AWS Lambda Reviews

AWS Lambda has serverless programming, like Logic Apps from Azure. You just configure the run-time and then they start coding. It is event-driven. It started with my obtaining Salesforce. Salesforce is a low-code and non-code program and totally SAS. Everything starts from the event, from the trigger. You get the trigger and you work at the program. You have some other models, maybe faster or fancier models. But in my opinion, this kind of program is started by locating the system and identifying where the trigger and entry point of the program are. Then you get the full advantage of the program. You don't need to worry about any infrastructure.

I think this is the future. Compared with the EC2, you don't have to pay anything if you don't run it. Otherwise, with EC2 when our client provisions the system and the instances, you always have to pay. There are other tremendous advantages, like flexibility. After you provision EC2 you can write something that does not totally follow the cloud convention. You use it to provision the container. With the program you need to have those 10 principles of cloud computing. Especially recently, within the past four or five years, I have gotten away from DevOps, or the software development life cycle. Even though I researched the product portfolio from DevOps and then the life cycle for DevOps, I try to position myself as an architect with hands-on experience.

In my opinion, Lambda is very similar to Salesforce, which is the original for the SaaS platform and is an extremely low-code environment. With Microsoft and AWS you can say, "Okay. You can choose whatever language you need to make it even more flexible." 

Everything is the cloud. Lambda is a fully managed service. If you want to do it either as a private cloud or on-premise, I'm sure you can do that, too. But I don't know how to manage the pricing structure. But then you've lost the point of Lambda because if you do not use it, you do not pay. Again, I just want to emphasize, I'm not a Lambda expert. But, logically thinking, the big advantage of serverless programming for the customer is that you just use it and pay. Pay and go. You don't need to provision anything.

All my experience with AWS Azure is on the public cloud. We do not get too deep. In IBM we do. When we do sales training we always get the private cloud on-premise. There are many reasons for this. One reason is that IBM lost the battle for the public cloud so we get into it much deeper. We go to the enterprise and we can deploy programs to your data center and offices. But for the tech data for AWS and Azure, we are all using the public cloud as a showcase when we talk to the customer and to the retailer.

The number one feature with AWS Lambda is that it is fully managed. From the developer's perspective, you get the coding much more easily. Now many situations are not using code. You plug in, assemble it, and configure it. Lambda makes it low-code. I come from being a Java certified developer for 15 years. You configure the environment for deployment just like in DevOps. That was always the most challenging part as a developer. You identified when to trigger it. If the program can't facilitate it, then 80% is gone. With 20% you just Lose Syntax. You can use Lose Syntax with any programming language as a reference finding out the variables, the statements, the loop, and what other kinds of things you can do. Just follow that to where you can plot it into your business system. 

They might think to have the business benefits say, "Hey, if you don't like it, no need to pay." So, potentially, you can save. If the future is going to be serverless, that's what I think the future of something like Salesforce will be. Programming is getting much easier and does not need a lot of configuration because step-by-step abstraction starts from the infrastructure service. You can replace your hardware, but you still need to do a lot of things in the abstract. The environment now is totally fully managed. I'm not sure if we're totally aligned there. I always talk against those aspects in the Salesforce situation. But I believe Lambda is a comparable peer, apples to apples.

There's a lot of use cases. The solution is used for immediate processing, so it's used everywhere. When data comes in, you process a Lambda function to tag it and categorize it. I've used Lambda functions to process inbound videos to make them smaller. I've used a Lambda function as a serverless backend for a customer-facing app, so I didn't have servers running.

With a highly variable load, our idle cost is pretty much zero, and we haven't had any scale barriers, so we've scaled smoothly.

We are building microservices in Lambda and exposing them via an API Gateway for the end consumer. These microservices talk to DynamoDB, or third-party APIs but can also be event-driven. These microservices carry out specific business functionalities.

We have plans to increase usage in the future. We have been modernizing our usage of SOA technology and rewriting those SOA services on the cloud using AWS Lambda. We are transitioning to a serverless environment using Lambda. 

Lambda is the preferred compute option because of on-demand cost. We don't have to provision any hardware beforehand. We don't have to provision the capacity required for the services because it is serverless. 

AWS takes care of things behind the scenes and we pay only for usage. We don't have to incur uptime or the upfront cost to procure a EC2 instance or create any ECS service.

Our primary use case for Lambda is for serverless computing in our project. We have an environment in AWS with Lambda, EC2, S3, SQS, RDS, and Redshift. Our Lambda function is triggered whenever a new object is put into S3. It will validate, extract data from S3 then input metadata into MySQL and put the main data into Redshift as the data warehouse. An SQS message will be created so our Application in EC2 is alerted that there is new data to have processed.

With AWS Lambda, we found it easy to integrate with other AWS services such as S3, SQS, RDS, etc. This allows us to scale our services in an almost unlimited fashion, as data input into S3 sometimes peak up to a thousand objects and need to be processed as soon as possible.

I am using AWS Lambda for building web and mobile applications.

AWS Lambda has helped my organization by making it easier to code and it is less costly.

Our primary use case for AWS Lambda is a backend service module. Thanks to this solution, we do not need to worry about hardware or resource utilization. It saves us time. 

It saves us a lot of setup time. And, because it's our code, we will use Lambda. Lambda is the best AWS product we can use for running our code and it is very quick for the developers. All they have to do is commit their codes and, once we set up our code pipeline once after committing the code and building and deploying to our Lambda, the project will be up and running in the market. This setup is better than managing on EC2. We don't need to use EC2 in this case. 

My opinion is that the integration could be improved in this solution. We have had some difficulties integrating the EC2 module, but we found a solution for that by ourselves. I would say the integration needs to be improved.

I have found this solution very useful. By using Lambda, we can use Python code and the Boto3 solution. 

The triggering feature is also valuable. For example, if we are using Kafka, we need to be aware that the language comes in Kafka when we write in Python, and that we are transforming our data into the meaningful server and dumping that into the S3 bucket.

I would like to see a find and replace function as part of Lambda's future releases. Currently, if we want to replace a code, we copy the code into Notepad, then find and replace it, and then copy that to Lambda. This would improve the editing function of the product.

Lambda would benefit from a debugging feature as well. For example, if you want to debug code running in Python and deployed in Lambda, it would be beneficial to have a debugging feature.

Lambda is basically a serverless computation service. We are partners with AWS and I'm a consultant. 

Because Lambda is serverless, it has optimized our resources. There's no need to worry about capacity.