Google Cloud Stackdriver and Dynatrace Integration

Input and output integration overview

This plugin enables the collection of monitoring data from Google Cloud services through the Stackdriver Monitoring API. It is designed to help users monitor their cloud infrastructure’s performance and health by gathering relevant metrics.

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

Google Cloud Stackdriver

The Stackdriver Telegraf plugin allows users to query timeseries data from Google Cloud Monitoring using the Cloud Monitoring API v3. With this plugin, users can easily integrate Google Cloud monitoring metrics into their monitoring stacks. This API provides a wealth of insights about resources and applications running in Google Cloud, including performance, uptime, and operational metrics. The plugin supports various configuration options to filter and refine the data retrieved, enabling users to customize their monitoring setup according to their specific needs. This integration facilitates a smoother experience in maintaining the health and performance of cloud resources and assists teams in making data-driven decisions based on historical and current performance statistics.

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

Google Cloud Stackdriver

[[inputs.stackdriver]]
  ## GCP Project
  project = "erudite-bloom-151019"

  ## Include timeseries that start with the given metric type.
  metric_type_prefix_include = [
    "compute.googleapis.com/",
  ]

  ## Exclude timeseries that start with the given metric type.
  # metric_type_prefix_exclude = []

  ## Most metrics are updated no more than once per minute; it is recommended
  ## to override the agent level interval with a value of 1m or greater.
  interval = "1m"

  ## Maximum number of API calls to make per second.  The quota for accounts
  ## varies, it can be viewed on the API dashboard:
  ##   https://cloud.google.com/monitoring/quotas#quotas_and_limits
  # rate_limit = 14

  ## The delay and window options control the number of points selected on
  ## each gather.  When set, metrics are gathered between:
  ##   start: now() - delay - window
  ##   end:   now() - delay
  #
  ## Collection delay; if set too low metrics may not yet be available.
  # delay = "5m"
  #
  ## If unset, the window will start at 1m and be updated dynamically to span
  ## the time between calls (approximately the length of the plugin interval).
  # window = "1m"

  ## TTL for cached list of metric types.  This is the maximum amount of time
  ## it may take to discover new metrics.
  # cache_ttl = "1h"

  ## If true, raw bucket counts are collected for distribution value types.
  ## For a more lightweight collection, you may wish to disable and use
  ## distribution_aggregation_aligners instead.
  # gather_raw_distribution_buckets = true

  ## Aggregate functions to be used for metrics whose value type is
  ## distribution.  These aggregate values are recorded in in addition to raw
  ## bucket counts; if they are enabled.
  ##
  ## For a list of aligner strings see:
  ##   https://cloud.google.com/monitoring/api/ref_v3/rpc/google.monitoring.v3#aligner
  # distribution_aggregation_aligners = [
  #  "ALIGN_PERCENTILE_99",
  #  "ALIGN_PERCENTILE_95",
  #  "ALIGN_PERCENTILE_50",
  # ]

  ## Filters can be added to reduce the number of time series matched.  All
  ## functions are supported: starts_with, ends_with, has_substring, and
  ## one_of.  Only the '=' operator is supported.
  ##
  ## The logical operators when combining filters are defined statically using
  ## the following values:
  ##   filter ::=  {AND  AND  AND }
  ##   resource_labels ::=  {OR }
  ##   metric_labels ::=  {OR }
  ##   user_labels ::=  {OR }
  ##   system_labels ::=  {OR }
  ##
  ## For more details, see https://cloud.google.com/monitoring/api/v3/filters
  #
  ## Resource labels refine the time series selection with the following expression:
  ##   resource.labels. = 
  # [[inputs.stackdriver.filter.resource_labels]]
  #   key = "instance_name"
  #   value = 'starts_with("localhost")'
  #
  ## Metric labels refine the time series selection with the following expression:
  ##   metric.labels. = 
  #  [[inputs.stackdriver.filter.metric_labels]]
  #    key = "device_name"
  #    value = 'one_of("sda", "sdb")'
  #
  ## User labels refine the time series selection with the following expression:
  ##   metadata.user_labels."" = 
  #  [[inputs.stackdriver.filter.user_labels]]
  #    key = "environment"
  #    value = 'one_of("prod", "staging")'
  #
  ## System labels refine the time series selection with the following expression:
  ##   metadata.system_labels."" = 
  #  [[inputs.stackdriver.filter.system_labels]]
  #    key = "machine_type"
  #    value = 'starts_with("e2-")'
</code></pre>

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

Google Cloud Stackdriver

1. Integrating Cloud Metrics into Custom Dashboards: With this plugin, teams can funnel metrics from Google Cloud into personalized dashboards, allowing for real-time monitoring of application performance and resource utilization. By customizing the visual representation of cloud metrics, operations teams can easily identify trends and anomalies, enabling proactive management before issues escalate.

2. Automated Alerts and Analysis: Users can set up automated alerting mechanisms leveraging the plugin’s metrics to track resource thresholds. This capability allows teams to act swiftly in response to performance degradation or outages by providing immediate notifications, thus reducing the mean time to recovery and ensuring continued operational efficiency.

3. Cross-Platform Resource Comparison: The plugin can be used to draw metrics from various Google Cloud services and compare them with on-premise resources. This cross-platform visibility helps organizations make informed decisions about resource allocation and scaling strategies, as well as optimize cloud spending versus on-premise infrastructure.

4. Historical Data Analysis for Capacity Planning: By collecting historical metrics over time, the plugin empowers teams to conduct thorough capacity planning. Understanding past performance trends facilitates accurate forecasting for resource needs, leading to better budgeting and investment strategies.

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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