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.

AWS Lambda's serverless scaling handled our 10k req/sec spikes perfectly, cutting costs 60% vs. EC2. Quick Python setup, seamless DynamoDB integration. Cold starts fixed with concurrency; minor timeout limits.​

Pros: Auto-scale, pay-per-use.

Cons: VPC latency.

Highly recommend! Review collected by and hosted on G2.com.

AWS Lambda has notable limitations like cold starts that delay initial function invocations. The 15-minute execution timeout restricts longer-running tasks.

Main Drawbacks

Monitoring can feel fragmented without third-party tools, complicating debugging in complex apps. VPC integration adds latency and setup overhead.

Vendor Lock-in

Heavy reliance on AWS services reduces portability to other clouds. Deployment package size limits (250 MB unzipped) hinder large dependencies. Review collected by and hosted on G2.com.

AWS Lambda is easy to use and simple to implement, especially for event-driven workflows. It integrates seamlessly with other AWS services, which makes building automation and serverless APIs very smooth. We use it frequently for scheduled jobs and lightweight backend tasks. The feature set is strong, with support for layers, versioning, and multiple runtime options. Customer support is decent, backed by solid documentation, although response times can vary. Overall, Lambda is a reliable and efficient serverless compute option. Review collected by and hosted on G2.com.

Cold starts can be frustrating at times, and debugging or monitoring distributed serverless functions is harder compared to traditional applications. Review collected by and hosted on G2.com.

1. A serverless service, which can be used for automating the work. ex: volume backup, scheduling the stopping of unused servers

2. Implementation is easy; creating the function is very easy. and it lets u run code according to your coding language

3. As a user, we do not need to maintain; by default, AWS will manage.

4. Triggers can be added for the invocation of other services, such as s3, and event driven process

5. it reduces the human efforts for getting the reports from databases as well.

6. one function can be used for many types of work. Support for lambda is quick Review collected by and hosted on G2.com.

There are limitations that lambda can only execute for 15 min, if there is any function that needs to operate above 15 min then lambda is not suitable service. also the memory , disck space are limited only, thes which makes few operations tough Review collected by and hosted on G2.com.

AWS Lambda makes it easy to run code without managing servers, which significantly reduces operational overhead. Implementation is fast, especially when integrated with other AWS services like API Gateway, S3, and DynamoDB. It scales automatically, supports frequent use for event-driven workloads, and offers a strong set of features for building modern, serverless applications. The pay-per-use pricing model is efficient, and AWS documentation and support are reliable. Review collected by and hosted on G2.com.

Debugging and monitoring can be challenging compared to traditional server-based applications, especially for complex workflows. Cold start latency can impact performance for certain use cases, and local development and testing are not always straightforward. While integration within AWS is excellent, portability outside the AWS ecosystem is limited. Review collected by and hosted on G2.com.

I love that I don’t have to worry about servers at all. I just write my code, upload it, and AWS runs it for me whenever it’s needed. It scales automatically if 1 person uses my app or 10,000 persons Lambda handles it without me doing anything extra. Plus, I only pay when the code actually runs, so it’s often cheaper than keeping a server running all the time. Review collected by and hosted on G2.com.

Sometimes there is a small delay the first time a function runs, which can be an issue for real-time apps. Also, you can’t control the underlying server or install custom system-level software Lambda works best when your code fits neatly into its model.

And debugging or monitoring can be trickier than a regular server, though tools like CloudWatch help. Review collected by and hosted on G2.com.

I like AWS Lambda because it runs code without managing servers scales automatically and you only pay when it runs. It also works smoothly with others AWS services, making development faster and easier.implementation is easy.i have use lambda in my most of use case. Review collected by and hosted on G2.com.

The debugging and monitoring can be harder compared to traditional servers and limited execution time. Review collected by and hosted on G2.com.

Code is completely free and I have trial it with not require upgrade, it can be start, everytime, I can try to upload code with ZIP and image, it like AI and it will be complete code.

AWS Lambda shines with its ability to run code without provisioning or managing servers, making deployment incredibly fast and efficient. It automatically scales based on demand, so you only pay for what you use—down to the millisecond. Plus, its seamless integration with other AWS services like S3, DynamoDB, and API Gateway makes building complex applications surprisingly smooth. Review collected by and hosted on G2.com.

AWS Lambda can become expensive at scale, especially when functions are invoked frequently or run for extended durations. The cost model—based on number of requests and execution time—can be hard to predict, making budgeting tricky for complex applications. Additionally, integrating Lambda with other AWS services may incur extra charges, increasing the overall product cost beyond just the function itself. Review collected by and hosted on G2.com.

What I value most about AWS Lambda is its serverless compute model, as it entirely removes the need to provision, manage, or scale servers. Review collected by and hosted on G2.com.

A major drawback is the potential for "cold starts," which may lead to noticeable latency when a function hasn't been invoked for a while. Review collected by and hosted on G2.com.

I like AWS Lambda for its serverless, event-driven model that allows me to focus purely on code without worrying about infrastructure. It significantly reduces operational overhead and helps deliver features faster. AWS Lambda automatically scales based on demand, which is especially valuable for unpredictable or bursty workloads. I also appreciate that it lowers costs by charging only for execution time. The initial setup of AWS Lambda was generally straightforward, and this simplicity is another positive aspect. Review collected by and hosted on G2.com.

Cold start latency can be an issue for infrequently used functions. Debugging and troubleshooting can also be challenging compared to traditional servers. Review collected by and hosted on G2.com.