Operator configuration

All configuration options

The following table lists the configurable parameters for the DatadogAgent resource. For example, if you wanted to set a value for agent.image.name, your DatadogAgent resource would look like the following:

apiVersion: datadoghq.com/v1alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  agent:
    image:
      name: "gcr.io/datadoghq/agent:latest"

agent.additionalAnnotations: AdditionalAnnotations provide annotations that will be added to the Agent Pods.
agent.additionalLabels: AdditionalLabels provide labels that are added to the cluster checks runner pods.
agent.apm.enabled: Enable this to enable APM and tracing on port 8126. See the Datadog Docker documentation.
agent.apm.env: The Datadog Agent supports many environment variables.
agent.apm.hostPort: Number of the port to expose on the host. If specified, this must be a valid port number, 0 < x < 65536. If HostNetwork is specified, this must match ContainerPort. Most containers do not need this.
agent.apm.resources.limits: Limits describes the maximum amount of compute resources allowed. For more info, see the Kubernetes documentation.
agent.apm.resources.requests: Requests describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified. Otherwise, it defaults to an implementation-defined value. For more info, see the Kubernetes documentation.
agent.config.checksd.configMapName: Name of a ConfigMap used to mount a directory.
agent.config.collectEvents: Enables starting event collection from the Kubernetes API. See the Event Collection documentation.
agent.config.confd.configMapName: Name of a ConfigMap used to mount a directory.
agent.config.criSocket.criSocketPath: Path to the container runtime socket (if different from Docker). This is supported starting from Agent 6.6.0.
agent.config.criSocket.dockerSocketPath: Path to the Docker runtime socket.
agent.config.ddUrl: The host of the Datadog intake server to send Agent data to. Only set this option if you need the Agent to send data to a custom URL. Overrides the site setting defined in site.
agent.config.dogstatsd.dogstatsdOriginDetection: Enable origin detection for container tagging. See the Unix Socket origin detection documentation.
agent.config.dogstatsd.useDogStatsDSocketVolume: Enable DogStatsD over a Unix Domain Socket. See the Unix Socket documentation.
agent.config.env: The Datadog Agent supports many environment variables.
agent.config.hostPort: Number of the port to expose on the host. If specified, this must be a valid port number, 0 < x < 65536. If HostNetwork is specified, this must match ContainerPort. Most containers do not need this.
agent.config.leaderElection: Enables leader election mechanism for event collection.
agent.config.logLevel: Set logging verbosity. Valid log levels are: trace, debug, info, warn, error, critical, and off.
agent.config.podAnnotationsAsTags: Provide a mapping of Kubernetes Annotations to Datadog Tags. <KUBERNETES_ANNOTATIONS>: <DATADOG_TAG_KEY>
agent.config.podLabelsAsTags: Provide a mapping of Kubernetes labels to Datadog tags. <KUBERNETES_LABEL>: <DATADOG_TAG_KEY>
agent.config.resources.limits: Describes the maximum amount of compute resources allowed. See the Kubernetes documentation.
agent.config.resources.requests: Describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified. Otherwise, it defaults to an implementation-defined value. See the Kubernetes documentation.
agent.config.securityContext.allowPrivilegeEscalation: Controls whether a process can gain more privileges than its parent process. This boolean determines whether or not the no_new_privs flag is set on the container process. AllowPrivilegeEscalation is always true when the container is run as both Privileged and has CAP_SYS_ADMIN.
agent.config.securityContext.capabilities.add: Added capabilities.
agent.config.securityContext.capabilities.drop: Removed capabilities.
agent.config.securityContext.privileged: Run the container in privileged mode. Processes in privileged containers are essentially equivalent to root on the host. Defaults to false.
agent.config.securityContext.procMount: procMount denotes the type of proc mount to use for the containers. The default is DefaultProcMount which uses the container runtime defaults for read-only paths and masked paths. This requires the ProcMountType feature flag to be enabled.
agent.config.securityContext.readOnlyRootFilesystem: Whether this container has a read-only root file system. Default is false.
