Kibana and Sumo Logic Integration

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 Sumo Logic plugin is designed to facilitate the sending of metrics from Telegraf to Sumo Logic’s HTTP Source. By utilizing this plugin, users can analyze their metric data in the Sumo Logic platform, leveraging various output data formats.

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.

Sumo Logic

This plugin facilitates the transmission of metrics to Sumo Logic’s HTTP Source, employing specified data formats for HTTP messages. Telegraf, which must be version 1.16.0 or higher, can send metrics encoded in several formats, including graphite, carbon2, and prometheus. These formats correspond to different content types recognized by Sumo Logic, ensuring that the metrics are correctly interpreted for analysis. Integration with Sumo Logic allows users to leverage a comprehensive analytics platform, enabling rich visualizations and insights from their metric data. The plugin provides configuration options such as setting URLs for the HTTP Metrics Source, choosing the data format, and specifying additional parameters like timeout and request size, which enhance flexibility and control in data monitoring workflows.

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"

Sumo Logic

[[outputs.sumologic]]
  ## Unique URL generated for your HTTP Metrics Source.
  ## This is the address to send metrics to.
  # url = "https://events.sumologic.net/receiver/v1/http/"

  ## Data format to be used for sending metrics.
  ## This will set the "Content-Type" header accordingly.
  ## Currently supported formats:
  ## * graphite - for Content-Type of application/vnd.sumologic.graphite
  ## * carbon2 - for Content-Type of application/vnd.sumologic.carbon2
  ## * prometheus - for Content-Type of application/vnd.sumologic.prometheus
  ##
  ## More information can be found at:
  ## https://help.sumologic.com/03Send-Data/Sources/02Sources-for-Hosted-Collectors/HTTP-Source/Upload-Metrics-to-an-HTTP-Source#content-type-headers-for-metrics
  ##
  ## NOTE:
  ## When unset, telegraf will by default use the influx serializer which is currently unsupported
  ## in HTTP Source.
  data_format = "carbon2"

  ## Timeout used for HTTP request
  # timeout = "5s"

  ## Max HTTP request body size in bytes before compression (if applied).
  ## By default 1MB is recommended.
  ## NOTE:
  ## Bear in mind that in some serializer a metric even though serialized to multiple
  ## lines cannot be split any further so setting this very low might not work
  ## as expected.
  # max_request_body_size = 1000000

  ## Additional, Sumo specific options.
  ## Full list can be found here:
  ## https://help.sumologic.com/03Send-Data/Sources/02Sources-for-Hosted-Collectors/HTTP-Source/Upload-Metrics-to-an-HTTP-Source#supported-http-headers

  ## Desired source name.
  ## Useful if you want to override the source name configured for the source.
  # source_name = ""

  ## Desired host name.
  ## Useful if you want to override the source host configured for the source.
  # source_host = ""

  ## Desired source category.
  ## Useful if you want to override the source category configured for the source.
  # source_category = ""

  ## Comma-separated key=value list of dimensions to apply to every metric.
  ## Custom dimensions will allow you to query your metrics at a more granular level.
  # dimensions = ""
</code></pre>

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.

Sumo Logic

1. Real-Time System Monitoring Dashboard: Utilize the Sumo Logic plugin to continuously feed performance metrics from your servers into a Sumo Logic dashboard. This setup allows tech teams to visualize system health and load in real-time, enabling quicker identification of any performance bottlenecks or system failures through detailed graphs and metrics.

2. Automated Alerting System: Configure the plugin to send metrics that trigger alerts in Sumo Logic for specific thresholds such as CPU usage or memory consumption. By setting up automated alerts, teams can proactively address issues before they escalate into critical failures, significantly improving response times and overall system reliability.

3. Cross-System Metrics Aggregation: Integrate multiple Telegraf instances across different environments (development, testing, production) and funnel all metrics to a central Sumo Logic instance using this plugin. This aggregation enables comprehensive analysis across environments, facilitating better monitoring and informed decision-making across the software development lifecycle.

4. Custom Metrics with Dimensions Tracking: Use the Sumo Logic plugin to send customized metrics that include dimensions identifying various aspects of your infrastructure (e.g., environment, service type). This granular tracking allows for more tailored analytics, enabling your team to dissect performance across different application layers or business functions.

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.