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Kibana 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/kibana-influxdb/">Kibana and InfluxDB</a>.

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Infrastructure Monitoring with Telegraf

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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 Kibana plugin enables users to obtain status metrics from Kibana, a data visualization tool for Elasticsearch. By connecting to the Kibana API, this plugin captures various performance indicators and the health status of the Kibana service.</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

Kibana

<p>The Kibana input plugin is designed to query the Kibana API to gather service status information. This plugin allows users to monitor their Kibana instances effectively by pulling metrics related to its health, performance, and operational metrics. By querying the Kibana API, this plugin provides insights into key parameters such as the current health status (green, yellow, red), uptime, heap memory usage, and request performance metrics. This information is crucial for administrators and operational teams looking to maintain optimal system performance and quickly address any issues that may arise. The configuration settings allow for flexible integration with other components in a microservices architecture, facilitating comprehensive monitoring solutions aligned with organizational needs, making it an essential tool for those leveraging the Elastic Stack in their infrastructure.</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

Kibana

<pre><code class="language-toml">[[inputs.kibana]] ## Specify a list of one or more Kibana servers servers = ["http://localhost:5601"] ## Timeout for HTTP requests timeout = "5s" ## HTTP Basic Auth credentials # username = "username" # password = "pa$$word" ## 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 ## If 'use_system_proxy' is set to true, Telegraf will check env vars such as ## HTTP_PROXY, HTTPS_PROXY, and NO_PROXY (or their lowercase counterparts). ## If 'use_system_proxy' is set to false (default) and 'http_proxy_url' is ## provided, Telegraf will use the specified URL as HTTP proxy. # use_system_proxy = false # http_proxy_url = "http://localhost:8888" </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

Kibana

<ol> <li> <p><strong>Kibana Health Monitoring</strong>: Implement a dedicated dashboard to periodically poll the metrics from Kibana. This setup allows operations teams to have a real-time view of their Kibana instances’ health and metrics, enabling proactive performance management and immediate response capabilities in case of service degradation or failure.</p> </li> <li> <p><strong>Automated Alerting System</strong>: Integrate the metrics gathered from the Kibana plugin with an alerting system using tools like Prometheus or PagerDuty. By setting thresholds for key metrics (e.g., response time or heap usage), this integration can automatically notify the relevant personnel of performance issues, thereby reducing downtime and improving the response time for operational issues.</p> </li> <li> <p><strong>Resource Optimization Strategy</strong>: Use the memory usage and response time metrics collected by this plugin to formulate strategies for optimizing resource allocation in Kubernetes or other orchestration platforms. By analyzing trends over time, teams can adjust resource limits and requests dynamically, ensuring that Kibana instances function efficiently without over-provisioning resources.</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

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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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