Live Containers
New announcements from Dash: Incident Management, Continuous Profiler, and more! New announcements from Dash!

Live Containers


Datadog Live Containers enables real-time visibility into all containers across your environment.

Taking inspiration from bedrock tools like htop, ctop, and kubectl, live containers give you complete coverage of your container infrastructure in a continuously updated table with resource metrics at two-second resolution, faceted search, and streaming container logs.

Coupled with integrations for Docker, Kubernetes, ECS, and other container technologies, plus built-in tagging of dynamic components, the live container view provides a detailed overview of your containers’ health, resource consumption, logs, and deployment in real time:

Kubernetes Resources

Kubernetes Resources for Live Containers is currently in private beta. Fill out this form to request access.

If you’re using Kubernetes, enable Kubernetes Resources for Live Containers to gain multi-dimensional visibility into all Kubernetes workloads across your clusters. Inspired by the kubectl tool, this feature gives you complete coverage of your Kubernetes infrastructure in a continuously updated table with curated resource metrics, faceted search, per-workload detailed view, and visualized maps.


Follow the Docker or Kubernetes Agent installation instructions. Enable the Process Agent to populate your Live Containers view. Container metrics are available without additional configuration after installation.

Kubernetes Resources for Live Containers requires installation of:

Kubernetes Resources

To enable Kubernetes Resources for Live Containers, follow the Helm instructions and add the following changes to your values.yaml file:


    enabled: true
    enabled: true
  enabled: true
    repository: datadog/cluster-agent
    tag: latest
    pullPolicy: Always
    repository: datadog/agent
    tag: latest
    pullPolicy: Always

In cases where the Agent is not able to automatically detect the Kubernetes cluster name, you must set it in values.yaml:


   clusterName: <PLACEHOLDER>

Note: The cluster name must be 40-characters or less.

On Google’s GKE, AWS EKS, and Azure AKS, this is unnecessary, unless the Agent and the cluster Agent don’t have access to the cloud metadata APIs, or the cluster name is longer than 40 characters.


Include or exclude containers

It is possible to include and/or exclude containers from real-time collection:

  • Exclude containers either by passing the environment variable DD_CONTAINER_EXCLUDE or by adding container_exclude: in your datadog.yaml main configuration file.
  • Include containers either by passing the environment variable DD_CONTAINER_INCLUDE or by adding container_include: in your datadog.yaml main configuration file.

Both arguments take an image name as value; regular expressions are also supported.

For example, to exclude all Debian images except containers with a name starting with frontend, add these two configuration lines in your datadog.yaml file:

    - name: DD_LOGS_ENABLED
      value: "true"
      value: "true"

    - name: pointerdir
      mountPath: /opt/datadog-agent/run

  - hostPath:
      path: /opt/datadog-agent/run
    name: pointerdir
container_exclude: ["image:debian"]
container_include: ["name:frontend.*"]

Note: For Agent 5, instead of including the above in the datadog.conf main configuration file, explicitly add a datadog.yaml file to /etc/datadog-agent/, as the Process Agent requires all configuration options here. This configuration only excludes containers from real-time collection, not from Autodiscovery.

Getting started

Navigate to the Containers page. This will automatically bring you to the Containers view.

Searching, filtering, and pivoting

Containers are, by their nature, extremely high cardinality objects. Datadog’s flexible string search matches substrings in the container name, ID, or image fields.

If you’ve enabled Kubernetes Resources, strings such as pod, deployment, ReplicaSet, and service name, as well as Kubernetes labels are searchable in a Kubernetes Resources view.

To combine multiple string searches into a complex query, you can use any of the following Boolean operators:

ANDIntersection: both terms are in the selected events (if nothing is added, AND is taken by default)java AND elasticsearch
ORUnion: either term is contained in the selected eventsjava OR python
NOT / !Exclusion: the following term is NOT in the event. You may use the word NOT or ! character to perform the same operationjava NOT elasticsearch
equivalent: java !elasticsearch

Use parentheses to group operators together. For example, (NOT (elasticsearch OR kafka) java) OR python.

Filtering and pivoting

The screenshot below displays a system that has been filtered down to a Kubernetes cluster of nine nodes. RSS and CPU utilization on containers is reported compared to the provisioned limits on the containers, when they exist. Here, it is apparent that the containers in this cluster are over-provisioned. You could use tighter limits and bin packing to achieve better utilization of resources.

Container environments are dynamic and can be hard to follow. The following screenshot displays a view that has been pivoted by kube_service and host—and, to reduce system noise, filtered to kube_namespace:default. You can see what services are running where, and how saturated key metrics are:

You could pivot by ECS ecs_task_name and ecs_task_version to understand changes to resource utilization between updates.

For Kubernetes resources, select Datadog tags such as environment, service, or pod_phase to filter by. You can also use the container facets on the left to filter a specific Kubernetes resource. Group pods by Datadog tags to get an aggregated view which allows you to find information quicker.


