The computing industry is at an inflection point where we have an opportunity to revisit the fundamentals of what has led to current conventional wisdom and best practices for building computing infrastructure. I'm most excited about the innovation we're driving through our software and hardware developments – we have a unique opportunity to define what the architectural principles for infrastructure over the coming decades. So whether it's through machine learning capabilities, top-tier security, reliability, and availability, or the rise of Edge computing and sovereignty, we're providing our customers with the right foundation to leverage the transformative power of compute infrastructure. These principles for the infrastructure of the future will enable services that can improve our productivity, health, and happiness in ways that we cannot imagine today.

The scale and impact of Google services give me a unique opportunity to use the world's resources wisely and improve the productivity of an enormous number of people.

I like that my work addresses an important problem. Networking is critical to running the business and serving the users of Google. The work is deeply technically challenging and the ecosystem is organizationally complicated and incredibly rich – which means that I’m continually being stretched (in a good way!) and yet still have opportunities to grow and learn.

What attracted me to Google nine years ago was that they were defining this Cloud architecture, the set of cloud services that will define how people will do computing for the next several decades. And what’s been further exciting is that this is not a static answer. The abstractions we were defining nine years ago formed the baseline layer of a cloud infrastructure. Now we can build on that baseline layer and provide higher-level, more powerful abstractions.

The most exciting system problems these days have to do with scale. We get scale because of the immense workload that we support: Websearch, YouTube, Knowledge Graph, Google Assistant, Android, Chrome, Maps, Cloud. Each one of these businesses alone runs at a really large scale. We get to look at the underlying infrastructure.

I think of systems as the technical discipline of integrating hardware, software, and distributed systems building blocks to solve a complex problem. Some examples of exciting systems projects I've worked on at Google include: building scalable and reliable data center networks; integrating hardware accelerators into our cloud network and storage systems; and, building record, replay, and simulations systems that can permit Google to capture and troubleshoot operational issues in production networks. A Systems engineer can assemble, evolve, and optimize building blocks into something that is powerful and capable.

As the silicon space undergoes transformation from the dramatic slowing of Moore's Law and the democratization of silicon development (open source hardware), Google is in a unique place to become a leader in silicon. Google's scale and expertise in the open source space, along with its full stack ownership, allows the company to innovate and contribute in ways that many others simply cannot. I am excited to be expanding Google's presence in the dynamic field of chip design as my team and I advance custom silicon and chip implementation methodologies for Google and Alphabet.

Highly performant, reliable and efficient systems can only be possible with a culture of deep collaboration between compute, storage and networking along with vertical integration with application teams, something we strive hard to enable within Google. The tight feedback loop we have from applications, service owners, and customers provides early input on the impact of a new technology to the end user.