Jenkins and AWS Redshift 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 enables Telegraf to send metrics to Amazon Redshift using the PostgreSQL plugin, allowing metrics to be stored in a scalable, SQL-compatible data warehouse.

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.

AWS Redshift

This configuration uses the Telegraf PostgreSQL plugin to send metrics to Amazon Redshift, AWS’s fully managed cloud data warehouse that supports SQL-based analytics at scale. Although Redshift is based on PostgreSQL 8.0.2, it does not support all standard PostgreSQL features such as full JSONB, stored procedures, or upserts. Therefore, care must be taken to predefine compatible tables and schema when using Telegraf for Redshift integration. This setup is ideal for use cases that benefit from long-term, high-volume metric storage and integration with AWS analytics tools like QuickSight or Redshift Spectrum. Metrics stored in Redshift can be joined with business datasets for rich observability and BI analysis.

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

AWS Redshift

[[outputs.postgresql]]
  ## Redshift connection settings
  host = "redshift-cluster.example.us-west-2.redshift.amazonaws.com"
  port = 5439
  user = "telegraf"
  password = "YourRedshiftPassword"
  database = "metrics"
  sslmode = "require"

  ## Optional: specify a dynamic table template for inserting metrics
  table_template = "telegraf_metrics"

  ## Note: Redshift does not support all PostgreSQL features; ensure your table exists and is compatible

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.

AWS Redshift

1. Business-Aware Infrastructure Monitoring: Store infrastructure metrics from Telegraf in Redshift alongside sales, marketing, or customer engagement data. Analysts can correlate system performance with business KPIs using SQL joins and window functions.

2. Historical Trend Analysis for Cloud Resources: Use Telegraf to continuously log CPU, memory, and I/O metrics to Redshift. Combine with time-series SQL queries and visualization tools like Amazon QuickSight to spot trends and forecast resource demand.

3. Security Auditing of System Behavior: Send metrics related to system logins, file changes, or resource spikes into Redshift. Analysts can build dashboards or reports for compliance auditing using SQL queries across multi-year data sets.

4. Cross-Environment SLA Reporting: Aggregate SLA metrics from multiple cloud accounts and regions using Telegraf, and push them to a central Redshift warehouse. Enable unified SLA compliance dashboards and executive reporting via a single SQL interface.

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.