Containers are tagged with all existing host-level tags, as well as with metadata associated with individual containers.

All containers are tagged by image_name, including integrations with popular orchestrators, such as ECS and Kubernetes, which provide further container-level tags. Additionally, each container is decorated with Docker, ECS, or Kubernetes icons so you can tell which are being orchestrated at a glance.

ECS containers are tagged by:

  • task_name
  • task_version
  • ecs_cluster

Kubernetes containers are tagged by:

  • pod_name
  • kube_pod_ip
  • kube_service
  • kube_namespace
  • kube_replica_set
  • kube_daemon_set
  • kube_job
  • kube_deployment
  • kube_cluster

If you have configuration for Unified Service Tagging in place, env, service, and version will also be picked up automatically. Having these tags available will let you tie together APM, logs, metrics, and live container data.


Containers View

The Containers view includes Scatter Plot and Timeseries views, and a table to better organize your container data by fields such as container name, status, and start time.

Scatter plot

Use the scatter plot analytic to compare two metrics with one another in order to better understand the performance of your containers.

To access the scatter plot analytic in the Containers page click on the Show Summary graph button and select the “Scatter Plot” tab:

By default, the graph groups by the short_image tag key. The size of each dot represents the number of containers in that group, and clicking on a dot displays the individual containers and hosts that contribute to the group.

The query at the top of the scatter plot analytic allows you to control your scatter plot analytic:

  • Selection of metrics to display.
  • Selection of the aggregation method for both metrics.
  • Selection of the scale of both X and Y axis (Linear/Log).

Real-time monitoring

While actively working with the containers page, metrics are collected at a 2-second resolution. This is important for highly volatile metrics such as CPU. In the background, for historical context, metrics are collected at 10s resolution.

Kubernetes Resources View

If you have enabled Kubernetes Resources for Live Containers, toggle between the Pods, Deployments, ReplicaSets, and Services views in the View dropdown menu in the top left corner of the page. Each of these views includes a data table to help you better organize your data by field such as status, name, and Kubernetes labels, and a detailed Cluster Map to give you a bigger picture of your pods and Kubernetes clusters.

Cluster map

A Kubernetes Cluster Map gives you a bigger picture of your pods and Kubernetes clusters. You can see all of your resources together on one screen with customized groups and filters, and choose which metrics to fill the color of the pods by.

Drill down into resources from Cluster Maps by click on any circle or group to populate a detailed panel.

Information panel

Click on any row in the table or on any object in a Cluster Map to view information about a specific resource in a side panel. This panel is useful for troubleshooting and finding information about a selected container or resource, such as:

  • Logs: View logs from your container or resource. Click on any log to view related logs in Logs Explorer.
  • Metrics: View live metrics for your container or resource. You can view any graph full screen, share a snapshot of it, or export it from this tab.
  • Network: View a container or resource’s network performance, including source, destination, sent and received volume, and throughput fields. Use the Destination field to search by tags like DNS or ip_type, or use the Group by filter in this view to group network data by tags, like pod_name or service.
  • Traces: View traces from your container or resource, including the date, service, duration, method, and status code of a trace.

Kubernetes Resources views have a few additional tabs:

  • Processes: View all processes running in the container of this resource.
  • YAML: A detailed YAML overview for the resource.
  • Events: View all Kubernetes events for your resource.

For a detailed dashboard of this resource, click the View Dashboard in the top right corner of this panel.

Container logs

View streaming logs for any container like docker logs -f or kubectl logs -f in Datadog. Click any container in the table to inspect it. Click the Logs tab to see real-time data from Live Tail or indexed logs for any time in the past.

Live Tail

With Live Tail, all container logs are streamed. Pausing the stream allows you to easily read logs that are quickly being written; unpause to continue streaming.

Streaming logs can be searched with simple string matching. For more details about Live Tail, see the Live Tail documentation.

Note: Streaming logs are not persisted, and entering a new search or refreshing the page clears the stream.

Indexed logs

You can see logs that you have chosen to index and persist by selecting a corresponding timeframe. Indexing allows you to filter your logs using tags and facets. For example, to search for logs with an Error status, type status:error into the search box. Autocompletion can help you locate the particular tag that you want. Key attributes about your logs are already stored in tags, which enables you to search, filter, and aggregate as needed.

Notes and known issues

  • Real-time (2s) data collection is turned off after 30 minutes. To resume real-time collection, refresh the page.
  • RBAC settings can restrict Kubernetes metadata collection. Refer to the RBAC entites for the Datadog Agent.
  • In Kubernetes the health value is the containers’ readiness probe, not its liveness probe.

Kubernetes Resources

  • Data is updated automatically in constant intervals. Update intervals may change during beta.
  • In clusters with 1000+ Deployments or ReplicaSets you may notice elevated CPU usage from the Cluster Agent. There is an option to disable container scrubbing in the Helm chart, see add link for more details.

Further reading