AWS Lambda Reviews & Product Details

What I like most about AWS Lambda is that I don’t have to worry about managing servers or infrastructure. I can just focus on writing and deploying my code, and Lambda automatically handles the scaling based on demand. It’s also convenient for building event-driven applications, and I like that I only pay for the compute time my functions actually use. Review collected by and hosted on G2.com.

One thing I dislike about AWS Lambda is that it can take some time to understand and configure properly, especially when you’re new to the AWS ecosystem. Cold starts can also be an issue for certain applications where quick response times are important. Debugging and monitoring can sometimes feel a bit complicated compared to running a traditional application on a server. 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 for more than 15 min, then Lambda is not a suitable service. Also, the memory and disk space are limited, thes which makes a few operations tough Review collected by and hosted on G2.com.

I like the serverless model and automatic scaling of AWS Lambda because I don't have to manage servers, and it scales automatically according to workload. Its ability to integrate with other AWS Services is great for automation and event-driven applications. The pay-per-use pricing model is also appealing, making it cost-effective for non-continuously running workloads. I value the automatic scaling, event-driven triggers, and seamless integration with services like API Gateway, S3, CloudWatch, and EventBridge for building automation and event-based workflows. CloudWatch logging and monitoring are crucial for troubleshooting and tracking performance. Using environment variables and IAM execution roles makes managing configuration and access control easier and more secure. I found the initial setup relatively easy, especially because creating a function and configuring basic triggers and IAM permissions through the AWS console is straightforward. Review collected by and hosted on G2.com.

One area that could be improved is the cold-start latency, especially for functions that are invoked infrequently or have large runtime and dependencies. Troubleshooting can also become challenging when a solution involves multiple Lambda functions and AWS services, as logs and execution flows can be spread across different places. I would also like to see simpler debugging and monitoring capabilities, more predictable performance for certain workloads, and easier local testing of complex event-driven applications. Review collected by and hosted on G2.com.

What I like best about AWS Lambda is its simplicity and flexibility. I can focus on writing the application logic without worrying about managing servers or infrastructure. It automatically scales based on demand, which makes it ideal for handling unpredictable workloads. I also appreciate its seamless integration with other AWS services like API Gateway, S3, and DynamoDB, making it easy to build event-driven applications. For smaller projects and automation tasks, Lambda helps reduce operational overhead while keeping costs efficient since you only pay for the compute time you use. Review collected by and hosted on G2.com.

One drawback of AWS Lambda is that debugging and troubleshooting can be more challenging compared to traditional applications, especially when multiple AWS services are involved. Cold starts can also introduce noticeable delays for infrequently used functions, which may impact performance for latency-sensitive applications. In addition, managing function time limits, deployment packages, and permissions can become complex as projects grow. While Lambda is a powerful serverless solution, larger applications often require careful architecture and monitoring to avoid unnecessary complexity. Review collected by and hosted on G2.com.

Aws lambda is a game changer for deploying code without tension of managing and maintaining servers. Being able to write code in our desirable language and push it live whereas aws will handle all the difficult part like scaling , concurrency, patching of new os , security updates. This makes lambda functions perfect light weight compute options where one requires micro services integrated with native aws services like s3, dynamodb and much more. Review collected by and hosted on G2.com.

Debugging lambda functions can be tricky, particularly when they are part of larger , complex code architecture. Another downside is cold starts, languages like Java would get visible amount cold start if not ran frequently. Furthermore a lambda function can run for maximum of 15 minutes, do if a task requires heavy and long processing it is not sufficient to complete the task. Also the management of packages is quite tiresome there should be managed repository where one can fetch and use any packages. Review collected by and hosted on G2.com.

What I like most about AWS Lambda is how easy it makes it to run backend logic without having to manage servers. It’s especially useful for building event-driven workflows, where code can run automatically in response to triggers from services like API Gateway, S3, SQS, or CloudWatch. For me, the main benefits are scalability, cost efficiency, and less infrastructure maintenance overall. Because of that, I can spend more time on the business logic and the automation flow, rather than worrying about server setup, capacity planning, or uptime. Review collected by and hosted on G2.com.

