Apache Aurora and Sensu Integration

Input and output integration overview

This plugin gathers metrics from Apache Aurora schedulers, providing insights necessary for effective monitoring of Aurora clusters.

This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.

Integration details

Apache Aurora

The Aurora plugin is designed to gather metrics from Apache Aurora schedulers. This plugin connects to specified schedulers using their respective URLs and retrieves operational metrics that help in monitoring the health and performance of Aurora clusters. It primarily captures numeric data from the /vars endpoint, ensuring key metrics related to task execution and resource utilization are monitored. The plugin enhances operational insights by utilizing HTTP Basic Authentication for secure access. With optional TLS configuration, it further bolsters security when transmitting data. The plugin provides a robust way to interface with Apache Aurora, reflecting a focus on operational reliability and ongoing performance assessment across distributed systems.

Sensu

This plugin writes metrics events to Sensu via its HTTP events API. Sensu is a monitoring system that enables users to collect, analyze, and manage metrics from various components in their infrastructure. The plugin facilitates the integration of Telegraf, a server agent for collecting and reporting metrics, with the Sensu monitoring platform. Users can configure settings such as backend and agent API URLs, API keys for authentication, and optional TLS settings. The plugin’s core functionality is centered around sending metric events, including check and entity specifications, to Sensu, allowing for comprehensive monitoring and alerting. The API reference provides extensive details about the events and metrics structure, ensuring users can efficiently leverage Sensu’s capabilities for observability and incident response.

Configuration

Apache Aurora

[[inputs.aurora]]
  ## Schedulers are the base addresses of your Aurora Schedulers
  schedulers = ["http://127.0.0.1:8081"]

  ## Set of role types to collect metrics from.
  ##
  ## The scheduler roles are checked each interval by contacting the
  ## scheduler nodes; zookeeper is not contacted.
  # roles = ["leader", "follower"]

  ## Timeout is the max time for total network operations.
  # timeout = "5s"

  ## Username and password are sent using HTTP Basic Auth.
  # 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

Sensu

[[outputs.sensu]]
  ## BACKEND API URL is the Sensu Backend API root URL to send metrics to
  ## (protocol, host, and port only). The output plugin will automatically
  ## append the corresponding backend API path
  ## /api/core/v2/namespaces/:entity_namespace/events/:entity_name/:check_name).
  ##
  ## Backend Events API reference:
  ## https://docs.sensu.io/sensu-go/latest/api/events/
  ##
  ## AGENT API URL is the Sensu Agent API root URL to send metrics to
  ## (protocol, host, and port only). The output plugin will automatically
  ## append the correspeonding agent API path (/events).
  ##
  ## Agent API Events API reference:
  ## https://docs.sensu.io/sensu-go/latest/api/events/
  ##
  ## NOTE: if backend_api_url and agent_api_url and api_key are set, the output
  ## plugin will use backend_api_url. If backend_api_url and agent_api_url are
  ## not provided, the output plugin will default to use an agent_api_url of
  ## http://127.0.0.1:3031
  ##
  # backend_api_url = "http://127.0.0.1:8080"
  # agent_api_url = "http://127.0.0.1:3031"

  ## API KEY is the Sensu Backend API token
  ## Generate a new API token via:
  ##
  ## $ sensuctl cluster-role create telegraf --verb create --resource events,entities
  ## $ sensuctl cluster-role-binding create telegraf --cluster-role telegraf --group telegraf
  ## $ sensuctl user create telegraf --group telegraf --password REDACTED
  ## $ sensuctl api-key grant telegraf
  ##
  ## For more information on Sensu RBAC profiles & API tokens, please visit:
  ## - https://docs.sensu.io/sensu-go/latest/reference/rbac/
  ## - https://docs.sensu.io/sensu-go/latest/reference/apikeys/
  ##
  # api_key = "${SENSU_API_KEY}"

  ## 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

  ## Timeout for HTTP message
  # timeout = "5s"

  ## HTTP Content-Encoding for write request body, can be set to "gzip" to
  ## compress body or "identity" to apply no encoding.
  # content_encoding = "identity"

  ## NOTE: Due to the way TOML is parsed, tables must be at the END of the
  ## plugin definition, otherwise additional config options are read as part of
  ## the table