agent.config.securityContext.runAsGroup: The GID to run the entrypoint of the container process. Uses runtime default if unset. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.config.securityContext.runAsNonRoot: Indicates that the container must run as a non-root user. If true, the Kubelet validates the image at runtime to ensure that it does not run as UID 0 (root) and fail to start the container if it does. If unset or false, no such validation is performed. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.config.securityContext.runAsUser: The UID to run the entrypoint of the container process. Defaults to user specified in image metadata if unspecified. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.config.securityContext.seLinuxOptions.level: SELinux level label that applies to the container.
agent.config.securityContext.seLinuxOptions.role: SELinux role label that applies to the container.
agent.config.securityContext.seLinuxOptions.type: SELinux type label that applies to the container.
agent.config.securityContext.seLinuxOptions.user: SELinux user label that applies to the container.
agent.config.securityContext.windowsOptions.gmsaCredentialSpec: GMSACredentialSpec is where the GMSA admission webhook inlines the contents of the GMSA credential spec named by the GMSACredentialSpecName field. This field is alpha-level and is only honored by servers that enable the WindowsGMSA feature flag.
agent.config.securityContext.windowsOptions.gmsaCredentialSpecName: GMSACredentialSpecName is the name of the GMSA credential spec to use. This field is alpha-level and is only honored by servers that enable the WindowsGMSA feature flag.
agent.config.securityContext.windowsOptions.runAsUserName: The UserName in Windows to run the entrypoint of the container process. Defaults to the user specified in image metadata if unspecified. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence. This field is beta-level and may be disabled with the WindowsRunAsUserName feature flag.
agent.config.tags: List of tags to attach to every metric, event, and service check collected by this Agent. See the Tagging documentation.
agent.config.tolerations: If specified, the Agent pod’s tolerations.
agent.config.volumeMounts: Specify additional volume mounts in the Datadog Agent container.
agent.config.volumes: Specify additional volumes in the Datadog Agent container.
agent.customConfig.configData: Corresponds to the configuration file content.
agent.customConfig.configMap.fileKey: Corresponds to the key used in the ConfigMap.Data to store the configuration file content.
agent.customConfig.configMap.name: Name the ConfigMap.
agent.daemonsetName: Name of the DaemonSet to create or migrate from.

agent.deploymentStrategy.canary.duration :

agent.deploymentStrategy.canary.paused :

agent.deploymentStrategy.canary.replicas :

agent.deploymentStrategy.reconcileFrequency: The reconcile frequency of the ExtendDaemonSet.
agent.deploymentStrategy.rollingUpdate.maxParallelPodCreation: The maximum number of pods created in parallel. Default value is 250.
agent.deploymentStrategy.rollingUpdate.maxPodSchedulerFailure: maxPodSchedulerFailure is the maximum number of pods scheduled on its Node due to a scheduler failure: resource constraints. Value can be an absolute number (ex: 5) or a percentage of total number of DaemonSet pods at the start of the update (ex: 10%). Absolute.
agent.deploymentStrategy.rollingUpdate.maxUnavailable: The maximum number of DaemonSet pods that can be unavailable during the update. Value can be an absolute number (ex: 5) or a percentage of total number of DaemonSet pods at the start of the update (ex: 10%). Absolute number is calculated from percentage by rounding up. This cannot be 0. Default value is 1.
agent.deploymentStrategy.rollingUpdate.slowStartAdditiveIncrease: Value can be an absolute number (ex: 5) or a percentage of total number of DaemonSet pods at the start of the update (ex: 10%). Default value is 5.
agent.deploymentStrategy.rollingUpdate.slowStartIntervalDuration: The duration interval. Default value is 1min.
agent.deploymentStrategy.updateStrategyType: The update strategy used for the DaemonSet.
agent.dnsConfig.nameservers: A list of DNS name server IP addresses. This are appended to the base nameservers generated from dnsPolicy. Duplicated nameservers are removed.
agent.dnsConfig.options: A list of DNS resolver options. These are merged with the base options generated from dnsPolicy. Duplicated entries are removed. Resolution options given in options override those that appear in the base dnsPolicy.
agent.dnsConfig.searches: A list of DNS search domains for host-name lookup. This are appended to the base search paths generated from dnsPolicy. Duplicated search paths are removed.
agent.dnsPolicy: Set DNS policy for the pod. Defaults to ClusterFirst. Valid values are ClusterFirstWithHostNet, ClusterFirst, Default, or None. DNS parameters given in dnsConfig are merged with the policy selected with dnsPolicy. To have DNS options set along with hostNetwork, you have to specify dnsPolicy explicitly to ClusterFirstWithHostNet.
agent.env: Environment variables for all Datadog Agents. See the Docker environment variables documentation.
agent.hostNetwork: Host networking requested for this pod. Use the host’s network namespace. If this option is set, the ports that are used must be specified. Defaults to false.
agent.hostPID: Use the host’s PID namespace. Optional: Defaults to false.
agent.image.name: Define the image to use gcr.io/datadoghq/agent:latest for Datadog Agent 6. Use gcr.io/datadoghq/dogstatsd:latest for stand-alone Datadog Agent DogStatsD. Use gcr.io/datadoghq/cluster-agent:latest for Datadog Cluster Agent.
agent.image.pullPolicy: The Kubernetes pull policy. Use Always, Never, or IfNotPresent.
agent.image.pullSecrets: Specifies the Docker registry credentials. See the Kubernetes documentation.
agent.log.containerCollectUsingFiles: Collect logs from files in /var/log/pods instead of using container runtime API. This is usually the most efficient way of collecting logs. See the Log Collection documentation. Default: true.
agent.log.containerLogsPath: Allow log collection from the container log path. Set to a different path if not using docker runtime. See the Kubernetes documentation. Defaults to /var/lib/docker/containers.
agent.log.enabled: Enable this to activate Datadog Agent log collection. See the Log Collection documentation.
agent.log.logsConfigContainerCollectAll: Enable this to allow log collection for all containers. See the Log Collection documentation.
agent.log.openFilesLimit: Set the maximum number of logs files that the Datadog Agent tails up to. Increasing this limit can increase resource consumption of the Agent. See the Log Collection documentation. Defaults to 100.
agent.log.podLogsPath: Set this to allow log collection from pod log path. Defaults to /var/log/pods.
agent.log.tempStoragePath: This path (always mounted from the host) is used by the Datadog Agent to store information about processed log files. If the Datadog Agent is restarted, it allows you to start tailing the log files from the right offset. Defaults to /var/lib/datadog-agent/logs.
agent.priorityClassName: If specified, indicates the pod’s priority. system-node-critical and system-cluster-critical are two special keywords which indicate the highest priorities with the former being the highest priority. Any other name must be defined by creating a PriorityClass object with that name. If not specified, the pod priority is set to default or zero if there is no default.
agent.process.enabled: Enable this to activate live process monitoring. Note: /etc/passwd is automatically mounted to allow username resolution. See the Process documentation.
agent.process.env: The Datadog Agent supports many environment variables.
agent.process.resources.limits: Describes the maximum amount of compute resources allowed. See the Kubernetes documentation.
agent.process.resources.requests: Describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified, otherwise to an implementation-defined value. See the Kubernetes documentation.
agent.rbac.create: Used to configure RBAC resources creation.
agent.rbac.serviceAccountName: Used to set up the service account name to use Ignored if the field Create is true.
agent.systemProbe.appArmorProfileName: Specify an AppArmor profile.
agent.systemProbe.bpfDebugEnabled: Logging for kernel debug.
agent.systemProbe.conntrackEnabled: Enable the system-probe agent to connect to the netlink/conntrack subsystem to add NAT information to connection data. See the Conntrack documentation.
agent.systemProbe.debugPort: Specify the port to expose pprof and expvar for system-probe agent.
agent.systemProbe.enabled: Enable this to activate live process monitoring. Note: /etc/passwd is automatically mounted to allow username resolution. See the Process documentation.
agent.systemProbe.env: The Datadog SystemProbe supports many environment variables.
agent.systemProbe.resources.limits: Describes the maximum amount of compute resources allowed. See the Kubernetes documentation.
agent.systemProbe.resources.requests: Describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified, otherwise to an implementation-defined value. See the Kubernetes documentation.
agent.systemProbe.secCompCustomProfileConfigMap: Specify a pre-existing ConfigMap containing a custom SecComp profile.
agent.systemProbe.secCompProfileName: Specify a seccomp profile.
agent.systemProbe.secCompRootPath: Specify the seccomp profile root directory.
agent.systemProbe.securityContext.allowPrivilegeEscalation: Controls whether a process can gain more privileges than its parent process. This boolean determines whether or not the no_new_privs flag is set on the container process. AllowPrivilegeEscalation is true always when the container is: 1) run as Privileged 2) has CAP_SYS_ADMIN.
agent.systemProbe.securityContext.capabilities.add: Added capabilities.
agent.systemProbe.securityContext.capabilities.drop: Removed capabilities.
agent.systemProbe.securityContext.privileged: Run container in privileged mode. Processes in privileged containers are essentially equivalent to root on the host. Defaults to false.
agent.systemProbe.securityContext.procMount: Denotes the type of proc mount to use for the containers. The default is DefaultProcMount which uses the container runtime defaults for read-only paths and masked paths. This requires the ProcMountType feature flag to be enabled.
agent.systemProbe.securityContext.readOnlyRootFilesystem: Whether this container has a read-only root filesystem. Default is false.
agent.systemProbe.securityContext.runAsGroup: The GID to run the entrypoint of the container process. Uses runtime default if unset. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.systemProbe.securityContext.runAsNonRoot: Indicates that the container must run as a non-root user. If true, the Kubelet validates the image at runtime to ensure that it does not run as UID 0 (root) and fail to start the container if it does. If unset or false, no such validation is performed. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.systemProbe.securityContext.runAsUser: The UID to run the entrypoint of the container process. Defaults to user specified in image metadata if unspecified. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence.
agent.systemProbe.securityContext.seLinuxOptions.level: SELinux level label that applies to the container.
agent.systemProbe.securityContext.seLinuxOptions.role: SELinux role label that applies to the container.
agent.systemProbe.securityContext.seLinuxOptions.type: SELinux type label that applies to the container.
agent.systemProbe.securityContext.seLinuxOptions.user: SELinux user label that applies to the container.
agent.systemProbe.securityContext.windowsOptions.gmsaCredentialSpec: GMSACredentialSpec is where the GMSA admission webhook inlines the contents of the GMSA credential spec named by the GMSACredentialSpecName field. This field is alpha-level and is only honored by servers that enable the WindowsGMSA feature flag.
agent.systemProbe.securityContext.windowsOptions.gmsaCredentialSpecName: GMSACredentialSpecName is the name of the GMSA credential spec to use. This field is alpha-level and is only honored by servers that enable the WindowsGMSA feature flag.
agent.systemProbe.securityContext.windowsOptions.runAsUserName: Use the UserName in Windows to run the entry point of the container process. Defaults to the user specified in image metadata if unspecified. May also be set in PodSecurityContext. If set in both SecurityContext and PodSecurityContext, the value specified in SecurityContext takes precedence. This field is beta-level and may be disabled with the WindowsRunAsUserName feature flag.
agent.useExtendedDaemonset: Use ExtendedDaemonset for Agent deployment. Default value is false.
clusterAgent.additionalAnnotations: AdditionalAnnotations provide annotations that are added to the Cluster Agent Pods.
clusterAgent.additionalLabels: AdditionalLabels provide labels that are added to the cluster checks runner Pods.
clusterAgent.affinity.nodeAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (resource request and requiredDuringScheduling affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node matches the corresponding matchExpressions; the node(s) with the highest sum are the most preferred.
clusterAgent.affinity.nodeAffinity.requiredDuringSchedulingIgnoredDuringExecution.nodeSelectorTerms: Required. A list of node selector terms. The terms are ORed.
clusterAgent.affinity.podAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (such as resource request and requiredDuringScheduling affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node has pods which matches the corresponding podAffinityTerm. The node(s) with the highest sum are the most preferred.
clusterAgent.affinity.podAffinity.requiredDuringSchedulingIgnoredDuringExecution: If the affinity requirements specified by this field are not met at scheduling time, the pod is not scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (for example, due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected; all terms must be satisfied.
