CloudFoundry vs. IBM Cloud Functions

It's well suited if:

• The organization has large number of applications that needs to be deployed frequently.
• The organization is tied to the DevOps mindset.
• The organization has programs in different languages.
• The applications does not need EJB's support that servers like web logic provide.

It's less suited if:

• The applications needs security configuration within the same CloudFoundry instance.
• The organization, for whatever reason does not want developers to manage the instances.

Incentivized

IBM Cloud Functions [is] not the worse product on the IBM cloud. I decided to write this review as I thought it would be balanced. I would still use functions to set up a serverless architecture where execution time is pretty quick and the code is relatively simple. I wouldn't use IBM Cloud Functions for async calls obviously, as costs could be higher. The functions documentation is lacking in terms of CI/CD, and there are unexplainable errors occurring - like the network connection that I mentioned. So I wouldn't just rely on IBM Cloud Functions too much for the entire system, but make sure it's diversified.

• Support for Orgs and Spaces that allow for managing users and deployables within a large organization.
• Easy deployment, deploying code is as simple as executing single line from CLI, thanks to build-packs.
• Solid and rich CLI, that allows for various operations on the instance.
• Isolated Virtual Machines called Droplets, that provide clean run time environment for the code. This used to be a problem with Weblogic and other application servers, where multiple applications are run on the same cluster and they share resources.
• SSH capability for the droplet (isolated VM's are called droplets), that allows for real time viewing of the App code while the application is running.
• Support for multiple languages, thanks to build-packs.
• Support for horizontal scaling, scaling an instance horizontally is a breeze.
• Support for configuring environment variable using the service bindings.
• Supports memory and disk space limit allocation for individual applications.
• Supports API's as well as workers (processes without endpoints)
• Supports blue-green deployment with minimal down time

Incentivized

• Validate raw data files - check the validity of raw data input to the system, to make sure we analyze only the relevant data. The raw data stream rate is hard to be predicted, since it depends on real world activities.
• Analyze raw data - analyzing of valid raw data, described above.
• Insert data to LOCAL data base.

Incentivized

• Does not support stateful containers and that would be a nice to have.
• Supports showing logs, but does not persist the logs anywhere. This makes relying on Cloud Foundry's logs very unreliable. The logs have to be persisted using other third party tools like Elk and Kibana.

Incentivized

• Billing can be a hassle, not the most responsive customer service/support team
• Handles & executes most functionalities, but other platforms offer more scalability if you're seeking consistent and stable growth

Incentivized

While Docker shines in providing support for volumes and stateful instances, Cloud foundry shines in providing support for deploying stateless services. Heroku shines in integrating with Git and using commits to git as hooks to trigger deployments right from the command line. But it does not provide on-premise solution that Cloud foundry provides.

Incentivized

AWS Lambda is 100 times more robust than IBM cloud functions. They essentially do the same thing, but AWS works. AWS is stable. we have had epic failures with cloud functions. Support was horrible. We literally had an open ticket with them for 2 months and it literally went nowhere. They said it could do 100 calls a minute. We proved over and over that we couldn't get above 20 without getting failures. They had NO explanation whatsoever. The ticket got closed because we were tired of asking them questions and getting no understandable or usable response.

Incentivized

• Positive impact, since it simplifies the deployment time by a huge margin. Without cloud foundry, deploying a code needs coordination with infrastructure teams, while with cloud foundry, its a simple one line command. This reduces the deployment time from at least few hours to few minutes. Faster deployments promote faster dev cycle iterations.
• Code maintenance such as upgrading a Node or Java version is as simple as updating the build-pack. Without cloud foundry, using web logic, the specific version only supports a specific version of Java. So updating the version involves upgrading the version of web logic that needs to involve few teams. So without cloud foundry, it takes at least few days, with cloud foundry, its a matter of few mins.
• Overall, happier Developers and thats harder to quantify.

Incentivized

• Definitely has positive impact due to the pay only when used feature
• Lightweight cloud services help with scaling without high investment in infrastructure

Incentivized