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To Go Serverless Or Not Is The Question

AWS Lambda was launched in 2014. Since then, serverless computing (Function as a Service) came into existence. We have been using Lambda for our projects for the last couple of years to build complete end-to-end web applications which includes usage of AWS Lambda with API Gateway (REST APIs), CloudWatch (logs), S3 (website hosting & data storage), and so on.

Google and Azure also provide serverless technologies like AWS. There is one more popular open-source solution, i.e. OpenWhisk. While implementing serverless applications on AWS, we have learned a lot about running a website on Lambda. Like every other technology, serverless also has its own set of benefits and drawbacks that we will discuss here.

What Does Serverless Mean?

Serverless is a dynamic cloud computing execution model where the server is run by the cloud providers i.e. AWS, Google, or Azure. This technology actually runs on the servers, but when they say serverless, it means that the servers are abstracted away from the users and provided as a service to them.

The Serverless World

There's so much excitement for serverless in the industry. But there are issues that sometimes outweigh the pros of serverless architecture and would need complex workarounds. AWS charges for each invocation of Lambda in multiple of 100ms increments. When there are thousands of incoming requests coming up for EC2 servers, we need to scale up servers to handle them, but Lambda does this on its own. We don't need to create auto-scaling or load balancers. But, how much does it cost to use Lambda? Let's compare that below.

Let's say, we have a serverless application with only 1 Lambda & 1 API Gateway,

  • API Gateway
    $3.50/API calls * 200 million API requests/Month = 700 USD
  • Lambda
    $0.00001667 GB-second * (200 million requests * 0.3 seconds per execution * 1 GB Memory - 400k free tier seconds in case of new account) = 1308 USD
  • Total = 2008 USD (This is a lot)

Now let’s see the example of the EC2 server,

  • 3 Highly available EC2 Server = 416 USD
    M5.xlarge: 16GB RAM, 4 vCPUs
  • Application Load Balancer = 39 USD
  • Total = 455 USD/Month

So, if you compare the above pricing, classic servers are cheaper than serverless.

This can be really useful for startups in their early stages where every rupee counts. In that case, Lambda or serverless will be very useful as it charges only for the number of hits coming on your server with less management and more development for the team. For example - you have your development environment for developers, so, instead of setting up new servers, you can go with serverless development.

Loss Of Control

One of the biggest disadvantages of serverless is that you don’t have the control over your services. We use a lot of services that are managed by third-party cloud providers, like Cloudwatch for logs and DynamoDB for databases. Also, various functions need to be managed as your project grows, and everything is handled by cloud providers. You lose portability as soon as you integrate with other services like Lambda with SNS, DynamoDB, Kinesis, and it also results in vendor lock-in. It becomes difficult for you to change the vendor later.

On the other hand, in the non-serverless world, we can manage our language versions, queues, or db queries. Basically. we have all codes at one place where we don’t need to manage multiple functions. But every technology has its pros and cons which we said earlier as well. In serverless, there is a loss of control that leads to focusing less on development and more on adding the business values of our product.

Choosing serverless or non-serverless will completely depend on the product type. If you have a simple application like selling cakes online and you need simple implementation or authentication, you can go with serverless. But if your application is really complex, you need to add some complex algorithm. To have the control over your code, security, and authentication, you should go with non-serverless.

Security Issues

The biggest risk in serverless or using cloud services is poorly configured functions, services, or applications. Bad configuration can lead to multiple issues in your application which can be either security-related or infrastructure-related. It doesn’t matter which cloud provider you are using, AWS, GCP, or Azure, it’s important to correctly configure your functions or services with the permission it needs to access other services and manage controls. Otherwise, it can lead to permission issues or security breach. Also, if you are connecting any third-party APIs with your provider, make sure the connections are safe and data is encrypted in the right format.

Giving correct configuration is the most important thing in both serverless and non-serverless applications. When you use cloud services and be very strict about it, you will interact less with security breaches or permission issues in the near future.

Testing & Debugging

Serverless applications are hard to test. Normally, developers test the code locally and then deploy it. But in the serverless world, testing on local seems to be complicated, as no such tool is available to mock the cloud services on the local environment. So, we need to perform a decent amount of integration testing before moving forward. Currently, you can test & debug the code using Console or Print statement which will be visible in your Cloudwatch logs like below is one code snippet in Node.js.


For serverless applications, it is important to give some time & effort upfront to architect your application correctly and create good integration tests over cloud infrastructure.

It is difficult to test or debug the applications in serverless. In non-serverless applications, we debug the code, but in serverless, we need to debug end-to-end integration with multiple services that we use. Lambdas are so short-lived that till the time you search for the logs, they disappear. So, in this situation, we can use AWS Cloudwatch or Google Stackdriver that are meant to do that.

Cold Start

Regular cold start

Source: AWS re: Invent

An issue remains an issue until you trace that, and some technical issues are hard to find until you know or face them. Yes, Lambda has one such drawback which is known as Cold start. Lambda gets cold, it means, Lambda code runs on the server which is managed by Amazon. To make it feasible, Amazon doesn’t keep everyone’s code warm, i.e. it doesn’t serve all requests at the same time. So, if your particular function hasn't run in a while, a request has to wait for Lambda to spin up the server then invoke the code, which will take some time for Lambda to give the result for that request.

But, wait for how long? I was using Node.js and it took around 4 seconds to respond. This is not good for the end-user experience and it can impact your business. This kind of issue is not tolerable in today's world where we need requests to respond faster to provide a better user experience.

The problem is not much for limited Lambdas, but what if the number of Lambdas increases. Let's say, there are 50s-100s of Lambdas, and warming up every Lambda can be annoying. You have to call Lambdas before the user calls it again, I mean, why? But there isn't any solution rather than warming it. I particularly used the Serverless Framework for my serverless implementation. It helped me achieve most of the problems of Lambdas and other resources that we used to build serverless applications.


Serverless has many problems, I agree, but which tech doesn’t. When you choose either serverless or non-serverless, make sure you do your study and analyze your requirements to decide which direction to enter. If you want to implement quicker, small applications with strict deadlines and less budget, go with serverless, otherwise, choose EC2 servers. It mainly depends on the requirements. If you are using serverless, some frameworks will help you a lot. Also, you can compare the pricing here.

If you are new to serverless and want to implement it from scratch, you can have a look at the following link.

Currently, serverless has its downsides, but hoping that Amazon and other cloud providers will come up with some good solutions to make it more efficient. We look forward to learning as the technology evolves.

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