Azure Benchmarking

Introduction

This guide provides instructions on how to deploy and benchmark Azure Functions using STeLLAR.

Pre-requisites

1. Microsoft Azure account with an active subscription ID

Setup

To deploy functions and run experiments on Azure Functions through STeLLAR, the Serverless framework and the serverless-azure-functions plugin must be installed. Azure credentials also need to be configured.

1. Run the setup script to install dependencies required for running STeLLAR (Note: You may need to change permissions of the script to allow execution):

   chmod +x ./scripts/setup.sh
   ./scripts/setup.sh

2. Create an Azure Service Principal with a secret (for more information, see here):

   az ad sp create-for-rbac --name "STeLLAR" --role contributor \
   --scopes /subscriptions/<your_azure_subscription_id> \
   --sdk-auth

3. Set the following environment values:

   AZURE_SUBSCRIPTION_ID=<your_azure_subscription_id>
   AZURE_TENANT_ID=<your_azure_tenant_id>
   AZURE_CLIENT_ID=<your_azure_client_id>
   AZURE_CLIENT_SECRET=<your_azure_client_secret>
   

In addition, STeLLAR requires two core components to deploy and benchmark serverless functions: The function code and a JSON file specifying experiment parameters.

Function code

Put your code directory at src/setup/deployment/raw-code/serverless/azure/<function_code_dir>.

Experiment JSON file

The JSON file specifying configurations can be placed at any path. The folder for our examples can be located under the experiments/ folder. For examples of experiment JSON files, see here.

Summary of experiment JSON file values:

Key	Type	Description
Sequential	boolean	Specifies whether to run sub-experiments sequentially or in parallel.
Provider	string	Specifies the Cloud Provider to deploy the function to. (e.g. aws, azure, gcr, cloudflare etc.)
Runtime	string	Specifies the runtime of the function. (e.g. python3.8, nodejs18 etc.)
SubExperiments	array	Array of objects specifying specific experiment parameters for each sub-experiment.
Title	string	Name of the sub-experiment.
Function	string	Name of the function. This must be the same value as <function_code_dir>.
Handler	string	Entry point of the function. This should follow the format of <your_file_name_without_extension>.<your_handler_function_name>.
PackageType	string	Specifies the type of packaging for function upload. Only Zip is currently accepted for STeLLAR benchmarking of Azure.
Bursts	number	Specifies the number of bursts to send to the deployed function(s).
BurstSizes	array	Specifies the size of each burst when invoking the deployed function(s). STeLLAR iterates and cycles through the array for each burst.
DesiredServiceTimes	array	Specifies the desired service execution time(s) when invoking the deployed function(s). STeLLAR iterates and cycles through the array for each burst. These execution times are achieved by calculating the corresponding busy spin count for the desired time on the host running the STeLLAR client.
FunctionImageSizeMB	number	Specifies the target size of the function to upload.
Parallelism	number	Specifies the number of concurrent endpoints to deploy and benchmark. Useful for obtaining cold-start samples within a shorter period of time.

Benchmarking

1. Compile the STeLLAR binary at the src directory:

   cd src
   go build main.go

2. Run the compiled binary:

   ./main -o <output_folder_path> -c <experiment_json_file_path> -l <log_level>

Summary of the flags available:

Flag	Description
-o	Specifies the directory in which to store experiment results. Each experiment creates a folder named after the timestamp when it was created which is stored inside this directory.
-c	Specifies the path of the experiment JSON file which is used to run the experiments on.
-l	Specifies the log level to print to the console output. Default value is set to info. Possible values: info, debug

Obtaining Results

STeLLAR generates statistics as well as a CDF diagram after the experiments are completed. These results can be found under <output_folder_path/<experiment_timestamp>. It contains:

• /<subexperiment_title>/latencies.csv: All recorded request latencies for individual invocations
• /<subexperiment_title>/statistics.csv: Statistical information such as percentile, standard deviation, etc.
• /<subexperiment_title>/empirical_CDF.png: A CDF diagram of the sample latencies