploy a new version of code to production.

Ecosystem

Marketplace

With the new Datadog Marketplace, Datadog Partners can now use Datadog as a development and collaboration platform to build custom apps, including third-party integrations and monitoring tools, and offer them to their customers and the Datadog community at large. Backed by strict vetting standards and a fully managed billing system, the Marketplace opens up new ways for our Partners to increase the scope of their monitoring solutions and provide original integrations to customers. For more information, see our blog post here.

Datadog Partners can use Marketplace to build custom applications and offer them to their own customers and the broader Datadog community.

Smart alerting is essential to any monitoring workflow; alerts draw your attention to problems in your system before they become critical. But as your stack grows and evolves, it’s not always clear which monitoring data is most important. Now, Datadog provides Recommended Monitors, a suite of preconfigured, customizable alert queries and thresholds that enable customers to enact monitoring best practices for the technologies they rely on with the click of a button. Recommended Monitors are based on the expertise of our many technology partners, as well as our own experience and the experience of thousands of customers, so you can trust that problems in your system will not go undetected. Recommended Monitors are currently in Preview. For more information, read our blog post here.

Datadog now shows you a list suggested, preconfigured monitors that can be enabled in a single click.

BigPanda integration

BigPanda is a data analysis platform that takes alert input from monitoring tools and uses machine learning to correlate them and perform automatic root cause analysis. With Datadog’s new integration, you can send your Datadog alerts to BigPanda in order to surface patterns and identify the cause more quickly. After setting up the integration, Datadog will forward all your configured Datadog alerts to BigPanda for processing. BigPanda correlates them with your other app data to determine the cause of a change in a service. When BigPanda identifies a correlation and creates an incident, it will also push events back to Datadog. For more information, read our blog post here.

Log Management

Amazon Data Firehose

Datadog customers can now send their AWS service logs directly to Datadog with an Amazon Data Firehose delivery stream. Through this easy-to-configure process, users can explore and analyze service logs to gain deeper insights into the state of their AWS infrastructure and applications. Logs streaming from Data Firehose automatically include key metadata such as their source, so users can quickly identify which AWS service generated the log. And with features like Logging without Limits™, users can analyze and generate metrics from all their logs, letting them uncover and alert on trends in their AWS services while only storing the logs they need. Read more about how to get started here.

Users can now send their AWS logs to Datadog through Amazon Kinesis Data Firehose, which gives them even deeper visibility into their AWS infrastructure and applications.

Serverless

Zero instrumentation serverless observability

Datadog now integrates with AWS Serverless Application Model (SAM) and AWS Cloud Developer Kit (CDK) to provide zero instrumentation serverless observability. With these new integrations—and our preexisting Serverless Framework plugin—teams can use their choice of developer tooling to streamline how they build, manage, and troubleshoot their serverless applications. Datadog’s new CloudFormation macro automatically ingests enhanced Lambda metrics, traces, and logs, without any code changes. Once you’re monitoring your serverless infrastructure with Datadog, you can easily search and filter functions by any tag, alert on cold starts, visualize how requests flow across Lambda functions and their dependencies, and more. Read our blog post to get started with the macro.

Datadog integrates with a number of serverless tools and services—including AWS SAM, AWS CDK, and Serverless Framework—to deliver serverless observability without any manual instrumentation.

Scale up, speed up

At Dash 2020, a global community of leaders and developers came together to bring their teams, infrastructure, and applications to the next level of scale and velocity. If you missed our virtual event, stay tuned for videos from our keynotes and technical talks to learn how companies like Zillow, Nextdoor, and Wayfair develop a culture of observability. If you’re new to Datadog, you can sign up for a 14-day free trial now to start using all our latest features and products.