I have a google app engine application that uses the cloud datastore. My application usage is increasing, I cannot maintain it as “free” since I am paying
for the read/write operations to the datastore
the storage of data in the cloud
instance hours
I plan to charge “by the drink.” In other words, as I am charged for application usage, I will pass on that charge on to my clients. Before developing my own solution to do this, I realize that there must be countless others who have solved this problem. If so, what technique(s) have you employed?
Thank you in advance for your suggestions.
Unfortunately there is no silver bullet for this situation. Be advised, unless you really think this through keeping track of your users consumption might end up costing as much as the actual usage.
Without knowing anything else about your app its hard to help but my advice would be to use appstats to figure out the actual cost of a given service and charge the user per time accessed.
Most users do not like (actually, hate) to be charged for something they (a) do not understand, and (b) have no control over. If a phone company tells its customers to go ahead and use their service without telling them how much - exactly - they are going to pay, it will lose all customers in no time. How are you going to explain read/write datastore costs to your users, with indexed properties and all? How about query costs and instance hours? It's a difficult task even if all of your customers are software engineers.
I recommend charging users for something they understand, like creating a free and a premium version of your app with additional features, or charging per game, or per document processed (you did not tell us what your app is doing), etc.
Related
I aim to create an application that will be deployed thanks to Google App Engine.
Before that I would like to calculate the cost of Google App Engine.
For this I have to provide the Number of instances, per hour. How can caluculate this number of Instances ?
To reformulate, imagine I have 1 thousand users connected, how many users can 1 instance afford ?
Thank you for your answer and help
Regards
Benoit
It's really hard to answer without more info. App engine consumption will depend on the nature of your app, the average session span and usage hours, how well you optimize your implementation and so much more variables...
Don't think about how many instances, think about how many instance hours you'll need to serve your users if you can figure how much you'll be consuming you could get an estimate using the App engine pricing calculator .
Completely depends on the code that runs on each request. You need to make it more specific to get a better answer. Ive had carefully implemented apps that receives thousands of requests per minute with a single instance. How long each request takes and the memory it consumes is key as well as the frontend instance type you select to use.
Appengine also lets you calibrate some parameters like min/max latency to control when more instances are launched.
I have a background in web programming where both the data and the code live on the server. Web hosts with mysql or the like are plentiful and cheap so using the application from multiple pcs was never a problem.
However I'm considering switching to building desktop applications but the only factor that annoys me is the syncing of data across the many pcs I use. I was thinking of perhaps setting up a light amazon ec2 instance with a postgresql on it and having my desktop applications use that.
I have a few questions:
I'm curious as to what latency I might expect by running the database on ec2 instead of the local network, any experience or insight is appreciated.
Are there better/more obvious/cheaper solutions?
I've looked at the pricing and it seems to come down to 24.48$ per month for a yearly contract. Whilst not really expensive, it is not exactly cheap either. At what point does it become more interesting to run a local server?
I'm obviously not using my applications for large parts of the day (sleep, work,...). I was wondering if I can have the amazon server go into a sort of "sleep" mode and wake up when poked. An initial delay for the first desktop application is acceptable. The reason behind this behavior would be to save money on the instance if it is only actually needed for 10% of the day.
I welcome any feedback at all on how this problem is best tackled.
This could get ugly. Every single query you do will have latency associated with it. If you have a lot of queries, this can add up very fast. So keep your query count low, and try to pre-fetch and cache data when possible.
Not enough information to answer that question.
Depends on the cost of your local server. Keep in mind that you will need to pay for electricity to keep it on.
You can stop your instance when you are not needing it, with the exception of high utilization reservations, you wont get billed when its in stopped state. With high utilization reservations you will still pay the full cost.
When I try to enable billing in app engine for using blob store, I found a notice for Minimum Spend $2.10 Per Week.
The Minimum spend subtotal is in support of our new pricing model. The new model requires that you spend at least $2.10/week. This subtotal indicates the value beyond your other spend that we need to add to your contract. To make the transition to the new model smoother we are beginning to account for this minimum when we authorize new budget changes. Please note that you will not be charged for the minimum spend until our new model takes effect.
I search online and found no one ask about it. I use app engine just for a school assignment, so the usage won't be excess free quota. So, Must I pay $2.10 per week even I do not excess free quota? It sounds unreasonable.
As of April 2013, "We’re happy to announce that billing-enabled applications will no longer be required to spend a minimum of $2.10 per week. This means that you can enable billing for a free tier application and continue running within the free tier without concern that a spike in traffic will terminate serving (note that you can always specify a daily dollar budget). The minimum spend was originally intended to prevent abuse and ensure that we can offer a stable, reliable system with a free tier. We have determined that we can continue to support the free tier, without relying on the minimum spend. So, goodbye $2.10!"
Google has removed the $2.10/week for billing-enabled application from now onwards. You can enable billing for a free tier application and continue running within the free tier without concern that a spike in traffic will terminate serving.
http://googleappengine.blogspot.com/2013/04/app-engine-177-released.html
I enabled billing because I needed to add Google Cloud SQL. The notice said that minimal Cloud SQL was free for now. We're still in early development and aren't using any resources, so we're not over the quota for anything. I don't think I was ever advised by any page that I'd be billed even if under the free thresholds. In fact, I think one of the pages explicitly said I would not be.
It really isn't a lot of money. Probably not even if you add all the users who have been deceptively billed together, so it probably won't attract any lawyers. But unless I missed some notice (and even if I did if that notice was intentionally hidden) this is legally wrong, as well as ethically so.
