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NATS 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 <a href="/integrations/nats_consumer-influxdb/">NATS and InfluxDB</a>.

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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.

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Input and output integration overview

<p>The NATS Consumer Input Plugin enables real-time data consumption from NATS messaging subjects, integrating seamlessly into the Telegraf data pipeline for monitoring and metrics gathering.</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

NATS

<p>The NATS Consumer Plugin allows Telegraf to read metrics from specified NATS subjects and create metrics based on supported input data formats. Utilizing a Queue Group allows multiple instances of Telegraf to read from a NATS cluster in parallel, enhancing throughput and reliability. This plugin also supports various authentication methods, including username/password, NATS credentials files, and nkey seed files, ensuring secure communication with the NATS servers. It is particularly useful in environments where data persistence and message reliability are critical, thanks to features such as JetStream that facilitate the consumption of historical messages. Additionally, the ability to configure various operational parameters makes this plugin suitable for high-throughput scenarios while maintaining performance integrity.</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

NATS

<pre><code class="language-toml">[[inputs.nats_consumer]] ## urls of NATS servers servers = ["nats://localhost:4222"] ## subject(s) to consume ## If you use jetstream you need to set the subjects ## in jetstream_subjects subjects = ["telegraf"] ## jetstream subjects ## jetstream is a streaming technology inside of nats. ## With jetstream the nats-server persists messages and ## a consumer can consume historical messages. This is ## useful when telegraf needs to restart it don't miss a ## message. You need to configure the nats-server. ## https://docs.nats.io/nats-concepts/jetstream. jetstream_subjects = ["js_telegraf"] ## name a queue group queue_group = "telegraf_consumers" ## Optional authentication with username and password credentials # username = "" # password = "" ## Optional authentication with NATS credentials file (NATS 2.0) # credentials = "/etc/telegraf/nats.creds" ## Optional authentication with nkey seed file (NATS 2.0) # nkey_seed = "/etc/telegraf/seed.txt" ## Use Transport Layer Security # secure = 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 ## Sets the limits for pending msgs and bytes for each subscription ## These shouldn't need to be adjusted except in very high throughput scenarios # pending_message_limit = 65536 # pending_bytes_limit = 67108864 ## Max undelivered messages ## This plugin uses tracking metrics, which ensure messages are read to ## outputs before acknowledging them to the original broker to ensure data ## is not lost. This option sets the maximum messages to read from the ## broker that have not been written by an output. ## ## This value needs to be picked with awareness of the agent's ## metric_batch_size value as well. Setting max undelivered messages too high ## can result in a constant stream of data batches to the output. While ## setting it too low may never flush the broker's messages. # max_undelivered_messages = 1000 ## Data format to consume. ## Each data format has its own unique set of configuration options, read ## more about them here: ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md data_format = "influx" </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

NATS

<ol> <li> <p><strong>Real-Time Analytics Dashboard</strong>: Utilize the NATS plugin to gather metrics from various NATS subjects in real time and feed them into a centralized analytics dashboard. This setup allows for immediate visibility into live application performance, enabling teams to react swiftly to operational issues or performance degradation.</p> </li> <li> <p><strong>Distributed System Monitoring</strong>: Deploy multiple instances of Telegraf configured with the NATS plugin across a distributed architecture. This approach allows teams to aggregate metrics from various microservices efficiently, providing a holistic view of system health and performance while ensuring no messages are dropped during transmission.</p> </li> <li> <p><strong>Historical Message Recovery</strong>: Leverage the capabilities of NATS JetStream along with this plugin to recover and process historical messages after Telegraf has been restarted. This feature is particularly beneficial for applications that require high reliability, ensuring that no critical metrics are lost even in case of service disruptions.</p> </li> <li> <p><strong>Dynamic Load Balancing</strong>: Implement a dynamic load balancing scenario where Telegraf instances consume messages from a NATS cluster based on load. Adjust the queue group settings to control the number of active consumers, allowing for better resource utilization and performance scaling as demand fluctuations occur.</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>

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.

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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