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 Code Engine
Score 8.8 out of 10
N/A
IBM Cloud Code Engine is a fully managed, serverless platform that unifies the deployment of containers and applications including web apps, microservices, event-driven functions, or batch jobs. This serverless compute service aims to remove the burden of building, deploying, and managing workloads in Kubernetes so users can focus on writing code and not on the infrastructure that is needed to host it. With IBM Cloud Code Engine users can run any workload…
Having only some hands-on with the other services, The cloud engine is considerably simpler to operate, with a very clear interface and management. Each application can be easily configured and altered without needing to know anything about different subscription tiers or the …
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.
It would be a good solution for running serverless applications. Because infrastructure setup and maintenance expenses can be avoided, the investment will pay for itself. The time to value is short, allowing IT to respond to business demands quickly. It aided us in customizing security as well as operating a personal project using to autoscale up and down approach. Also, because there isn't much hassle, items can be pushed into production as soon as possible. Simply push a container, create an application, and you're ready to go. But, It is less suited when you have a static machine or need to keep data in some way and do not want to utilize network storage or a database.
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.
the pricing structure is complicated, and the servers are expensive. I really think they should offer better pricing options and support for more languages
sometimes the servers go down, and they take too long to respond to support tickets
uploading documents is slow since I have to do it one by one, making the process much longer than it should be
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.
Consumers can purchase individual components as well as unlocking new bundles with special features and services including the extensive data management governance capabilities of the Automation range. Kubernetes containerizing for effective service implementation and an agile, flexible multi-cloud data program help both utilization expansion and deployment to be improved by this architecture.
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
What impresses me most about IBM Cloud Code Engine is the container workload management capability and the Cloud services and dataflow monitoring functionalities. Data security and network security control via IBM Cloud Code Engine is quite excellent and very responsive data integration functions and the first deployment is not very technical.
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.
