Serverledge is a Function-as-a-Service (FaaS) framework designed to work in Edge-Cloud environments.

Serverledge allows user to define and execute functions across distributed nodes located in Edge locations or in Cloud data centers. Each Serverledge node serves function invocation requests using a local container pool, so that functions are executed within containers for isolation purposes. When Edge nodes are overloaded, they can to offload computation to neighbor Edge nodes or to the Cloud.

Note that Serverledge is a research prototype and it is not (yet) meant to be used for production use, as it may lack critical security features.

Serverledge has been first described in a paper presented at IEEE PerCom 2023. If you use Serverledge in your own work, please cite it:

@inproceedings{serverledge2023percom,
  author={Russo Russo, Gabriele and Mannucci, Tiziana and Cardellini, Valeria and Lo Presti, Francesco},
  booktitle={2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)}, 
  title={Serverledge: Decentralized Function-as-a-Service for the Edge-Cloud Continuum}, 
  year={2023},
  pages={131-140},
  doi={10.1109/PERCOM56429.2023.10099372}
}

Serverledge has been used in other scientific papers, including:

• F. Righetti, B. Cornacchia, G. Russo Russo, N. Tonellotto, V. Cardellini, C. Vallati, Energy-Efficient Function Invocation Scheduling for Edge FaaS Platforms, Proc. of 2025 IEEE Int'l Conference on Smart Computing (SMARTCOMP '25), doi

• R. Farahani, N. Mehran, S. Ristov, R. Prodan, HEFTLess: A Bi-Objective Serverless Workflow Batch Orchestration on the Computing Continuum. Proc. of IEEE Int'l Conference on Cluster Computing (CLUSTER '24): 286-296, doi

• G. Russo Russo, D. Ferrarelli, D. Pasquali, V. Cardellini, F. Lo Presti, QoS-aware offloading policies for serverless functions in the Cloud-to-Edge continuum, Future Gener. Comput. Syst. 156: 1-15 (2024), doi

• A. Semjonov, H. Bornholdt, J. Edinger, G. Russo Russo, Wasimoff: Distributed Computation Offloading Using WebAssembly in the Browser, Proc. of *LESS 2024 (in conjunction with IEEE PerCom '24), 203-208, doi

Requirements

• Linux OS
• Docker Engine
• Golang 1.24+

Building from sources

Download a copy of the source code and build the project:

$ make

You will find executables in ./bin/.

Running (single-node deployment)

As functions are executed within Docker containers, you need Docker to be installed on the host. Furthermore, Serverledge needs permissions to create containers.

You also need an etcd server to run Serverledge. To quickly start a local server, just download a recent release of etcd and just run ./etcd.

Start a local Serverledge node:

$ bin/serverledge

Creating and invoking functions

Register a function func from example python code (the handler is formatted like this: $(filename).$(functionName)):

$ bin/serverledge-cli create -f func --memory 600 --src examples/hello.py --runtime python310 --handler "hello.handler"

Register a function func from example javascript code (the handler is formatted like this: $(filename) and the name of the function is "handler"):

$ bin/serverledge-cli create -f func --memory 600 --src examples/hello.js --runtime nodejs17ng --handler "hello"
$ bin/serverledge-cli create -f func --memory 600 --src examples/inc.js --runtime nodejs17ng --handler "inc"

Invoke func with arguments a=2 and b=3:

$ bin/serverledge-cli invoke -f func -p "a:2" -p "b:3"

For non-trivial inputs, it is recommended to specify function arguments through a JSON file, instead of using the -p flag, as follows:

$ bin/serverledge-cli invoke -f func --params_file input.json

where input.json may contain:

{
	"a": 2,
	"b": 3
}

Getting function standard output

You may want to see the content printed by the function to its standard output/error. To do so, add the --return_output flag (-o for short):

$ bin/serverledge-cli invoke -f func -p "a:2" -p "b:3" --return_output

Note that we currently support output capture only for some runtimes (e.g., Python supports it).

Distributed Deployment

This repository provides an Ansible playbook to deploy Serverledge in a distributed configuration.

In this case, you can instruct serverledge-cli to connect to a node other than localhost or use a non-default port by means of environment variables or command-line options:

• Use --host <HOST> (or -H <HOST>) and/or --port <PORT> (or, -P <PORT>) to specify the server host and port on the command line
• Alternatively, you can set the environment variables SERVERLEDGE_HOST and/or SERVERLEDGE_PORT, which are read by the client.

Example:

$ bin/serverledge-cli status -H <host ip-address> -P <port number>

Configuration

You can provide a configuration file using YAML or TOML syntax. Depending on the chosen format, the default file name will be serverledge-conf.yaml or serverledge-conf.toml. The file can be either placed in /etc/serverledge, in the user $HOME directory, or in the working directory where the server is started.

Alternatively, you can indicate a specific configuration file when starting the server:

$ bin/serverledge <config file>

Further information about supported configuration options is available here.

Example

The configuration file may look like this:

container.pool.memory: 4096
etcd.address: "1.2.3.4:2379"
scheduler.queue.capacity: 0
metrics.enabled: true

Workflows

Serverledge has been extended to support the composition of multiple functions into workflows. More information here

Additional Documentation

• API reference
• Writing functions
• Serverledge Internals: Executor
• Metrics

Related Projects

A graphical UI to demonstrate the functionality of Serverledge has been developed at the Dept. of Information Engineering @ University of Pisa, Italy. The project can be found here

License

Serverledge is distributed under the terms of the MIT license.