Challenges and opportunities in sustainable serverless computing

Our preliminary empirical investigation suggests that FaaS applications can be up to 15× more energy hungry than conventional web services. This energy and carbon (in)efficiency is unfortunately a fundamental attribute of serverless functions owing to their programming model and security isolation requirements. As FaaS usage continues its exponential growth, understanding and narrowing this energy gap will be vital for the carbon footprint of the overall computing ecosystem.

Serverless functions can provide some unique opportunities to reduce cloud carbon footprint, because of their location independence and programming model. Many energy-first techniques such as workload migration and demandresponse scaling, which are challenging for conventional VMs and containers, can be significantly easier to develop and optimize for serverless functions that can be “run anywhere”. FaaS can thus provide new energy knobs to cloud platforms for moving applications to carbon-friendly locations quickly and in a fine-grained manner, which will be especially beneficial for distributed edge clouds powered by intermittent renewable energy like solar and wind.

The control plane itself is highly distributed with many components such as API gateways, distributed message queues (such as Kafka), and databases. Thus the resource and energy footprint of functions is spread out across function initialization and virtualization components, and the control plane itself.

Measuring the energy consumption of applications is non-trivial because of multi-processing, limited hardware support, and fairly attributing the consumption of shared resources (such as the OS) [12, 20]. Software power monitors [13, 14, 41] use application and system level power models that relates resource consumption (such as CPU time and frequency) to actual physical power [11].

FaaS virtualization overheads can increase the energy consumption by more than 15x compared to conventional HTTP servers.

The conventional web server (python’s builtin httpserver), which does not incur any virtualization over- heads, requires around 0.6 Joules to serve a simple static “GET /” request. The FaaS approach requires using a Docker container, and the overhead of creating the container increases the energy footprint by 15×. Specifically, we measure the average energy consumption of a docker run command which spawns a container, and prints the contents of the home directory (equivalent to the above HTTP server’s output), and destroys the container. Finally, we investigate full hardware virtualization, by spawning a Firecracker lightweight VM [4], and find its energy consumption to be more than 30× that of the simple HTTP server.

Keeping function execution environments in memory is likely to reduce the energy footprint just like it does the performance [15, 29], but the extra memory (and hence energy) consumption may offset those benefits.

By decoupling computation from its location, serverless computing allows us to run functions at the most energy-suitable location. Thus even though individual functions may not be energy efficient, they can be run in carbon-friendly locations to achieve better carbon efficiency.