Amazon ECS and SQLite 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.

Telegraf’s SQL output plugin stores metrics in an SQL database by creating tables dynamically for each metric type. When configured for SQLite, it utilizes a file-based DSN and a minimal SQL schema tailored for lightweight, embedded database usage.

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.

SQLite

The SQL output plugin writes Telegraf metrics to an SQL database using a dynamic schema where each metric type corresponds to a table. For SQLite, the plugin uses the modernc.org/sqlite driver and requires a DSN in the format of a file URI (e.g., ‘file:/path/to/telegraf.db?cache=shared’). This configuration leverages standard ANSI SQL for table creation and data insertion, ensuring compatibility with SQLite’s capabilities.

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"

SQLite

[[outputs.sql]]
  ## Database driver
  ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
  ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
  driver = "sqlite"

  ## Data source name
  ## For SQLite, the DSN is a filename or URL with the scheme "file:".
  ## Example: "file:/path/to/telegraf.db?cache=shared"
  data_source_name = "file:/path/to/telegraf.db?cache=shared"

  ## Timestamp column name
  timestamp_column = "timestamp"

  ## Table creation template
  ## Available template variables:
  ##  {TABLE}        - table name as a quoted identifier
  ##  {TABLELITERAL} - table name as a quoted string literal
  ##  {COLUMNS}      - column definitions (list of quoted identifiers and types)
  table_template = "CREATE TABLE {TABLE} ({COLUMNS})"

  ## Table existence check template
  ## Available template variables:
  ##  {TABLE} - table name as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL (optional)
  init_sql = ""

  ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
  connection_max_idle_time = "0s"

  ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
  connection_max_lifetime = "0s"

  ## Maximum number of connections in the idle connection pool. 0 means unlimited.
  connection_max_idle = 2

  ## Maximum number of open connections to the database. 0 means unlimited.
  connection_max_open = 0

  ## Metric type to SQL type conversion
  ## The values on the left are the data types Telegraf has and the values on the right are the SQL types used when writing to SQLite.
  #[outputs.sql.convert]
  #  integer       = "INT"
  #  real          = "DOUBLE"
  #  text          = "TEXT"
  #  timestamp     = "TIMESTAMP"
  #  defaultvalue  = "TEXT"
  #  unsigned      = "UNSIGNED"
  #  bool          = "BOOL"

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.

SQLite

1. Local Monitoring Storage: Configure the plugin to write metrics to a local SQLite database file. This is ideal for lightweight deployments where setting up a full-scale database server is not required.
2. Embedded Applications: Use SQLite as the backend for applications embedded in edge devices, benefiting from its file-based architecture and minimal resource requirements.
3. Quick Setup for Testing: Leverage SQLite’s ease of use to quickly set up a testing environment for Telegraf metrics collection without the need for external database services.
4. Custom Schema Management: Adjust the table creation templates to predefine your schema if you require specific column types or indexes, ensuring compatibility with your application’s needs.

Feedback

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