Every modern business is turning to serverless computing. Why? Because this latest cloud computing technology frees businesses from all kinds of worries about the infrastructure and allows them to focus on their core competencies. Serverless Computing is the latest approach to delivering software as a service, popularly known as SaaS.
Instead of managing servers and installing software on them, you use a virtual machine to run your code on the cloud. This contrasts with cloud computing where a physical server manages other servers. You can scale your business independently since you don’t have to worry about infrastructure issues or maintenance charges.
However, along with the benefits, there are limitations to serverless computing. And that’s what we are going to explore in this article, what server computing means, why you should use it, and its limitations. So let’s get started.
What is serverless computing?
Serverless computing is a brand new technique on how to build bots and applications. The idea is that you don’t need to worry about servers, infrastructure, or even the cloud. Instead, you write your code once and then deploy it to any number of cloud providers.
This makes serverless computing inherently scalable because you don’t need to worry about where your code will run; it can be run anywhere. And if you need more computing power at any point in time, simply add more instances of your service on-demand (there are no upfront costs).
Serverless computing allows you to focus on providing the right services at the right time rather than worrying about the infrastructure required to run them. This makes serverless computing great for startups and SMBs that need their apps to scale out quickly as they grow.
Top reasons and benefits why should use Serverless computing
Price per server time
The most important advantage of serverless computing is the price per server time, which is significantly lower than that of traditional on-premise implementation.
Serverless applications can scale to demand by provisioning servers only as needed. This means you can add more capacity in real time and scale up or down as needed. The cost of adding capacity is much lower than what it would be for traditional cloud providers, which are typically charged based on a monthly fee per server.
Inherently scalable
The most obvious benefit of serverless computing is the inherent scalability. Applications that run on AWS Lambda are executed as a function, which means you can scale up or down as needed. If you need more resources, you just create more instances of the same process and pay for them in the same way.
You can also scale out by running multiple instances of your function in parallel and paying only for the resources consumed by a single instance. This is especially important if you want to run your application at high volumes or with high latency loads.
Freedom from vendor lock-in
Serverless architectures allow developers to use any cloud provider they want, so they can choose the right platform for their needs. In addition to that, serverless platforms are open source, which means there is no vendor lock-in when it comes to choosing a cloud provider.
Easy Adoption
The advantages of using serverless architectures don’t stop there! They also make it easier for IT organizations to adopt new technologies into their existing infrastructure because there’s no need for change management or migration processes.
No services management
With serverless, you don’t need to maintain servers nor worry about scaling up or down your service as needed. Serverless computing is an ideal solution for startups and small businesses, as it allows them to focus on building their business rather than constantly worrying about how to scale up or down services when they need more or less capacity.
Easier testing and debugging
With serverless computing, you don’t need to manage any instances or servers. Instead, you simply describe your function in code and then deploy it to a cloud provider like AWS Lambda or Azure Function App (formerly Azure Logic Apps). This means you don’t have to worry about running complex tests or debugging issues because everything happens automatically behind the scenes. You can even create automated tests for your functions using tools like Karma and Mocha for JavaScript testing and Jest for NodeJS testing respectively.
Quick deployment and updates
Serverless computing allows you to quickly change your application’s code without having to stop traffic or update servers. This makes it easier for developers to respond quickly to changes in business requirements or market conditions.
Faster innovation
You don’t have to spend time planning for or developing system architecture for your new feature or product; serverless computing can be used as a foundation for experimenting with new ideas.
Reduced maintenance costs
Reduced maintenance costs are another advantage of serverless computing because you don’t have to worry about maintaining your software. Instead, you pay for only what you use no more and no less so there’s no need to add extra capacity just to keep up with demand.
Cons of Serverless Computing
Limited Performance Control
You can’t control and monitor the performance of your application. AWS acts as the server and provides bandwidth, storage, and processing power to your app. This means that you often have to accept reduced performance because AWS is handling all of the work for you.
This is why many organizations choose to use a managed cloud or platform as opposed to a self-managed cloud infrastructure. You can’t just turn off a serverless service in your application and expect everything to continue running smoothly. It will be very difficult for you to tune your application and get it running at the optimal performance level.
No servers to access your data
Another issue with serverless computing is that you don’t have access to your servers in case something goes wrong. If there’s an issue with one of your servers, then it’s likely that all of your applications will experience downtime as well. With managed cloud solutions, you always have access to your physical servers so that you can fix any issues quickly and easily.
No Data Retention
When your application runs on servers, it’s possible to retain data for years or even decades after it was created. Data retention is a feature of traditional server-based applications that allow customers to access their information when needed or wanted. With serverless computing, however, customers cannot access this data later on — and this can be a major problem for businesses that rely on historical information for marketing purposes or other reasons.
Not very reliable
In comparison to traditional architectures, serverless architectures could be more reliable. To provide better reliability and take advantage of Amazon’s ability to automatically scale up and down based on demand, many serverless applications run on multiple instances across multiple availability zones (AZs).
If one or more AZs experience an outage, or if the system cannot handle the load due to a spike in usage beyond what was originally planned for (e.g., during peak hours), then sudden spikes in latency or errors in your application code can cause inconsistent behavior that would be difficult if not impossible to detect with traditional architectures
Response Latency
Response latency is a major factor in the success of any application. Since serverless functions are executed on a remote server, they are susceptible to delays in response time. This can be mitigated by using multiple functions and/or using an asynchronous function call to reduce the length of time it takes for these functions to complete.
Responsiveness is also impacted by network connectivity, which can vary from location to location. To combat this, you can use cloud bursting or distribute caching techniques to increase responsiveness across all instances of your application
Conclusion
Serverless computing is an approach that you can use when building your application, without having a server running at all. You can have it deployed on a server but the service works without having to pay someone else to host it on their server. The power of this technique is that you can scale up or down in reaction to demand, when a new customer signs up for an account or stops running a feature, for instance. Although there are several advantages to this approach, and many use cases for it out there, there are some pitfalls and considerations that we should consider before taking the leap.
I hope this helps. Thanks for reading!
