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 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:
The Datadog Agent and Cluster Agent can be configured to retrieve Kubernetes resources for Live Containers. This feature allows you to monitor the state of pods, deployments and other Kubernetes concepts in a specific namespace or availability zone, view resource specifications for failed pods within a deployment, correlate node activity with related logs, and more.
Kubernetes resources for Live Containers requires Agent version >= 7.21.1 and Cluster Agent version >= 1.9.0 prior to the configurations below.
If you are using the official Datadog Helm Chart:
datadog.orchestratorExplorer.enabled to true in values.yamlIn some setups, the Process Agent and Cluster Agent are unable to automatically detect a Kubernetes cluster name. If this happens the feature will not start, and you will see a WARN log in the Cluster Agent logs saying Orchestrator explorer enabled but no cluster name set: disabling. In this case you must set datadog.clusterName to your cluster name in values.yaml.
Cluster Agent version >= 1.9.0 is required before configuring the DaemonSet. The Cluster Agent must be running, and the Agent must be able to communicate with it. See the Cluster Agent Setup documentation for configuration.
Set the Cluster Agent container with the following environment variable:
- name: DD_ORCHESTRATOR_EXPLORER_ENABLED
value: "true"
Set the Cluster Agent ClusterRole with the following RBAC permissions.
Note particularly that for the apps apiGroups, Live Containers need permissions
to collect common kubernetes resources (pods, services, nodes, etc.),
which should be already in the RBAC if you followed Cluster Agent Setup
documentation. But if they are missing, ensure they are added (after
deployments, replicasets):
ClusterRole:
- apiGroups: # To create the datadog-cluster-id CM
- ""
resources:
- configmaps
verbs:
- create
- get
- update
...
- apiGroups: # Required to get the kube-system namespace UID and generate a cluster ID
- ""
resources:
- namespaces
verbs:
- get
...
- apiGroups: # To collect new resource types
- "apps"
resources:
- deployments
- replicasets
# Below are in case RBAC was not setup from the above linked "Cluster Agent Setup documentation"
- pods
- nodes
- services
verbs:
- list
- get
- watch
These permissions are needed to create a datadog-cluster-id ConfigMap in the same Namespace as the Agent DaemonSet and the Cluster Agent Deployment, as well as to collect Deployments and ReplicaSets.
If the cluster-id ConfigMap doesn’t get created by the Cluster Agent, the Agent pod will not start, and fall in CreateContainerConfigError status. If the Agent pod is stuck because this ConfigMap doesn’t exist, update the Cluster Agent permissions and restart its pods to let it create the ConfigMap and the Agent pod will recover automatically.
The Process Agent, which runs in the Agent DaemonSet, must be enabled and running (it doesn’t need to run the process collection), and configured with the following options:
- name: DD_ORCHESTRATOR_EXPLORER_ENABLED
value: "true"
- name: DD_ORCHESTRATOR_CLUSTER_ID
valueFrom:
configMapKeyRef:
name: datadog-cluster-id
key: id
In some setups, the Process Agent and Cluster Agent are unable to automatically detect a Kubernetes cluster name. If this happens the feature will not start, and you will see a WARN log in the Cluster Agent logs saying Orchestrator explorer enabled but no cluster name set: disabling. In this case you must add the following options in the env section of both the Cluster Agent and the Process Agent:
- name: DD_CLUSTER_NAME
value: "<YOUR_CLUSTER_NAME>"
It is possible to include and/or exclude containers from real-time collection:
DD_CONTAINER_EXCLUDE or by adding container_exclude: in your datadog.yaml main configuration file.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:
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
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.
Navigate to the Containers page. This will automatically bring you to the Containers view.
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:
| Operator | Description | Example |
AND | Intersection: both terms are in the selected events (if nothing is added, AND is taken by default) | java AND elasticsearch |
OR | Union: either term is contained in the selected events | java OR python |
NOT / ! | Exclusion: the following term is NOT in the event. You may use the word NOT or ! character to perform the same operation | java NOT elasticsearch equivalent: java !elasticsearch |
Use parentheses to group operators together. For example, (NOT (elasticsearch OR kafka) java) OR python.
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_nametask_versionecs_clusterKubernetes containers are tagged by:
pod_namekube_pod_ipkube_servicekube_namespacekube_replica_setkube_daemon_setkube_jobkube_deploymentkube_clusterIf 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.
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.
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.
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.
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.
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:
DNS or ip_type, or use the Group by filter in this view to group network data by tags, like pod_name or service.Kubernetes Resources views have a few additional tabs:
For a detailed dashboard of this resource, click the View Dashboard in the top right corner of this panel.
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; unpause to continue streaming.
Streaming logs can be searched with simple string matching. For more details about live tail, see the 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.
health value is the containers' readiness probe, not its liveness probe.Additional helpful documentation, links, and articles:
