AWS Lambda Reviews

AWS Lambda is used only by the DevOps team. I can use the solution to configure and set up all the requirements for testing the application and test code.

AWS Lambda should improve its compatibility with the language used to write the code. I would like to be able to choose a different language to code in AWS Lambda.

I have been using AWS Lambda for six months.

Around 15 to 20 users work with AWS Lambda in our organization. The solution is used by different teams, including the DevOps, testing, and development teams.

I faced some challenges when we worked on the migration. I raised tickets to the support team, and they helped me.

The solution's initial setup can be done with the help of documents.

AWS Lambda is not expensive for micro testing but is expensive if used for long deployment or long services.

It is not difficult for a beginner to learn to use AWS Lambda for the first time because it has good documentation.

Overall, I rate the solution a five out of ten.

Lambda is essentially a serverless computing service offered by AWS. It allows you to run your code or applications without needing to manage servers. You can deploy your IT code or applications, and it seamlessly integrates with other AWS services, like S3 for data storage. You don't need to purchase or manage any servers. So, Lambda offers a way to run applications without the complexity of infrastructure.

The best feature of AWS Lambda is its scalability and security. It's a highly scalable service, making it suitable for a range of applications.  

AWS Lambda, like other services offered by AWS, SAP, or Azure, is already quite advanced. However, when considering improvements, it's more about how you write and optimize your applications.

There's always room for enhancement in terms of resource allocation and management for high-demand applications.

Performance issues can arise depending on how you allocate resources within Lambda. For example, if you're running a new application with a significant load, you need to be prepared for potential bottlenecks. 

It's essential to control network interactions and optimize for the type of application you're running. Lambda is excellent for small and lightweight applications, but for more resource-intensive tasks, you might need to look at other AWS services or a more distributed storage environment.

AWS Lambda could greatly benefit from enhancements in handling large-scale applications to support heavy workloads. This is actually feasible, but there is a need for further development in this area. 

Additionally, improvements in resource control optimization are crucial. For instance, enabling users to run data-intensive applications using a limited number of resources without compromising performance would be a valuable addition.

I have used it for three years.

I have interacted with the AWS support team. They have a large customer base, which sometimes leads to delays, but overall, their support is excellent.

They categorize issues effectively and provide prompt support for critical issues. Even for less critical issues from the customer's perspective, their response is adequate. They are usually quick to respond, especially when the issue is critical, and they provide effective support.

Positive

The initial setup of AWS Lambda is very straightforward and quick.

If you have a data application with a huge number of users that requires frequent user interaction, AWS Lambda may not be the best fit. However, it's suitable for applications with less frequent user interaction, like those accessed periodically, maybe every few minutes or hours.

For lightweight applications, AWS Lambda is a ten out of ten.

We use it primarily for image resizing in batch and scheduled jobs. Additionally, one of our clients relies on Lambda for running a continuously active custom API, handling their ongoing API requests.

Leveraging it to run containers directly from Amazon Elastic Container Registry has proven to be highly valuable. The utilization of containers is particularly beneficial in overcoming the size limitations imposed on Lambda functions which not only allows us to work around these constraints but also contributes to the improvement and maintenance of our code.

There's room for improvement in the testing setup. Attempting to test it through the AWS CLI also posed issues, and when trying to test the Lambda function on my local machine, I encountered difficulties in obtaining comprehensive logs or error messages to diagnose what might be going wrong.

I have been working with it for one year.

It provides a high level of stability, and I have not encountered any issues so far. The system demonstrated stability whenever we attempted to update the function or perform any operations. Responses consistently aligned with the timeframes specified on the AWS website, remaining within the service level agreement. I would rate it nine out of ten.

The scalability is notably high, I would rate it nine out of ten. Approximately sixty percent of my clients are utilizing this approach. While I serve two major organizations, the majority of my clientele consists of small and medium-sized businesses.

The technical support from Amazon has been excellent, and I've consistently had positive experiences. During a customer migration from another cloud provider to AWS, the entire technical team provided valuable insights and enhanced the architecture. Their assistance not only improved the overall design but also ensured smooth transition and support. Even for minor issues, the response times have consistently exceeded the expectations stated on the website. For instance, if a 24-hour response time is indicated, they typically respond within twelve hours. I would rate it nine out of ten.

Positive

I would rate the initial setup around seven out of ten. While it wasn't overly challenging, it did demand a certain level of technical proficiency. Someone without substantial technical knowledge might find it less straightforward to set up.

In our container-based approach, we initiated by constructing containers on the local developer machine, then we pushed these containers to AWS Elastic Container Repository. Following this, we established a Lambda function that utilized the uploaded ECR image, allowing it to execute the associated container. Additionally, we incrementally built services to utilize those containers at Lambda functions. The deployment took less than three hours.

The pricing varies based on the specific solution you're implementing, and in comparison to the value it provides, the overall cost is reasonable. When used appropriately for its intended purpose, the price is relatively low. However, if Lambda is employed outside its intended scope, the cost can escalate exponentially. I would rate it four out of ten.

I recommend thoroughly reading the documentation to determine if it is a suitable solution for your specific use case. It's essential to understand the nuances of your use case before proceeding with the implementation. Overall, I would rate it eight out of ten.

As a platform team, we had to enable a light-weight ingestion platform ensuring the aspects of governance were baked into the platform and the business teams could accelerate their cloud adoption and only develop the business logic.

