>From Rackspace (London):
ab -n 1000 -c 200 http://sven-anagramhero.appspot.com/client/loadtest
This is ApacheBench, Version 2.3 <$Revision: 655654 $>
Server Software: Google
Server Hostname: sven-anagramhero.appspot.com
Server Port: 80
Document Path: /client/loadtest
Document Length: 2 bytes
Concurrency Level: 200
Time taken for tests: 15.694 seconds
Complete requests: 1000
Failed requests: 0
Write errors: 0
Total transferred: 171000 bytes
HTML transferred: 2000 bytes
Requests per second: 63.72 [#/sec] (mean)
Time per request: 3138.712 [ms] (mean)
Time per request: 15.694 [ms] (mean, across all concurrent requests)
Transfer rate: 10.64 [Kbytes/sec] received
Connection Times (ms)
min mean[+/-sd] median max
Connect: 8 8 1.5 8 22
Processing: 139 2827 1197.6 2910 8487
Waiting: 139 2827 1197.6 2910 8487
Total: 147 2835 1197.6 2918 8494
Percentage of the requests served within a certain time (ms)
50% 2918
66% 3341
75% 3620
80% 3874
90% 4257
95% 4700
98% 5900
99% 6131
100% 8494 (longest request)
ab -n 1000 -c 500 http://sven-anagramhero.appspot.com/client/loadtest
This is ApacheBench, Version 2.3 <$Revision: 655654 $>
Server Software: Google
Server Hostname: sven-anagramhero.appspot.com
Server Port: 80
Document Path: /client/loadtest
Document Length: 2 bytes
Concurrency Level: 500
Time taken for tests: 6.879 seconds
Complete requests: 1000
Failed requests: 0
Write errors: 0
Total transferred: 171000 bytes
HTML transferred: 2000 bytes
Requests per second: 145.37 [#/sec] (mean)
Time per request: 3439.463 [ms] (mean)
Time per request: 6.879 [ms] (mean, across all concurrent requests)
Transfer rate: 24.28 [Kbytes/sec] received
Connection Times (ms)
min mean[+/-sd] median max
Connect: 8 17 9.0 11 28
Processing: 144 2210 1535.1 1885 6831
Waiting: 144 2210 1535.2 1885 6831
Total: 152 2227 1539.7 1894 6853
Percentage of the requests served within a certain time (ms)
50% 1894
66% 2410
75% 3100
80% 3225
90% 4492
95% 5628
98% 6418
99% 6484
100% 6853 (longest request)
On Friday, August 3, 2012 3:04:55 PM UTC+2, Richard wrote:
>
> Connection pooling might be a good idea. Since there are people in every
> game round and each round is 3 minutes, the SQL db will always be up. I
> did try it, but I think my connection from home was limited.
>
> RE: SQL solution: Can some of you with LOTS of bandwidth (from a *nix
> machine), please AB the following URL:
>
> http://sven-anagramhero.appspot.com/client/loadtest
>
> Try at least 1000 connections with 250-500 concurrent and report back here
> please.
>
> WRT costs: DB read/writes are around $3/day. Whereas 10 B1 backends
> would be almost $20/day.
>
> In addition, the B1 solution does not scale. Lets say the app suddenly
> gets a lot of new users. Now I need to update the backend. Additionally,
> peak load is approximately 4x the lowest value. Now, for part of each day,
> I need to have enough instances to handle the peak load just doing minimal
> work. This is not scaling automatically. I always need to pay the maximum
> of whatever is needed to handle peak load.... or else update the backends
> every few hours to add/remove B1's. Not exactly fulfilling the automatic
> scaling promise!
>
>
>
> On Friday, August 3, 2012 3:49:24 AM UTC-4, Mauricio Aristizabal wrote:
>>
>> Takashi, is there some more detailed information on why Google doesn't
>> encourage using a connection pool? Is it simply to encourage allowing the
>> db instance to wind down instead of being kept alive only by pool
>> connection health checks? If so I'm sure it could be configured to avoid
>> this.
>>
>> It does seem to me that it could reduce Richard's costs drastically, by
>> 2/3 just on the writes to the db by his own numbers.
>>
>> I've been using pooling without issue for several months now, though
>> admittedly with very little traffic so far, so if you think this is going
>> to get me in trouble later I'm very eager to hear why.
>>
>>
>>
>> On Fri, Aug 3, 2012 at 12:28 AM, Richard Watson <[email protected]
>> > wrote:
>>
>>> What are the performance characteristics of connecting to Google Compute
>>> Engine? Maybe slap the in-memory app onto that.
>>>
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>>
>>
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