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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
2018 year in review
2019-01-25 · via Datadog | The Monitor blog

There were some big IT headlines this past year. Microsoft acquired GitHub and IBM bought Red Hat. Kubernetes graduated from the CNCF incubator program. And the biggest headline of all—at least to those of us at Datadog, where we live and breathe monitoring—we released Datadog Agent version 6, a completely new monitoring agent written in Go!

As we start the new year, we’d like to take a moment to recognize some of the incredible things our engineers accomplished in 2018.

Teaching Datadog some new tricks

In addition to completely rewriting the Datadog Agent, we added lots of new features to extend your visibility into the systems and applications you run.

Logs: The third pillar

We released Datadog log management and analytics in early 2018. Logs, when combined with metrics and traces (APM), provide the third pillar of observability. But what makes Datadog log management even more powerful is how well our engineers and UX teams have integrated it into the Datadog experience. Logs are collected by the Datadog Agent, so enabling log collection is as easy as making a small configuration change in your existing Agent installation. Once logs are enabled, you can click on a timeseries graph in Datadog to view related logs, and when you view a request trace in Datadog APM, you automatically have access to the logs related to that trace as well.

Throughout the year, we continued to innovate on log management. First we introduced Logging without Limits™, which gives you the ability to collect all of your logs, Live Tail them to see all of your log data immediately, and choose which logs to index later—giving you flexible cost-efficiency without sacrificing the visibility you need. We also introduced Log Patterns, which intelligently groups your logs in real time so you can quickly identify and investigate issues.

New APM languages and visualizations

We expanded our APM support to include Java and Node.js, allowing you to instrument even more applications. We also made Preview releases of our .NET and PHP APM libraries, and both will move to full GA releases soon. When you start sending traces from your applications, you can use our new Service Map to instantly visualize how your services interact and find bottlenecks and dependency issues.

Finding the needle-in-the-haystack trace

Finding application bottlenecks and interrelated service issues became easier when we introduced App Analytics. Now you can filter and search your traces using high-cardinality tags such as customer IDs, transaction types, product SKUs, or any dimension that matters to your product and business.

Datadog for serverless

Datadog Serverless view for serverless monitoring

As more and more of our customers take advantage of serverless technologies, we wanted to ensure that you have the same visibility into serverless architectures that we’ve long provided for your servers, containers, applications, and cloud services. Our new Serverless view brings together all the metrics, traces, and logs from your serverless applications so you can monitor the performance, utilization, and resource consumption of your serverless functions.

Watchdog

Traditionally, you’ve had to manually create monitors to receive alerts. But often there are issues that you didn’t know to watch for. That’s why we launched Watchdog. Watchdog applies the machine learning that powers our industry-leading anomaly detection to your application metrics and automatically informs you of irregularities.

New ways to support you

We also opened a Datadog EU region, which allows our European customers to keep their monitoring, analytics, and log data in Europe.

If you need help learning how to use all of our new features, we launched the Datadog Learning Center—an online training portal to help you get the most out of Datadog.

Constantly improving

We didn’t just create new features last year. Every day, our engineers work with you, our customers, to find ways to make Datadog even better by helping you gain more context, evaluate information, and take action faster than ever before.

Container map

The Host Map is one of Datadog’s most beloved features, because it allows you to quickly see high-level patterns in your infrastructure and drill down to individual nodes. In order to accommodate ever larger infrastructure, we completely rewrote the Host Map using WebGL. We also added the Container Map to give you the same powerful interface for all of your containerized infrastructure.

We added lists and popularity to make it easier for you to find the dashboards you need. With lists, you can create a collection of dashboards related to a service or team. Popularity scores highlight the dashboards that others in your organization are using most.

We also made hundreds of smaller improvements, such as tags for monitors, so you can quickly filter to find the monitors applicable to your service, environment, and more; and an API endpoint, so you can programmatically manage and search your monitors. Together, these small changes add up to a big improvement in your experience and efficiency.

Spreading the monitoring love

One thing that attracts new users to Datadog is the number of integrations in our ecosystem. If there’s an application or service you use that needs monitoring, we probably have it covered. In 2018 we added even more and now have over 250 integrations! Our new integrations include cloud platforms like Pivotal Cloud Foundry, databases like Cockroach DB and Oracle, and security services like Aqua.

We also extended many of our existing integrations, such as adding support for Microsoft Azure’s Chinese, German, and Government regions; adding Amazon MQ and AWS health integrations; and providing an AWS Lambda Layer to simplify the process of monitoring your Lambda applications.

No stopping

These highlights are just a small sampling of the work we did in 2018. But as exciting as 2018 was, we have a lot more planned for 2019!

Datadog Synthetics has been in Preview for a few months and will soon be available publicly. And our .NET and PHP APM tracers will graduate from Preview status soon.

If you don’t have a Datadog account, sign up for a free account and give our new features a try. If you are a Datadog user, you can keep up-to-date with the latest feature releases in the monthly customer newsletter and the release notes in Datadog.