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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 - 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Streamline communication workflows with the Datadog Slack integration
2020-10-08 · via Datadog | The Monitor blog

Slack is integral to the way many organizations coordinate the management of their systems and applications. The Datadog Slack integration provides a range of features that enable you to make seamless use of Datadog’s resources within your communication workflows—from targeted monitor notifications to robust incident management capabilities, the automation of routine data-sharing processes, and more.

In this post, we’ll guide you through using the Datadog Slack integration to:

Streamline your response to monitor notifications and incidents

Providing essential monitoring data within Slack minimizes the need for context switching as DevOps and security teams communicate. You can use our Slack integration to target Datadog monitor notifications to specific channels and customize them to include snapshots of the queries that triggered them, as well as messages, tags, and lists of recipients.

The integration also enables you to quickly take action on urgent issues. Let’s say you receive a notification from Datadog that indicates persistent service degradation. You can quickly declare an incident by running the /datadog incident command in any Slack channel. This command opens an incident creation modal inside Slack, enabling you to immediately create an incident in Datadog without context switching. Here, you can summarize the nature of the incident, set a severity level, assign an incident commander and response teams, add custom notifications, and more.

You can use the `/datadog incident` command to declare an incident from within Slack.

Creating a new incident using the /datadog incident command generates a dedicated Slack channel where team members can quickly launch into coordinated troubleshooting and stakeholders can monitor progress. Within these channels, you can directly update an incident’s status and severity level using the /datadog incident update command.

For more context, you can access incidents created via Slack in Datadog Incident Management. Here you can find a detailed overview of each incident, including a timeline that is set up as soon as you declare an incident in Datadog. Incident timelines can help you track incidents as they unfold and build a clear picture of your response to them after the fact, making them valuable assets during postmortem analysis. You can manually add any Slack message to an incident timeline by hovering over it, clicking “More actions,” and then selecting “Add to Incident Timeline.” You can also use Slack reactions to quickly push messages to a timeline, or mirror all messages from an incident channel.

You can push Slack messages to incident timelines either manually or automatically.

Quickly get up to speed with Bits AI

Dedicated Slack channels for incidents help keep your responders on the same page. But as new responders join in—especially during prolonged or severe incidents—they often must spend precious time getting up to speed.

Our Bits AI copilot—currently available in Preview—provides responders with concise incident summaries as they join incident Slack channels, reducing the time spent on catch-up to a minimum and eliminating the need to scroll back through reams of messages and sift through threads.

You can use Bits AI to provide incident summaries to quickly bring incident responders up to speed.

Bits AI can also surface important assets for incident remediation, such as runbooks or Datadog workflows that could help you contain impact—for example, by automatically blocking malicious IPs during DDoS attacks.

Access key monitoring resources without context switching

To quickly access a range of Datadog resources as you communicate with your teammates, you can use our integration’s Home tab. The Home tab provides links to your starred dashboards, notebooks, and services. It also displays all of your monitors that have been triggered (without being resolved) in the past 24 hours, and allows you to quickly pivot to their associated Slack channels.

You can quickly access key resources in Datadog using the Datadog integration's Home tab in Slack.

In addition to enabling you to directly copy and paste widgets from dashboards, the Datadog Slack integration enables you to easily and directly pull graphs into Slack channels either by simply linking to them or by using the /datadog dashboard command. Automatic link unfurling displays previews of dashboard widgets as well as log events and traces. The /datadog dashboard command opens a modal in which you can search your dashboards, select a widget, specify the time span you want to display, and filter to a predefined context from your saved views. A helpful preview lets you check your selection before you share it to the channel.

Get started with the Datadog Slack integration today

The Datadog Slack integration is available in the Slack App Directory. You can also install it through the Slack integration tile in Datadog. For more information on how to get started, check out our documentation. If you’re not yet a Datadog customer, you can sign up for a 14-day free trial.