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ntpq and Elasticsearch Integration

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider using the <a href="/integrations/ntpq-influxdb/">ntpq plugin with InfluxDB</a>.

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Input and output integration overview

<p>The ntpq plugin collects standard metrics related to the Network Time Protocol (NTP) by executing the ntpq command. It gathers essential information about the synchronization state of the local machine with remote NTP servers, providing valuable insights into timekeeping accuracy and network performance.</p>

<p>The Telegraf Elasticsearch Plugin seamlessly sends metrics to an Elasticsearch server. The plugin handles template creation and dynamic index management, and supports various Elasticsearch-specific features to ensure data is formatted correctly for storage and retrieval.</p>

Integration details

ntpq

<p>The ntpq Telegraf plugin provides a way to gather metrics from the Network Time Protocol (NTP) by querying the NTP server using the <code>ntpq</code> executable. This plugin collects a variety of metrics related to the synchronization status with remote NTP servers, including delay, jitter, offset, polling frequency, and reachability. These metrics are crucial for understanding the performance and reliability of time synchronization efforts in systems that rely on accurate timekeeping. NTP plays a vital role in networked environments, enabling synchronized clocks across devices which is essential for logging, coordination of activities, and security protocols. Through this plugin, users can monitor the effectiveness of their time synchronization processes, making it easier to identify issues related to network delays or misconfigurations, thus ensuring that systems remain in sync and operate efficiently.</p>

Elasticsearch

<p>This plugin writes metrics to Elasticsearch, a distributed, RESTful search and analytics engine capable of storing large amounts of data in near real-time. It is designed to handle Elasticsearch versions 5.x through 7.x and utilizes its dynamic template features to manage data type mapping properly. The plugin supports advanced features such as template management, dynamic index naming, and integration with OpenSearch. It also allows configurations for authentication and health monitoring of the Elasticsearch nodes.</p>

Configuration

ntpq

<pre><code class="language-toml">[[inputs.ntpq]] ## Servers to query with ntpq. ## If no server is given, the local machine is queried. # servers = [] ## If false, set the -n ntpq flag. Can reduce metric gather time. ## DEPRECATED since 1.24.0: add '-n' to 'options' instead to skip DNS lookup # dns_lookup = true ## Options to pass to the ntpq command. # options = "-p" ## Output format for the 'reach' field. ## Available values are ## octal -- output as is in octal representation e.g. 377 (default) ## decimal -- convert value to decimal representation e.g. 371 -&gt; 249 ## count -- count the number of bits in the value. This represents ## the number of successful reaches, e.g. 37 -&gt; 5 ## ratio -- output the ratio of successful attempts e.g. 37 -&gt; 5/8 = 0.625 # reach_format = "octal" </code></pre>

