Install Metricbeat on every server you want to observe, enable its System module, send the events to Elasticsearch, and inspect them in Kibana. The System module collects local CPU, load, memory, network, process, filesystem, file-system statistics and uptime data; service modules add metrics for supported applications. Elasticsearch stores and searches the events, while Kibana supplies the dashboards and time-based views.
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A reliable deployment depends on four choices: which metricsets you need, how often they run, which credentials they use, and whether the host security policy permits the required operating-system reads. The procedure below takes you from an empty host to a working metricbeat-* data view, then covers tuning and the failure modes that make a new installation look broken.
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What Metricbeat collects and where the data goes
Metricbeat is a lightweight agent installed on each server being monitored. It gathers measurements from the local operating system and enabled services, turns each observation into a structured event, and publishes those events to a configured destination. In the standard Elastic workflow, Elasticsearch receives, indexes and searches the events; Kibana reads the resulting indices and presents dashboards, tables and time-series charts.
The collection model is modular. A module contains the logic for a service or platform, while a metricset is a related group of measurements fetched by that module. The System module is the starting point for host telemetry. Modules are normally configured as YAML files in modules.d; settings there take precedence over equivalent settings in metricbeat.yml. That precedence lets a host keep global output and security settings in one file while tailoring collection locally.
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| Component | Role | Typical location or example |
|---|---|---|
| Metricbeat agent | Runs on the server and schedules collection | One installation per monitored host |
| Module | Knows how to obtain metrics from a service or operating system | system module |
| Metricset | Defines a related set of fields emitted by a module | cpu, memory, filesystem |
| Elasticsearch | Receives, indexes and searches Metricbeat events | Configured output endpoint |
| Kibana | Displays dashboards and ad-hoc searches | metricbeat-* data view |
This is a host-collection design, not a remote scrape of arbitrary machines. The System module reads the server where Metricbeat is running, so it does not use a hosts setting. If ten servers need metrics, install and configure ten agents (or use an approved image or configuration-management process to distribute the same configuration).
Plan the deployment before installing
Choose the signals you actually need
Start with an operational question rather than enabling every available metricset. CPU saturation, memory pressure, network throughput, storage capacity and process health are common requirements, but a short-lived troubleshooting task may need only CPU and filesystem data. Every additional metricset creates work on the host and more events to index.
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- Capacity planning: CPU, memory, filesystem and network metricsets provide the baseline.
- Availability checks: uptime and load help distinguish a reboot or stalled host from an application fault.
- Application diagnosis: process and process-summary data show which workloads consume resources.
- Storage analysis: filesystem reports mounted filesystems, while fsstat provides aggregate file-system statistics where supported.
- Socket investigation: socket-summary data can help identify connection pressure, subject to operating-system permissions.
Decide how fresh the data must be
The period controls how often a metricset runs. A ten-second interval gives faster feedback than a one-minute interval, but it also increases host reads, event volume, network traffic and Elasticsearch indexing work. Set the period per metricset or at module level according to the incident-response or capacity-planning requirement. A single fast interval for every metricset is rarely necessary.
Prepare identities and network access
Create or obtain credentials that can publish to the chosen Elasticsearch destination and, if setup loads assets, permissions that allow the required template and dashboard operations. Use the least privilege that still permits collection and publishing. Confirm DNS or routing from the monitored server to Elasticsearch, the destination port and any TLS requirements before debugging Metricbeat itself.
Install Metricbeat on the monitored server
Install the package or other distribution that matches the operating system and the Elastic stack release you run. Package paths, service names and configuration locations can differ between distributions and releases, so use the installation instructions shipped for that exact package. After installation, identify the executable and configuration directory; the examples below assume the conventional /etc/metricbeat layout on Linux.
Do not copy a configuration from a different major release without checking its syntax. Module names, fields and setup behavior can change, and a configuration accepted by one release may be rejected or silently omit data in another.
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Metricbeat needs an authenticated output before it can publish events. Edit metricbeat.yml and configure the Elasticsearch output supplied by your deployment. Keep credentials out of shell history and world-readable files; use the package’s supported secret mechanism where available, and restrict the configuration file to the service account and administrators.
# /etc/metricbeat/metricbeat.yml
output.elasticsearch:
hosts: ["https://elasticsearch.example.internal:9200"]
username: "metricbeat_writer"
password: "use-the-approved-secret-method"
The endpoint and account above are illustrative values, not universal defaults. Replace them with the address, TLS settings and credentials issued for your environment. If your deployment uses certificates, configure the trusted certificate authorities and verification settings required by that release rather than disabling verification.
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Keep output configuration in metricbeat.yml and module-specific collection choices in modules.d. Because module files take precedence over equivalent module settings, a host-level override in modules.d can explain why changing a global value appears to have no effect.
