Amazon Web Services vs. Apache CloudStack

We are using RDS for the database services. With RDS, we don't have to manage much, as most of the DBA tasks are automated. For development purposes, we are using Kubernetes pods, which makes it easy to deploy applications and scale up as needed. AWS integration with in-house applications is seamless, making it easy to keep a data-sensitive application on-premises while still utilizing AWS services.

Incentivized

CloudStack is well suited if you want to keep the costs low and still need a reliable and robust tool to cloud virtualization orchestration. The end user interface is friendly so users can find and use functionalities quickly. Also, the newer version allows you to integrate CloudStack with external authentication using SAML for single sign-on. It can be less appropriate for an administrator that does not want to do a lot of interventions using a command line or that does not use the Linux operating system.

Incentivized

• Starting an instance and accessing it for testing purpose, demo or production deployment its always easy.
• All the things which are available over AWS are pretty well managed and easy to use.
• You might find everything you required for an product and other development over AWS.
• Its suitable for both either an enterprise or an startup
• Various resources and documentation are available in case you struck somewhere.

Incentivized

• New functionalities
• Fixing bugs
• Private and public clouds

• The AWS Management Console can be overwhelming. so a better dashboard and organizing it would improve usability.
• The pricing models are complex. We need a more clear price calculators and cost management tools to manage our expenses better.
• Enhancements in cross service compatibility and easier third party integrations could streamline workflow.
• Simplifying model training in SageMaker and improving IAM for granular access control would make AWS more user friendly

Incentivized

• Maintenance tools
• Less command line interventions
• Server logs not so friendly
• Upgrades are not so straightforward
• The graphical interface performance in big environments can get a little bit slow

Incentivized

I would gladly rely on AWS for any large-scale application deployment. For prototyping and small-scale applications, a more heavily managed environment on top of the 'bare metal' virtual infrastructure, such as Heroku or Elastic Bean Stalk, is probably a more productive approach in most cases

Amazon Web Services is a great tool when it comes to middle size organizations like us. It provides multiple tools and functionalities in low costs. The best feature we have to pay as we go. No financial burden on company for the unused instances. It also comes with greater level of security such as two level authorization such as multi factor authorization.

Availability is very good, with the exception of occasional spectacular outages.

AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.

The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to
immediately search for their compatible software's and also to guide them in a
good direction. Moreover, this product is a good suggestion for every type of
company because of its affordability and ease of use.

Incentivized

The API's were very well documented and was Janova's main point of entry into the services.

In my personal experience, AWS is superior to both GCP and Azure in the majority of usable applications. GCP suffers from the near total misunderstanding of how support system is even supposed to work, and while _some_ services are pretty nifty and well-polished, some are mindbogglingly designed black boxes with self-conflicting documentation. Some of it comes from having legacy systems, sure, but AWS somehow manages, even having a rather big lead start. Azure, from my limited experience, is limited to people somehow coerced into its usage by external constraints. That being said, IF you can design and implement something there, it will probably run fine.

Incentivized

The University, my first large implementation, had a big issue with 149 small data centers spread on São Paulo State, this data centers costs to university were very high, the consolidation idea in two data centers were awesome, but were worried with the management, so we adopted ACS to management of all 576 physical hosts. Now a days the university is delivering IaaS for all staff, students, teachers and researchers, they are using these resources to delivery services to their clients and have a great results in research area

• Provisioning resources like large database instances is really quick. We can easily scale our instances up or down as per need.
• Storing files in S3 instead of onprem NAS drives is much more economical, especially for the files stored in glacier deep archive for compliance purposes.
• Backup snapshots of EBS volumes and RDS instances may increase the cost of cloud if not cleaned up properly.

Incentivized

• Minimal impact at migration from the earlier solution used (Citrix CloudPortal), once both solutions have a common kernel.
• Reduction to 0 with payment of software license.