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Auto-scaling is the ability (with certain cloud infrastructure management tools like enStratus-in a limited beta through the end of the year) to add and remove capacity into a cloud infrastructure based on actual usage. No human intervention is necessary. It sounds amazing-no more overloaded web sites. Just stick your site into the cloud and come what may! You just pay for what you use. But I don't like auto-scaling.

Public Data Sets on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community, and like all AWS services, users pay only for the compute and storage they use for their own applications.

So here's the real trick: cloud computing is real. Everything is moving into the cloud, in whole or in part. The utility layer of cloud computing will be just that, a utility, without outsized profits. But the cloud platform, like the software platform before it, has new rules for competitive advantage. And chief among those advantages are those that we've identified as "Web 2.0", the design of systems that harness network effects to get better the more people use them.

What if you could contribute to a computational (Map-Reduce) job by simply pointing your browser to a URL? Surely your social network wouldn't mind opening a background tab to help you crunch a dataset or two! Instead of focusing on high-throughput proprietary protocols and high-efficiency data planes to distribute and deliver the data, we could use battle tested solutions: HTTP and your favorite browser.

Database systems are notorious for being hard to use. It is even more difficult to integrate data from multiple sources and collaborate on large data sets with people outside your organization. Without an easy way to offer all the collaborators access to the same server, data sets get copied, emailed and ftp'd--resulting in multiple versions that get out of sync very quickly. Today we're introducing Google Fusion Tables on Labs, an experimental system for data management in the cloud. It draws on the expertise of folks within Google Research who have been studying collaboration, data integration, and user requirements from a variety of domains. Fusion Tables is not a traditional database system focusing on complicated SQL queries and transaction processing. Instead, the focus is on fusing data management and collaboration: merging multiple data sources, discussion of the data, querying, visualization, and Web publishing. We plan to iteratively add new features to the systems as we get feedback from users.

This document is intended to initiate a conversation that will bring together the emerging cloud computing community (both cloud users and cloud providers) around a core set of principles. We believe that these core principles are rooted in the belief that cloud computing should be as open as all other IT technologies.

The Drizzle project is building a database optimized for Cloud and Net applications. It is being designed for massive concurrency on modern multi-cpu/core architecture. The code is originally derived from MySQL.