AWS Lambda Reviews

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.

Essentially, I use AWS Lambda to run Python code. Usually, I set up triggers for other parts of AWS. It's really basic programming tasks.

AWS Lambda is more integrable than other code software, which is a significant advantage. Given my software development experience, I find its integration with the cloud easier than with other platforms. There haven't been any problems while using it during my three-month internship.

A very minor improvement would be to simplify the instructions on setting a trigger, as I had to read through them multiple times at the start.

I have used AWS Lambda for three months.

AWS Lambda is entirely stable. I never encountered any issues while using it.

I haven't used it extensively, however, it seems scalable. During my internship, scalability hasn't been critical to what I've used it for.

I have never needed to communicate with technical support for AWS Lambda.

Positive

The initial setup was extremely easy. AWS Lambda is significantly easier compared to other IDEs or Visual Studio Code.

There is no specific advice I can provide at the moment because I've only done a short internship. Overall, I would rate AWS Lambda a ten out of ten.

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.

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.

Our primary use case for the solution is automation. There was a scenario where we tried to reduce cost in our environment using Instance Scheduler, where the AWS Lambda function was also used during that process. So we use it for automation and tagging.

The solution has helped our organization with cost optimization. So we have used AWS Lambda for consolidated billing.

The automation feature is valuable.

The runtime for the solution can be improved.

We have been using the solution for approximately two years.

The solution is stable. I rate it a nine out of ten.

The solution is scalable, and I rate it a ten out of ten.

The initial setup was straightforward.

The solution is very expensive.

I rate the solution a nine out of ten.

Our company uses the solution as a function engine to deploy triggered events for customers. We have a team of twelve developers and our deployments have 1,000 to 2,000 customers during peak times. 

The solution runs on the latest cloud technology so it is easy to deploy cloud-native projects. 

The solution is very useful for managing triggered events. 

It can be a bit difficult to switch between accounts when creating services for customers. 

I have been using the solution for one year. 

The solution is cloud-based so of course it is stable as long as the cloud is available. 

The solution is scalable. 

We have not needed technical support. We utilize available documents that contain content for solving any issues. 

The solution is serverless computing so there is no setup. You just launch the service, write your code, and run it. 

The solution is part of the AWS subscription model that is paid annually. There is no charge for monthly usage. 

There are many calculation criteria for AWS services or licenses. It is difficult to say whether the solution reasonably priced or expensive. Each company weighs price against the benefits and efficiencies provided by the solution. 

AWS is the pioneer of cloud computing and they lead the industry in innovations. Other providers follow in AWS' footsteps to implement similar features and service levels. 

AWS has differentiated the use cases for serverless computing. Lambda is used for basic capabilities like triggered events and Fargate is used for extended capabilities. 

I started using Lambda for a specific use case and I continue to use Lambda and Fargate for use cases as recommended by AWS. 

I definitely recommend the solution and rate it a ten out of ten. 

We are primarily using AWS Lambda for real-time API services. We use AWS Redshift to support our Lambda code functions. 

This solution is cloud-based. 

One of the most valuable features of AWS Lambda is the performance. Lambda is very technical and has very high performance, as well as good real-time performance. 

AWS Lambda could be improved with better stability. 

I have been using AWS Lambda for more than two years. 

This solution is very, very stable. 

In our organization, there are around 300 users of AWS Lambda. We have plans to increase our usage. 

I have contacted Amazon's technical support, and they were very excellent. 

The installation is straightforward. The process took us under three hours, and we did it ourselves. For deployment and maintenance, we have a team of 10 engineers and developers. 

We implemented this solution through an in-house team. 

For licensing, we pay a yearly subscription. 

I rate AWS Lambda a nine out of ten. To those looking to implement AWS Lambda, I would recommend this solution, and say that Lambda has a learning curve in order to enhance the service when using it for the first time. I would advise the user to study hard to use Lambda as a tool.

We are a startup, and we are doing faster and cheaper storage for IT. We are going to offer our storage services in about two months, and we are starting with AWS. We do lossless compression using microservices. We do the compute in a lossless compression way similar to gzip, WinZip, or PKZIP, except that we are giving a discount to customers.

The product that we are developing is not yet in the market. We are doing alpha testing for select customers who are using AWS. The biggest advantage is that you get faster storage without doing a forklift upgrade, and you get 35% cheaper storage. So, you get 2X faster storage with a 35% to 50% lower monthly bill.

We use AWS Lambda to encode and decode data. I work on the encode and decode software. I am working with a cloud developer. He works on the Lambda deliverable and wraps my C code with his C++ wrappers. They get bundled together with no JS stuff.

The cool thing about AWS Lambda is that AWS does all the management. For compression, it is all about making the data small and then making it regular size again. We have an encode function and a decode function. AWS Lambda schedules each of those for us. It has a load balancer and all the fancy stuff, depending on the demand.

The most valuable part of AWS Lambda is that I only need to write the software. I need to write two functions, and my cloud developer turns them into two AWS Lambda instances. That's it.

One area of improvement is to include support for more programming languages. AWS Lambda does not support a lot of programming languages. You have to write the Lambda functions in a certain programming language. We are using C++. My developer knows a couple of other languages. Python is his favorite language, but Python is not supported in AWS Lambda.

I have been using AWS Lambda since it came out in 2016.

It is very stable.

Its scalability is great. We write an encode function, and my cloud developer turns that into an AWS Lambda instance. We then write a decode function, and he turns it into another AWS Lambda instance. We just hook it up and use an API gateway for doing the security check, encryption, and other things.

We did not require any support. Most of the stuff in the cloud is anyways self-serve.

The initial setup was straightforward.

They have a program for AWS customers called Activate. With the Activate program, you can get compute and storage credits. They gave us like $10,000 worth of credit over 18 months.

I would recommend using this solution. It was the first microservice. It doesn't have much overhead, and it does what it claims to do. 

I would rate AWS Lambda an eight out of ten. It is a good solution.