Saving Cloud Cost by Going Serverless
One of the biggest disputes among many others for going serverless is the dramatic cost reduction one can experience. Since the whole gist of serverless is that you only pay for the time your code is being run, it will result in significantly lower AWS bill in most cases.
What Serverless Means?
Serverless computing is a type of application deployment architecture that allows developers to write code and run it on-demand. From the developer’s perspective serverless makes it possible to deploy application code without having a server to host the code. That saves time.
Using cloud, serverless can also save cost because you typically pay only for the time in which your operations are functioning as opposed to having to pay for dedicated server.
This definition captures the two main features of serverless computing:
As servers and their utilization is not part of serverless computing model, then it is natural to pay only when code is running. Developers will only have to pay for what has been utilized. This cost model is very attractive to workloads that must executed occasionally. Serverless significantly supports “scaling to zero” and avoid need to pay for idle servers.
Since developers do not have control over servers on which their code is running, nor do they know the number of servers their code runs on, decisions about scaling is up to cloud providers. Developers do not need to write auto-scaling rules or define policies on how machine-level usage CPU, memory and so on translates to application usage. Developers also can assume the cloud provider will take care of maintenance, security updates, availability, and reliable monitoring of servers.
Below are main types of serverless frameworks that you can adopt for your business:
1: Serverless with Cloud:
Serverless application code is uploaded to a cloud-based serverless environment and run inside that environment whenever it is triggered by a function. That is why you sometimes hear serverless presented as functions-as-a-service.
2: On-Premises Serverless:
Because cloud based FaaS environments have dominated the serverless market and conversation, many IT developers like to see the cloud as a key ingredient for building serverless architectures. However, it is possible to execute serverless functions on-demand using local, on-premises infrastructure rather than a cloud-based service.
Serverless is an encouraging architecture for saving time and money when deploying applications but companies should not limit themselves to thinking about serverless just in the cloud. On-premises platforms have a great deal of potential depending on the industry and workload among other considerations.
1. Pay per execution pricing model:
Running code on traditional servers all come with an hourly/monthly cost even if the server is sitting around idle with no incoming requests.
In the serverless model, you only pay for the exact amount of time your server-side code runs by the millisecond.
2. Auto Scales for you:
Serverless functions will auto scale for you. You no longer need to think about how many instances of your application you with need to run, writing policies or how to handle load balancing.
3. Leverage third party services:
Serverless is not just about Functions or FAAS (Functions as a service) providers. The meaning of something being “serverless” extends to other third-party software providers.
4. Improved Flexibility:
It is easier to begin implementation with serverless than traditional methods. Because of that going serverless means you can advance faster as well. It is also easy to pivot in situations where you need to restructure.
5. Improved Latency:
Serverless architectures have access points on a global scale. That means that it will be easy to handle users anywhere in the world. This way one can scale without affecting the performance of their application.
6.Zero Infrastructure Maintenance:
You do not have a dedicated cloud environment or infrastructure to maintain. You are basically ‘borrowing’ someone else’s computer to execute your code. Pay a small fee for every code execution and you can completely forget about the infrastructure maintenance.
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