AWS Lambda vs CloudFoundry

• Lambda provides multiple methods for triggering functions, this includes AWS resources and services and external triggers like APIs and CLI calls.
• The compute provided my Lambda is largely hands off for operations teams. Once the function is deployed, the management overhead is minimal since there are no servers to maintain.
• Lambda's pricing can be very cost effective given that users are only charged for the time the function runs and associated costs like network or storage if those are used. A function that executes quickly and is not called often can cost next to nothing.

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• 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

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• Putting a significant portion of your codebase into AWS Lambda and taking advantage of the high level of integration with other AWS services comes with the risk of vendor lock-in.
• While the AWS Lambda environment is "not your problem," it's also not at your disposal to extend or modify, nor does it preserve state between function executions.
• AWS Lambda functions are subject to strict time limitations, and will be aborted if they exceed five minutes of execution time. This can be a problem for some longer-running tasks that are otherwise well-suited to serverless delivery.

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• 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.

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• I was able to perform a lot of processing on data delivered from my website and little or no cost. This was a big plus to me.
• Programming AWS Lambda is quite easy once you understand the time limits to the functions.
• AWS Lambda has really good integration with the AWS S3 storage system. This a very good method of delivering data to be processed and a good place to pick it up after processing.

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• 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.

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