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:
After deploying the Docker Agent, container metrics are available without additional configuration. To enable log collection follow these steps:
logs_enabled: true listeners: - name: docker config_providers: - name: docker polling: true
dd-agentuser must have permissions to access docker.sock.
Follow the instructions for the Docker Agent, passing in the following attributes, in addition to any other custom settings as appropriate:
-e DD_LOGS_ENABLED=true -e DD_LOGS_CONFIG_CONTAINER_COLLECT_ALL=true
Note: Logs are indexed by default, however Exclusion Filters are configurable for fine-grained controls over indexing and uniquely receiving Live Tail data.
dd-agent.yaml manifest used to create the DaemonSet, add the following environment variables, volume mount, and volume:
env: - name: DD_LOGS_ENABLED value: "true" - name: DD_LOGS_CONFIG_CONTAINER_COLLECT_ALL value: "true" volumeMounts: - name: pointerdir mountPath: /opt/datadog-agent/run volumes: - hostPath: path: /opt/datadog-agent/run name: pointerdir
For more information about activating log integrations, see the Log collection documentation.
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.
With Live Tail, all container logs are streamed – pausing the stream allows you to easily read logs that are quickly being written; un-pause 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.
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.
Containers are, by their nature, extremely high cardinality objects. Datadog’s flexible string search matches substrings in the container name, ID, or image fields.
To combine multiple string searches into a complex query, you can use any of the following Boolean operators:
|Intersection: both terms are in the selected events (if nothing is added, AND is taken by default)||java AND elasticsearch|
|Union: either term is contained in the selected events||java OR python|
|Exclusion: the following term is NOT in the event. You may use the word ||java NOT elasticsearch|
equivalent: java !elasticsearch
Use parentheses to group operators together. For example,
(NOT (elasticsearch OR kafka) java) OR python.
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:
Kubernetes containers are tagged by:
The screenshot below displays a system that has been filtered down to a Kubernetes cluster of 9 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 pivotted by
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_version to understand changes to resource utilization between updates.
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:
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.
Note that Live Containers is not metered. Including or excluding containers does not affect billing.
It is possible to include and/or exclude containers from real-time collection:
datadog.yamlmain configuration file.
datadog.yamlmain 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
ac_exclude: ["image:debian"] ac_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.
healthvalue is the containers’ readiness probe, not its liveness probe.
Additional helpful documentation, links, and articles: