Live Processes

Introduction

Datadog’s Live Processes gives you real-time visibility into the processes running on your infrastructure. Use Live Processes to:

• View all of your running processes in one place
• Break down the resource consumption on your hosts and containers at the process level
• Query for processes running on a specific host, in a specific zone, or running a specific workload
• Monitor the performance of the internal and third-party software you run using system metrics at two-second granularity
• Add context to your dashboards and notebooks

Installation

If you are using Agent 5, follow this specific installation process. If you are using Agent 6 or 7, see the instructions below.

process_config:process_collection:enabled:true

-v /etc/passwd:/etc/passwd:ro
-e DD_PROCESS_CONFIG_PROCESS_COLLECTION_ENABLED=true

datadog:# (...)processAgent:enabled:trueprocessCollection:true

helm upgrade -f datadog-values.yaml <RELEASE_NAME> datadog/datadog

apiVersion:datadoghq.com/v2alpha1kind:DatadogAgentmetadata:name:datadogspec:global:credentials:apiKey:<DATADOG_API_KEY>features:liveProcessCollection:enabled:true

kubectl apply -n $DD_NAMESPACE -f datadog-agent.yaml

env:- name:DD_PROCESS_CONFIG_PROCESS_COLLECTION_ENABLEDvalue:"true"volumeMounts:- name:passwdmountPath:/etc/passwdreadOnly:truevolumes:- hostPath:path:/etc/passwdname:passwd

{
 "taskDefinitionArn": "...",
 "containerDefinitions": [
 {
 "name": "datadog-agent",
 "image": "public.ecr.aws/datadog/agent:latest",
 ...
 "environment": [
 {
 "name": "DD_PROCESS_AGENT_PROCESS_COLLECTION_ENABLED",
 "value": "true"
 }
 ...
 ]
 ...
 }
 ]
 ...
}

"pidMode": "task"

I/O stats

I/O and open files stats can be collected by the Datadog system-probe, which runs with elevated privileges. To collect these stats, enable the process module of the system-probe:

1. Copy the system-probe example configuration:

   sudo -u dd-agent install -m 0640 /etc/datadog-agent/system-probe.yaml.example /etc/datadog-agent/system-probe.yaml
   

2. Edit /etc/datadog-agent/system-probe.yaml to enable the process module:

   system_probe_config:process_config:enabled:true

3. Restart the Agent:

   sudo systemctl restart datadog-agent
   

   Note: If the systemctl command is not available on your system, run the following command instead: sudo service datadog-agent restart

Optimized process collection footprint

On Linux, the Datadog Agent’s overall footprint is reduced by running container and process collection in the core Datadog Agent (instead of the separate Process Agent). In Datadog Agent v7.65.0+, this is enabled by default. Note: the Process Agent is still required for Cloud Network Monitoring.

The Agent status for this feature is listed under the Process Component section, for example:

=================
Process Component
=================
 Enabled Checks: [process rtprocess]
 System Probe Process Module Status: Not running
 Process Language Detection Enabled: False
 =================
 Process Endpoints
 =================
 https://process.datadoghq.com. - API Key ending with:
 - *****
 =========
 Collector
 =========
 Last collection time: 2026-01-14 10:04:49
 Docker socket: /var/run/docker.sock
 Number of processes: 48
 Number of containers: 0
 Process Queue length: 0
 RTProcess Queue length: 0
 Connections Queue length: 0
 Event Queue length: 0
 Pod Queue length: 0
 Process Bytes enqueued: 0
 RTProcess Bytes enqueued: 0
 Connections Bytes enqueued: 0
 Event Bytes enqueued: 0
 Pod Bytes enqueued: 0
 Drop Check Payloads: []
 Number of submission errors: 0

Process arguments scrubbing

In order to hide sensitive data on the Live Processes page, the Agent scrubs sensitive arguments from the process command line. This feature is enabled by default and any process argument that matches one of the following words has its value hidden.

"password", "passwd", "mysql_pwd", "access_token", "auth_token", "api_key", "apikey", "secret", "credentials", "stripetoken"

Note: The matching is case insensitive.

process_config:scrub_args:truecustom_sensitive_words:['personal_key','*token','sql*','*pass*d*']

process_config:strip_proc_arguments:true

datadog:# (...)processAgent:enabled:trueprocessCollection:trueagents:containers:processAgent:env:- name:DD_SCRUB_ARGSvalue:"true"- name:DD_CUSTOM_SENSITIVE_WORDSvalue:"personal_key,*token,*token,sql*,*pass*d*"

datadog:# (...)processAgent:enabled:trueprocessCollection:trueagents:containers:processAgent:env:- name:DD_STRIP_PROCESS_ARGSvalue:"true"

Queries

Scoping processes

Processes are, by nature, extremely high cardinality objects. To refine your scope to view relevant processes, you can use text and tag filters.

Text filters

When you input a text string into the search bar, fuzzy string search is used to query processes containing that text string in their command lines or paths. Enter a string of two or more characters to see results. Below is Datadog’s demo environment, filtered with the string postgres /9..

Note: /9. has matched in the command path, and postgres matches the command itself.

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

AND

Intersection: both terms are in the selected events (if nothing is added, AND is taken by default)
Example: java AND elasticsearch

OR

Union: either term is contained in the selected events
Example: 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
Example: java NOT elasticsearch or java !elasticsearch

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

Tag filters

You can also filter your processes using Datadog tags, such as host, pod, user, and service. Input tag filters directly into the search bar, or select them in the facet panel on the left of the page.

Datadog automatically generates a command tag, so that you can filter for:

• Third-party software, for example: command:mongod, command:nginx
• Container management software, for example: command:docker, command:kubelet
• Common workloads, for example: command:ssh, command:CRON

Containerized environment tags

Furthermore, processes in ECS containers are also tagged by:

• task_name
• task_version
• ecs_cluster

Processes in Kubernetes containers are tagged by:

• pod_name
• kube_service
• kube_namespace
• kube_replica_set
• kube_daemon_set
• kube_job
• kube_deployment
• kube_cluster_name

If you have configuration for Unified Service Tagging in place, env, service, and version are picked up automatically. Having these tags available lets you tie together APM, logs, metrics, and process data. Note: This setup applies to containerized environments only.

Rules to create custom tags

You can create rule definitions to add manual tags to processes based on the command line.

1. On the Manage Process Tags tab, select the New Process Tag Rule button
2. Select a process to use as a reference
3. Define the parsing and match criteria for your tag
4. If validation passes, create a new rule

After a rule is created, tags are available for all process command line values that match the rule criteria. These tags are available in search and can be used in the definition of Live Process Monitors and Custom Metrics.

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 Processes page click on the Show Summary graph button then select the “Scatter Plot” tab:

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

The options at the top of the graph allow 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).

Process monitors

Use the Live Process Monitor to generate alerts based on the count of any group of processes across hosts or tags. You can configure process alerts in the Monitors page. To learn more, see the Live Process Monitor documentation.

Processes in dashboards and notebooks

You can graph process metrics in dashboards and notebooks using the Timeseries widget. To configure:

1. Select Processes as a data source
2. Filter using text strings in the search bar
3. Select a process metric to graph
4. Filter using tags in the From field

Monitoring third-party software

Autodetected integrations

Datadog uses process collection to autodetect the technologies running on your hosts. This identifies Datadog integrations that can help you monitor these technologies. These auto-detected integrations are displayed in the Integrations search:

Each integration has one of two status types:

• + Detected: This integration is not enabled on any host(s) running it.
• ✓ Partial Visibility: This integration is enabled on some, but not all relevant hosts are running it.

Hosts that are running the integration, but where the integration is not enabled, can be found in the Hosts tab of the integrations tile.

Integration views

After a third-party software has been detected, Live Processes helps to analyze the performance of that software.

1. To start, click on Views at the top right of the page to open a list of pre-set options, including Nginx, Redis, and Kafka.
2. Select a view to scope the page to only the processes running that software.
3. When inspecting a heavy process, shift to the Integration Metrics tab to analyze the health of the software on the underlying host. If you have already enabled the relevant Datadog integration, you can view all performance metrics collected from the integration to distinguish between a host-level and software-level issue. For instance, seeing correlated spikes in process CPU and MySQL query latency may indicate that an intensive operation, such as a full table scan, is delaying the execution of other MySQL queries relying on the same underlying resources.

You can customize integration views (for example, when aggregating a query for Nginx processes by host) and other custom queries by clicking the +Save button at the top of the page. This saves your query, table column selections, and visualization settings. Create saved views for quick access to the processes you care about without addition configuration, and to share process data with your teammates.

Processes across the platform

Live Containers

Live Processes adds extra visibility to your container deployments by monitoring the processes running on each of your containers. Click on a container in the Live Containers page to view its process tree, including the commands it is running and their resource consumption. Use this data alongside other container metrics to determine the root cause of failing containers or deployments.

APM

In APM Traces, you can click on a service’s span to see the processes running on its underlying infrastructure. A service’s span processes are correlated with the hosts or pods on which the service runs at the time of the request. Analyze process metrics such as CPU and RSS memory alongside code-level errors to distinguish between application-specific and wider infrastructure issues. Clicking on a process brings you to the Live Processes page. Related processes are not supported for serverless and browser traces.

Cloud Network Monitoring

When you inspect a dependency in the Network Analytics page, you can view processes running on the underlying infrastructure of the endpoints such as services communicating with one another. Use process metadata to determine whether poor network connectivity (indicated by a high number of TCP retransmits) or high network call latency (indicated by high TCP round-trip time) could be due to heavy workloads consuming those endpoints’ resources, and thus, affecting the health and efficiency of their communication.

Real-time monitoring

Processes are normally collected at 10s resolution. While actively working with the Live Processes page, metrics are collected at 2s resolution and displayed in real time, which is important for volatile metrics such as CPU. However, for historical context, metrics are ingested at the default 10s resolution.

Additional information

• Real-time (2s) data collection is turned off after 30 minutes. To resume real-time collection, refresh the page.
• In container deployments, the /etc/passwd file mounted into the docker-dd-agent is necessary to collect usernames for each process. This is a public file and the Process Agent does not use any fields except the username. If the Agent is running unprivileged, the mount does not occur. Even without access to the /etc/passwd file, all features except the user metadata field still function. Note: Live Processes only uses the host passwd file and does not perform username resolution for users created within containers.

Further Reading

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