Baresoil Image Resizing API Benchmark

This benchmark is for reproducibly measuring the real-world performance and cost of hosting a simple image processing API on a Baresoil cluster running on AWS.

Latest Benchmark Report · Demo · Homepage

The API accepts JPEG image uploads via HTTP POST requests, and uses GNU ImageMagick to return the following results:

• a data URL representation of a cropped, oriented, square thumbnail of the upload, up to 128x128 pixels, stripped of metadata.
• a data URL representation of an oriented, resized, and color-corrected version of the upload, up to 640x640 pixels, stripped of metadata.
• A JSON object containing all Exif camera metadata found in the uploaded image.

The project's client component contains a simple web UI to invoke the API and display its results.

Requirements

Install the Benchoid cloud benchmarking framework:

npm install -g benchoid

Benchoid requires Terraform, OpenSSH, and rsync available on your system, and an AWS access key.

Download or clone this repository into a directory and run the commands below inside it.

Subdirectories

• agent: Simulated user agent to generate traffic.
• analysis: Scripts for processing experimental data output.
• project: Baresoil app project to be deployed to the server.
• render: Template for generating reports.
• run_data: Experimental data generated by Benchoid.

Instructions

1. Deploy the Baresoil project in the project directory to the server that is to be load tested. Change the variable ENDPOINT in the file agent/main.js to point to the top-level domain name of the server. If using HTTPS, ensure that the protocol is set to wss:// rather than ws://.
2. Run benchoid create-cluster in the current directory to generate Terraform files to provision a client cluster to be used for generating artificial traffic to the target server or load balancer.
3. Run benchoid setup-cluster to execute the contents of setup.sh in parallel on all client tier machines.
4. Run benchoid sync to rsync the contents of the agent directory to all hosts in the client tier.
5. Run benchoid run to prompt for parameters for a new experimental run and then to execute the agent according to those parameters.
6. Run benchoid analyze to run analysis functions on the raw event data.
7. Run benchoid render to create a self-contained HTML report in the dist subdirectory.