Why can't people write their own scheduler if the they pay for instances On May 18, 12:49 am, "Gregory D'alesandre" <[email protected]> wrote: > Hello All! > > As you've likely heard, when Google App Engine leaves Preview in the second > half of 2011, the pricing model will change. Prices are listed > here:http://www.google.com/enterprise/appengine/appengine_pricing.html. But > that > leaves a lot of questions unanswered, this FAQ is intended to help answer > some of the frequently asked questions about the new model. We are > interested in hearing additional thoughts and comments you have based on > this. Once it is relatively stable I'll add it to our official docs. If > you find there is something you want to know but it is not yet answered, > just ask and I'll try to answer it as clearly as possible. We've made some > changes based on the feedback we've gotten (from this group in particular), > they are bolded below but not updated on the external pages yet. There are > still blanks to fill in and I will be sending that information to this group > first in order as it is available. Finally, thank you for your questions > and bearing with us as we are ironing out details, I and the whole App > Engine team very much appreciate it. > > Greg D'Alesandre > Senior Product Manager, Google App Engine > > ------------------- > > *Definitions* > *Instance*: A small virtual environment to run your code with a reserved > amount of CPU and Memory. > *Frontend Instance*: An Instance running your code and scaling dynamically > based on the incoming requests but limited in how long a request can run. > *Backend Instance*: An Instance running your code with limited scaling based > on your settings and potentially starting and stopping based on your > actions. > *Scheduler*: Part of the App Engine infrastructure that determines which > Instance should serve a request including whether or not a new Instance is > needed. > > *Serving Infrastructure* > Q: What’s an Instance? > A: When App Engine starts running your code it creates a small virtual > environment to run your code with a reserved amount of CPU and Memory. For > example if you are running a Java app, we will start a new JVM for you and > load your code into it. > > Q: Is an App Engine Instance similar to a VM from infrastructure providers? > A: Yes and no, they both have a set amount of CPU and Memory allocated to > them, but GAE instances don’t have the overhead of operating systems or > other applications running, so a much larger percentage of the CPU and > memory is considered “usable.” They also operate against high-level APIs and > not down through layers of code to virtual device drivers, so it’s more > efficient, and allows all the services to be fully managed. > > Q: How does GAE determine the number of Frontend Instances to run? > A: For each new request, the Scheduler decides whether there is an available > Instance for the request, the request should wait, or a new Instance should > be created to service the request. It looks at the number of Instances, the > throughput of the Instances, and the number of requests waiting. Based on > that it predicts how long it will take before it can serve the request (aka > the Pending Latency). If it predicts the delay will be over 1 second, a new > Instance is created. If it looks like an Instance is no longer needed, it > will take that Instance down. > > Q: Should I assume I will be charged for the number of Instances currently > being shown in the Admin console? > A: No, we are working to change the Scheduler to optimize the utilization of > instances, so that number should go down somewhat. If you are using Java, > you can also make your app threadsafe and take advantage of handling > concurrent requests. You can look at that as an upper bound on how many > Instances you will be charged for. > > Q: How can I control the number of instances running? > A: With the new Scheduler you’ll have the ability to choose a set of > parameters that will help you specify how many instances are spun up to > serve your traffic. More information about the specific parameters and how > they will affect the Scheduler will be available on this within a few weeks. > > Q: What can I control in terms of how many requests an Instance can handle? > A: The single largest factor is your application’s latency in handling the > request. If you service requests quickly, a single instance can handle a > lot of requests. Also, Java apps support concurrent > requests<http://code.google.com/appengine/docs/java/config/appconfig.html#Usin...>, > so it can handle additional requests while waiting for other requests to > complete. This can significantly lower the number of Instances your app > requires. > > Q: Will there be a solution for Python concurrency? Will this require any > code changes? > Python concurrency will be handled by our release of Python 2.7 on App > Engine. We’ve heard a lot of feedback from our Python users who are worried > that the incentive is to move to Java because of its support for concurrent > requests, so we’ve made a change to the new pricing to account for > that. *While > Python 2.7 support is currently in progress it is not yet done so we will be > providing a half-sized instance for Python (at half the price) until Python > 2.7 is released.