Google released App Engine 1.1.9 this week, including new capacity ceilings for developers and better compatibility with existing Python code. The new App Engine supports standard HTTP libraries, larger files, triples the response deadline, and removes limitations on CPU-intensive processes.
I have learned a few App Engine best practices over over the past month and would like to share some best practices for App Engine development gained mostly through trial and error. In this post I will share data optimization tips for Google’s hosted Bigtable instance, reduce the errors and resource usage of your application, and add a few steps to your deployment checklist.
Google App Engine lets any Python developer execute CGI-driven Web applications, store its results, and serve static content from a fault-tolerant geo-distributed computing grid built exclusively for modern Web applications. In this post I will summarize Google App Engine from a developer’s point of view, outline its major features, and examine pitfalls for developers and startups interested in deploying web applications on Google’s servers.