Amazon CloudWatch and SQLite Integration

Input and output integration overview

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

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 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.

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 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"

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 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.

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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