  ## Sensu Event details
  ##
  ## Below are the event details to be sent to Sensu.  The main portions of the
  ## event are the check, entity, and metrics specifications. For more information
  ## on Sensu events and its components, please visit:
  ## - Events - https://docs.sensu.io/sensu-go/latest/reference/events
  ## - Checks -  https://docs.sensu.io/sensu-go/latest/reference/checks
  ## - Entities - https://docs.sensu.io/sensu-go/latest/reference/entities
  ## - Metrics - https://docs.sensu.io/sensu-go/latest/reference/events#metrics
  ##
  ## Check specification
  ## The check name is the name to give the Sensu check associated with the event
  ## created. This maps to check.metadata.name in the event.
  [outputs.sensu.check]
    name = "telegraf"

  ## Entity specification
  ## Configure the entity name and namespace, if necessary. This will be part of
  ## the entity.metadata in the event.
  ##
  ## NOTE: if the output plugin is configured to send events to a
  ## backend_api_url and entity_name is not set, the value returned by
  ## os.Hostname() will be used; if the output plugin is configured to send
  ## events to an agent_api_url, entity_name and entity_namespace are not used.
  # [outputs.sensu.entity]
  #   name = "server-01"
  #   namespace = "default"

  ## Metrics specification
  ## Configure the tags for the metrics that are sent as part of the Sensu event
  # [outputs.sensu.tags]
  #   source = "telegraf"

  ## Configure the handler(s) for processing the provided metrics
  # [outputs.sensu.metrics]
  #   handlers = ["influxdb","elasticsearch"]

Input and output integration examples

Apache Aurora

1. Dynamic Resource Allocation Monitoring: Utilize the Aurora plugin to build a real-time dashboard displaying metrics related to resource allocation in your Aurora clusters. By aggregating data from multiple schedulers, you can visualize how resources are distributed among various roles (leader and follower), enabling proactive management of resource utilization and helping prevent bottlenecks in production workloads.

2. Alerting on Scheduler Health: Implement alerting mechanisms where the Aurora plugin checks the health of schedulers periodically. If a scheduler role responds with a status that indicates a failure to communicate (non-200 status), alerts can be automatically generated and sent to the operations team via email or messaging apps, ensuring immediate attention to critical issues and maintaining availability in service management.

3. Performance Benchmarking Over Time: By continuously collecting metrics such as job update events and execution times, this plugin can assist teams in benchmarking the performance of their Apache Aurora deployment over time. Relevant metrics can be logged into a time-series database, enabling historical analysis, trend identification, and understanding how changes in the system, such as configuration adjustments or workload changes, impact performance.

4. Integration with CI/CD Pipelines: Integrate the metrics collected via the Aurora plugin with CI/CD pipeline tools to monitor how deployments affect runtime metrics in Aurora. Teams can thereby ensure that new releases do not adversely impact scheduler performance and can roll back changes seamlessly if any metric exceeds predefined thresholds after deployment.

Sensu

1. Real-Time Infrastructure Monitoring: Utilize the Sensu plugin to send performance metrics from various servers and services directly to Sensu. This real-time data flow enables teams to visualize infrastructure health, track resource usage, and receive immediate alerts for any anomalies detected. By centralizing monitoring through Sensu, organizations can create a holistic view of their systems and respond swiftly to issues.

2. Automated Incident Response Workflows: Leverage the plugin to automatically trigger incident response workflows based on the metrics events sent to Sensu. For example, if CPU usage exceeds a defined threshold, the Sensu system can be configured to alert the operations team, which can then initiate automated remediation processes, reducing downtime and maintaining system reliability. This integration allows for proactive management of system resources.

3. Dynamic Scaling of Resources: Use the Sensu plugin to feed metrics into an auto-scaling system that adjusts resources based on demand. By tracking metrics like request load and resource utilization, organizations can automatically scale their infrastructure up or down, ensuring optimal performance and cost efficiency without manual intervention.

4. Centralized Logging and Monitoring: Combine the Sensu with logging tools to send logs and performance metrics to a centralized monitoring system. This comprehensive approach allows teams to correlate logs with metric events, providing deeper insights into system behavior and performance, which aids in troubleshooting and performance optimization over time.

Feedback

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