Kibana and Clarify Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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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 Kibana and InfluxDB.

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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

Input and output integration overview

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.

The Clarify plugin allows users to publish Telegraf metrics directly to Clarify, enabling enhanced analysis and monitoring capabilities.

Integration details

Kibana

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.

Clarify

This plugin facilitates the writing of Telegraf metrics to Clarify, a platform for managing and analyzing time series data. By transforming metrics into Clarify signals, this output plugin enables seamless integration of collected telemetry data into the Clarify ecosystem. Users must obtain valid credentials, either through a credentials file or basic authentication, to configure the plugin. The configuration also provides options for fine-tuning how metrics are mapped to signals in Clarify, including the ability to specify unique identifiers using tags. Given that Clarify supports only floating point values, the plugin ensures that any unsupported types are effectively filtered out during the publishing process. This comprehensive connectivity aligns with use cases in monitoring, data analysis, and operational insights.

Configuration

Kibana

[[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 & 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"

Clarify

[[outputs.clarify]]
  ## Credentials File (Oauth 2.0 from Clarify integration)
  credentials_file = "/path/to/clarify/credentials.json"

  ## Clarify username password (Basic Auth from Clarify integration)
  username = "i-am-bob"
  password = "secret-password"

  ## Timeout for Clarify operations
  # timeout = "20s"

  ## Optional tags to be included when generating the unique ID for a signal in Clarify
  # id_tags = []
  # clarify_id_tag = 'clarify_input_id'

Input and output integration examples

Kibana

  1. Kibana Health Monitoring: 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.

  2. Automated Alerting System: 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.

  3. Resource Optimization Strategy: 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.

Clarify

  1. Automated Data Monitoring: By integrating the Clarify plugin with sensor data collection, organizations can automate the monitoring of environmental conditions, such as temperature and humidity. The plugin processes metrics in real-time, sending updates to Clarify where they can be analyzed for trends, alerts, and historical tracking. This use case makes it easier to maintain optimal conditions in data centers or production environments, reducing the risk of equipment failures.

  2. Performance Metrics Analysis: Companies can leverage this plugin to send application performance metrics to Clarify. By transmitting key indicators such as response times and error rates, developers and operations teams can utilize Clarify’s capabilities to visualize and analyze application performance over time. This insight can drive improvements in user experience and help identify areas in need of optimization.

  3. Sensor Data Aggregation: Utilizing the plugin to push data from multiple sensors to Clarify allows for a comprehensive view of physical environments. This aggregation is particularly beneficial in sectors such as agriculture, where metrics from various sensors can be correlated to decision-making about resource allocations, pest control, and crop management. The plugin ensures the data is accurately mapped and transformed for effective analysis.

  4. Real-Time Alerts and Notifications: Implement the Clarify plugin to trigger real-time alerts based on predefined thresholds within the metrics being sent. For instance, if temperature readings exceed certain levels, alerts can be generated and sent to operational staff. This proactive approach allows for immediate responses to potential issues, enhancing operational reliability and safety.

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.

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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