Developing software applications is a pretty complex task, where developers have to focus on many other activities, along with writing code. Once they develop code, they need to ensure it runs on all the computers connected over a network. Also, they have to check whether all those computers are working smoothly.
As a result, the development team ends up spending most of their time taking care of or provisioning the underlying physical machine on which their code runs.
Over the past decade, a plethora of technologies has evolved, such as containers, cloud computing , and virtual machines, that let the development team majorly focus on writing clean and effective codes. Among all, serverless computing is one of the emerging technologies that allow developers to build applications, eliminating the need to manage servers.
It is the best solution for teams who wish to unburden themselves from managing and maintaining servers and desire to run their applications at scale. If you are searching for an effective method to develop and release applications efficiently, you must consider serverless computing.
This blog post aims at explaining what exactly serverless computing is and its upsides and downsides. Also, it introduces you to the differences between serverless and other cloud compute models.
So, let us begin our discussion!
What is Serverless Computing?
It is the cloud computing execution model that lets you develop applications and run them without requiring you to manage servers. Many people are perplexed by the term "serverless," believing that there are no servers. This is not the case. Here, the term "serverless" refers to the fact that no server management is required while designing apps.
In this model, the cloud providers are in charge of administering and managing the servers. More specifically, they dynamically allocate all the computing resources, including servers, storage, databases , and networking, required to run your application.
Such management of servers or backend infrastructure by cloud providers lets developers solely focus on writing code and business logic. They just need to write the application code and deploy it on the containers that the cloud providers manage.
Moreover, the cloud providers scale the cloud infrastructure up and down as the application’s requirements. They are also responsible for regular infrastructure management, including updates and patches to the operating system, system monitoring, security management, and many more.
Needless to mention, with serverless, you need to pay only for the resources you use and not for the idle cloud infrastructure. This is because the cloud provider allocates all the computing resources at the time of code execution and takes them back when the execution stops.
In a nutshell, serverless computing entails the use of servers, but the cloud provider is responsible for the provisioning and management of servers.
Who Should Leverage Serverless Computing?
Serverless is great for developers who want to shorten the time it takes to develop their apps and make them live to the public. Also, it is a perfect solution for creating flexible, lightweight apps that can be upgraded quickly and easily.
A serverless setup is ideal and cost-effective for applications that have alternate peak periods and little to no traffic. If you opt to purchase a server that runs all the time even when it is not in use, you end up wasting a lot of resources and, of course, money. This is not the case in the serverless setup, as it responds only when your application needs and charges you accordingly.
When Should You Not Use Serverless Computing?
There are certain applications for which serverless is not a cost-effective solution. For complex and large applications that have predictable and constant workloads, using dedicated servers, whether they are self-managed or offered by third-party vendors, would be ideal. In addition, using a traditional setup for such applications may require lower costs than a serverless setup.
Advantages and Disadvantages of Serverless Computing
There is no surprise that serverless computing provides a wide range of business and technical advantages. However, there are certain drawbacks to it as well. Let us now shed light on some remarkable advantages and disadvantages of the serverless cloud execution model.
Advantages
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Improved Developer Productivity
As this cloud compute model does not require developers to manage and provision servers, their sole concentration is on writing code. In addition, they get a lot of time to improve and optimize their application’s front-end features and business logic. Therefore, serverless ensures improved developer productivity.
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Pay-As-You-Go
One of the most desirable benefits of serverless is that it charges you only for the computing resources you use. Whenever your application makes requests for the resources, the pricing meter starts, and it ends when the execution of the application stops.
However, this is in contrast with Infrastructure-as-a-Service (IaaS). In IaaS, you need to pay for computing resources from the time you start provisioning them until you inactivate them explicitly.
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Build Applications in any Language
Serverless provides flexibility for developers to develop applications in any language and use any framework with which they are comfortable. As a result, it is a polyglot environment.
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Simplified Operations
The cloud providers are responsible for ensuring that the performance of the server meets the requirements and demands of an enterprise. Developers are not engrossed in any activities of managing servers. As a result, serverless simplest DevOps, i.e., the development team focuses on writing application code, and the cloud providers manage the operations.
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High and Cost-Effective Performance
Unlike other sorts of compute models, serverless serves as a cost-effective solution and provides high performance when it comes to stream processing, parallel processing, and some other data processing tasks.
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Cost-Effective
Serverless is cost-effective, and it significantly has a positive impact on the overall budget for developing applications. Since the cloud providers manage servers, you can save your maintenance costs. Furthermore, you do not need to hire an expert to manage servers on a continuous basis.
