Amazon CloudWatch and GroundWork Integration

Input and output integration overview

This plugin will pull Metric Statistics from Amazon CloudWatch, streamlining the process of monitoring and analyzing AWS resources.

This plugin writes to a GroundWork Monitor instance, allowing for effective metrics management and monitoring in a centralized manner.

Integration details

Amazon CloudWatch

The Amazon CloudWatch Plugin allows users to pull detailed metric statistics from Amazon’s CloudWatch service. As a monitoring solution, CloudWatch enables users to track various metrics related to AWS resources and applications, facilitating improved operational and performance insights. The plugin uses a structured authentication method that prioritizes security and flexibility through a combination of STS (Security Token Service), shared credentials, environment variables, and EC2 instance profiles, ensuring robust access control to AWS resources. Key features include the ability to define specific metric namespaces, aggregated periods for metrics, and optional inclusion of linked accounts for cross-account monitoring. A significant aspect of this plugin is its capacity to handle both sparse and dense metric formats, allowing for varied output structures depending on user preference. Thus, it supports versatile use cases in cloud monitoring and analytics by providing comprehensive, timely data directly from CloudWatch.

GroundWork

The GroundWork plugin enables Telegraf to send metrics to a GroundWork Monitor instance, specifically supporting GW8 and newer versions. This integration allows users to leverage the robust monitoring capabilities of GroundWork, enabling comprehensive oversight of metrics collected from diverse sources. Users can specify various parameters such as the GroundWork instance URL, agent IDs, and authentication credentials, allowing for a tailored fit within their existing monitoring setups. It also supports secret-store secrets to enhance security for sensitive fields like username and password. Tags used within the plugin provide fine-grained control over how metrics are categorized and displayed within the GroundWork interface, allowing for custom configurations that adapt to different monitoring needs. However, users should be aware that string metrics are currently not supported by GroundWork, impacting how they manage their data.

Configuration

Amazon CloudWatch

[[inputs.cloudwatch]]
  region = "us-east-1"
  # access_key = ""
  # secret_key = ""
  # token = ""
  # role_arn = ""
  # web_identity_token_file = ""
  # role_session_name = ""
  # profile = ""
  # shared_credential_file = ""
  # include_linked_accounts = false
  # endpoint_url = ""
  # use_system_proxy = false
  # http_proxy_url = "http://localhost:8888"
  period = "5m"
  delay = "5m"
  interval = "5m"
  #recently_active = "PT3H"
  # cache_ttl = "1h"
  namespaces = ["AWS/ELB"]
  # metric_format = "sparse"
  # ratelimit = 25
  # timeout = "5s"
  # batch_size = 500
  # statistic_include = ["average", "sum", "minimum", "maximum", sample_count]
  # statistic_exclude = []
  # [[inputs.cloudwatch.metrics]]
  #  names = ["Latency", "RequestCount"]
  #  [[inputs.cloudwatch.metrics.dimensions]]
  #    name = "LoadBalancerName"
  #    value = "p-example"

GroundWork

[[outputs.groundwork]]
  ## URL of your groundwork instance.
  url = "https://groundwork.example.com"

  ## Agent uuid for GroundWork API Server.
  agent_id = ""

  ## Username and password to access GroundWork API.
  username = ""
  password = ""

  ## Default application type to use in GroundWork client
  # default_app_type = "TELEGRAF"

  ## Default display name for the host with services(metrics).
  # default_host = "telegraf"

  ## Default service state.
  # default_service_state = "SERVICE_OK"

  ## The name of the tag that contains the hostname.
  # resource_tag = "host"

  ## The name of the tag that contains the host group name.
  # group_tag = "group"

Input and output integration examples

Amazon CloudWatch

1. Cross-Account Monitoring: Utilize this plugin to monitor resources across multiple AWS accounts by enabling the include_linked_accounts option. This scenario allows companies managing multiple AWS accounts to aggregate metrics into a central monitoring dashboard, providing a unified view of all metrics while ensuring secure data access and compliance through proper role management.

2. Dynamic Alerting System: Integrate this plugin with alerting tools to create an automated system that triggers alerts based on defined thresholds for CloudWatch metrics. For instance, if latency metrics exceed specified limits, alerts can be sent to relevant teams, enabling proactive responses to performance issues and reducing downtime.

3. Cost Management Dashboard: Use the metrics gathered from the plugin to build a cost management dashboard that visualizes AWS service usage metrics over time. By correlating these metrics with billing data, organizations can identify high-cost services and take informed actions to optimize their resource usage and spending.

4. Performance Benchmarking for Applications: Leverage the metrics collected from applications running on AWS to perform performance benchmarks. For example, by tracking latency and request count metrics for an ELB, developers can assess the impact of application changes on its performance, making data-driven decisions for optimization.

GroundWork

1. Centralized Monitoring Dashboard: Use the GroundWork plugin to aggregate metrics from multiple Telegraf instances into a single GroundWork Monitor dashboard. This configuration offers complete visibility into system health across various components, enabling swift identification of performance bottlenecks and improved incident response times.

2. Service Health Monitoring with Alerts: Configure this plugin to send critical service metrics to GroundWork, establishing a robust alerting system. Metrics such as CPU usage and service statuses can trigger alerts based on threshold values, informing administrators of potential issues before they escalate, thereby enhancing system reliability.

3. Historical Data Analysis: Leverage the historical metric capabilities of GroundWork using this plugin to conduct trend analysis over time. This application allows organizations to make data-driven decisions based on comprehensive historical performance metrics, which can assist in capacity planning and optimize resource allocation.

4. Custom Service Tags for Enhanced Monitoring: Extend the functionality of this plugin by utilizing custom tags for different services and hosts. By customizing these tags, users can filter and categorize metrics more effectively within their monitoring framework, leading to tailored monitoring experiences that align specifically with business objectives.

Feedback

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