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A framework for trace-driven simulation of serverless Function-as-a-Service platforms

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faas-sim: A trace-driven Function-as-a-Service simulator
========================================================

Faas-sim is a powerful trace-driven simulation framework to simulate container-based function-as-a-service platforms.
It can be used to develop, and evaluate the performance of operational strategies for such systems, like scheduling, autoscaling, load balancing, and others.
faas-sim was developed at the [Distributed Systems Group](https://dsg.tuwien.ac.at) at TU Wien as part of a larger research effort surrounding serverless edge computing systems.

High-level architecture
-----------------------

faas-sim is based on the [SimPy](https://simpy.readthedocs.io) discrete-event simulation framework.
It uses [Ether](https://github.com/edgerun/ether) as network simulation layer, and to create cluster configurations and network topologies.
By default, it uses the [Skippy](https://github.com/edgerun/skippy-core) scheduling system for resource scheduling,
but schedulers, autoscalers, and load-balancers can be plugged in by the user.
faas-sim is trace-driven, and relies on profiling data from workloads and devices to simulate function execution.
It comes pre-packaged with traces from several common computing devices and representative cluster workloads.
The following figure shows a high-level overview:

Run examples
------------

You can run the examples we provide in https://github.com/edgerun/faas-sim/tree/master/examples by first creating a virtual environment and installing the necessary dependencies.

make venv
    source .venv/bin/activate
    python -m examples.<example>.main

Where example refers to the specific example package.
Check out the examples [README](https://github.com/edgerun/faas-sim/tree/master/examples/README.md) for more information.

Run notebooks
-------------

Notebooks are located in `notebooks`.
You need to install `faas-sim` in editable state to run the notebooks.
Inside `notebooks` import modules from `sim`.

To install the project (assuming you already created and activated a virtual environment via `make venv`):

pip install -e .
      jupyter notebook

Documentation
-------------

You can find the documentation at https://edgerun.github.io/faas-sim/

Maintainers
------------

* [Thomas Rausch](https://github.com/thrau)
* [Philipp Raith](https://github.com/phip123)

Development
-----------

The simulator has seen a major refactoring in the branch `/feature/adapt-to-galileo-faas` and aims to be compatible with the other galileo projects.
Only this branch is in active development.

Related publications
--------------------

1. Raith, P., Rausch, T., Furutanpey, A., & Dustdar, S. (2023).
   **faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms.**
   In *Software: Practice and Experience*. Wiley Online Library.
   [[Paper](https://onlinelibrary.wiley.com/doi/pdf/10.1002/spe.3277)]
1. Raith, P. (2021)
   Container Scheduling on Heterogeneous Clusters using Machine Learning-based Workload Characterization.
   *Diploma Thesis*. TU Wien.
   [[Thesis](https://repositum.tuwien.at/handle/20.500.12708/16871)]
1. Rausch, T., Lachner, C., Frangoudis, P. A., Raith, P., & Dustdar, S. (2020).
   Synthesizing Plausible Infrastructure Configurations for Evaluating Edge Computing Systems.
   In *3rd USENIX Workshop on Hot Topics in Edge Computing (HotEdge 20)*. USENIX Association.
   [[Paper](https://www.usenix.org/conference/hotedge20/presentation/rausch)]
1. Rausch, T., Rashed, A., & Dustdar, S. (2020)
   Optimized container scheduling for data-intensive serverless edge computing.
   In *Future Generation Computer Systems.*.
   [[Paper](https://www.sciencedirect.com/science/article/pii/S0167739X2030399X)]
1. Rashed, A. (2020)
   Optimized Container Scheduling for Serverless Edge Computing.
   *Diploma Thesis*. TU Wien.
   [[Thesis](http://repositum.tuwien.ac.at/obvutwhs/content/titleinfo/4671607)]

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