* > > Q: How many requests can an average instance handle? > A: Single-threaded Instances (python or java) can currently handle 1 > concurrent request. Single-threaded Instances (python or java) can > currently handle 1 concurrent request. Therefore there is a direct > relationship between the latency and number of requests which can be handled > on the instance per second, for instance: 10ms latency = 100 > request/second/Instance, 100ms latency = 10 request/second/Instance, etc. > Multi-Threaded Instances can handle many concurrent requests. Therefore > there is a direct relationship between the cpu consumed and the number of > requests/second. For instance, for a B4 (approx 2.4GHz) instance: consuming > 10 Mcycles/request = 240 request/second/Instance, 100 Mcycles/request = 24 > request/second/Instance, etc. These numbers are the ideal case but they are > pretty close to what you should be able to accomplish on an Instance. > Multi-Threaded instances are currently only supported for Java; we are > planning support for Python later this year. > > Q: Why is Google charging for instances rather than CPU as in the old model? > Were customers really asking for this? > A: CPU time only accounts for a portion of the resources used by App Engine. > When App Engine runs your code it creates an Instance, this is a maximum > amount of CPU and Memory that can be used for running a set of your code. > Even if the CPU is not currently working due to waiting for responses, the > instance is still resident and considered “in use” so, essentially, it still > costs Google money. Under the current model, apps that have high latency > (or in other words stay resident for long periods of time without doing > anything) are not able to scale because it would be cost-prohibitive to > Google. So, this change is designed to allow developers to run any sort of > application they would like but pay for all of the resources that are being > used. > > Q: What does this mean for existing customers? > A: Many customers have optimized for low CPU usage to keep bills low, but in > turn are often using a large amount of memory (by having high latency > applications). This new model will encourage low latency applications even > if it means using larger amounts of CPU. > > Q: How will always-on work under the new model? > A: Still determining how this will work, answer coming very soon (no > seriously, we are almost done). > > Q: What is the difference between On-demand Instances and Reserved > Instances? > A: On-demand Instances have no pre-commitment in terms of the number that > will be used. You pay for them as you use them. Reserved Instances are > pre-commitment to a certain number of Instance Hours in a week. They are > cheaper but you must pay for all the Instance Hours that you have > pre-committed to whether you use them or not. This does not mean they have > to be running the whole time. > > Q: Wait, so Reserved instances don’t mean you have to keep them running the > whole time? > A: No, it is just a way to get cheaper instance-hours by pre-committing to > them. > > Q: What is the time granularity of the instance pricing? ie if I have an > instance up for 5 minutes, what am I charged, $0.08 / 60*5? > A: Instances are charged for their uptime and until they are idle for 15 > minutes (when the scheduler takes them down). So if you have an on-demand > Instance only serving traffic for 5 minutes, you will pay for 5+15 minutes, > or $0.08 / 60 * 20 = 2.6 cents. > > Q: You seem to be trying to account for RAM in the new model. Will I be > able to purchase Frontend Instances that use different amounts of memory? > A: We are only planning on having one size of Frontend Instance. > > Q: Do Frontend instances handle Task Queues and Cron? > A: Yes. > > Q: Can the experimental Go Runtime handle concurrent requests? > A: Not currently. > > *Costs* > Q: Is the $9/app/month a fee or a minimum spend? > A: *Based on the feedback we’ve received we are changing this $9 fee to be a > minimum spend rather than a fee a originally listed*. In other words you > will still have to spend $9/month in order to scale but you won’t pay an > additional $9 for your first $9 worth of usage each month. The > $500/account/month will still be a fee as it covers the cost of operational > support. > > Q: Will most customers have to move to Paid Apps? > A: No, we expect the majority of current active apps will still fall under > the free quota. > > Q: Will existing apps be grandfathered in and continue under today’s billing > model? > A: No, existing apps will fall under the new billing model once App Engine > is out of preview. > > Q: Will most customers’ bills increase? If so, why is Google increasing the > price for App Engine? > A: Yes, most paying customers will see higher bills. During the preview > phase of App Engine we have been able to observe what it costs to run the > product as well as what typical use patterns have been. We are changing the > prices now because GAE is going to be a full product for Google and ... > > read more »
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