clusterAgent.affinity.podAntiAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (resource request and requiredDuringScheduling anti-affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
clusterAgent.affinity.podAntiAffinity.requiredDuringSchedulingIgnoredDuringExecution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod is not scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (for example, due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected; all terms must be satisfied.
clusterAgent.config.admissionController.enabled: Enable the admission controller to be able to inject APM/DogStatsD config and standard tags (env, service, version) automatically into your pods.
clusterAgent.config.admissionController.mutateUnlabelled: Enables injecting config without having the pod label admission.datadoghq.com/enabled="true"
clusterAgent.config.admissionController.serviceName: Corresponds to the webhook service name.
clusterAgent.config.clusterChecksEnabled: Enable the Cluster Checks and Endpoint Checks feature on both the Cluster Agent and the DaemonSet. See the Cluster Checks documentation. Autodiscovery through Kube Service annotations is automatically enabled.
clusterAgent.config.confd.configMapName: Name of a ConfigMap used to mount a directory.
clusterAgent.config.env: The Datadog Agent supports many environment variables.
clusterAgent.config.externalMetrics.enabled: Enable the metricsProvider to be able to scale based on metrics in Datadog.
clusterAgent.config.externalMetrics.port: If specified, configures the metricsProvider external metrics service port.
clusterAgent.config.externalMetrics.useDatadogMetrics: Enable usage of DatadogMetrics CRD (allow to scale on arbitrary queries).
clusterAgent.config.logLevel: Set logging verbosity. Valid log levels are: trace, debug, info, warn, error, critical, and off.
clusterAgent.config.resources.limits: Describes the maximum amount of compute resources allowed. See the Kubernetes documentation.
clusterAgent.config.resources.requests: Describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified, otherwise to an implementation-defined value. See the Kubernetes documentation.
clusterAgent.config.volumeMounts: Specify additional volume mounts in the Datadog Cluster Agent container.
clusterAgent.config.volumes: Specify additional volumes in the Datadog Cluster Agent container.
clusterAgent.customConfig.configData: Corresponds to the configuration file content.
clusterAgent.customConfig.configMap.fileKey: Corresponds to the key used in the ConfigMap.Data to store the configuration file content.
clusterAgent.customConfig.configMap.name: Name the ConfigMap.
clusterAgent.deploymentName: Name of the Cluster Agent Deployment to create or migrate from.
clusterAgent.image.name: Define the image to use. Use gcr.io/datadoghq/agent:latest for Datadog Agent 6. Use gcr.io/datadoghq/dogstatsd:latest for stand-alone Datadog Agent DogStatsD. Use gcr.io/datadoghq/cluster-agent:latest for Datadog Cluster Agent.
clusterAgent.image.pullPolicy: The Kubernetes pull policy. Use Always, Never, or IfNotPresent.
clusterAgent.image.pullSecrets: Specifies Docker registry credentials. See the Kubernetes documentation.
clusterAgent.nodeSelector: Selector which must be true for the pod to fit on a node. Selector which must match a node’s labels for the pod to be scheduled on that node. See the Kubernetes documentation.
clusterAgent.priorityClassName: If specified, indicates the pod’s priority. system-node-critical and system-cluster-critical are two special keywords that indicate the highest priorities with the former being the highest priority. Any other name must be defined by creating a PriorityClass object with that name. If not specified, the pod priority is set to default or zero if there is no default.
clusterAgent.rbac.create: Used to configure RBAC resources creation.
clusterAgent.rbac.serviceAccountName: Used to set up the service account name to use. Ignored if the field Create is true.
clusterAgent.replicas: Number of the Cluster Agent replicas.
clusterAgent.tolerations: If specified, the Cluster Agent pod’s tolerations.
clusterChecksRunner.additionalAnnotations: Provide annotations that will be added to the cluster checks runner Pods.
clusterChecksRunner.additionalLabels: Provide labels that will be added to the cluster checks runner Pods.
clusterChecksRunner.affinity.nodeAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (resource request and requiredDuringScheduling affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node matches the corresponding matchExpressions; the node(s) with the highest sum are the most preferred.
clusterChecksRunner.affinity.nodeAffinity.requiredDuringSchedulingIgnoredDuringExecution.nodeSelectorTerms: Required. A list of node selector terms. The terms are ORed.
