It’s serverless, so we don’t have to worry about managing servers—AWS handles that for us. We use AWS Lamda for running our performance tests, we don't have to keep server running, whenever we need we can spin up and run the tests for API's, good for short running tasks. Easy to maintain and integrate it from command line. Price wise also we don't spend much since it's costing us for what we run. Later to trouble shoot issues, we cna go to UI and check the aws cloudwatch logs, AI can help as well if we want are trougble shooting something specific, and onboarding same process for other env is easy. Review collected by and hosted on G2.com.

I wish it could support more than 15 minutes; if they could extend it to 30 minutes, that would be great. Also, it takes a while to bootstrap and start running. Review collected by and hosted on G2.com.

No infrastructure management: You just deploy your function and AWS handles servers, scaling, and maintenance.

Automatic scaling: It scales instantly from zero to thousands of requests without configuration.

Cost efficiency: You only pay for execution time, not idle server time. Review collected by and hosted on G2.com.

Cold starts: Functions can have latency delays when they haven’t been used recently, which affects performance in time-sensitive apps.

Execution limits: There are strict timeouts (max runtime), memory constraints, and ephemeral storage limits, which make it unsuitable for long-running or heavy compute tasks. Review collected by and hosted on G2.com.

What I like most about AWS Lambda is that it allows you to execute business logic and automations without having to manage servers. It is very useful for building lightweight integrations, responding to events, and decoupling processes within an AWS architecture. I also appreciate that it integrates well with other services like S3, EventBridge, Step Functions, IAM, and CloudWatch, which greatly facilitates the construction of serverless workflows. For specific tasks, event processing, and auxiliary components of pipelines, it is very practical and scalable. Review collected by and hosted on G2.com.

What I like least is that debugging and troubleshooting can become more complex when the function depends on multiple services, permissions, or external configurations. There are also limitations that require careful design of certain use cases, such as maximum execution times, handling heavier packages, or specific dependencies. In some scenarios, monitoring errors or understanding integration failures takes longer than expected. Review collected by and hosted on G2.com.

I like AWS Lambda because it's serverless and secure, especially since we can run it in a private subnet. It also provides a secure protocol URL for executing Lambda functions. It integrates very well with AWS services, making it efficient for our use. The initial setup is very easy, so even beginners can create serverless functions quickly. I also appreciate its impact on cost savings and incident resolution through automation. I think it's a 10 out of 10 service, especially for small teams or those relying on APIs, as it's secure and cost-effective. Review collected by and hosted on G2.com.

I think they need to improve at Security in public because if we put function in public then we don't have restriction like security group or this IPs can be call to Lambda. Right now we have to give our servers if we wanted security for Lambda but in Lambda itself we need a security group-like feature so we can restrict calling our Lambda by network or by IPs. Functions would be more secure if they are in a public subnet or directly connected with an internet gateway. Review collected by and hosted on G2.com.

I like AWS Lambda for its simplicity and scalability. It allows me to run code without managing servers and deploy very quickly, which is handy. I only pay for actual usage, which I find efficient. AWS Lambda is very useful for automation, API integrations, and handling workloads efficiently. It automatically handles changes in workloads, whether it's a few requests or a sudden spike in traffic, saving a lot of time and reducing operational effort. Also, the initial setup was fairly easy, especially for basic functions, thanks to AWS's straightforward console templates and good integrations with services like API Gateway and S3 buckets. Review collected by and hosted on G2.com.

I would say, one area that could be improved is cold start performance for some workloads. Especially when, functions are not evoked frequently. Because debugging across these multiple services can also take extra efforts in, like, complex architectures. And, better visibility and simple troubleshooting tools would make it even more efficient. Review collected by and hosted on G2.com.

it removes the need to manage servers and scales automatically with demand. The most helpful part is the pay-as-you-go model, where you’re only charged for the actual execution time, which makes it cost-efficient. Upsides include quick deployment, easy integration with other AWS services, and the ability to build event-driven applications without worrying about infrastructure. Review collected by and hosted on G2.com.

AWS Lambda is the cold start delay, which can impact performance for latency-sensitive applications. The least helpful part is the limited execution time and resource constraints, which make it harder to handle very heavy workloads. Downsides include vendor lock-in, debugging complexity, and the need to design carefully around its limits to avoid unexpected issues. Review collected by and hosted on G2.com.

I like AWS Lambda because it’s event-driven, highly scalable, and can save a lot of money by charging only for actual execution time instead of keeping servers running continuously. I also like that it removes server management entirely and integrates easily with services like API Gateway, S3, and DynamoDB, which makes it efficient to build scalable, cost-effective applications. Review collected by and hosted on G2.com.

I don’t like that AWS Lambda cold-start latency, which hurts performance for infrequently used functions especially when an app is time-sensitive. Review collected by and hosted on G2.com.

From my experience, what I like most about AWS Lambda is that it removes the need to manage infrastructure while automatically scaling with demand, integrates seamlessly with other AWS services, and provides a cost-efficient way to build and run event-driven workloads. Review collected by and hosted on G2.com.

The limits:

- The size limit of 250 MB.

- The concurrency limit issue.

- The limited supported programming languages Review collected by and hosted on G2.com.

It’s truly a zero-administration, serverless model, so there’s no need to manage hardware or worry about patching the operating system. It allows me and my team to focus 100% on writing code instead of spending time on server maintenance and ongoing upkeep. Review collected by and hosted on G2.com.

Debugging and observability: When you’re debugging but don’t have access to the underlying server, you can’t SSH in to see what’s wrong, which makes troubleshooting much harder. Review collected by and hosted on G2.com.

The best part of AWS Lambda is that there’s essentially zero server management. Not having to patch OS versions or manage clusters lets our engineering team focus fully on writing and improving code instead of dealing with infrastructure overhead. The event-driven model also feels seamless—triggering functions from S3 uploads, DynamoDB changes, or API Gateway requests simply works as expected. On top of that, the scaling is impressive: whether we see 10 requests or 10,000, Lambda handles the concurrency without us needing to tweak a single scaling policy. Review collected by and hosted on G2.com.

The “Cold Start” issue is still a factor, particularly for functions written in Java or .NET, and it can add slight latency when requests are infrequent. In addition, the 15-minute execution limit means it isn’t a great fit for long-running or heavy data-processing tasks. With these constraints in mind, you really have to be intentional about how you design and architect your workflows so everything stays within the guardrails. Review collected by and hosted on G2.com.