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Serverless Development and Deployment Best Practices Serverless has streamlined the application development process so much that it has made up the minds of many, including you, to go serverless. However, simply determining to go serverless is not adequate.   

When it comes to serverless architecture, you need to follow some structured practices in order to deploy applications for rapid application development, maintain application security, and minimize bugs.    

DataVizz has been working on serverless for quite a few years. And, with the knowledge we gained in the process, we have stepped ahead to list the best practices of Serverless Development as well as Deployment.   

If you have weighed serverless as a serious business, following these best practices would make a significant contribution to it.   

Serverless Application Development

Serverless computing implies a method wherein developers get to build applications without having to manage the infrastructure.   

The face of application development has not only changed but also enhanced with serverless technologies. When using a serverless model, you can:   

Eliminate server issues   

Write shorter codes   

Increase core development period   

In a nutshell, serverless lets developers focus more on writing codes and not worry about the maintenance and management of servers. Even so, servers are still used, the developers need not look after the infrastructure. Once the code is written, the cloud service provider shall look after the rest.   

In order to develop serverless applications, the developers need to write serverless codes without provisioning a server, ensuring functionality, maintaining server uptime, and creating test environments. All these tedious responsibilities are on the shoulders of the service providers.   

It wouldn’t be surprising to say that Serverless is one of the oldest, yet, robust deployment frameworks for serverless applications.   

Building applications using Lambda facilitates speedy application development. Unlike in the server-based model, as mentioned earlier, you can write a small percentage of codes.  

What is Serverless Framework?

The Serverless Framework is an open-source framework that is written using Node.js. The first framework developed for building applications is Serverless. It was built on AWS Lambda, which is a serverless computing platform. AWS Lambda is a part of the Amazon web Services.    

The serverless app aids lambda functions to accomplish tasks as well as supports all runtimes within the selected cloud service provider. The serverless framework aids you in developing as well as deploying AWS Lambda functions with the AWS infrastructure resources.   

If you ask how the Serverless Framework is different and above the rest, here’s the answer:   

Serverless Framework not only manages your codes but also your infrastructure   

Serverless Framework supports more than one language such as Java, Python, Node.js, and so on.   

Best Practices

Now that you are through Serverless Development and Serverless framework, you are all set to learn the best practices of Serverless. However, remember that the best practices may differ because of different operating models and many other reasons.   

For Development   

Let us first begin with the best practices for serverless development:   

Go Local foremost

Starting serverless app development can bag you a good amount of time. On the contrary, when Lambda starts getting intricate, you might have to make several optimizations to the functions code as well as configuration.    

Now, every tweak you make eventually increases the waiting period for code deployment and lets the stack go live. And, as a developer, you have to save your time, as much as possible (We don’t even need to say that).   

Therefore, instead of running your development cycle as 1. Save 2. Open Console 3. Deploy 4. Wait 5. Refresh 6. Wait, you can consider switching the cycle to:   

Save   

Build   

Refresh   

Moreover, the lambdas, API endpoints, and many more can be cloned in the local Docker container by the AWS Serverless Application Model.

Practice 1 Function at a time

Did you know that single function proxy has isolated issues and that it does not scale well with HTTP?   

Now that you know, here’s something more. When the function of a set of routes is sternly joined to a single table, it gets detached from the serverless application.    

You might have got one additional layer of complicacy. However, if it helps in sealing-off issues and errors while scaling your serverless application, isn’t it worthwhile?   

Quit Overwriting Codes

If you are new to the Serverless Framework, here’s something you should know:   

In a Serverless Framework, JavaScript is the supreme language.   

Therefore, when you write codes in JavaScript, they shall be interpreted as well as executed in the best possible way. If you face a performance issue, do understand that overwriting codes is not the way to solve it. Rather, you can:   

Reverse useful error data   

Pause loops   

Merge several requests   

Execute Load Testing   

In a serverless environ, you may have to deal with intricate applications. Besides, you may not be advised of the dependencies that failed to perform a function extensively, within your application.    

In order to know the optimal timeout value, you can consider load testing your lambda functions. It can also help you determine memory allocation.    

Load testing can potentially aid you in pointing out the potential issues that could be critical in sustaining application uptime.    

For Deployment   

And now we would detail the best practices for serverless deployment:

Deal well with Secrets

Your applications must be able to securely deal with database credentials. API keys, or other such secrets. And, when we term it as dealing, it implies storing as well as accessing the secrets effectively.    

Although there are many components of this, some of the most vital ones are:   

Practising unique secrets at different application stages (at least wherever applicable)   

Confining accessibility to secrets   

Protecting secrets away from source control   

Employing environment variables for configuration (with Lambda)   

Moreover, you can add various parameters that’ll let you configure secrets across application stages, AWS accounts, and services.    

Limit Deployment Period

Did you know that you can lock your deployments for a definite period? Irrespective of the time range you choose, and the reason you wish to lock it, you can inspect your readable serverless file, as well as the Cloud Formation templates.    

Define Stages and Regions

Conventions help developers understand a set of standards while learning about other parts of a system. One such universal convention is that there is a separate place for code and another one for the developers that are not ready for the customers yet. These are known as stages. With stage configuration you can determine the region stages or AWS account deployment, the parameters and secrets used, etc. It lets you block development stage deployments, and do much more to support your requirements.   

If you are working with a team that is scattered across boundaries, the default AWS region for different developers would be different. These differences can potentially create issues in your coding or might include other such limitations. To prevent this from happening, you along with other developers can employ a single region or a division of regions, as per your requirements. You need to specify the allowed regions by which you are ensured of servicing to that specific region or list of regions.    

Name and Describe Functions

While managing stages and regions, naming and describing functions in your infrastructure can do wonders. By doing so, you can ensure that your lambda functions have a consistent name, stage, and function. Also, it will help you find relevant functions, provided they belong to the same AWS account. In simple terms, when you name and describe the functions, you’ll precisely know what to call the function you are looking for.   

Food for Thought   

Business Benefits of Cloud-Native Engineering Being cloud-native is inclusive of everything from infrastructure services to automation, virtualization and containerization, microservices, and observability. In a nutshell, your application is built with modern cloud technologies. It enhances DevOps speed, efficiency, and agility. Now businesses can enjoy an automated management experience over the private, public, as well as hybrid cloud.

It increases the efficacy and agility of the operations. It spreads a good word about you and your service action into the market out there, as such architectures allow you to address your customer’s queries and concerns in the swiftest/speediest way possible.

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