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Chrome Frame - How to add command line parameters

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Chrome frame intentionally does stuff without getting in the way of the user. This sometimes makes things harder to debug. For example how can one debug an issue if chrome frame doesn't even launch ? Apparently there is a flag for that. But you have to know how to enable it. Here are the steps. Make sure chrome frame is installed. We can enable startup flags for dumping debug logs using a policy called AdditionalLaunchParameters If this is just for one desktop, I recommend doing a registry edit (it can be pushed via GPO as well) Add a REG_SZ property " AdditionalLaunchParameters " to " SoftwarePoliciesGoogleChromeAdditionalLaunchParameters " with the value "--enable-logging --v=1" (also documented here  and mentioned here )  [ Attachment 1 ] Next kill the IE browser and make sure chrome is also dead by checking taskmgr Restart IE and go to " gcf:about:version " and confirm that the parameters you added show up next to "Command Line:"
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Creating your first chrome app on a Chromebook

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Doing development on Chromebook usually means developing online. There are a lot of sites around for that. But with the APIs getting more mature, its just a matter of time before someone builds a kick-ass IDE which runs natively on Chromebooks without network connectivity. One such tool which I've been exploring for a last few weeks is from Google and called " Chrome Dev Editor " If you have never built and run a chrome app or extension, I'll show you how to do this in 3 easy steps.     Step 1 Launch the app and click on the "+" button to add a new project. Pick a project name and select "JavaScript Chrome App" in the drop down menu.       Step 2 Notice how it automatically adds the minimum code required for it to run. This will be the template you are going to work with. You are almost done, but lets review the files in there to understand why they are there.   manifest.json - This is the most important file. Modify the app name, version number
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Brewers CAP Theorem on distributed systems

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Large distributed systems run into a problem which smaller systems don’t usually have to worry about. “ Brewers CAP Theorem ” [ Ref 1 ] [ Ref 2 ] [ Ref 3 ]  defines this problem in a very simple way. It states, that though its desirable to have Consistency, High-Availability and Partition-tolerance in every system, unfortunately no system can achieve all three at the same time . C onsistent : A fully Consistent system is one where the system can guarantee that once you store a state (lets say “x=y”) in the system, it will report the same state in every subsequent operation until the state is explicitly changed by something outside the system. [ Example 1 ] A single MySQL database instance is automatically fully consistent since there is only one node keeping the state. [ Example 2 ] If two MySQL servers are involved, and if the system is designed in such a way that all keys starting “a” to “m” is kept on server 1, and keys “n” to “z” are kept on server
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