Kibana and Mimir 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.

This plugin sends Telegraf metrics directly to Grafana’s Mimir database using HTTP, providing scalable and efficient long-term storage and analysis for Prometheus-compatible metrics.

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.

Mimir

Grafana Mimir supports the Prometheus Remote Write protocol, enabling Telegraf collected metrics to be efficiently ingested into Mimir clusters for large-scale, long-term storage. This integration leverages Prometheus’s well-established standards, allowing users to combine Telegraf’s extensive data collection capabilities with Mimir’s advanced features, such as query federation, multi-tenancy, high availability, and cost-efficient storage. Grafana Mimir’s architecture is optimized for handling high volumes of metric data and delivering fast query responses, making it ideal for complex monitoring environments and distributed systems.

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"

Mimir

[[outputs.http]]
  url = "http://data-load-balancer-backend-1:9009/api/v1/push"
  data_format = "prometheusremotewrite"
  username = "*****"
  password = "******"
  [outputs.http.headers]
     Content-Type = "application/x-protobuf"
     Content-Encoding = "snappy"
     X-Scope-OrgID = "****"

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.

Mimir

1. Enterprise-Scale Kubernetes Monitoring: Integrate Telegraf with Grafana Mimir to stream metrics from Kubernetes clusters at enterprise scale. This enables comprehensive visibility, improved resource allocation, and proactive troubleshooting across hundreds of clusters, leveraging Mimir’s horizontal scalability and high availability.

2. Multi-tenant SaaS Application Observability: Use this plugin to centralize metrics from diverse SaaS tenants into Grafana Mimir, enabling tenant isolation and accurate billing based on resource usage. This approach provides reliable observability, efficient cost management, and secure multi-tenancy support.

3. Global Edge Network Performance Tracking: Stream latency and availability metrics from globally distributed edge servers into Grafana Mimir. Organizations can quickly identify performance degradation or outages, leveraging Mimir’s fast querying capabilities to ensure optimal service reliability and user experience.

4. Real-Time Analytics for High-Volume Microservices: Implement Telegraf metrics collection in high-volume microservices architectures, feeding data into Grafana Mimir for real-time analytics and anomaly detection. Mimir’s powerful querying enables teams to detect anomalies and quickly respond, maintaining high service availability and performance.

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