- Effective DevOps with AWS
- Yogesh Raheja Giuseppe Borgese Nathaniel Felsen
- 316字
- 2021-07-23 16:27:21
Just-in-time infrastructure
As you just saw, when deploying in the cloud, you only pay for the resources that you are provided with. Most cloud companies use this to their advantage, in order to scale their infrastructure up or down as the traffic to their site changes. This ability to add or remove new servers and services in no time and on demand is one of the main differentiators of an effective cloud infrastructure.
In the following example, you can see the amount of traffic at https://www.amazon.com/ during the month of November. Thanks to Black Friday and Cyber Monday, the traffic triples at the end of the month:
If the company were hosting their service in an old-fashioned way, they would need to have enough servers provisioned to handle this traffic, so that only 24% of their infrastructure would be used during the month, on average:
However, thanks to being able to scale dynamically, they can provide only what they really need, and then dynamically absorb the spikes in traffic that Black Friday and Cyber Monday trigger:
You can also see the benefits of having fast auto-scaling capabilities on a very regular basis, across multiple organizations using the cloud. This is again a real case study taken by the company medium, very often. Here, stories become viral, and the amount of traffic going on drastically changes. On January 21, 2015, the White House posted a transcript of the State of the Union minutes before President Obama began his speech: http://bit.ly/2sDvseP. As you can see in the following graph, thanks to being in the cloud and having auto-scaling capabilities, the platform was able to absorb five times the instant spike of traffic that the announcement made, by doubling the number of servers that the front service used. Later, as the traffic started to drain naturally, you automatically removed some hosts from your fleet:
- 現(xiàn)代測(cè)控系統(tǒng)典型應(yīng)用實(shí)例
- 機(jī)器學(xué)習(xí)實(shí)戰(zhàn):基于Sophon平臺(tái)的機(jī)器學(xué)習(xí)理論與實(shí)踐
- 機(jī)器學(xué)習(xí)及應(yīng)用(在線實(shí)驗(yàn)+在線自測(cè))
- 基于LabWindows/CVI的虛擬儀器設(shè)計(jì)與應(yīng)用
- 傳感器技術(shù)實(shí)驗(yàn)教程
- 大數(shù)據(jù)技術(shù)入門(第2版)
- JMAG電機(jī)電磁仿真分析與實(shí)例解析
- 人工智能工程化:應(yīng)用落地與中臺(tái)構(gòu)建
- Hybrid Cloud for Architects
- Ceph:Designing and Implementing Scalable Storage Systems
- 空間站多臂機(jī)器人運(yùn)動(dòng)控制研究
- 嵌入式操作系統(tǒng)原理及應(yīng)用
- 計(jì)算機(jī)組成與操作系統(tǒng)
- 從零開始學(xué)Java Web開發(fā)
- Learning ServiceNow