AWS每月免费额度:
750 hours of EC2 running Linux/Unix Micro instance usage
750 hours of Elastic Load Balancing plus 15 GB data processing
10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services
GAE每月免费额度:
CPU Time 30*6.50 = 195 CPU hours
Outgoing Bandwidth 30*1.00 = 30 GBytes
Incoming Bandwidth 30*1.00 = 30 GBytes
Total Stored Data 30*1.00 = 30 GBytes
Recipients Emailed 30*2,000 = 60000
以上GAE的配额周期是以天为计数,所以我将它乘以30得出月免费配额,
通过对比,假如某个应用日访问量平均,那么GAE在配额还是比较合适,
而如果应用日访问量不平均,比如某天用户访问量突发高,那么AWS月总配额方式更为合理。
两者对比,似乎AWS对大部分人更有吸引力,起码产品环境更为自由,假如AWS能永久拥有这个免费套餐,似乎是件相当不错的事情。
二者我都不算熟悉,不知道这些数据罗列得正确不正确,乱发出来希望能在这得到大家更为合理的分析...
750 hours of EC2 running Linux/Unix Micro instance usage
750 hours of Elastic Load Balancing plus 15 GB data processing
10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services
GAE每月免费额度:
CPU Time 30*6.50 = 195 CPU hours
Outgoing Bandwidth 30*1.00 = 30 GBytes
Incoming Bandwidth 30*1.00 = 30 GBytes
Total Stored Data 30*1.00 = 30 GBytes
Recipients Emailed 30*2,000 = 60000
以上GAE的配额周期是以天为计数,所以我将它乘以30得出月免费配额,
通过对比,假如某个应用日访问量平均,那么GAE在配额还是比较合适,
而如果应用日访问量不平均,比如某天用户访问量突发高,那么AWS月总配额方式更为合理。
两者对比,似乎AWS对大部分人更有吸引力,起码产品环境更为自由,假如AWS能永久拥有这个免费套餐,似乎是件相当不错的事情。
二者我都不算熟悉,不知道这些数据罗列得正确不正确,乱发出来希望能在这得到大家更为合理的分析...