Enable and tailor the System module
Enable the module
Use the installed package’s module-management command to enable the System module. On conventional Linux packages this is commonly:
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Select metricsets and set the period
The documented System module metricsets are cpu, load, memory, network, process, process_summary, socket_summary, filesystem, fsstat and uptime. You can select a subset. A minimal Linux-oriented configuration that covers the most common host questions is:
# /etc/metricbeat/modules.d/system.yml
- module: system
metricsets:
- cpu
- memory
- network
- process
- filesystem
- uptime
period: 10s
process.cgroups.enabled: true
The ten-second interval in this example is a starting point, not a required value. Increase it when indexing volume or host overhead matters more than near-real-time visibility; shorten it only for a defined operational need. Add load, fsstat or socket_summary when those signals answer a question you actually monitor. The process metricset emits one document per process, so enabling it on a host with many short-lived processes can create substantially more events than host-level metricsets.
Understand process collection
The process metricset supports regular-expression filtering, allowing you to focus on selected process names instead of indexing every process. Cgroup collection is enabled by default when that metricset is active; the example sets it explicitly so the intent is visible. Process CPU percentages based on deltas require at least two observations. The first document for a process, or a process that exits between observations, may therefore lack a percentage field. Treat that absence as an expected characteristic of delta-based measurement, not automatically as a publishing failure.
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Add service modules when host metrics are not enough
Enable a service module for each supported application that needs its own metrics. A service module supplies service-specific collection logic and one or more metricsets; its configuration belongs in a file under modules.d. Keep the System module enabled for host context even when a service module is present, because application throughput is difficult to interpret without CPU, memory, network and filesystem information.
For every additional module, check four items before starting it:
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- the module is included in the Metricbeat release installed on the host;
- the service endpoint, socket or credentials are reachable from that host;
- the selected metricsets and period match the diagnostic value you need;
- the service account has read-only access wherever possible.
Use the module’s packaged example as the starting point, then remove unused metricsets. Avoid enabling a broad set simply because it is available: unnecessary events increase storage and can obscure the signals operators need during an incident.
Load templates and dashboards with setup
Before starting continuous collection, run the setup operation documented for the installed package and release. In many Linux package installations the command is:
sudo metricbeat setupSome environments require additional flags, a Kibana endpoint or an explicit configuration path. Use the exact syntax for your release. Setup commonly loads index templates and, where applicable, Kibana assets so that fields are mapped correctly and prebuilt dashboards can render the incoming data. It is an administrative operation, so the credentials used for setup may need permissions beyond those granted to the long-running publisher.
If your security model separates setup from runtime publishing, run setup once with an administrator-approved identity, then store only the lower-privilege publishing credentials in the service configuration. Record which release created the templates and dashboards; repeat setup deliberately during upgrades rather than treating it as an arbitrary troubleshooting command.
Start Metricbeat and verify the first events
Start and enable the service
On a systemd-based Linux installation, the conventional service command is:
sudo systemctl enable --now metricbeatUse the service manager appropriate to your operating system if systemd is not present. Check the service status and logs immediately after starting it. A running process alone is not proof of successful publishing; the logs must show that modules loaded and events were accepted by the output.
Open Kibana
- Open Kibana and go to the data-view management area.
- Select or create the
metricbeat-*data view used by your deployment. - Open Discover or a Metricbeat dashboard and choose a time range that includes the expected collection period.
- Filter on the host name and inspect fields from the enabled metricsets, such as CPU, memory, filesystem, network and uptime values.
The default Kibana time filter in the quick-start path shows only the last 15 minutes. When validating a newly started agent, widen the range if installation, setup or troubleshooting took longer than that window. Also confirm that the selected data view is metricbeat-*; a correct agent can appear silent when Discover is pointed at another index pattern.
Use a repeatable verification checklist
- Configuration: YAML parses without errors and the intended module file is enabled.
- Authentication: the publishing identity is valid and authorized for the destination.
- Connectivity: the host can resolve and reach Elasticsearch, including TLS negotiation when enabled.
- Collection: logs show the selected metricsets starting at the configured period.
- Indexing: Elasticsearch receives new
metricbeat-*documents with current timestamps. - Visualization: Kibana uses the matching data view and a time range that covers those timestamps.
- Content: expected fields are present; absent process percentages during the first observation are not, by themselves, an error.
Perform this checklist on one host before rolling the configuration to a fleet. It separates collection problems from destination, permission and visualization problems and prevents a dashboard query from becoming the first debugging tool.
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Troubleshoot common failures
Kibana is empty
First verify that the Metricbeat service is running and that its logs do not report authentication, TLS or connection errors. Next confirm that the credentials permit publishing and that Elasticsearch is receiving current documents. In Kibana, select metricbeat-* and expand the time range beyond the default 15 minutes. A wrong data view or a time filter that excludes the first events is more common than a broken dashboard.
The System module starts but fields are missing
Inspect the enabled metricsets in modules.d/system.yml. A metricset omitted from that list cannot emit its fields. Check the module logs for operating-system access errors, and compare the running configuration with the file you edited; a duplicate or higher-precedence module setting can override a value in metricbeat.yml.
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Process CPU percentages are calculated from changes between observations. Allow at least two collection periods for a long-lived process, and expect no percentage for a process that terminates before the next sample. If entire process documents are missing, investigate permissions, process filters and host security controls rather than waiting indefinitely.
