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Cold-start latency is determined by the time it takes to load all the classes needed to handle the request. If you upload a JAR file, but nothing references it, it won't be loaded, and thus won't affect your cold-start latency.

Only those jars under WEB-INF/lib will be uploaded to GAE. You can prevent GWT jars from being uploaded by not placing them under WEB-INF/lib, rather by externally linking to them in your project build path.

The remote_api module consists of two parts: A 'handler', which you install on the server to handle remote datastore requests, and a 'stub', which you set up on the client to translate datastore requests into calls to the remote handler. remote_api works at the lowest level of the datastore, so once you've set up the stub, you don't have to worry about the fact that you're operating on a remote datastore: With a few caveats, it works exactly the same as if you were accessing the datastore directly.

Note that the handler specifies "login: admin". This is extremely important, since we don't want to give just anyone unfettered access to our datastore!

Since you're accessing the datastore over HTTP, there's a bit more overhead and latency than when you access it locally. In order to speed things up and decrease load, try to limit the number of round-trips you do by batching gets and puts, and fetching batches of entities from queries. This is good advice not just for remote_api, but for using the datastore in general, since a batch operation is only considered to be a single Datastore operation

About loading request/performance, there're lots of discussions that you can find in the groups, please just try google it. Here are some notes based on reading those. Latency causes by 1- time to start new JVM 2- time to load your application To reduce load time by 1) others star request to a) pay to reserve JVM b) request Google to load your app before start dispatch request to that instance c) accept the situation For 2) we try to a- try to use/replace frameworks with light-weight ones: datastore access framework, MVC framework,... b- try to limit calculation in your index page to alleviate the impact of loading request c- design your object model based on your need, so that you do calculation at insert time, not at query time. For example, in my app, if I want to report on year and quarter, then I have 5 summary "record" for those, instead of querying and computing those d- caching result. For example, If I know 1 one 5 piece of data above would be read frequently, then I will read those 5 all, and put into memcache for later use ... So it's application-specific, I don't know if each of above can help you. But only you who can know if which one of your code can be cached and how...