One drawback of AWS Lambda is that debugging and troubleshooting distributed serverless applications can become difficult as the number of functions and integrations increases. Cold starts can also add latency for infrequently used functions, and staying within execution time, deployment package size, and service limits takes careful planning. While Lambda works very well for event-driven workloads, very long-running or highly stateful processes may be better handled by other compute services. Review collected by and hosted on G2.com.

What I like most about AWS Lambda is that it lets me run code without having to manage servers. It scales easily, integrates smoothly with other AWS services, and reduces the amount of infrastructure management I need to handle, so I can stay focused on building applications. Review collected by and hosted on G2.com.

One downside of AWS Lambda is that debugging and monitoring can be challenging, especially in more complex applications. Cold starts can also introduce slight delays, and as applications grow, managing execution limits and handling dependencies may take extra effort. Review collected by and hosted on G2.com.

The best part about AWS Lambda is that it allows you to run code without the need for managing servers. It automatically handles the scaling and execution which makes it very easy for event driven workloads.

Additionally, the pricing model is very low as we need to pay only for the compute time your code actually runs. Review collected by and hosted on G2.com.

One thing that i disliked about AWS Lambda is the execution limit, which makes it less suitable for running long process. Debugging can also be slighty difficult compared to the tradition server rest all if fine Review collected by and hosted on G2.com.

As a DevOps/SRE engineer, AWS Lambda has completely transformed how we handle event-driven automation.

The ability to trigger functions in response to AWS events — whether it's an S3 upload, an SNS notification, a CloudWatch alarm, or a DynamoDB stream — without provisioning or managing any servers is incredibly powerful.

The pay-per-invocation pricing model means we're not paying for idle compute, which has noticeably reduced our cloud costs. Review collected by and hosted on G2.com.

The cold start latency can be a challenge, especially for latency-sensitive automation tasks that aren't invoked frequently.

While Provisioned Concurrency helps, it adds cost. Also, the 15-minute execution limit means Lambda isn't suitable for long-running jobs — for those, we still rely on ECS or Step Functions.

Debugging complex multi-function workflows can also get tricky without proper distributed tracing set up via X-Ray. Review collected by and hosted on G2.com.

What I like most about AWS Lambda is how easy it is to build and run serverless applications without worrying about managing infrastructure. We use it extensively for automation tasks, event-driven workflows, and integrations with other AWS services, and it has significantly reduced the operational overhead compared to maintaining dedicated servers.

The integration with services like Amazon S3, CloudWatch, EventBridge, API Gateway, SNS, and SQS is seamless, making it straightforward to build scalable workflows. The AWS Management Console is easy to navigate for creating and monitoring functions, while support for infrastructure as code through CloudFormation and Terraform makes deployments consistent and repeatable.

Performance is excellent for most workloads, with automatic scaling handling traffic spikes without any manual intervention. The pay-per-use pricing model is another major advantage since we only pay for actual execution time, making it a cost-effective solution for workloads that don't need to run continuously.

AWS also provides good documentation, examples, and monitoring tools, which makes onboarding relatively smooth for developers familiar with the AWS ecosystem. Features like Amazon CodeWhisperer and AI-assisted log analysis have also been helpful for speeding up development and troubleshooting, although they're complementary to Lambda rather than built into the service itself.

Overall, AWS Lambda has helped us build reliable, scalable, and cost-efficient applications while allowing the team to focus more on business logic instead of infrastructure management. Review collected by and hosted on G2.com.

AWS Lambda works very well for most use cases, but there are a few areas that could be improved. Debugging distributed, event-driven applications can sometimes be challenging, especially when a function interacts with multiple AWS services. While CloudWatch logs are helpful, troubleshooting complex workflows can still take time.

Cold starts can occasionally introduce noticeable latency, particularly for infrequently invoked functions or larger deployments, although AWS has made improvements over the years. Managing environment variables, IAM permissions, and deployment packages can also become more complex as the number of functions grows.

The AWS Console is feature-rich, but navigating through different configuration pages can feel overwhelming for new users. Overall, these are manageable limitations, and they haven't outweighed the benefits of using Lambda for scalable, serverless applications. Review collected by and hosted on G2.com.