WebAssembly (WASM) - The Silent Infrastructure Revolution

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Which of the following topics are you most excited by?

I am particularly excited about WebAssembly(WASM) and the impact this technology can have on the infrastructure space.

Why does it excite you?

WASM has the potential to change the cloud landscape. As a smaller deployment unit with a shorter cold start time, it can enable workload deployments at the edge and dramatically densify cloud workload.

It’s a silent revolution because — if it reaches full potential — developers will be able to simply repackage/recompile existing software to WASM to leverage it, instead of packaging and deploying in containers.

WASM is already enabling developers to run external code safely within their applications, or allowing developers to create rich applications that run in the browser. It also allows the use of LLM in web browsers, both on desktop and mobile. A promising solution alongside the SML trend. This helps democratize model usage on the client side instead of the server side, which can strengthen privacy/security since it avoids sending private data to remote models.

Overall, WASM excites me because it will densify cloud deployment, enable more AI workloads at the edge, drive down cost, drive down general resource consumption, and help manage data privacy at the edge. And this is just the beginning.

What are the trends in this area or products in this area that you are the fondest of? Why?

There is a lot of innovation when it comes to WASM. I am particularly fond of wasmCloud and all the efforts they make in standardizing WASM capability providers. With the help of Cosmonic and a common customer, we’ve developed a WASM provider that enables developers to use Couchbase's core database functionalities (key/value, SQL, and full text or vector search) in wasmCloud architecture. This already allows developers to build scalable, function-based applications, and to benefit from the consumption reduction that comes along with Function-as-a-Service architectures.

What are the positive impacts they can have on society?

Deploying software across edge locations and cloud data centers with zero scaling capabilities could reduce infrastructure requirements, potentially decreasing both energy consumption and hardware resource usage. This is an important consideration to address technology’s innovation impact on climate change.

This method also reduces operational and consumption costs and leads to more commoditization of hardware — similar to what we’ve seen at the beginning of the cloud industry. Fun fact: the Couch in Couchbase originated from CouchDB, which stands for a cluster of unreliable commodity hardware.

What are the negative impacts they can have on society?

For better or worse, WASM will accelerate the adoption of AI and other new technologies at the Edge or in the browser, and as such, increase our reliance on connected devices or the WEB. This could reinforce the Digital Divide.

What are your predictions on how these technologies will evolve?

It is still early for the WASM ecosystem. A lot of work still needs to be done on WASM runtimes to reach its full potential. While this might not happen in the immediate future, we can see some runtimes aiming at POSIX compatibility. This would be an incredible step to make WASM ubiquitous.

WASM is being integrated into existing software platforms as a plugin system. This allows platforms to safely run code from third-party developers without compromising security. We will also see more platform teams embrace WASM as a common runtime for ephemeral workloads like FaaS, ETL, or AI agents.

What are your predictions on the ethics of future societies in relation to these technologies?

Being able to ship workload or run software directly on devices could reverse the current trend. Instead of shipping our data to the cloud, software vendors could run computational tasks and processing directly on our personal computers, phones, and IoT devices using WASM. This can have immediate impacts on personal data and privacy, as sensitive information like health data, financial records, and personal photos can be processed locally without ever leaving your device.

I am particularly interested in what progress we will see in the space of federated/distributed learning as it gets enabled by WASM, where ML models can be trained across multiple devices while keeping each user's data private and secure. This could revolutionize how we develop AI applications that respect user privacy.