AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
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IBM Cloud Foundry
Score 8.1 out of 10
N/A
IBM Cloud Foundry is an IBM version of the open-source platform designed for building, testing, deploying, and scaling applications. Enterprises can run Cloud Foundry in a public isolated environment, while natively integrating with other IBM Cloud services, such as AI, Blockchain, and IoT.
[AWS Lambda] is very well suited for the projects that doesn't have any infra but needs it where short running processes are required. But if your application need to run continuously than this might not be the very apt tool for you.
As it is an open-source platform as a service, it is very easy to operate, scale, and deploy regardless of what programming language and framework it's written in. However, it could be improved in terms of scalability. There should be proper documentation for easier and clearer understanding to make the process smooth.
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.
Simplicity - the command line tool provided can get you up and running within minutes.
Resourceful - IBM Cloud Foundry is built on top of the open source Cloud Foundry technology, so any resources you find online about Cloud Foundry generally can be applied.
Feature rich - provides all the necessary features for a cloud based platform, such as auto-scaling, 0 downtime deployment.
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.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
I have not needed support for AWS Lambda, since it is already using Python, which has resources all over the internet. AWS blog posts have information about how to install some libraries, which is necessary for some more complex operations, but this is available online and didn't require specific customer support for.
Azure Functions is another product that provides lambda functionality, but the documentation for some of Azure's products is quite hard to read. Additionally, AWS Lambda was one of the first cloud computing products on a large cloud service that implemented lambda functions, so they have had the most time to develop the product, increase the quality of service, and extend functionality to more languages. Amazon, by far, has the best service for Lambda that I know.
CF is what we initially went with to establish a development pipeline and start our cloud journey, now we are expanding this and although we are now pulling in many other tools and functions around CF, it is not being replaced. It stands out as having a key place working ‘with’ git, Kubernetes, IBM cloud etc, not against or segregated from it.
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.
IBM Bluemix is mainly a foundation enabler at this stage, although our business plan does look promising.
The low cost of development on Bluemix for a start-up like us is so helpful......we had no spare cash for this project besides what we could save or borrow at first, and that wasn't much. We are still trying to attract venture capital to cover the main Cordova Coding effort plus the launch "Cash Burn".
Features like push notifications, mobile-back end, and world-beating security help us to sell our SaaS products/services.
The pure (usually!) functionality of IBM products and services is very rewarding to work with.They are so insightful and thoughtful, to say naught of clever!
