Jenkins and Mimir Integration

Input and output integration overview

The Jenkins plugin collects vital information regarding jobs and nodes from a Jenkins instance through its API, facilitating comprehensive monitoring and analysis.

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

Jenkins

The Jenkins Telegraf plugin allows users to gather metrics from a Jenkins instance without needing to install any additional plugins on Jenkins itself. By utilizing the Jenkins API, the plugin retrieves information about nodes and jobs running in the Jenkins environment. This integration provides a comprehensive overview of the Jenkins infrastructure, including real-time metrics that can be used for monitoring and analysis. Key features include configurable filters for job and node selection, optional TLS security settings, and the ability to manage request timeouts and connection limits effectively. This makes it an essential tool for teams that rely on Jenkins for continuous integration and delivery, ensuring they have the insights they need to maintain optimal performance and reliability.

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

Jenkins

[[inputs.jenkins]]
  ## The Jenkins URL in the format "schema://host:port"
  url = "http://my-jenkins-instance:8080"
  # username = "admin"
  # password = "admin"

  ## Set response_timeout
  response_timeout = "5s"

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Use SSL but skip chain & host verification
  # insecure_skip_verify = false

  ## Optional Max Job Build Age filter
  ## Default 1 hour, ignore builds older than max_build_age
  # max_build_age = "1h"

  ## Optional Sub Job Depth filter
  ## Jenkins can have unlimited layer of sub jobs
  ## This config will limit the layers of pulling, default value 0 means
  ## unlimited pulling until no more sub jobs
  # max_subjob_depth = 0

  ## Optional Sub Job Per Layer
  ## In workflow-multibranch-plugin, each branch will be created as a sub job.
  ## This config will limit to call only the lasted branches in each layer,
  ## empty will use default value 10
  # max_subjob_per_layer = 10

  ## Jobs to include or exclude from gathering
  ## When using both lists, job_exclude has priority.
  ## Wildcards are supported: [ "jobA/*", "jobB/subjob1/*"]
  # job_include = [ "*" ]
  # job_exclude = [ ]

  ## Nodes to include or exclude from gathering
  ## When using both lists, node_exclude has priority.
  # node_include = [ "*" ]
  # node_exclude = [ ]

  ## Worker pool for jenkins plugin only
  ## Empty this field will use default value 5
  # max_connections = 5

  ## When set to true will add node labels as a comma-separated tag. If none,
  ## are found, then a tag with the value of 'none' is used. Finally, if a
  ## label contains a comma it is replaced with an underscore.
  # node_labels_as_tag = false

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

Jenkins

1. Continuous Integration Monitoring: Use the Jenkins plugin to monitor the performance of continuous integration pipelines by collecting metrics on job durations and failure rates. This can help teams identify bottlenecks in the pipeline and improve overall build efficiency.

2. Resource Allocation Analysis: Leverage Jenkins node metrics to assess resource usage across different agents. By understanding how resources are allocated, teams can optimize their Jenkins architecture, potentially reallocating agents or adjusting job configurations for better performance.

3. Job Execution Trends: Analyze historical job performance metrics to identify trends in job execution over time. With this data, teams can proactively address potential issues before they grow, making adjustments to the jobs or their configurations as needed.

4. Alerting for Job Failures: Implement alerts that leverage the Jenkins job metrics to notify team members in case of job failures. This proactive approach can enhance operational awareness and speed up response times to failures, ensuring that critical jobs are monitored effectively.

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.

Feedback

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