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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
Datadog is a Docker Ecosystem Technology Partner
2015-06-09 · via Datadog | The Monitor blog
Alexis Lê-Quôc

Alexis Lê-Quôc

We are excited to be part of Docker’s Ecosystem Technology Partner (ETP) program. Docker is a popular open platform for distributed applications to build modern applications with microservices. The promise to run the same code bit-for-bit between environments has turned continuous delivery from an ideal into a reality. Datadog has been supporting Docker since its pre-1.0 days via our Datadog Agent.

How Docker performance monitoring works

To keep deployment and management simple the Datadog Agent is perfectly happy to run in its own container on a host and monitor all of the other containers that run on that host.

Where the Agent fits in a Docker environment
where the Agent fits
Where the Agent fits in a Docker environment

Since Docker uses existing kernel constructs (namespaces and cgroups) in order to run containers, the Datadog Agent uses the native cgroup accounting metrics to gather CPU, memory, network and I/O metrics of the containers every 15 seconds before they are forwarded to Datadog.

A Docker screenboard

With easy-to-use, lightweight containers, you will likely dial up several times more running containers than the number of underlying hosts in your infrastructure. Datadog allows users to track and monitor all of them using tags.

Tags are the key to monitoring a lot of containers without additional effort. By default, the Agent will monitor your containers and turn the Docker “name”, “image” and “command” attributes into a “tag”.

Tags
Docker tags in Datadog
Tags

In Datadog, you define the metrics shown in dashboards and graphs based on one or many tags. This allows you to track specific metrics for many containers in aggregate. Using tags, you can easily create a graph for a metric drawn from all containers running a given image.

In the example below, we are showing the amount of CPU consumed, broken down by image.

Using tags to visualize Docker performance
Graph metrics by Docker tag
Using tags to visualize Docker performance

Alerts

Tags are also very useful to define alerts that span clusters of containers. For instance, let us say that you are running a cluster of Redis containers and you want to be alerted when one of the containers is running out of memory.

Instead of defining one alert per container, you only have to create a multi-alert on the docker.mem.rss metric and Datadog will trigger an alert if any container misbehaves.

You can also mix and match tags to express more complex conditions. For instance, you can monitor all Redis containers running the redis2.8 image with a simple tag selection:

Monitoring all containers that run a given image on a given host
Docker alerts
Monitoring all containers that run a given image on a given host

Monitor your containers’ lifecycle

Since containers are designed to be as short-lived (or long-lived) as traditional OS processes, it can be very useful to track particular containers throughout their lifecycles.

Much like any other meaningful event in your infrastructure, you can search for Docker container create/start/stop/destroy events using the event stream. Simply use “sources:docker” as the search filter.

Docker-related events
Docker events
Docker-related events

You can also apply the same search to any timeboard to visualize Docker container events in the context of Docker and non-Docker metrics. In the following example, we overlay containers starting and stopping over memory and CPU metrics.

Docker metrics & events correlated on the same timeboard
Correlate Docker events and metrics
Docker metrics & events correlated on the same timeboard

Explore Docker metrics

To explore the Docker metrics that are available, you can use the Metrics Explorer in Datadog and type “docker” in the first drop-down.

Explore Docker metrics with Datadog

You can find detailed descriptions about all the metrics in Docker’s Runtime Metrics guide.

To monitor Docker in your own environment, sign up for a 14-day free trial of Datadog.