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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WSO2 Enterprise Service Bus
Score 7.1 out of 10
Enterprise companies (1,001+ employees)
WSO2 says they have taken a fresh look at old-style,
centralized ESB architectures, and designed their unique WSO2 Enterprise Service Bus
from the ground up as the highest performance, lowest footprint, and most
interoperable service oriented architecture (SOA) and integration middleware
today. Additionally, the vendor says that by relying on their carbon technology
the ESB is able to deliver a smooth start-to-finish project experience.
Scenarios where AWS Lambda is well suited: 1. When we need to run a periodic task few times in a day or every hour, we may deploy it on AWS Lambda so it would not increase load on our server which is handling client requests and at the same time we don't have to pay for AWS Lambda when it is not running. So, overall we only pay for few function invocations. 2. When some compute intensive processing is to be done but the number of requests per unit of time fluctuates. For example, we had deployed an AWS Lambda for processing images into different sizes and storing them on AWS S3 once user uploads them. Now, this is something that may happen few times every hour on a particular day or may not happen even once on other days. To handle this kind of tasks AWS Lambda is a better choice as we don't have to pay for the idle time of the server and also we don't have to worry about scaling when the load is high. Scenarios where AWS Lambda is not appropriate to use: 1. When we expect a large request volume continuously on the server. 2. When we don't want latency even in case of concurrent requests.
WSO2 ESB is an awesome product for companies looking to venture into the world of SOA with an ESB. They have a lot of other products too that can work really well with their carbon infrastructure. The interface is simple for deploying and managing proxy services. You can also write custom modules within the ESB using Java with IDE like Eclipse
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.
One of the basic requirement of an ESB product is that it should be able to support transformation. WSO2 ESB provides support of XSLT, so you can transform your request to whatever format. Moreover, transformations like converting your xml payload into JSON and JSON payload to XML are out of the box available.
WSO2 ESB provides a scheduler feature, by which you can configure your own scheduler to call a proxy service at a particular time of day or or initiate sequence.
WSO2 ESB provides excellent error handling techniques, WSO2 ESB provides detailed error handling scenarios to tackle all the situations. WSO2 ESB also provides custom error handling by which you can make your own custom error message before sending it back to client.
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.
Lack of auto-restart built-in capabilities. In case of running out of memory there are no built-in methods to recover from a crash, just for example, Oracle WebLogic Node Manager.
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.
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.
