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* For companies running their own web server infrastructure, autoscaling typically means allowing some servers to go to sleep during times of low load, saving on electricity costs (as well as water costs if water is being used to cool the machines).<ref name=facebook/>
* For companies using infrastructure hosted in the cloud, autoscaling can mean lower bills, because most cloud providers charge based on total usage rather than maximum capacity.<ref name=newvem/>
* Even for companies that cannot reduce the total compute capacity they run or pay for at any given time, autoscaling can help by allowing the company to run less time-sensitive workloads on machines that get freed up by autoscaling during times of low traffic.<ref>{{cite web|url = http://techblog.netflix.com/2015/09/creating-your-own-ec2-spot-market.html|title = Creating Your Own EC2 Spot Market|
* Autoscaling solutions, such as the one offered by Amazon Web Services, can also take care of replacing unhealthy instances and therefore protecting somewhat against hardware, network, and application failures.<ref name=cloudonaut/>
* Autoscaling can offer greater uptime and more availability in cases where production workloads are variable and unpredictable.
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Third-party autoscaling software for AWS began appearing around April 2008. These included tools by Scalr<ref>{{cite news|url=https://techcrunch.com/2008/04/03/scalr-the-auto-scaling-open-source-amazon-ec2-effort/|title = Scalr: The Auto-Scaling Open-Source Amazon EC2 Effort|date = April 3, 2008|accessdate = March 21, 2015|work = [[TechCrunch]]|last = Work|first = Henry}}</ref> and RightScale. RightScale was used by Animoto, which was able to handle Facebook traffic by adopting autoscaling.<ref>{{cite news|url = http://www.zdnet.com/article/rightscale-cloud-management-extends-to-mysql/#!|title = RightScale cloud management extends to MySQL. RightScale, which specializes in cloud computing management for the Amazon Web Services platform today announced support for MySQL Enterprise. The service, which goes live July 1, provides automated deployment, management and scaling, coupled with MySQL Enterprise premium-level support for large database applications.|last = Howlett|first = Dennis|date = June 25, 2008|accessdate = December 16, 2016|work = [[ZDNet]]}}</ref><ref>{{cite web|url = http://www.rightscale.com/blog/enterprise-cloud-strategies/animotos-facebook-scale|title = Animoto's Facebook Scale-Up|last = von Eicken|first = Thorsten|date = April 23, 2008|accessdate = December 16, 2016|archive-url = https://web.archive.org/web/20161220212607/http://www.rightscale.com/blog/enterprise-cloud-strategies/animotos-facebook-scale|archive-date = December 20, 2016|url-status = dead}}</ref>
On May 18, 2009, Amazon launched its own autoscaling feature along with [[load balancing (computing)|Elastic Load Balancing]], as part of [[Amazon Elastic Compute Cloud]].<ref name=autoscaling-and-elb>{{cite web |url=https://aws.amazon.com/blogs/aws/new-aws-load-balancing-automatic-scaling-and-cloud-monitoring-services/ |title=New Features for Amazon EC2: Elastic Load Balancing, Auto Scaling, and Amazon CloudWatch |publisher = [[Amazon Web Services]] |date=May 18, 2009|last = Barr|first = Jeff|accessdate= June 15, 2016}}</ref> Autoscaling is now an integral component of Amazon's EC2 offering.<ref name=aws/><ref name=whatis>{{cite web|url=http://searchcloudapplications.techtarget.com/definition/autoscaling|title = What is autoscaling?|publisher = TechTarget|accessdate = March 21, 2015}}</ref><ref>{{cite web|url=https://aws.amazon.com/blogs/aws/auto-scaling-update-lifecycle-standby-detach/|title = Auto Scaling Update – Lifecycle Management, Standby State, and DetachInstances|last = Barr|first = Jeff|date = July 30, 2014|accessdate = March 21, 2015|publisher = [[Amazon Web Services]] (official blog)}}</ref> Autoscaling on Amazon Web Services is done through a web browser or the command line tool.<ref>{{cite web|url=https://aws.amazon.com/developertools/2535|title = Auto Scaling Command Line Tool|accessdate = March 21, 2015|publisher = [[Amazon Web Services]] (community-edited page)}}</ref> On May 2016 Autoscaling was also offered in AWS ECS Service.<ref>{{Cite web|url=https://aws.amazon.com/blogs/compute/automatic-scaling-with-amazon-ecs/|title=Automatic Scaling with Amazon ECS|date=18 May 2016}}</ref>
On-demand video provider [[Netflix]] documented their use of autoscaling with Amazon Web Services to meet their highly variable consumer needs. They found that aggressive scaling up and delayed and cautious scaling down served their goals of uptime and responsiveness best.<ref name=netflix>{{cite web|url=http://techblog.netflix.com/2012/01/auto-scaling-in-amazon-cloud.html|title = Auto Scaling in the Amazon Cloud|date = January 18, 2012|accessdate = March 21, 2012|publisher = [[Netflix]] Tech Blog|
In an article for ''[[TechCrunch]]'', Zev Laderman, the co-founder and CEO of Newvem, a service that helps optimize AWS cloud infrastructure, recommended that startups use autoscaling in order to keep their Amazon Web Services costs low.<ref name=newvem>{{cite news|url=https://techcrunch.com/2012/04/22/amazon-web-services-mistakes/|title = The 10 Biggest Mistakes Made With Amazon Web Services|last = Laderman|first = Zev|date = April 22, 2012|accessdate = March 21, 2015|work = [[TechCrunch]]}}</ref>
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===Facebook===
In a blog post in August 2014, a Facebook engineer disclosed that the company had started using autoscaling to bring down its energy costs. The blog post reported a 27% decline in energy use for low traffic hours (around midnight) and a 10-15% decline in energy use over the typical 24-hour cycle.<ref name=facebook>{{cite web|url=https://code.facebook.com/posts/816473015039157/making-facebook-s-software-infrastructure-more-energy-efficient-with-autoscale/|title = Making
===Kubernetes Horizontal Pod Autoscaler===
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This approach to autoscaling uses [[predictive analytics]]. The idea is to combine recent usage trends with historical usage data as well as other kinds of data to predict usage in the future, and autoscale based on these predictions.
For parts of their infrastructure and specific workloads, Netflix found that Scryer, their predictive analytics engine, gave better results than Amazon's reactive autoscaling approach. In particular, it was better for:<ref name=netflix-scryer>{{cite web|last1=Jacobson|first1=Daniel|last2=Yuan|first2=Danny|last3=Joshi|first3=Neeraj|title=Scryer:
* Identifying huge spikes in demand in the near future and getting capacity ready a little in advance
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