Another primary reason for serverless being cost-effective is it charges only for runtimes. The cloud provider does not obligate you to pay for infrastructure that is no longer in use.
Disadvantages
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Security
Security is crucial in serverless like in any other technology. In serverless, the responsibility of security is solely on the cloud providers and not customers. Many large servers having multiple entry points are vulnerable to attacks. In such a case, customers are helpless since they have to rely on the cloud provider to disclose and recover.
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Debugging
It is pretty difficult to debug serverless code. Developers find it hard to spot errors or issues in the serverless code as the code does not allow itself to delve deeper to review issues or code smells . With all these issues or problems in the serverless code, developers may find it critical to meet the end user’s requirements.
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Limitations
As you get resources from the cloud providers on-demand, they restrict the resource limit, which is not ideal for high-computing operations. Though the cloud provider does not limit the resources, serverless is not a cost-effective solution for certain applications.
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Response Latency
It is one of the biggest drawbacks of serverless. We define response latency as the period between when the application makes a request and when it starts processing.
We know that the serverless does not run continuously. It gets turned off between every consecutive request. As a result, serverless may take several seconds to spin up and process your application code. If timing is a critical aspect, this would definitely be one of the greatest disadvantages of serverless computing.
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Not Ideal for Long-Running Processes
As serverless is based on pay-as-you-go, it charges for the amount of time your code runs. If your application has long-running processes, it may cost you a lofty amount as the application code takes a long time to run.
Serverless vs PaaS, Containers, and Virtual Machines
We have already discussed what exactly serverless computing is. Let us now briefly understand some other cloud computing models, such as PaaS, containers, and virtual machines.
PaaS: PaaS stands for Platform-as-a-Service. It is a cloud environment with resources that enables you to develop and deploy all kinds of applications, from simple cloud-based to complex cloud-enabled enterprise applications. Here, the cloud provider offers resources and charges you on a pay-as-you-go basis.
Containers: A container is a unit of software that combines the application code, along with all the libraries and dependencies so that the application can run on any platform and environment.
Virtual Machines: A virtual machine is analogous to a physical computer, laptop, server, or mobile device. It is a software-defined computer existing only as a code within the physical servers. More interestingly, a virtual machine has a CPU, memory, and disk for storage and can connect to the internet if required.
Serverless vs Other Compute Models
Let us now move on to discussing the difference between serverless and the above three compute models.
Attributes |
Serverless Computing |
PaaS |
Containers |
Virtual Machines |
Provisioning Time (measured in) |
Milliseconds |
Minutes to hours |
Minutes to hours |
Minutes to hours |
Administrative Burden |
No administrative burden |
Light administrative burden |
Medium to heavy administrative burden |
Medium to heavy administrative burden |
Maintenance |
100% maintenance by cloud providers |
100% maintenance by cloud providers |
Requires significant maintenance, including operating system updates, connections, and container images |
Requires significant maintenance, like managing and updating operating systems |
Scaling |
Supports auto-scaling and can even scale to zero |
Slow scaling and does not support scaling to zero |
Like PaaS, it offers slow scaling and no scaling to zero. |
Similar to PaaS and containers. |
Capacity Planning |
Not required |
Requires a blend of capacity planning and automatic scalability |
Same as PaaS |
Same as PaaS |
Billing Granularity |
Billed in the units of 100 milliseconds |
Metered by an hour or the minute |
Billed in the unites of an hour or the minute |
Metered by an hour or the minute |
High Availability and Disaster Recovery |
No additional cost and extra effort required |
Requires management effort and extra cost |
Needs extra cost and management effort, and the infrastructure restarts automatically |
Extra cost and management effort with automation restarting of the infrastructure |
Serverless Computing vs FaaS
FaaS is an acronym for Function-as-a-Service. It is pretty analogous to serverless; however, serverless is an umbrella term for FaaS.
FaaS is a cloud computing service or type of serverless computing that lets developers run the application code or containers, eliminating the need to manage the infrastructure required to execute the code.
It lets us create functions for existing applications. These functions exist as separate services and complement existing applications. Generally, FaaS is useful in developing microservices-based applications.
Meanwhile, serverless is a complete pile of services that responds to specific requests or events. It is not just constrained to designing and developing functions. It is an ideal cloud computing execution model for large-scale complex applications that require multiple technologies.
Conclusion
This concludes our take on serverless computing. It is a cloud computing execution model that lets developers solely focus on writing the front-end of applications and the business logic without requiring to manage servers. The cloud provider is in charge of managing the servers and allocating resources as needed by the application.
We hope you have gained enough clarity on the topic through this article. If you have any questions or concerns about the topic, please leave them in the comments box below.
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