clusterChecksRunner.affinity.podAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (resource request and requiredDuringScheduling affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
clusterChecksRunner.affinity.podAffinity.requiredDuringSchedulingIgnoredDuringExecution: If the affinity requirements specified by this field are not met at scheduling time, the pod is not scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (for example, due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected; all terms must be satisfied.
clusterChecksRunner.affinity.podAntiAffinity.preferredDuringSchedulingIgnoredDuringExecution: The scheduler prefers to schedule pods to nodes that satisfy the anti-affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights. For each node that meets all of the scheduling requirements (resource request and requiredDuringScheduling anti-affinity expressions), compute a sum by iterating through the elements of this field and adding “weight” to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.
clusterChecksRunner.affinity.podAntiAffinity.requiredDuringSchedulingIgnoredDuringExecution: If the anti-affinity requirements specified by this field are not met at scheduling time, the pod is not scheduled onto the node. If the anti-affinity requirements specified by this field cease to be met at some point during pod execution (for example, due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected; all terms must be satisfied.
clusterChecksRunner.config.env: The Datadog Agent supports many environment variables.
clusterChecksRunner.config.logLevel: Set logging verbosity. Valid log levels are: trace, debug, info, warn, error, critical, and off.
clusterChecksRunner.config.resources.limits: Limits describes the maximum amount of compute resources allowed. See the Kubernetes documentation.
clusterChecksRunner.config.resources.requests: Describes the minimum amount of compute resources required. If requests is omitted for a container, it defaults to limits if that is explicitly specified, otherwise to an implementation-defined value. See the Kubernetes documentation.
clusterChecksRunner.config.volumeMounts: Specify additional volume mounts in the Datadog Cluster Check Runner container.
clusterChecksRunner.config.volumes: Specify additional volumes in the Datadog Cluster Check Runner container.
clusterChecksRunner.customConfig.configData: Corresponds to the configuration file content.
clusterChecksRunner.customConfig.configMap.fileKey: Corresponds to the key used in the ConfigMap.Data to store the configuration file content.
clusterChecksRunner.customConfig.configMap.name: Name the ConfigMap.
clusterChecksRunner.deploymentName: Name of the cluster checks deployment to create or migrate from.
clusterChecksRunner.image.name: Define the image to use Use gcr.io/datadoghq/agent:latest for Datadog Agent 6. Use gcr.io/datadoghq/dogstatsd:latest for standalone Datadog Agent DogStatsD. Use gcr.io/datadoghq/cluster-agent:latest for Datadog Cluster Agent.
clusterChecksRunner.image.pullPolicy: The Kubernetes pull policy. Use Always, Never, or IfNotPresent.
clusterChecksRunner.image.pullSecrets: It is possible to specify docker registry credentials. See the Kubernetes documentation.
clusterChecksRunner.nodeSelector: Selector which must be true for the pod to fit on a node. Selector which must match a node’s labels for the pod to be scheduled on that node. See the Kubernetes documentation.
clusterChecksRunner.priorityClassName: If specified, indicates the pod’s priority. system-node-critical and system-cluster-critical are two special keywords which indicate the highest priorities with the former being the highest priority. Any other name must be defined by creating a PriorityClass object with that name. If not specified, the pod priority is set to default or zero if there is no default.
clusterChecksRunner.rbac.create: Used to configure RBAC resources creation.
clusterChecksRunner.rbac.serviceAccountName: Used to set up the service account name to use. Ignored if the field Create is true.
clusterChecksRunner.replicas: Number of the Cluster Agent replicas.
clusterChecksRunner.tolerations: If specified, the Cluster Check pod’s tolerations.
clusterName: Set a unique cluster name to allow scoping hosts and Cluster Checks Runner easily.
credentials.apiKey: Set this to your Datadog API key before the Agent runs.
credentials.apiKeyExistingSecret: DEPRECATED. To pass the API key through an existing secret, consider apiSecret instead. If set, this parameter takes precedence over apiKey.
credentials.apiSecret.keyName: Key of the secret to use.
credentials.apiSecret.secretName: Name of the secret.
