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 Private
Score 9.6 out of 10
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IBM Cloud Private is a Kubernetes-based container platform allowing users to build cloud-native applications on their own infrastructure. In addition, it offers common services for self-service deployment, monitoring, logging and security, as well as middleware, data and analytics.
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AWS Lambda
IBM Cloud Private
Editions & Modules
128 MB
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1024 MB
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10240 MB
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AWS Lambda
IBM Cloud Private
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Premium Consulting/Integration Services
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AWS Lambda
IBM Cloud Private
Features
AWS Lambda
IBM Cloud Private
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
IBM Cloud Private is an ideal platform for companies to accelerate their business growth. It helps in reducing the cost of IT and operations while delivering a great customer experience. With IBM Cloud Private, you can gain agility and security with a flexible hybrid model that fits your needs. It's highly recommended to my colleagues from me.
Capacity On Demand to scale up and down environments
SaaS model allows our team to have less involvement in managing or controlling the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities.
SaaS model allows our team to worry less about upgrades, fix packs, environment support etc.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
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.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
With VMware cloud, each VMware Cloud customer must have an SDDC account(VMC) as well as a general AWS account. The two accounts must be linked for the service to work which is a tiresome thing to do for some clients but with IBM Cloud Private all these issues are solved.
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
