Amazon ECS and Clarify Integration

Input and output integration overview

The Amazon ECS Input Plugin enables Telegraf to gather metrics from AWS ECS containers, providing detailed insights into container performance and resource usage.

The Clarify plugin allows users to publish Telegraf metrics directly to Clarify, enabling enhanced analysis and monitoring capabilities.

Integration details

Amazon ECS

The Amazon ECS plugin for Telegraf is designed to collect metrics from ECS (Elastic Container Service) tasks running on AWS Fargate or EC2 instances. By utilizing the ECS metadata and stats API endpoints (v2 and v3), it fetches real-time information about container performance and health within a task. This plugin operates within the same task as the inspected workload, ensuring seamless access to metadata and statistics. Notably, it incorporates ECS-specific features that distinguish it from the Docker input plugin, such as handling unique ECS metadata formats and statistics. Users can include or exclude specific containers and adjust which container states to monitor, along with defining tag options for ECS labels. This flexibility allows for a tailored monitoring experience that aligns with the specific needs of an ECS environment, thereby enhancing observability and control over containerized applications.

Clarify

This plugin facilitates the writing of Telegraf metrics to Clarify, a platform for managing and analyzing time series data. By transforming metrics into Clarify signals, this output plugin enables seamless integration of collected telemetry data into the Clarify ecosystem. Users must obtain valid credentials, either through a credentials file or basic authentication, to configure the plugin. The configuration also provides options for fine-tuning how metrics are mapped to signals in Clarify, including the ability to specify unique identifiers using tags. Given that Clarify supports only floating point values, the plugin ensures that any unsupported types are effectively filtered out during the publishing process. This comprehensive connectivity aligns with use cases in monitoring, data analysis, and operational insights.

Configuration

Amazon ECS

[[inputs.ecs]]
  # endpoint_url = ""
  # container_name_include = []
  # container_name_exclude = []
  # container_status_include = []
  # container_status_exclude = []
  ecs_label_include = [ "com.amazonaws.ecs.*" ]
  ecs_label_exclude = []
  # timeout = "5s"

[[inputs.ecs]]
  endpoint_url = "http://169.254.170.2"
  # container_name_include = []
  # container_name_exclude = []
  # container_status_include = []
  # container_status_exclude = []
  ecs_label_include = [ "com.amazonaws.ecs.*" ]
  ecs_label_exclude = []
  # timeout = "5s"

Clarify

[[outputs.clarify]]
  ## Credentials File (Oauth 2.0 from Clarify integration)
  credentials_file = "/path/to/clarify/credentials.json"

  ## Clarify username password (Basic Auth from Clarify integration)
  username = "i-am-bob"
  password = "secret-password"

  ## Timeout for Clarify operations
  # timeout = "20s"

  ## Optional tags to be included when generating the unique ID for a signal in Clarify
  # id_tags = []
  # clarify_id_tag = 'clarify_input_id'

Input and output integration examples

Amazon ECS

1. Dynamic Container Monitoring: Use the Amazon ECS plugin to monitor container health dynamically within an autoscaling ECS architecture. As new containers spin up or down, the plugin will automatically adjust the metrics it collects, ensuring that each container’s performance data is captured efficiently without manual configuration.

2. Custom Resource Allocation Alerts: Implement the ECS plugin to establish thresholds for resource usage per container. By integrating with notification systems, teams can receive alerts when a container’s CPU or memory usage exceeds predefined limits, enabling proactive resource management and maintaining application performance.

3. Cost-Optimization Dashboard: Leverage the metrics gathered from the ECS plugin to create a dashboard that visualizes resource usage and costs associated with each container. This insight allows organizations to identify underutilized resources, optimizing costs associated with their container infrastructure, thus driving financial efficiency in cloud operations.

4. Advanced Container Security Monitoring: Utilize this plugin in conjunction with security tools to monitor ECS container metrics for anomalies. By continuously analyzing usage patterns, any sudden spikes or irregular behaviors can be detected, prompting automated security responses and maintaining system integrity.

Clarify

1. Automated Data Monitoring: By integrating the Clarify plugin with sensor data collection, organizations can automate the monitoring of environmental conditions, such as temperature and humidity. The plugin processes metrics in real-time, sending updates to Clarify where they can be analyzed for trends, alerts, and historical tracking. This use case makes it easier to maintain optimal conditions in data centers or production environments, reducing the risk of equipment failures.

2. Performance Metrics Analysis: Companies can leverage this plugin to send application performance metrics to Clarify. By transmitting key indicators such as response times and error rates, developers and operations teams can utilize Clarify’s capabilities to visualize and analyze application performance over time. This insight can drive improvements in user experience and help identify areas in need of optimization.

3. Sensor Data Aggregation: Utilizing the plugin to push data from multiple sensors to Clarify allows for a comprehensive view of physical environments. This aggregation is particularly beneficial in sectors such as agriculture, where metrics from various sensors can be correlated to decision-making about resource allocations, pest control, and crop management. The plugin ensures the data is accurately mapped and transformed for effective analysis.

4. Real-Time Alerts and Notifications: Implement the Clarify plugin to trigger real-time alerts based on predefined thresholds within the metrics being sent. For instance, if temperature readings exceed certain levels, alerts can be generated and sent to operational staff. This proactive approach allows for immediate responses to potential issues, enhancing operational reliability and safety.

Feedback

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