Amazon ECS and AWS Redshift Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
Table of Contents
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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.
This plugin enables Telegraf to send metrics to Amazon Redshift using the PostgreSQL plugin, allowing metrics to be stored in a scalable, SQL-compatible data warehouse.
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.
AWS Redshift
This configuration uses the Telegraf PostgreSQL plugin to send metrics to Amazon Redshift, AWS’s fully managed cloud data warehouse that supports SQL-based analytics at scale. Although Redshift is based on PostgreSQL 8.0.2, it does not support all standard PostgreSQL features such as full JSONB, stored procedures, or upserts. Therefore, care must be taken to predefine compatible tables and schema when using Telegraf for Redshift integration. This setup is ideal for use cases that benefit from long-term, high-volume metric storage and integration with AWS analytics tools like QuickSight or Redshift Spectrum. Metrics stored in Redshift can be joined with business datasets for rich observability and BI analysis.
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"
AWS Redshift
[[outputs.postgresql]]
## Redshift connection settings
host = "redshift-cluster.example.us-west-2.redshift.amazonaws.com"
port = 5439
user = "telegraf"
password = "YourRedshiftPassword"
database = "metrics"
sslmode = "require"
## Optional: specify a dynamic table template for inserting metrics
table_template = "telegraf_metrics"
## Note: Redshift does not support all PostgreSQL features; ensure your table exists and is compatible
Input and output integration examples
Amazon ECS
-
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.
-
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.
-
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.
-
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.
AWS Redshift
-
Business-Aware Infrastructure Monitoring: Store infrastructure metrics from Telegraf in Redshift alongside sales, marketing, or customer engagement data. Analysts can correlate system performance with business KPIs using SQL joins and window functions.
-
Historical Trend Analysis for Cloud Resources: Use Telegraf to continuously log CPU, memory, and I/O metrics to Redshift. Combine with time-series SQL queries and visualization tools like Amazon QuickSight to spot trends and forecast resource demand.
-
Security Auditing of System Behavior: Send metrics related to system logins, file changes, or resource spikes into Redshift. Analysts can build dashboards or reports for compliance auditing using SQL queries across multi-year data sets.
-
Cross-Environment SLA Reporting: Aggregate SLA metrics from multiple cloud accounts and regions using Telegraf, and push them to a central Redshift warehouse. Enable unified SLA compliance dashboards and executive reporting via a single SQL interface.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration