Web development is evolving as we speak and we are seeing the introduction of fast and much more efficient computing models that have made web development much easier and along with helping developers bring out more performance with the same level of effort.
That is exactly why today we are going to talk about two very important types of computing models in the form of Edge Runtime Computing and Serverless Computing.
We will look at how both Edge Computing and Serverless Computing are different from each other in terms of performance and cost efficiency and we will compare them on multiple levels.
Additionally, we are also going to check out the key features of each type of computing model in order to find out which is the best-suited one for you.
Apart from that we are also going to look at how they are able to process data for modern tasks such as AI inference and much more.
This is an important blog because if you are a developer and you are planning on running code with or without maintaining a server underlying infrastructure then you should definitely understand the benefits of each of these computing models.
These two models dictate the market of web development and as you can see the edge computing market is already at evaluation of $83.72 billion by 2024 and is expected to reach nearly a trillion dollars by 2035 with CARG of 30.23%.
Now if you tell you that Edge Computing was introduced just in 2019 then this growth rate would be much more admirable simply because it speaks to the popularity of this technology.
That does not mean Serverless Computing is insignificant when it comes to market relevance because as you can see it too holds a lot of market authority although not as much as Edge Computing.
So, let us first understand what these models mean.
What is Serverless Computing?
Serverless Computing is basically the execution of a cloud-native model which means developers can run code within it without the need for managing servers or provisioning servers.
Serverless Computing is a very efficient way of doing things as these are services provided to developers only when they need it as developers can rent a certain function of a server and use it without being concerned about managing the server infrastructure.
The reason why this is so good is simply because it cuts down a lot of time that would be otherwise spent by the developer on managing the server.
Serverless Computing allows the developers to simply focus on writing the code and deploying code in an event-driven model where resources are allocated primarily based on demand.
It is like running a restaurant where you can rent equipment based on the kind of need you have at the moment and you do not have to permanently buy equipment.
Serverless Computing has its own set of advantages with some of them truly convincing enough for developers to consider it over edge.
We will talk about that as well but let us understand what is Edge Runtime Computing.
What is Edge Runtime Computing?
Edge Computing is a computing model that is quite different from the serverless category simply because it is a decentralized computing model where data is processed much closer to the source of data generation.
This means if you are able to compute near the point of data origin or at the network’s edge then you are able to get a lot more opportunities and benefits such as improved response times and an overall better experience.
Edge Computing therefore is an excellent model if you want to improve real-time processing speed and also reduce the latency of your processing because you are not going to need to send out data over long distances.
That is why Edge Computing has its benefits over serverless computing.
Let us now look at the benefits of each of these two types of computing models.
Benefits of Serverless Computing
Auto-Scaling
Serverless Computing brings a lot to the table as well as one of the most important benefits and features of Serverless Computing is in the form of auto-scaling.
This simply means serverless functions can scale automatically and do it completely based on demand.
Since you are removing the element of manual intervention you can expect the functions to scale up during high traffic where new instances can be created dynamically in order to balance out the performance and never bottleneck the server.
Similarly, things can scale down just as easily in order to make sure that too many resources are not being utilised and left idle.
Cost Efficiency
Serverless computing is not just about scaling functions as you want automatically because it is also about not paying a cent extra for something you are not using.
With Serverless computing you only have to pay for what you are using and what your function runs on and this means you do not have to pay for idle resources that are not being utilised.
This is very different from traditional cloud computing where you have servers that always stay on and always consume resources.
This is just like having to pay rent and not even being able to live in that apartment or not being able to completely utilise all the rooms in that apartment.
Infrastructure Management
Serverless computing can be about a lot of things but it is mostly about the simplification of infrastructure management.
When you run a traditional server, you have to manage different aspects of the server such as server provisioning and you also have to keep updates in mind and make sure all the security patches are up to date.
You eliminate all of that with Serverless computing because now developers do not have to manage servers in the traditional sense of the way so they can focus on writing logic instead of thinking of managing infrastructure.
You do not want your developers to also play the role of managers because if they start doing both of these things then they will not have time to be good developers.
Event-Driven Execution
Serverless computing is about event-driven execution which simply means that functions are only executed when they are triggered.
This is an excellent use case for event-based applications and can be utilised for a lot of things.
We are talking about everything from database changes to file uploads as regards and also include API requests as well as scheduled jobs and much more.
The use case of something like this is tremendous and you just need to utilise it in the best way you can.
Benefits of Edge Computing
Ultra-Low Latency
Edge Computing has a lot of benefits but nothing comes close to the level of ultra-low latency you can get with Edge Computing runtimes.
This is simply because all the requests do not have to travel a lot of distance from cloud centres because everything is situated significantly close.
This has a direct effect on the kind of response times you get.
There are a lot of use cases for something like this and it can be very important if you are creating an application that needs real-time interactions.
Apart from that Edge Computing is also great for applications with the need for AI-driven analytics.
Reduced Server Load
One of the most important things to keep in mind about web development is that not every computing process out there will be good on the server because sometimes different processing can exert excessive load on a server.
If you are looking to avoid something like that then you can only do it by offloading processing to edge locations.
This means that the primary cloud infrastructure will not get as many requests and it will reduce the load of the overall server.
The benefit of this is also cost savings because you are not exerting load unnecessarily.
However, you must also understand that this can only be done for different smaller and lightweight operations and when you need more intensive processing you can then utilise the primary cloud resources.
Improved Privacy & Security
Edge Computing is good for a lot of things when it comes to performance and loading up resources quite quickly but we need to address something even better with this kind of computing.
Cloud solutions are generally secure enough but sometimes the data can be sensitive enough that the developers do not want to store it on the cloud or somewhere from the actual area of usage.
This is when they will prefer something told locally and that is possible with Edge Computing. We are talking about applications related to healthcare and the storage of sensitive patient information and we can also add finance into the list of sensitive data applications.
Sometimes the storage of data has to be done locally because of different regulatory compulsions and Edge Computing is the only solution that can make it happen with the storage of data near the area of the use case.
This provides an amazing level of security to data storage and prevents data from being misused.
Better Offline Support
Edge computing relies on the device for computational power which means much of the processing or almost all of the processing is done on the device which mostly is things like IoT devices and sensors.
Since that is the case, you do not really need any work to stay connected with the device through the internet because you can run a local network and still have access to the devices.
This opens up a whole new area of operations as now you can expect to utilise all the benefits of edge computing offline as well.
While you cannot really expect a lot of data handling and a lot of functionality with this kind of support without the Internet but you can still temporarily store some amount of data locally on these devices without syncing it to the cloud.
This might not sound much but it can make a lot of difference to the overall utilisation and applications.
Key Differences: Edge Runtime vs. Serverless
Serverless Computing and edge Computing are different from each other and before we go into talking about how one is better than the other, we need to understand the use cases for each of these computing methods.
Latency
If your requirement is latency then Edge Runtime Computing should be your choice because it offers ultra-low latency as the processing happens very close to the user and while Serverless Computing can also ensure low latency but not as much as Edge Computing.
Infrastructure
Apart from that when you have the requirement for infrastructure, Edge Runtime Computing runs on edge nodes within a CDN or even a local processing unit which eliminates the need for infrastructure. Serverless Computing on the other hand has a need for cloud provider infrastructure.
Scalability
Let us now venture into the aspect of scalability as Edge Computing has the capability for scaling regionally and it is completely based on local demand. With serverless Computing, you get the option for auto-scaling across different cloud regions.
Execution Model
When it comes to Edge Runtime Computing you get the benefit of the processing happening near the user which means the delays are minimal. The execution model of Serverless Computing is a little bit different because it is event-driven and only triggered by requests.
Use Cases
The use cases for these two types of computing are also different because Edge Runtime Computing is mostly utilised for IoT, AI inference as well as Real-time and Geo personalization applications. With Serverless Computing, you get the use case of event-driven API calls in the form of API backends and Serverless Computing can also be utilised for different kinds of automation applications and data pipelines as well as batch jobs.
Costs
The cost associated with Edge Runtime Computing is usually higher because of Edge deployment expenses and Serverless Computing on the other hand is a lot more cost-effective because you are simply paying for the things that you need which can save a lot.
Offline Support
Edge Runtime Computing is the clear winner when it comes to the aspect of offline support because you can run Edge Runtime Computing offline with functions running through local caching. Serverless Computing needs continuous connectivity through the cloud in order to work.
We hope this will help you understand what to choose for your next app development project and we sure hope this blog has helped you understand everything you need to know on Edge Runtime Computing as well as Serverless Computing.
They both have their use cases and benefits and if you are looking for experienced developers with extensive knowledge and experience in working with both of these two types of approaches to computing then we are here for you.
We are Think To Share IT Solutions and we will help you with all your Edge Computing as well as Serverless Computing needs.
We welcome you to visit our website and check out everything we do.
