Amazon CloudWatch and MySQL Integration

Input and output integration overview

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

The Telegraf SQL output plugin allows you to store metrics from Telegraf directly into a MySQL database, making it easier to analyze and visualize the collected metrics.

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.

MySQL

This plugin saves Telegraf metric data to a MySQL database using a hard-coded database schema, which includes a table for each metric type. The plugin utilizes Golang’s generic database/sql interface to interact with various supported database drivers, including MySQL.

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"

MySQL

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

  ## Data source name
  ## The format of the data source name is different for each database driver.
  ## See the plugin readme for details.
  data_source_name = "username:password@tcp(host:port)/dbname"

  ## 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} - tablename as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL
  init_sql = "SET sql_mode='ANSI_QUOTES';"

  ## 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

  ## 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

  ## 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 data types Telegraf will use when sending to a database.
  ##
  ## The database values used must be data types the destination database
  ## understands. It is up to the user to ensure that the selected data type is
  ## available in the database they are using. Refer to your database
  ## documentation for what data types are available and supported.
  #[outputs.sql.convert]
  #  integer              = "INT"
  #  real                 = "DOUBLE"
  #  text                 = "TEXT"
  #  timestamp            = "TIMESTAMP"
  #  defaultvalue         = "TEXT"
  #  unsigned             = "UNSIGNED"
  #  bool                 = "BOOL"
  #  ## This setting controls the behavior of the unsigned value. By default the
  #  ## setting will take the integer value and append the unsigned value to it. The other
  #  ## option is "literal", which will use the actual value the user provides to
  #  ## the unsigned option. This is useful for a database like ClickHouse where
  #  ## the unsigned value should use a value like "uint64".
  #  # conversion_style = "unsigned_suffix"

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.

MySQL

1. Basic Configuration: Set up the MySQL output plugin by specifying the driver as mysql and the data source name to connect to your MySQL database.
2. Data Storage: Use this plugin to regularly save temperature and humidity metrics from a sensor into a MySQL database for later retrieval and analysis.
3. Custom Schema: Modify the table creation template to include additional metadata columns for more comprehensive data logging.

Feedback

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