Understanding the Power of Serverless Computing by Weighing Its Pros and Cons

The world of cloud computing is buzzing about a popular service: Serverless computing. Conventional computing can have advantages, especially for people who want “hands-off” style cloud serverless computing. 

Think carefully before making the switch to on-demand computing because of the serverless computing benefits and disadvantages. 

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No infrastructure to maintain 

The debate about whether the cloud is really “someone else’s machine” continues, but that debate has no place in serverless. 

Serverless computing means a way wherein the tiny fragments of code that perform a single operation are executed on pre-existing databases that often perform functions for many other customers. Since you are conducting serverless computing applications and their related operations on someone else’s device, there is no infrastructure to maintain, even digitally. 

No costs when functions are not running 

The price you pay for serverless computing is low, considering the alternative. In a serverless model, anybody with access can see or use your content or services, and there are no costs associated with running a server. 

For details on how much Lambda costs, visit the AWS pricing page. There are many serverless computing benefits where AWS Lambda is most helpful in managing data, performing processes such as analytics and other services, and running server applications. 

Those who compute less than one million and 400,000 Gigabytes per month are not required to pay anything. Beyond that, it is just $0.20 per additional million requests and $0.00001667 per additional GB-second of processing power. However, these prices are estimates and can differ depending on the amount of memory used for a task. All countries, except Hong Kong, have the exact pricing (see the AWS Lambda pricing page for details). 

Infinitely scalable 

When it comes to Google’s Cloud Functions, among the most compelling features is the ability to scale automatically. Like AWS and Azure serverless computing service, Google shares this capability—in reality, every serverless technology willing to invest in is built on rising in response to demand. 

Another serverless computing benefit is that there is no need to divide a new cloud server or buy extra computing resources for an existing example. All of this is taken care of by the serverless computing model, leaving you with no extra costs other than a marginally higher charge for additional computation power enabled by Microsoft azure serverless computing. 

Reduced latency 

Cloudflare states that using serverless features will significantly minimize end-user latency. Since serverless functions are not based on an origin server, there is no central location to which an end user’s traffic must be routed. 

Other than that, what serverless computing means is that every data center of a cloud service can be used to manage a serverless feature. This ensures that the function will be executed by the server nearest to the user, significantly minimizing response time. 

Reduced program complexity 

When writing code to run directly on a device, the IT team must consider several considerations: the operating system, the hardware resources used to execute specific functions, dependencies, and other variables. 

Serverless computing benefits also ensure that functions are not required to consider any of this; the code only must be provided by the cloud platform being used. Additionally, to be easier to create, serverless functions need significantly fewer coding skills, making production accessible to those with lower ability levels. 

Three drawbacks to serverless computing 

1. Security issues 

A server that performs serverless operations does so with many users, which raises many security issues. ZDNet, a sister site of TechRepublic, reports ten possible security threats associated with serverless cloud computing, which includes the following  

  • Introducing the function of event records is a SQL injection-style attack against a server that is running serverless functions. 
  • Any number of errors on the administrative end make them vulnerable to man-in-the-the-middle attacks. 
  • Inadequate tracking and recording of processes may alert administrators to attackers conducting reconnaissance to determine attack potential on any serverless computing platform. 
  • Insecure third-party dependencies—serverless tasks that rely on third-party dependencies can expose data to risk if those frameworks contain malicious code to leverage serverless computing benefits; and  
  • DDoS attacks on serverless systems can overwhelm them and shut down support for multiple users concurrently. 

2. Vendor lock-in 

Migrating serverless functions from one platform to another can be challenging. Code will need to be rewritten; APIs available on one platform may not be open on another, and add columns required to migrate from AWS to Azure or Google Cloud. 

If you are looking to benefit from using the serverless platform, ensure that the vendor meets all your requirements. Being dissatisfied with your hardware virtualization provider a few months and years into your service can be a significant issue. 

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3. Debugging is more difficult 

Whenever a serverless instance is launched, it has its distinct version, debugging and resolving impossible.  

Third-party tools exist but debugging a serverless process can be difficult is no longer the case. for example, it is crucial to go step-by-by-step with AWS. For example, it is necessary to drill along lines using a debugger to enable serverless computing. 

You can debug functions running on the serverless platform, but this can require a lot of time and money. 

Knowing if serverless computing is an ideal solution for your business 

Whenever a serverless instance is launched, it has its distinct version, debugging and resolving impossible. Third-party tools exist but debugging a serverless computing application process can be difficult is no longer the case. It is essential to go step-by-by-step with AWS; for example, it is necessary to drill along lines using a debugger. 

You can debug functions running on the serverless platform, but this can require a lot of time and money. 

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