credentials.appKey: If you are using clusterAgent.metricsProvider.enabled = true, you must set a Datadog application key for read access to your metrics.
credentials.appKeyExistingSecret: DEPRECATED. To pass the app key through an existing secret, consider appSecret instead. If set, this parameter takes precedence over appKey.
credentials.appSecret.keyName: Key of the secret to use.
credentials.appSecret.secretName: Name of the secret.
credentials.token: A preshared key between the Node Agents and the Cluster Agent. This needs to be at least 32 characters a-zA-z.
credentials.useSecretBackend: Use the Agent secret backend feature for retrieving all credentials needed by the different components: Agent, Cluster, Cluster Checks. If useSecretBackend:true, other credential parameters are ignored. Default value is false.
site: Set the site of the Datadog intake for Agent data: . Defaults to datadoghq.com.
features.kubeStateMetricsCore.clusterCheck: Configures the Kubernetes State Metrics Core check as a cluster check.
features.kubeStateMetricsCore.enabled: Enable this to start the Kubernetes State Metrics Core check. See the Kubernetes State Metrics Core documentation.
features.kubeStateMetricsCore.conf.configData: Corresponds to the configuration file content.
features.kubeStateMetricsCore.conf.configMap.fileKey: Corresponds to the key used in the ConfigMap.Data to store the configuration file content.
features.kubeStateMetricsCore.conf.configMap.name: Name the ConfigMap.
features.logCollection.containerCollectUsingFiles: Collect logs from files in /var/log/pods instead of using the container runtime API. Collecting logs from files is usually the most efficient way of collecting logs. Default is true. See the Kubernetes Log collection
features.logCollection.containerLogsPath: Allows log collection from the container log path. Set to a different path if you are not using the Docker runtime. Defaults to /var/lib/docker/containers.
features.logCollection.containerSymlinksPath: Allows the log collection to use symbolic links in this directory to validate container ID -> pod. Defaults to /var/log/containers.
features.logCollection.enabled: Enable this option to activate Datadog Agent log collection.
features.logCollection.logsConfigContainerCollectAll: Enable this option to allow log collection for all containers.
features.logCollection.openFilesLimit: Sets the maximum number of log files that the Datadog Agent tails. Increasing this limit can increase resource consumption of the Agent. Default is 100.
features.logCollection.podLogsPath: Allows log collection from pod log path. Defaults to /var/log/pods.
features.logCollection.tempStoragePath: This path (always mounted from the host) is used by Datadog Agent to store information about processed log files. If the Datadog Agent is restarted, it starts tailing the log files immediately. Default to /var/lib/datadog-agent/logs.
features.networkMonitoring.enabled: Enable networking monitoring.
features.orchestratorExplorer.additionalEndpoints: Additional endpoints for shipping the collected data as json in the form of {"https://process.agent.datadoghq.com": ["apikey1", ...], ...}'.
features.orchestratorExplorer.clusterCheck: Configures the Orchestrator Explorer check as a cluster check.
features.orchestratorExplorer.conf.configData: Corresponds to the configuration file content.
features.orchestratorExplorer.conf.configMap.fileKey: Corresponds to the key used in the ConfigMap.Data to store the configuration file content.
features.orchestratorExplorer.conf.configMap.name: Name the ConfigMap.
features.orchestratorExplorer.ddUrl: Set this for the Datadog endpoint for the orchestrator explorer.
features.orchestratorExplorer.enabled: Enable this to activate live Kubernetes monitoring. See Live Containers.
features.orchestratorExplorer.extraTags: Additional tags for the collected data in the form of a b c. In contrast to DD_TAGS, this is a Cluster Agent option that is used to define custom cluster tags.
features.orchestratorExplorer.scrubbing.containers: Deactivate this to stop the scrubbing of sensitive container data (passwords, tokens, etc.).
features.prometheusScrape.additionalConfigs: AdditionalConfigs allows adding advanced Prometheus check configurations with custom discovery rules.
features.prometheusScrape.enabled: Enable Autodiscovering pods and services exposing Prometheus metrics.
features.prometheusScrape.serviceEndpoints: Enable generating dedicated checks for service endpoints.