AWS Lambda improved our productivity and also enabled the business teams to build their ingestion systems at ease.

AWS Lambda's best feature is the lightweight framework that allowed us to bring down a lot of boilerplate code as part of platform capabilities and give the developers an opportunity to only write business-specific logic.

There were some timeout issues with AWS Lambda as the options provided didn't suit our business cases. In the next release, AWS Lambda should include integration with an IoT.

I've been using AWS Lambda for about a year.

AWS Lambda scales really well.

AWS Lambda is cost-effective, with a minimal maintenance cost.

I would rate AWS Lambda eight out of ten.

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. 

Lambda is very handy because it gives us the parallelism of computation. If you want to launch thousands of instances simultaneously, it can be done on one site. The solution has a 15-minute computation limit but you can create a chain with the same code so that the output automatically switches to another functionality after 15 minutes. 

The only issue is that if you have Lambda in one AWS account and want to utilize it in another account, it can't be done. It's a limitation of the solution. S3 bucket provides that option with its resource access management. If you have a Python library and want to package it, you have to create the package of those libraries. It requires changing the conflict file and the patent library to create the package because the configuration is a little difficult for beginners. They should simplify package creation and configuration. Writing test cases is a little difficult because of the memory and short duration. Your computation has to be finished within that time limit. 

I've been using this solution for five years. 

We haven't had any performance issues because Lambda automatically gauges the kind of computation required.

The scalability is excellent and there is no capacity limit. 

Provided the person deploying the solution knows the format of the input, the setup is relatively simple for experienced users. Deployment doesn't take long because of the integrated machine services. Our implementation was carried out in-house. It doesn't require any maintenance once it has run for a month.

Licensing costs are reasonable even though you have to pay for the computation and for the volume of data. Once the work is done, the storage is freed up so you only get charged for the instance. 

If an organization wants to go serverless, Lambda offers a truly serverless service. Even though there are some areas that could be improved, I rate this solution 10 out of 10. 

My primary use cases for AWS Lambda is collecting data from other systems through API, pre-calculations, and ETL.

The feature I found most valuable about Lambda is the fact that it's serverless.

I would like the layers to have a bigger volume. I would like to be able to add more. I don't want to be limited by the layer. 

In addition, writing temporary data to Lambda is not straightforward. Sometimes I use the S3 for that. I found it a little bit challenging. 

I have been using AWS Lambda for a couple of years.

My impression is that it is a stable solution.

I would rate the scalability of this solution a 10, on a scale of one to 10, with one being not scalable and 10 being very scalable.

I have never used Amazon's tech support.

I would say the initial setup was straightforward.

We required two technical staff to do the deployment and maintenance.

We have about 15 to 20 users of Lambda in our company and plan to expand.

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.

I think the most valuable features are event-based triggers. Basically, a Lambda function doesn't get called because you say, "I'm going to call it." It gets called because something happens: a file arrives, a message arrives, or a database gets written. It's really good for a reactive style when you want things to happen as soon as something else happens. That's the best pattern.

There's room for improvement in the solution's warm start, which refers to the minimum time it takes to start up a Lambda function if you haven't been running it. 

I have been using Lambda since 2014, so about eight years. 

This is a stable solution. 

This solution is scalable. We have hundreds of thousands of users, so everything in Lambda gets used a little bit at a time in different parts of the process. We have plans to increase our usage in the future. 

I would rate the technical support as a ten out of ten. You are able to pick a language, pick an environment, and deploy it. 

Positive

It is pretty straightforward to set up this solution. 

We've run some scenarios. For example, say you have three million requests per month, and 120 milliseconds each time someone requests. The total cost ends up being $2.73 a month, which is very cheap for what you get.

There's two charges for this solution. There's the charge for how many times you call a Lambda function, which is 20 cents for every million function calls. Then there's also the size and amount of time that the Lambda function runs, which is measured as 0.0000166667 dollars. It's a fraction of a penny for every gigabyte second. A gigabyte, if you ran it for like a million seconds, would cost one dollar. It computes by the cycle, and it's very cheap.

My advice is to think about the architecture first and don’t just throw your code into Lambda. Think about how your application is designed because using serverless is different.

I would rate this solution as a ten out of ten. It's a very critical service. 

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.

The valuable feature of AWS Lambda is the ease of coding. It is easier to code using the solution.

AWS Lambda can improve its file system-based sharing capabilities and restrictions.

I have been using AWS Lambda for approximately six years.

AWS Lambda is stable.

The scalability of AWS Lambda is good.

We have approximately 1.3 million users using the application that uses the solution. We have 10,000 to 20,000 new users added every month.

The support from AWS Lambda is good.

I rate the support from AWS Lambda a four out of five.

The initial setup of AWS Lambda is easy. The full implementation took us there to four months.

I rate the setup of AWS Lambda a four out of five.

We did the implementation of AWS Lambda in-house.

We migrated from an on-premise server to the cloud with the Lamda solution and we found it less than one-10th of the cost of what it used to be. We have 90 percent savings.

I rate the ROI of AWS Lambda a four out of five.

AWS Lambda license is paid on a monthly basis.

I rate the price of AWS Lambda a four out of five.

My advice to new users is I would recommend strongly going with AWS Lambda for all API-based solutions.

I rate AWS Lambda an eight out of ten.