Cloud computing changed how we develop applications for the web. Over the last decade, engineers have been learning how to build software in this new paradigm. The costs have gone down, but our nodes can fail at any time. We no longer have to manage individual servers, but the layers of virtualization and containerization require new strategies for communicating between services.
As we have adjusted to this new way of building applications, the term “cloud-native” has become a useful descriptor. Cloud native applications are modern distributed systems capable of scaling to tens of thousands of self healing multi-tenant nodes.
Open source projects such as Kubernetes, Prometheus, and Linkerd draw on the lessons of big technology companies like Google, Twitter, and SoundCloud. Engineers today don’t need to reinvent the key infrastructure of those companies. We can combine the open source cloud-native technologies and use them to build powerful systems.
Dan Kohn is the executive director of the Cloud Native Computing Foundation, and he joins me for an interview about the projects within the CNCF, how they fit together, and the future of computing.
Stay tuned at the end of the episode for Jeff Meyerson’s tip about job searching brought to you by Indeed Prime.
Measuring the Popularity of Kubernetes Using BigQuery
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Deep learning promises to dramatically improve how our world works. To make deep learning easier and faster, we need new kinds of hardware and software–which is why Intel acquired Nervana Systems, a platform for deep learning. Intel Nervana is hiring engineers to help develop a full stack for AI, from chip design to software frameworks. Go to softwareengineeringdaily.com/intel
to apply for a job at Intel Nervana. If you know don’t know much about the company, check out the interviews I have conducted with engineers from the company. You can find these at softwareengineeringdaily.com/intel