Set up metrics ingestion from an Amazon EC2 instance using remote write - Amazon Managed Service for Prometheus

Set up metrics ingestion from an Amazon EC2 instance using remote write

This section explains how to run a Prometheus server with remote write in an Amazon Elastic Compute Cloud (Amazon EC2) instance. It explains how to collect metrics from a demo application written in Go and send them to an Amazon Managed Service for Prometheus workspace.

Prerequisites

Important

Before you start, you must have installed Prometheus v2.26. We assume that you're familiar with Prometheus, Amazon EC2, and Amazon Managed Service for Prometheus. For information about how to install Prometheus, see Getting started on the Prometheus website.

If you're unfamiliar with Amazon EC2 or Amazon Managed Service for Prometheus, we recommend that you start by reading the following sections:

Create an IAM role for Amazon EC2

To stream metrics, you must first create an IAM role with the AWS managed policy AmazonPrometheusRemoteWriteAccess. Then, you can launch an instance with the role and stream metrics into your Amazon Managed Service for Prometheus workspace.

  1. Open the IAM console at https://console.aws.amazon.com/iam/

  2. From the navigation pane, choose Roles, and then choose Create role.

  3. For the type of trusted entity, choose AWS service. For the use case, choose EC2. Choose Next: Permissions.

  4. In the search bar, enter AmazonPrometheusRemoteWriteAccess. For Policy name, select AmazonPrometheusRemoteWriteAccess, and then choose Attach policy. Choose Next:Tags.

  5. (Optional) Create IAM tags for your IAM role. Choose Next: Review.

  6. Enter a name for your role. Choose Create policy.

Launch an Amazon EC2 instance

To launch an Amazon EC2 instance, follow the instructions at Launch an instance in the Amazon Elastic Compute Cloud User Guide for Linux Instances.

Run the demo application

  1. Use the following template to create a Go file named main.go.

    package main import ( "github.com/prometheus/client_golang/prometheus/promhttp" "net/http" ) func main() { http.Handle("/metrics", promhttp.Handler()) http.ListenAndServe(":8000", nil) }
  2. Run the following commands to install the correct dependencies.

    sudo yum update -y sudo yum install -y golang go get github.com/prometheus/client_golang/prometheus/promhttp
  3. Run the demo application.

    go run main.go

    The demo application should run on port 8000 and show all of the exposed Prometheus metrics. The following is an example of these metrics.

    curl -s http://localhost:8000/metrics ... process_max_fds 4096# HELP process_open_fds Number of open file descriptors.# TYPE process_open_fds gauge process_open_fds 10# HELP process_resident_memory_bytes Resident memory size in bytes.# TYPE process_resident_memory_bytes gauge process_resident_memory_bytes 1.0657792e+07# HELP process_start_time_seconds Start time of the process since unix epoch in seconds.# TYPE process_start_time_seconds gauge process_start_time_seconds 1.61131955899e+09# HELP process_virtual_memory_bytes Virtual memory size in bytes.# TYPE process_virtual_memory_bytes gauge process_virtual_memory_bytes 7.77281536e+08# HELP process_virtual_memory_max_bytes Maximum amount of virtual memory available in bytes.# TYPE process_virtual_memory_max_bytes gauge process_virtual_memory_max_bytes -1# HELP promhttp_metric_handler_requests_in_flight Current number of scrapes being served.# TYPE promhttp_metric_handler_requests_in_flight gauge promhttp_metric_handler_requests_in_flight 1# HELP promhttp_metric_handler_requests_total Total number of scrapes by HTTP status code.# TYPE promhttp_metric_handler_requests_total counter promhttp_metric_handler_requests_total{code="200"} 1 promhttp_metric_handler_requests_total{code="500"} 0 promhttp_metric_handler_requests_total{code="503"} 0

Create an Amazon Managed Service for Prometheus workspace

To create an Amazon Managed Service for Prometheus workspace, follow the instructions at Create a workspace in the Amazon Managed Service for Prometheus User Guide.

Run a Prometheus server

  1. Use the following example YAML file as a template to create a new file named prometheus.yaml. For url, replace my-region with your Region value and my-workspace-id with the workspace ID that Amazon Managed Service for Prometheus generated for you. For region, replace my-region with your region value.

    Example: YAML file

    global: scrape_interval: 15s external_labels: monitor: 'prometheus' scrape_configs: - job_name: 'prometheus' static_configs: - targets: ['localhost:8000'] remote_write: - url: https://aps-workspaces.my-region.amazonaws.com/workspaces/my-workspace-id/api/v1/remote_write queue_config: max_samples_per_send: 1000 max_shards: 200 capacity: 2500 sigv4: region: my-region
  2. Run the Prometheus server to send the demo application’s metrics to your Amazon Managed Service for Prometheus workspace.

    prometheus --config.file=prometheus.yaml

The Prometheus server should now send the demo application’s metrics to your Amazon Managed Service for Prometheus workspace.