Permission or security-policy errors appear
Grant only the permissions required by the selected metricsets, then inspect the operating-system security policy. On Linux, AppArmor and other Linux security modules can block access to protected process interfaces even when Metricbeat does not directly invoke ptrace. A service account may therefore have a readable file path in the traditional Unix permission model and still receive denials from a mandatory access-control policy. Adjust the policy through your normal security process, or disable the metricset that requires the blocked interface if that signal is not essential.
Event volume or host overhead is too high
Reduce the number of metricsets, lengthen their periods, or filter process collection to the workloads that matter. Process-level documents are often the largest contributor on busy hosts. Measure the effect after each change so that a lower event rate does not accidentally remove the metric needed for an alert or capacity report.
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Standardize configuration without erasing local differences
Distribute a reviewed baseline containing the output, authentication method and System module selection, then permit explicit host or role overrides for service modules and periods. Keep the list of enabled metricsets in version control and document why a non-default period exists. This makes a sudden rise in event volume traceable to a configuration change rather than a mysterious Elasticsearch workload spike.
Separate setup privileges from runtime privileges
Template and dashboard loading is an administrative task; continuous publishing is not. Use a setup identity with the permissions required to install assets, then run the service with a narrower identity that can write the intended Metricbeat data only. Rotate credentials through the same process used for other infrastructure agents and avoid embedding long-lived secrets in copied command lines.
Watch freshness as well as service state
A service can remain active while output is blocked by a revoked credential, a failed TLS handshake or a network partition. Monitor the arrival time of recent Metricbeat documents and alert when it exceeds the configured period by an agreed margin. Compare the observed interval with the configured period after upgrades; a change in module defaults or scheduling can affect both freshness and event volume.
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Plan for upgrades
Read the release-specific Metricbeat and module notes before upgrading. Validate configuration syntax, run the documented setup operation when templates or dashboards need updating, and test one host before broad deployment. Keep the previous configuration available for rollback, but do not reuse old templates blindly when field definitions have changed.
Metricbeat compared with other collectors
The right collector depends on the destination and operating model, not on a universal feature count. Use these axes when evaluating an alternative:
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| Decision axis | Metricbeat implication | Question to ask about an alternative |
|---|---|---|
| Collection model | Agent installed on each host; System reads local interfaces | Does the tool require an agent, or does it scrape remotely? |
| Built-in breadth | Modular host and service metricsets, with packaged configuration and dashboards where supported | Are the services you run covered without custom exporters? |
| Interval and volume | Per-metricset periods let you trade freshness against overhead | Can collection frequency be tuned independently for high- and low-value signals? |
| Permissions | Some metricsets need protected operating-system interfaces and policy exceptions | What access does the collector require on hardened hosts? |
| Destination | Natural fit when Elasticsearch is the storage and search layer | Does the tool write directly to your required backend without an extra bridge? |
| Visualization | Kibana data views and prebuilt assets fit the Elastic workflow | Will dashboards, alerting and field naming integrate with your existing stack? |
| Operational overhead | One agent per host plus module, credential and upgrade management | Does your organization already standardize another agent? |
Metricbeat is strongest when an organization already operates Elasticsearch and Kibana and wants ready-made modules plus host-local collection. A Prometheus-native scraping design, vendor-neutral storage requirement or mandatory existing agent standard can justify a different collector even when Metricbeat could gather the same basic CPU and memory values.
Production checklist
- Install the release matched to the operating system and Elastic stack.
- Configure an authenticated, TLS-appropriate output in
metricbeat.yml. - Enable the System module and select only required metricsets.
- Set periods based on freshness requirements and acceptable host and index overhead.
- Enable service modules only after verifying endpoints, credentials and permissions.
- Run the release-specific setup command to load templates and dashboards where applicable.
- Start the service and inspect logs for module and output errors.
- Verify current documents in Elasticsearch through Kibana’s
metricbeat-*data view. - Check process-percentage behavior after at least two observations.
- Document security-policy exceptions, credential ownership, periods and rollback steps.
What a healthy result looks like
After setup, each monitored host should contribute regularly timestamped documents to the metricbeat-* indices. Discover should show the fields corresponding to the metricsets you enabled, and dashboards should populate after the selected time range includes those documents. CPU, memory, network, filesystem and uptime data should arrive at the configured period; process records may appear immediately while delta-derived CPU percentages become meaningful on the following observation. If those conditions hold, you have a functioning baseline that can be extended with service modules without changing the basic Elasticsearch-and-Kibana workflow.
Frequently Asked Questions
Does the System module monitor a remote server?
No. The System module reads the operating system of the server where that Metricbeat instance runs and does not need a hosts setting. Install an agent on each host you want to monitor.
Why is a process CPU percentage missing from the first event?
The percentage is based on a delta between observations. Metricbeat needs at least two collection periods, and a very short-lived process may end before a second observation is available.
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Check that the service is running, publishing credentials and connectivity are valid, the metricbeat-* data view is selected, and Kibana’s time range includes the collection period rather than only an expired initial 15-minute window.
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