Take my cloud … please
This article compares the largest cloud services platforms: Amazon AWS vs. Google Cloud Platform vs. IBM Softlayer vs. Microsoft Azure vs. Alibaba Cloud vs. Rackspace.
Major multi-cloud vendors include Oracle, SalesForce Heroku, SkyTap.
Software for private clouds include Red Hat OpenStack and VMWare.
Advantages of Cloud
Evaluations can be based on the advantages of cloud:
- Trade capital expense for variable expense (conserve cash)
- Stop guessing about capacity (over-provisioning, which can be expensive)
- Benefit from economies of scale (tap into available capacity pooled among many customers)
- Expand and go global in minutes (make use of infrastructure established around the world, which is time consuming, expensive, and dangerous to do on your own) (leverage experts working within cloud vendors who can focus on facilities, security, and scalability capabilities)
- Stop spending money running and maintaining data centers “friends don’t let friends build data centers”
- Increase speed and agility (make use of innovations) PROTIP: Memorize the above list for exams.
Amazon’s “Well Architected” notes the constraints removed by being in the cloud:
- Test production at scale
- Make experimentation easier (overcome fear of change)
- Allow architecture to evolve (rather than being frozen in time)
TL;DR - The biggest differences
The perspective of an individual is not to select a cloud vendor, but to select the cloud vendor which provides the best career prospects. Here’s my logic:
- If you write in C# on .NET (and want to continue leveraging that experience), Azure is the natural choice. (But other clouds are trying to support Windows.)
- If you’re looking to get a job in cloud, go for AWS because of its current market share and pace of innovation. AWS has the most sophisticated authentication and database services.
- Due to competitive reasons, Target, Best Buy, eBay, and Sony Music use Google. WalMart uses Azure.
- If you’re running really large loads on each server, Google offers fast fiber networks that don’t limit what large machines can achieve. Plus Google is ahead in Machine Learning with its popular Tensorflow in Python.
Google’s SSD drives are expensive, though needed for speed.
- IBM has bare-metal machines, if that’s your thing. But since 2017 AWS provides them as well.
- Increasingly, companies doing business in a particular country are required to keep data within a cloud data center within that country (such as Google in Belgium).
EDITOR’s NOTE: This is not a complete treatment. Additional information will be added over time.
|Granularity of billing||per hour||per minute|
|# Data centers||24||100|
|Largest # cores||128||32|
|Largest RAM GB||1,952 GB||448 GB|
PROTIP: Moving up to double the RAM or cores usually does not yield a doubling of capacity due to overhead and limits in shared components such as networking.
Even though cloud vendors provide a great deal of transparency to how they price their services, there are so many variables to what affects the final bill that the only accurate way is to actually run services.
is Microsoft's Azure Pricing Calculator
is Amazon's AWS Pricing Calculator
- AWS has matched Azure pricing, and also per-minute billing.
Cowan analysis May 2016 (using 1.0 as average among vendors) rated Amazon 1.37 (above avarge) in prices (most expensive). Microsoft was rated the leader in price and APIs, but the lowest in support.
QUESTION: Is the comparison based on spot instances in AWS, which are of low cost because they can be taken away at any moment by someone who outbids.
Amazon had an early lead in 2006 and has maintaing its lead even though Microsoft and Google are growing fast as well with 50%+ annual growth*
Operating Systems in the cloud
As of May 2016, Microsoft Azure works with SUSE and Oracle Java, but not Red Hat Enterprise Linux (RHEL).
Amazon provides software to host whatever OS is put into images. But its free server images are based on CentOS, derived from Red Hat as both use the yum package manager. Amazon is working on “Linux2” based on Red Hat.
To compare network speeds:
http://cloudping.info measures current ping speed to various regions on Amazon’s EC2 cloud. Scroll down to click “HTTP Ping” to begin collection to a running line graph:
https://ping.varunagw.com/aws.htm provides green, yellow, red colors with Mean, Median, Min, and Max statistics based several measures of the speed to each EC2 region.
Amazon’s own EC2 Reachability Test does not provide ping speeds, only a green icon when it can be reached at any speed.
http://http://www.azurespeed.com measures current ping speed to various regions on Microsoft’s Azure cloud. To stop collection, click “uncheck all” or individual regions of interest:
http://www.gcping.com measures current ping speed to various regions on Google’s cloud. To stop collection, press the dot with the arrow.
https://status.aws.amazon.com is Amazon’s AWS Service Health Dashboard applicable to all users. Under the tab for each continent is a list of each service plus region combination.
PROTIP: Most new services begin in the N. Virginia region “US-EAST-1”, as do the most famous outages. So if you are running a production load, try to use a different region than that. Nevertheless, that’s where one must provision AWS Cloud Front CDN for worldwide distribution.
https://phd.aws.amazon.com is your Personal Health Dashboard for your account.
http://downdetector.com/status/aws-amazon-web-services provides 3rd-party crowd-source status.
https://istheservicedown.com/problems/amazon-web-services-aws/history is a private-party site reporting the history of downtimes on AWS. For example:
For a list of outages further back: https://outage.report/aws-amazon-web-services
Links to service brand names
Here are the names of brand names, some with links to marketing or documentation pages:
More on DevOps
This is one of a series on DevOps:
- ci-cd (Continuous Integration and Continuous Delivery)
- Git and GitHub vs File Archival
- Git Commands and Statuses
- Git Commit, Tag, Push
- Git Utilities
- Data Security GitHub
- GitHub API
- Choices for DevOps Technologies
- Java DevOps Workflow
- AWS DevOps (CodeCommit, CodePipeline, CodeDeploy)
- Cloud regions
- AWS Virtual Private Cloud
- Azure Cloud Onramp
- Azure Cloud
- Azure Cloud Powershell
- Digital Ocean
- Packer automation to build Vagrant images
Terraform multi-cloud provisioning automation
- Powershell Ecosystem
- Powershell on MacOS
- Jenkins Server Setup
- Jenkins Plug-ins
- Jenkins Freestyle jobs
- Dockerize apps
- Docker Setup
- API Management Microsoft
- Scenarios for load
More on cloud
This is one of a series on cloud computing:
- Serverless software app development
- SMACK = Spark, Mesos, Akka, Cassandra, Kafka
- Dockerize apps
- Kubernetes container engine
- Hashicorp Vault and Consul for keeping secrets
- Hashicorp Terraform
- Elastic Stack Ecosystem
- RDP client to access servers
- AWS IAM
- AWS IoT
- AWS On-boarding
- AWS DevOps (CodeCommit, CodePipeline, CodeDeploy)
- AWS Lambda
- API Management by Amazon
- AWS server deployment options
- Azure cloud introduction
- Azure cloud on-ramp
- Azure cloud certifications
- Dynatrace cloud monitoring
- AppDynamics cloud monitoring