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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
Monitor your Helm-managed Kubernetes applications with Datadog
2022-05-31 · via Datadog | The Monitor blog

Helm is a package manager that makes it easy to deploy and manage Kubernetes applications. Our new Helm integration allows you to monitor the availability and status of the Helm-managed applications deployed in your Kubernetes clusters. In this post, we’ll show you how you can visualize the status of your Helm releases and use monitors to notify you of important changes in your Helm environment.

A screenshot shows Helm events in the Events Explorer, which presents a list of messages that describe changes in status of releases in the cluster.

See the status of your Helm releases

Helm defines applications using charts, which are packaged collections of Kubernetes manifests. When you deploy a chart, Helm creates a new release—an application in your cluster—or applies a new configuration to upgrade an existing release to a new revision.

Datadog’s Helm integration includes an out-of-the-box dashboard that displays data about Helm releases. This allows you to see the status of your Helm-managed applications and helps you spot trends in key Helm activity like installations and upgrades. Template variables at the top of the dashboard allow you to filter your Helm data so you can see releases from a single cluster, for example. In the screenshot below, the dashboard displays a count of releases in the shepherd cluster that failed (shown in red) and a count of releases that are working properly (in green). A list of Helm events shows a history of status changes—including new releases, upgrades, and deletions—and a timeseries graph shows a breakdown of releases by status. The dashboard also provides a detailed overview of information from each Helm release, including the cluster name, datacenter, chart, and revision.

A dashboard shows a count of failed releases in red and healthy releases in green, plus a list of Helm events and a bar graph of Helm releases by status over time. The bottom of the dashboard shows a table displaying the cluster name and data center of each release, plus chart and revision information.

As you upgrade your Helm releases, Datadog tracks changes in the status of each release. If a release fails—for example, if it can’t be scheduled due to a resource constraint—you will be able to detect this change in the event stream widget on the dashboard. You can click the event to see more information, including tags that describe the release and the underlying infrastructure. For even more information, you can pivot to the host dashboard to see the worker node’s resource usage data.

Alert on changes in your Helm releases

To enable the Helm integration, set the Datadog Helm chart’s datadog.helmCheck.enabled and datadog.helmCheck.collectEvents parameters to true. The integration includes a service check that automatically detects if any Helm releases are in a failed state. You can also enable an out-of-the-box monitor—shown in the screenshot below—to notify your team when a service check fails. By default, the alert triggers if a release fails five consecutive service checks. This can help you quickly detect and troubleshoot issues that could affect the performance of your service, such as a liveness probe that fails due to an unhealthy container. You can start using this monitor right away, and you can clone it to create new versions that are scoped by tags like helm_release or kube_cluster_name to notify specific teams if a release that they’re responsible for has failed.

A screenshot shows the configuration of a Helm alert, which will trigger if the Helm service check fails five times on any release.

Get started with Helm monitoring

Datadog’s new integration provides deep visibility into your Helm releases alongside monitoring data from the rest of your orchestrated environment. Note that this integration requires Datadog Agent version 7.36.0+ and Cluster Agent version 1.20.0+. See our documentation for more information about monitoring Helm with Datadog. If you’re not yet using Datadog, you can start right away with a 14-day free trial.