AWS Lambda Reviews & Product Details

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.

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.

You can simply write your code and deploy it, as testing is straightforward. It's easy to connect to any runtime, and you can even trigger Lambda functions using SNS and EventBridge rules without much hassle. There's no need to manage a server—just attach an API Gateway, and you're set. Review collected by and hosted on G2.com.

What I dislike most is the cold start issue. In many of our applications, it leads to slow performance and occasionally causes errors when there are concurrent invocations. Review collected by and hosted on G2.com.

What I like most about AWS Lambda is how it completely removes the need to manage servers. You just focus on writing code, and it takes care of everything else—scaling, patching, provisioning. It’s incredibly efficient, especially for event-driven tasks like processing S3 uploads, reacting to database changes, or triggering workflows based on user actions. It also scales automatically, so whether you’re handling one request or a thousand, it just works without you needing to plan for capacity. Plus, the pay-as-you-go model means you're only charged for the time your code actually runs, which is great for keeping costs low. I also appreciate how well Lambda integrates with the rest of the AWS ecosystem—whether it's SQS, DynamoDB, or Step Functions, it all ties together seamlessly. It’s a powerful tool for building modern, scalable, and cost-effective applications. Review collected by and hosted on G2.com.

One of the main things I dislike about AWS Lambda is the **cold start latency**, especially when using certain runtimes like Java or when functions are in a VPC. That delay, even if it's just a couple of seconds, can be noticeable in user-facing applications. Another challenge is **limited observability** out of the box—while you can plug in tools like CloudWatch or X-Ray, it often takes extra effort to get clear visibility into performance and failures. Also, **debugging and testing locally** can be tricky, especially when dealing with event sources like API Gateway or DynamoDB streams. And while the simplicity is great for small functions, managing a large number of Lambdas can get messy fast—things like versioning, environment variables, permissions, and deployment pipelines need to be tightly organized. Finally, the **timeout and memory limits** make Lambda unsuitable for certain long-running or resource-heavy workloads, so you have to design around those constraints. Review collected by and hosted on G2.com.

- I like that I can write a specific function or unit of code which is focus on performing a single task

- You only pay for the amount of time you run it and this encourages you to optimize your code in terms of time and space complexities to save money

- Simple to use and setup and execute once you get the hang of it

- Can be used to re-write the origin of your CloudFront Distribution as well and allows the static hosting using S3

- I believe that lambda is at the core of AWS services and can be helpful in accomplishing many tasks across a range of services

- It can be used to create a range of microservices too Review collected by and hosted on G2.com.

- If you do not optimize the code, you may end up paying more

- Supports limited languages in which you can write the lambda Review collected by and hosted on G2.com.

The ease of deployment of an AWS Lambda function is amazing. I can literally have vs code editor in AWS Lambda for editing my code. This makes my testing and deployment very easy and efficient. I do the testing in the cloud IDE itself. Review collected by and hosted on G2.com.

The limitation of 15 minutes becomes sometimes annoying because I use lambda functions for processing data which sometimes is in GBs and hence 15 minutes are not enough. Review collected by and hosted on G2.com.