Apache Aurora and Dynatrace Integration

Input and output integration overview

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

The Dynatrace plugin allows users to send metrics collected by Telegraf directly to Dynatrace for monitoring and analysis. This integration enhances the observability of systems and applications, providing valuable insights into performance and operational health.

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.

Dynatrace

The Dynatrace plugin for Telegraf facilitates the transmission of metrics to the Dynatrace platform via the Dynatrace Metrics API V2. This plugin can function in two modes: it can run alongside the Dynatrace OneAgent, which automates authentication, or it can operate in a standalone configuration that requires manual specification of the URL and API token for environments without a OneAgent. The plugin primarily reports metrics as gauges unless explicitly configured to treat certain metrics as delta counters using the available config options. This feature empowers users to customize the behavior of metrics sent to Dynatrace, harnessing the robust capabilities of the platform for comprehensive performance monitoring and observability. It’s crucial for users to ensure compliance with version requirements for both Dynatrace and Telegraf, thereby optimizing compatibility and performance when integrating with the Dynatrace ecosystem.

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

Dynatrace

[[outputs.dynatrace]]
  ## For usage with the Dynatrace OneAgent you can omit any configuration,
  ## the only requirement is that the OneAgent is running on the same host.
  ## Only setup environment url and token if you want to monitor a Host without the OneAgent present.
  ##
  ## Your Dynatrace environment URL.
  ## For Dynatrace OneAgent you can leave this empty or set it to "http://127.0.0.1:14499/metrics/ingest" (default)
  ## For Dynatrace SaaS environments the URL scheme is "https://{your-environment-id}.live.dynatrace.com/api/v2/metrics/ingest"
  ## For Dynatrace Managed environments the URL scheme is "https://{your-domain}/e/{your-environment-id}/api/v2/metrics/ingest"
  url = ""

  ## Your Dynatrace API token.
  ## Create an API token within your Dynatrace environment, by navigating to Settings > Integration > Dynatrace API
  ## The API token needs data ingest scope permission. When using OneAgent, no API token is required.
  api_token = ""

  ## Optional prefix for metric names (e.g.: "telegraf")
  prefix = "telegraf"

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Optional flag for ignoring tls certificate check
  # insecure_skip_verify = false

  ## Connection timeout, defaults to "5s" if not set.
  timeout = "5s"

  ## If you want metrics to be treated and reported as delta counters, add the metric names here
  additional_counters = [ ]

  ## In addition or as an alternative to additional_counters, if you want metrics to be treated and
  ## reported as delta counters using regular expression pattern matching
  additional_counters_patterns = [ ]

  ## 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

  ## Optional dimensions to be added to every metric
  # [outputs.dynatrace.default_dimensions]
  # default_key = "default value"

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.

Dynatrace

1. Cloud Infrastructure Monitoring: Utilize the Dynatrace plugin to monitor a cloud infrastructure setup, feeding real-time metrics from Telegraf into Dynatrace. This integration provides a holistic view of resource utilization, application performance, and system health, enabling proactive responses to performance issues across various cloud environments.

2. Custom Application Performance Metrics: Implement custom application-specific metrics by configuring the Dynatrace output plugin to send tailored metrics from Telegraf. By leveraging additional counters and dimension options, development teams can gain insights that are precisely aligned with their application’s operational requirements, allowing for targeted optimization efforts.

3. Multi-Environment Metrics Management: For organizations running multiple Dynatrace environments (e.g., production, staging, and development), use this plugin to manage metrics for all environments from a single Telegraf instance. With proper configuration of endpoints and API tokens, teams can maintain consistent monitoring practices throughout the SDLC, ensuring that performance anomalies are detected early in the development process.

4. Automated Alerting Based on Metrics Changes: Integrate the Dynatrace output plugin with an alerting mechanism that triggers notifications when specific metrics exceed defined thresholds. This scenario involves configuring additional counters to monitor crucial application performance indicators, enabling swift remediation actions to maintain service availability and user satisfaction.

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