AWS Elastic Beanstalk vs IBM Cloud Object Storage

• AWS Elastic Beanstalk was easy to implement, we only had to insert the application code to have it up and running in a few minutes. This helps us to launch company campaigns for different areas such as marketing, commercial and human resources.
• It has a fast learning curve, since the training material of the platform is public on the manufacturer's portal, furthermore it is easy to interact and intuitive for developers.
• The productivity of the equipment is optimized since they are not worrying about preparing the platform or infrastructure, they only have to attend to what is required by the application and its operation and this maintenance.
• The indicators and metrics that it has, ensure that the application cannot be saturated and have a performance problem, with AWS Elastic Beanstalk the application can scale resources when needed automatically.

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• Highly secure way of storing and sharing data as it needs authorization to be accessible.
• Pre-built API calls and code snippers make accessing data via secure APIs a breeze.
• Easy to migrate data to and from data storage
• Ability to manage large amounts of data with considerable speed

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• Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example.
• It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made.

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• While this platform has been around, it does take some getting used. The interface could be refined. My Firefox Browser automatically closed when selecting some options and creating new objects as an example.
• The tutorials are a bit outdated in comparison to the screens shown. We understand the system is constantly improving. The tutorials should reflect the changes in the interface.
• There are many pre-trained models. However, it is not clear as to how those models were trained, what bias may exist in the training data, and how a user could improve those models unless we simply have to build our own.

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• till now we had not Calculated ROI as the project is still evolving and we had to keep on changing the environment implementation
• it meets our purpose of quick deployment as compared to on-premises deployment
• till now we look good as we also controlled our expenses which increased suddenly in the middle of deployment activity

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• Prior to cloud storage, we used on-premises storage devices to store and backup, and sometimes it was a headache to scale up or down the storage according to our needs. With the introduction of Cloud Object Storage, we don't have to worry about scaling.
• The uptime is also improved a lot after the introduction of Cloud Object Storage in our organization
• Obviously, it's a very cost-effective way to store and archive data.

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