How and When to Decide Deployment of Serverless Frameworks

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  • July 19 2019
  • 0 min read

Deploying an application requires performing a series of actions that makes it run on-demand as a Function as a Service(FaaS). As we know, a FaaS or a serverless framework is what is established to create stages for a project to be deployed. Since organizations are still on the learning curve of serverless, it is apt to take up the concerns surrounding serverless

In this blog, we will discuss the staging of environment, the pre-requisites of deployment, conditions that support and precautions to be taken before the deployment. 

a cup of coffee with a laptop on the table

Before you go Serverless: What do you need?

The serverless is indeed revolutionizing the development processes in the tech industry as we speak.

While we are still grasping on the concepts of serverless, organizations need to take a step back. Instead of just jumping the guns with industry giants, the DevOps teams of the organizations can gather an in-depth understanding of the serverless and the changes it will bring along within different aspects of the enterprise. 

This will serve as the base for the industry-wide scale requirements that serverless can be adopted for; while DevOps will help in implementing it with correct measures.  

Adopting a serverless environment doesn’t come cheap.

When can we Deploy?

There are always a few conditions that determine the deployment of serverless solutions for large scale enterprises. Let’s take a look at them:

Cloud Provider Limitations

As we’d touch on this topic in detail in the previous blog, we discussed how a cloud provider can create lock-in situations for the organizations with their unique implementations.  

The environments provided by a certain vendor, say AWS Lambda, cannot be re-written if you decide to switch the vendor. In order to avoid complications in the later stages, organizations should make sure that the services provided are in sync with their requirements and switching vendors does not involve too much hassle, in case the need arises.  

Unknown Costs

Adopting a serverless environment doesn’t come cheap. It involves huge investments and un-estimated costs. Since the cost is calculated upon the usage of the environment and its functionality, it becomes difficult to decipher the exact amount. In addition to this, there are hidden costs that might not float on the surface at first. For instance, when the transactions increase, the cost also shoots up. It can cross the anticipated amount due to scaling to unexpected volumes. 

You can fix this with efficient code writing or designing the application that allows a larger batch size of data to be ingested into the function.

High Latency

On the operational front, the spin-up time required to restart the Lambda function utilizes resources. This cold start soars up the latency rate. Whereas, the open source frameworks have a provision to pre-tune the resources and ensures minimum latency of the application. Now, it’s an organizational decision to be made whether to opt for serverless frameworks like Lambda or go for an open source framework, both having their pros and cons. 

CI/CD Pipelines

It might take some time for the Serverless to make their niche in the CI/CD toolchain. Being too new for the experiment, the FaaS frameworks needs a diligent attempt in integrating them with the Continuous Delivery pipelines.

  • These are a few things to consider before you implement that:
  • The involvement of the Ops team should be from stage one.
  • The load and performance testing should be increased before deploying the pipelines into production with serverless.
  • Each function should possess the rollback and roll forward capabilities.

Visible Monitoring

Many users have often complained of the unknown. Lambda doesn’t allow its users to know the ongoing operations on the serverless environments. They expect a higher level of technological advancements from the users implementing them. In contrast, open source frameworks have good visibility and built-in integration with native Kubernetes. Again, it’s a tough call to make on the enterprises’ end.

4 Ways to Deployment 

Now that you have a fair idea about the serverless and its concepts, you might be ready to process the deployment. But wait, the environments too have many attributes that you should be aware of. Though there are different deployment environments from Google Cloud Functions, Microsoft Azure Functions to Cloudify, but AWS Lambda is the most prominent choice of many.

As a stateless component, you can create an AWS Lambda function by packaging your NodeJS, Java or Python code for your service in a ZIP file. The primary point of AWS Lambda is its ability to run enough instances of your function to handle the load. 

In order to invoke a lambda function, there are four ways you can opt from:

  • Configure Lambda function invoked in response to an event generated by an AWS service
  • Configure the AWS Lambda Gateway to route HTTP requests to your lambda
  • Explicitly invoke your lambda function using the AWS Lambda Web Service API
  • Invoke a Lambda function is periodically using a cron-like mechanism.

Check out the implementation of serverless computing with Drupal here.


It is apparent that Serverless is not for everyone. You have a lot of challenges to consider before trying your hand at it. Since the technology itself is in the initial phase, there can be many more alterations in terms of how the functions will evolve with time and advancements. 

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