Elasticsearch

<pre><code class="language-toml"> [[outputs.elasticsearch]] ## The full HTTP endpoint URL for your Elasticsearch instance ## Multiple urls can be specified as part of the same cluster, ## this means that only ONE of the urls will be written to each interval urls = [ "http://node1.es.example.com:9200" ] # required. ## Elasticsearch client timeout, defaults to "5s" if not set. timeout = "5s" ## Set to true to ask Elasticsearch a list of all cluster nodes, ## thus it is not necessary to list all nodes in the urls config option enable_sniffer = false ## Set to true to enable gzip compression enable_gzip = false ## Set the interval to check if the Elasticsearch nodes are available ## Setting to "0s" will disable the health check (not recommended in production) health_check_interval = "10s" ## Set the timeout for periodic health checks. # health_check_timeout = "1s" ## HTTP basic authentication details. ## HTTP basic authentication details # username = "telegraf" # password = "mypassword" ## HTTP bearer token authentication details # auth_bearer_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9" ## Index Config ## The target index for metrics (Elasticsearch will create if it not exists). ## You can use the date specifiers below to create indexes per time frame. ## The metric timestamp will be used to decide the destination index name # %Y - year (2016) # %y - last two digits of year (00..99) # %m - month (01..12) # %d - day of month (e.g., 01) # %H - hour (00..23) # %V - week of the year (ISO week) (01..53) ## Additionally, you can specify a tag name using the notation {{tag_name}} ## which will be used as part of the index name. If the tag does not exist, ## the default tag value will be used. # index_name = "telegraf-{{host}}-%Y.%m.%d" # default_tag_value = "none" index_name = "telegraf-%Y.%m.%d" # required. ## Optional Index Config ## Set to true if Telegraf should use the "create" OpType while indexing # use_optype_create = false ## Optional TLS Config # tls_ca = "/etc/telegraf/ca.pem" # tls_cert = "/etc/telegraf/cert.pem" # tls_key = "/etc/telegraf/key.pem" ## Use TLS but skip chain &amp; host verification # insecure_skip_verify = false ## Template Config ## Set to true if you want telegraf to manage its index template. ## If enabled it will create a recommended index template for telegraf indexes manage_template = true ## The template name used for telegraf indexes template_name = "telegraf" ## Set to true if you want telegraf to overwrite an existing template overwrite_template = false ## If set to true a unique ID hash will be sent as sha256(concat(timestamp,measurement,series-hash)) string ## it will enable data resend and update metric points avoiding duplicated metrics with different id's force_document_id = false ## Specifies the handling of NaN and Inf values. ## This option can have the following values: ## none -- do not modify field-values (default); will produce an error if NaNs or infs are encountered ## drop -- drop fields containing NaNs or infs ## replace -- replace with the value in "float_replacement_value" (default: 0.0) ## NaNs and inf will be replaced with the given number, -inf with the negative of that number # float_handling = "none" # float_replacement_value = 0.0 ## Pipeline Config ## To use a ingest pipeline, set this to the name of the pipeline you want to use. # use_pipeline = "my_pipeline" ## Additionally, you can specify a tag name using the notation {{tag_name}} ## which will be used as part of the pipeline name. If the tag does not exist, ## the default pipeline will be used as the pipeline. If no default pipeline is set, ## no pipeline is used for the metric. # use_pipeline = "{{es_pipeline}}" # default_pipeline = "my_pipeline" # # Custom HTTP headers # To pass custom HTTP headers please define it in a given below section # [outputs.elasticsearch.headers] # "X-Custom-Header" = "custom-value" ## Template Index Settings ## Overrides the template settings.index section with any provided options. ## Defaults provided here in the config # template_index_settings = { # refresh_interval = "10s", # mapping.total_fields.limit = 5000, # auto_expand_replicas = "0-1", # codec = "best_compression" # } </code></pre>

Input and output integration examples

ntpq

<ol> <li> <p><strong>Network Time Monitoring Dashboard</strong>: Utilize the ntpq plugin to create a centralized monitoring dashboard for tracking the reliability and performance of network time synchronization across multiple servers. By visualizing metrics such as delay and jitter, system administrators can quickly identify which servers are providing accurate time versus those with significant latency issues, ensuring that all systems remain synchronized effectively.</p> </li> <li> <p><strong>Automated Alert System for Time Drift</strong>: Implement an automated alert system that leverages ntpq metrics to notify operations teams when time drift exceeds acceptable thresholds. By analyzing the offset and jitter values, the system can trigger alerts if any remote NTP server is out of sync, allowing for swift remediation actions to maintain time accuracy across critical infrastructure.</p> </li> <li> <p><strong>Comparative Analysis of Time Sources</strong>: Use the ntpq plugin to perform a comparative analysis of different NTP servers over time. By querying multiple NTP sources and monitoring their metrics, organizations can evaluate the performance and reliability of their time sources, making informed decisions about which NTP servers to configure as primary or secondary in their environments.</p> </li> <li> <p><strong>Historical Performance Tracking for NTP</strong>: Gather historical performance data on various NTP servers using the ntpq plugin, enabling long-term trend analysis for timekeeping accuracy. This can help organizations identify patterns or recurring issues related to specific servers, informing future decisions about infrastructure changes or adjustments related to time synchronization strategies.</p> </li> </ol>

Elasticsearch

<ol> <li> <p><strong>Time-based Indexing</strong>: Use this plugin to store metrics in Elasticsearch to index each metric based on the time collected. For example, CPU metrics can be stored in a daily index named<code>telegraf-2023.01.01</code>, allowing easy time-based queries and retention policies.</p> </li> <li> <p><strong>Dynamic Templates Management</strong>: Utilize the template management feature to automatically create a custom template tailored to your metrics. This allows you to define how different fields are indexed and analyzed without manually configuring Elasticsearch, ensuring an optimal data structure for querying.</p> </li> <li> <p><strong>OpenSearch Compatibility</strong>: If you are using AWS OpenSearch, you can configure this plugin to work seamlessly by activating compatibility mode, ensuring your existing Elasticsearch clients remain functional and compatible with newer cluster setups.</p> </li> </ol>

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Useful Links

Documentation

Telegraf Quickstart Training

Infrastructure Monitoring with Telegraf

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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