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Google Compute Engine and Google App Engine: What is the difference?

What is the difference between Google Compute Engine and Google App Engine?

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Google Compute Engine is Google's answer to Amazon AWS. It is an Infrastructure as a Service (IaaS) that allows enterprises to provision virtual servers and persistent storage to run practically any software that would run in the data center. Google App Engine, however, is a Platform as a Service (PaaS) that allows users to take advantage of Google's compute and storage infrastructure without managing implementation details associated with IaaS servers and storage.

If you want virtual hardware or all-you-can-use storage, then Google Compute Engine is a good start. You can run virtual machines with Ubuntu or CentOS operating systems, one to eight virtual cores and 3.75 GB or RAM per core. You also get persistent disks and access to Google Cloud Storage for object-based storage needs. With Google Compute Engine, you also have some control over the network. For example, you can use either static or dynamic addresses, and can configure a simple firewall for basic control of network traffic.

Currently, the Google App Engine supports PHP, Java, Python and GO. It also supports common Web technologies, performs automatic scaling and load balancing, provides for authentication using Google accounts and provides task queues and schedulers for background processing. If you develop a new Web- or compute-intensive application, or have an existing application using one of the supported technologies, then Google App Engine may be an option for you -- but watch out for vendor lock-in.

About the author:
Dan Sullivan, M.Sc., is an author, systems architect and consultant with more than 20 years of IT experience. He has had engagements in advanced analytics, systems architecture, database design, enterprise security and business intelligence. He has worked in a broad range of industries, including financial services, manufacturing, pharmaceuticals, software development, government, retail and education. Dan has written extensively about topics that range from data warehousing, cloud computing and advanced analytics to security management, collaboration and text mining.

This was first published in July 2013

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