It appears that their "new" system hasn't gone into effect yet so I would go ahead and use it. Besides, $2/week compared to the $150/book that I just spend isn't that bad. =/
As for enabling billing it appears that unless you need the new (per 1.5.3 version) unlimited blobstore then you should be fine with the free limits.
There have been quite a few occasions recently when app engine appears to run slower. To some degree that's understandable with the architecture of their cloud platform. I'm not talking about new server instances - just requests to warm servers. I'm also just referring to CPU, not datastore API, but I do wonder about that as well.
It seems that during these slow periods I get a lot more yellow warnings on my requests - saying I am using a lot of CPU. Certainly they take longer to complete during this period. What concerns me is that during these slow periods, my billable CPU seems to go up.
So to be clear - when app engine is fast, a request might complete in 100ms. In a slow period, it might take more than 1s for the same request. Same URI, same caching, same processing path, same datastore, same indexes - much more CPU. The yellow warnings, as I understand it, are referring to billable CPU usage, and there's many more of them when app engine is slower.
This seems to set up a bizarre situation where my app costs more to run when app engine performance is worse. This means google makes more money the more poorly the platform performs (up to the point where it fails or customers leave). Maybe I've got the situation all wrong, and it doesn't work like that - but if it does work like that, then as a customer the pressures and balances there are all wrong. That's not intimating any wrong-doing on google's part - just that the relationships between those two things don't seem right.
It almost seems like google's algorithm goes something like - 'If I give a processing job to a CPU and start my watch, then stop it when the job returns I get the billable CPU figure.' i.e. it doesn't measure CPU work at all. Surely that time should be divided by the number of processing jobs being concurrently executed plus some extra to cover the additional context switching. I'm sure that stuff is hard to measure - perhaps that's the reason.
I guess you could argue it is fair that you pay more when app engine is in high demand, but that makes budgeting close to impossible - you can't generate stats like '100 users costs me $1 a day', because that could change for a whole host of reasons - including app engine onboarding more customers than the infrastructure can realistically handle. If google over-subscribes app engine then all customers pay more - it's another relationship that doesn't sound right. Surely google's costs should go down as they onboard more customers, and those customers use more resources - based on economies of scale.
Should I expect two identical requests in my app to cost me roughly the same amount each time they run - regardless of how much wall-time app engine takes to actually complete them? Have I misunderstood how this works? If I haven't, is there a reason why I shouldn't be worried about it in the long term? Is there some documentation which makes this situation clearer? Cheers,
Colin
It would be more complicated, but they could change the billing algorithm to be a function of load. Or perhaps they could normalize the CPU measurements based on the performance of similar calls in the past.
I agree that this presents problems for the developers.
Yes this is true. It is a bummer. It also takes them over a second to start up my Java application (which I was billed for) every time they decided my site was in low demand, and didn't need the resources.
I ended up using a cron to auto ping my site every minute to keep it warm.. doing all the wasted work made my bill cheaper, as it didn't have the startup time, instead it just had lots of 2ms pings...
This question appears old and I think the pricing scheme must have changed...
The Google App Engine charges for "instance hours" and the instances currently spawned are viewable in the GAE console. And Google provides adjustments so you can decide cost vs latency for your app.
https://developers.google.com/appengine/docs/adminconsole/performancesettings
I did noticed that if the front-end is bogged down hitting a common backend resource that GAE will spawn a bunch of instances to get latency down. And you will pay for those instance hours even though latency/throughput doesn't improve. The adjustments I mentioned seem to help with that.
Here's the requirement at a very high level.
We are going to distribute desktop agents (or browser plugins) to collect certain information from tons of users (in thousands or possibly millions down the road).
These agents collect data and periodically upload it to a server app.
The server app will allow for analyzing collected data (filter, sort etc based on 4-5 attributes) and summarize in form of charts etc.
We should also be able to export some of the collected data (csv or pdf)
We are looking for an platform to host the server app. GAE seems attractive because of low administrative cost and scalability (as users base increases, the platform will handle the scale... hopefully!).
Is GAE a viable option for us?
One important consideration is that sometimes the volume of uploads from the agents can exceed 50MB per upload cycle. We will have users in places where Internet connections could be very slow too. Apparently GAE has a limit on the duration a request can last. The upload volume may cause the request (transferring data from an agent to the server) to last longer than 30 seconds. How would one handle such situation?
Thanks!
The time of the upload is not considered part of the script execution time, so no worries there.
Google App Engine is very good to perform a vast number of smaller jobs but not so much to do complex long running background jobs (because of the 30 sec limit + even smaller database connection time limit). So probably GAE would be a very good platform to GATHER the data but not for actually ANALYZING it. You probably would like to separate these two.
We went ahead an implemented the first version on GAE anyway. The experience has been very much what is described here http://www.carlosble.com/?p=719
For a proof-of-concept prototype, what we have built so far is acceptable. However, we have decided not to go with GAE (at least in its current shape) for the production version. The pains somewhat outweigh the benefits in our case.
The problems we faced were numerous. Unlike my experience dealing with J2EE stacks, when you run into an issue, many a times it is a dead end. Workarounds are very complicated and ugly, if you can find one.
By writing good prototypes one could figure out whether GAE is right for the solution being built, however, the hype is a problem. Many newcomers are going get overly excited about GAE due to its hype and end up failing badly. Because they will choose GAE for all kinds of purpose that it is not suitable for.