The Factors to Consider While Going Serverless

The ever-changing landscape of technology often presents new challenges for businesses, and as enterprises and developers race to keep up with these ever-changing trends, it’s important to be mindful of where the industry is headed.

The same goes for the cloud. The rise of serverless computing has lifted someconcerns off the shoulders of developers and businesses alike, making application development and deployment that little bit easier and more efficient than earlier. As per a report, 40% of companies have adopted serverless.In fact, as per a Datadog survey, more than 50% of AWS users have shifted to AWS serverless.

The soaring inclination stems from the fact that serverless makes the application more efficient and cost-effective by reducing the reliance on traditional servers. It’s a new model of computing that allows running the code without worrying about the infrastructure. 

While serverless architecture has been around for years, it has recently gained attention as more developers have started using it in production. It is an excellent choice for modern applications that need to scale quickly, respond quickly and be highly available.Besides, unlike traditional applications, which require extensive maintenance costs, serverless applications consume cloud resources only for the time they are running.

But it’s always wise to know all the ins-outs before you go Serverless. That said, here are several crucial factors to consider while going serverless.

1. Additional Latency and Cold Starts

The first thing to consider with serverless applications is that there could be higher latency than a traditional server-based application due to how they’re deployed. Additionally, every time a new function is created on AWS Lambda (for example), it takes time for that function to start up before it can process any requests — this is known as a “cold start” and increases latency further. 

This issue can be mitigated by using libraries such as Serverless Framework, which allows packaging up the functions into a single deployment package — but at the cost of having more dependencies in the project.

2. Vendor Lock-in

Serverless vendors offer a variety of programming models — Functions as a Service (FaaS), Platform as a Service (PaaS), and Container as a Service (CaaS). But each vendor has its environment, programming model, and libraries. 

For example, AWS Lambda only supports Node.js functions while Google Cloud Functions only supports JavaScript. Such lock-in could be an issue if one decides later that they want to move their application to another cloud service provider for cost or performance reasons.

3. Observability

Debugging can be a challenging task when working with serverless architecture as each service is isolated from other services, and one cannot debug them directly. Developers need to find a way to connect to the service and debug it. For example: if you want to debug your Function in AWS Lambda, you can use CloudWatch logs or function logs. 

Sometimes, developers will have to use application logs instead of function logs because there are no events in function logs after creating a new version of the code until it fails due to an error or timeout.

4. Additional Function and Microservice Calls

Function calls are the most expensive part of serverless architecture. They use cloud resources for every execution, so if the application has many functions that are not always needed, it will cost them more money. 

Also, if the app is composed of multiple microservices that communicate with each other via function calls, then again, this could increase the cost of executing the application.

5. Debugging and Monitoring

The biggest challenge with debugging serverless functions is that developers don’t know what happened in the function after it returns; they only get the function result. Therefore, if they try to debug the function to understand why it failed, they may not have enough information to debug it effectively.

For example, if you have an HTTP request that takes longer than expected, or if there were errors during processing, this information is lost when the function returns. It’s also possible that a failure could occur inside the function and not be visible from the outside. 

Suppose you are using persistent storage with Amazon S3 or DynamoDB tables and one of those services fails during the execution of your code. In that case, you will not see any error messages until after your code has finished running. 

6. Testing, Deployment, and Rollback Strategies

The first thing that you need to think about is how you will test your code. There are two ways of testing your code once it is deployed on a serverless platform: either by using the local development environment or by deploying the code to the provider’s staging or production environments. 

The first approach may not be suitable for some users because they may have multiple services running on their local machines, which could have some overhead, but it does allow them to test their code at all times. 

The second approach also has its limitations; for example, if there is no staging environment in place, you cannot test your code until it has been deployed on production servers, which could be risky sometimes.

How To Overcome These Challenges?  

Adopting a powerful serverless offering is a great way to overcome some of these challenges.


Google Cloud Platform (GCP) is a serverless offering from Google. It offers various services, including storage, databases, computing, and other services that can be used in a serverless fashion.

The advantage of GCP is that it provides easy access to multiple regions worldwide with great security features built-in. This allows businesses to run their application in any region without worrying about latency or data loss.


Microsoft Azure provides a global network of managed data centres through which customers can build, deploy, and manage applications and services. It expedites software as a service (SaaS), platform as a service (PaaS), infrastructure as a service (IaaS), and private cloud capabilities, which can power businesses of all sizes across various industries.

The key factor

While everyone seems to be talking about serverless, not everyone understands exactly what the technology could do for them. We work with a lot of startups looking to actualize their product ideas where we help drive the technology direction. That’s when many discussions turn to serverless. But there’s so much to factor into the decision.

Apart from the issues mentioned earlier, developers need to understand how to keep usage low even as heavy processes kick into gear. This is a massive influencer of ongoing costs and every developer must understand the nuances. If the team working with serverless has a deep understanding of how the cloud service bills, it’s possibleto drive real savings. How big? Well, in one instance, we were able to reduce the total cost of ownership from over $ 50000 to less than $ 5000.

That’s why and how to adopt serverless.Remember, time is the most valuable resource – so try focusing on designing applications rather than spending excessive time provisioning and managing the servers needed for deploying these applications.

With Zingworks on your side, you can adopt serverless smoothly. Connect with our experts today.

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