Amazon ECS and SigNoz 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.

This configuration turns any Telegraf agent into a Remote Write publisher for SigNoz, streaming rich metrics straight into the SigNoz backend with a single URL change.

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.

SigNoz

SigNoz is an open source observability platform that stores metrics, traces, and logs. When you deploy SigNoz, its signoz-otel-collector-metrics service exposes a Prometheus Remote Write receiver (default :13133/api/v1/write). By configuring Telegraf’s Prometheus plugin to point at this endpoint, you can push any Telegraf collected metrics, SNMP counters, cloud services, or business KPIs—directly into SigNoz. The plugin natively serializes metrics in the Remote Write protobuf format, supports external labels, metadata export, retries, and TLS or bearer-token auth, so it fits zero-trust and multi-tenant SigNoz clusters. Inside SigNoz, the data lands in ClickHouse tables that back Metrics Explorer, alert rules, and unified dashboards. This approach lets organizations unify Prometheus and OTLP pipelines, enables long-term retention powered by ClickHouse compression, and avoids vendor lock-in while retaining PromQL-style queries.

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"

SigNoz

[[outputs.prometheusremotewrite]]
  ## SigNoz OTEL-Collector metrics endpoint (Prometheus Remote Write receiver)
  ## Default port is 13133 when you install SigNoz with the Helm chart
  url = "http://signoz-otel-collector-metrics.monitoring.svc.cluster.local:13133/api/v1/write"

  ## Add identifying labels so you can slice & dice the data later
  external_labels = { host = "${HOSTNAME}", agent = "telegraf" }

  ## Forward host metadata for richer dashboards (SigNoz maps these to ClickHouse columns)
  send_metadata = true

  ## ----- Authentication (comment out what you don’t need) -----
  # bearer_token   = "$SIGNOZ_TOKEN"          # SaaS tenant token
  # basic_username = "signoz"                 # Basic auth (self-hosted)
  # basic_password = "secret"

  ## ----- TLS options (for SaaS or HTTPS self-hosted) -----
  # tls_ca                  = "/etc/ssl/certs/ca.crt"
  # tls_cert                = "/etc/telegraf/certs/telegraf.crt"
  # tls_key                 = "/etc/telegraf/certs/telegraf.key"
  # insecure_skip_verify    = false

  ## ----- Performance tuning -----
  max_batch_size = 10000      # samples per POST
  timeout        = "10s"
  retry_max      = 3

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.

SigNoz

1. Multi-Cluster Federated Monitoring: Drop a Telegraf DaemonSet into each Kubernetes cluster, tag metrics with cluster=<name>, and Remote Write them to a central SigNoz instance. Ops teams get a single PromQL window across prod, staging, and edge clusters without running Thanos sidecars.

2. Factory-Floor Edge Gateway: A rugged Intel NUC on the shop floor runs Telegraf to scrape Modbus PLCs and environmental sensors. It batches readings every 5 seconds and pushes them over an intermittent 4G link to SigNoz SaaS. ClickHouse compression keeps costs low while AI-based outlier detection in SigNoz flags overheating motors before failure.

3. SaaS Usage Metering: Telegraf runs alongside each micro-service, exporting per-tenant counters (api_calls, gigabytes_processed). Remote Write streams the data to SigNoz where a scheduled ClickHouse materialized view aggregates usage for monthly billing—no separate metering stack required.

4. Autoscaling Feedback Loop: Combine Telegraf’s Kubernetes input with the Remote Write output to publish granular pod CPU and queue-length metrics into SigNoz. A custom SigNoz alert fires when P95 latency breaches 200 ms and a GitOps controller reads that alert to trigger a HorizontalPodAutoscaler tweak—closing the loop between observability and automation.

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