Greg,
Still not clear on the datastore costs. For this you say, "This means
the cost of your queries will be tied exclusively to the size of your
result set." Is this the same whether you return just the keys (keys
only query) or also the entities. It seems like it should not be the
same since a fetch to get the whole entity is not required but I'm not
clear when you say "size of your result set." I think a lot of people
have tried to optimize some operations by just returning the keys and
not the entire entities and I hope that wasn't wasted effort.
Thanks,
Stephen

On Tue, May 17, 2011 at 10:13 PM, Robert Kluin <robert.kl...@gmail.com> wrote:
> Hi Greg,
>  I'm looking forward to seeing the scheduler improvements in the
> coming weeks.  Overall this looks promising, I'm actually pretty happy
> to see that the API calls 'with checks' will be included and just
> billed by time consumed.  Is the 4x cost relative to a master-slave
> (M/S) or high-replication (HR) apps?  Certainly if that is relative to
> M/S then it is not that bad, HR is totally worth it.  ;)
>
>  Thanks for listening to and addressing the community's feedback.
>
>
>
> Robert
>
>
>
>
>
>
>
> On Wed, May 18, 2011 at 00:49, Gregory D'alesandre <gr...@google.com> 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, 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
>> therefore needs to have a sustainable revenue model for years to come.
>>
>> APIs
>> Q: How were the APIs priced?
>> A: For the most part the APIs are priced similarly to what they cost today,
>> but rather than charging for CPU hours we are charging for operations.  For
>> instance the Channel API is $0.01/100 channels.  This is approximately what
>> users pay today (although it would be paid as a fraction of a CPU hour).
>>  The datastore API is the most significantly changed and is described below.
>>
>> Q: For the items under APIs on the pricing page that just have a check, what
>> does that mean?
>> A: Those items come free with using App Engine.
>>
>> Q: For XMPP, how does the new model work?  How much do presence messages
>> cost?
>> A: For XMPP we will only be charging an operation fee for outgoing stanzas.
>>  Incoming stanzas are just considered requests similar to any other request
>> and so we’ll charge for the bandwidth used as well as whatever it takes to
>> process the request in terms of Instance Hours.  We don’t charge for
>> presence messages other than the bandwidth it consumes.  This is almost
>> exactly how it works today with the exception that your bill would show CPU
>> hours as opposed to Stanzas.
>>
>> Q: For Email, how much do incoming emails cost?
>> A: Incoming emails will just be considered requests similar to any other
>> request and so we’ll charge for the bandwidth used as well as whatever it
>> takes to process the request in terms of Instance Hours.  This is in essence
>> how it works today.
>>
>> Q: Will the Front End Cache feature ever be formalized as an expected,
>> documented part of the service offering?
>> A: We are currently looking at various options, but don’t yet have any plans
>> for when this would happen.
>>
>> Q:  What is being charged for in terms of Datastore operations?  What do you
>> expect the ratio to be between the new pricing metric and the Datastore API
>> calls metric we have today?
>> A: Today we charge for the CPU consumed per entity written, index written,
>> entity read, query index scanned, and query result read.  Under the new
>> model we will charge per operation rather than CPU, and we will no longer
>> charge for query index scans.  This means the cost of your queries will be
>> tied exclusively to the size of your result set.  We expect the cost of
>> these operations will be approximately 4x the cost of the equivalent CPU
>> under today’s model, but for apps that make heavy use of indexes, this will
>> be somewhat offset by the fact that we will no longer be charging for query
>> index scans.  The admin console today shows total Datastore API Calls, but
>> this is not a good gauge of how many operations you will be charged for
>> under the new model.  Your costs will be highly dependent on the types and
>> contents of your API calls, not the number of calls themselves, which is
>> what we currently display.  For example a single get() API call may retrieve
>> 1 Entity or 100 Entities, and a beginTransaction() API call doesn’t consume
>> any billable resources.
>>
>> Q: Could emails sent to admins be cheaper or free?
>> A: That’s a possibility that we can look into.
>>
>> Usage Types
>> Q: What does the Premier cost of "$500/account" mean? Per Google Apps
>> Account? Per Developer Account, Per Application Owner Account?
>> A: It is per Organization (which would translate into per Google Apps
>> account if you are currently a Google Apps customer).  So, for instance if
>> you are working at gregco.com and you signed up for a Premier account,
>> gregco.com users will be able to create apps which are billed to the
>> gregco.com account.
>>
>> Q: Will there be special programs for non-profit usage?
>> A: Possibly, we are currently looking into this.
>>
>> Q: Will there be special programs for educational usage?
>> A: Possibly, we are currently looking into this.
>>
>> Q: Will there be special programs for open-source projects?
>> A: Possibly, we are currently looking into this.
>>
>> Usage Limits
>> Q: If I migrate to HR Datastore, does that mean I have a "newly created"
>> application, and will get the new, lower, free quota for email?  Could you
>> grandfather in migrated apps at the old 2000 limit?
>> A: Yes, we can grandfather in the email quota for HRD apps that are
>> migrating from M/S apps.
>>
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