Some things just naturally go well together. Peanut butter and jelly, fish and chips, and… Serverless technology and Python.
Serverless solutions enable businesses to achieve a great deal for a lot less time, money and effort. While they can be built in numerous languages, some options are always going to be better than others. In this case, we’ve found Python to be an excellent go-to choice when building Serverless products.
Why do Python and Serverless go together so well? The best way to explain that is to look at the advantages of both, before explaining how they both come together.
So, what are the benefits of using serverless python? Find out what advantages serverless computing has, what advantages python has, and what opportunities arise from combining them.
What is Serverless Computing? Definition
First, let’s discuss what serverless computing is.
Serverless is a Cloud execution model that enables a simpler, more cost-effective way to build and operate Cloud-native applications. Specifically, serverless:
- automatically provisions the computing required to run application code on demand, or in response to a specific event;
- automatically scales those resources up or down in response to changing demand;
- and automatically scales resources to zero when the application isn’t running anymore.
Technically, serverless offloads all management responsibility for backend Cloud infrastructure and operation tasks to Cloud providers. This includes processes like provisioning, calling, scheduling, patching, and more. As a result, developers gain more time to develop and optimize their front-end application code and business logic. So, with serverless, end-users never pay for idle capacity; they pay only for the resources they need to run their applications – and only when they are actually running.
Serverless Computing – Benefits
By going Serverless – moving your solutions to a system with costs paid by the function (e.g. Lambda) processing time or number of invocations, rather than paying for entire servers – you can gain numerous benefits.
Easily Scalable
With more users and more requests, you simply use more functions (let’s say it like this, for simplicity). This means you don’t run out of space or capacity, unlike the very real, defined limits of running (or renting) your own servers.
If that’s not enough, we can also scale by function, applying more processing power to the functions that need it, without having to equally waste CPU on less used features. For example, everyone will likely use a menu feature, but each subsequent option is only used by a fraction of those users; consequently, we will scale support for the menu up, but not every individual function that follows.
Likewise, we don’t need to spend time designing or coding solutions to work in limited confines. The extra support of Serverless models ensures that the final product runs smoothly, whether it’s currently experiencing ten or ten thousand users.
Cost-effective
Because you only pay per use, rather than paying regardless of usage, costs are typically greatly reduced. With a server, you have to run and maintain it 24/7, even if there are huge periods of time with little to no usage.
With Serverless, on the other hand, you don’t pay unless your code executes. Even then, AWS Lambda offers a free tier equal to 1 million requests, and 400,000 GB-seconds, each and every month, so the costs remain incredibly small.
A Stable Service
If you’ve tried running, maintaining and expanding your own server, you likely know that it is a lot of work. Both the hardware and software requirements take up your team’s time and the end result is rarely as stable as you would like. With Serverless, however, this isn’t a concern at all.
The servers your functions run on are managed by professional experts on the Cloud provider’s side and are completely stable and you never have to worry about maintenance, capacity limits, load balancing, or any of the other factors that go into maintaining your own hardware.
Faster Time To Market
Functions can be easily programmed and, because you don’t need to spend time setting up your own servers or hardware, systems can be implemented in a significantly shorter period.
This increased time to market enables us to quickly create prototypes or products, allowing for more agile and speedy development. This is also reflected in our increased ability to make changes or improvements. We don’t need to start with a discussion about whether or not our server can support it, or how much usage it can support at once – we just get to work.
Python Code – Good Because It’s Short
Likewise, Python has its own advantages that need to be considered here – these are the reasons that developing Serverless solutions in the language are so enjoyable and efficient.
Short Code
Python code can often be quite short and succinct when compared to other languages. This makes it very developer-friendly, as the amount of code needed doesn’t spiral exponentially with scale.
Here’s a simple demonstration, showing the same feature, as coded in both Python and Java:
This works well for Serverless designs, as it keeps each individual function short, succinct, and easily self-contained.
Easy To Read
As a language, Python has an emphasis on readability. This makes it exceptionally easy to read back, especially when performing code reviews or debugging. If something is wrong, we can easily find it, rather than wasting time looking for a needle in a digital haystack.
Combined with Serverless’s accessible nature, this means our solutions have an absolute, if any, downtime, whereas trying to find a bug in another language, just like trying to fix an issue with physical servers, could take significantly much more time – time that your solution isn’t available to your customers or clients.
As an example, here’s how a filter array looks in Python, compared to Java:
Python:
[x for x in [8, 7, -6, 5, -4] if x > 0]
#[8, 7, 5]
Java:
double[] d = {8, 7, -6, 5, -4};
Arrays.stream(d).filter(x -> x > 0).toArray();
//[8, 7, 5]
Very Versatile
Because of its simplistic nature, as well as the above-mentioned benefits, Python is a very versatile language. It’s suitable for a wide range of uses (we’ve previously explored the business benefits of Python already on this blog) and is very well supported.
The language is great for writing and working with API apps, web programs, the Internet of Things, and of course, Serverless solutions. Like many programming languages (but not all), Python is also Turing-complete, which goes some way to highlight its versatility. When we want to create something that will quickly work with the likes of AWS lambdas, we know Python gives us the reach and flexibility needed.
Serverless Computing and Python – How They Work Together?
Okay, so that’s enough about the individual benefits – just how well do Python and Serverless technology go together?
The biggest benefit is speed and efficiency, which is something both offer in their own way. Python works well on Serverless platforms because it loads very quickly and eliminates prolonged cold starts on AWS Lambdas, for instance, giving as much time as possible for the function to execute.
Scale, likewise, is always important. When you deploy more complex scripts, the cold start time naturally increases. Because Python Lambda still performs better than others, it keeps this increase to a minimum, ensuring the final service still runs as smoothly and reliably as possible. This can be further reduced by opting for more memory per function.
In terms of uses, both Serverless and Python are very flexible options. Together, they are great for web apps, backend services and more. We particularly like using this combination for Big Data systems, which need to be able to handle and process large volumes of data while still being able to pull requests from users.
Serverless Python – Conclusion
Paired together, Python and Serverless technology enable fast solutions that are highly flexible and versatile. In short, this helps companies get the most out of their services, providing cost-effect solutions that scale easily and can be readily implemented within a short time span.
We recommend Serverless Python solutions because they combine the very best of our expertise and allow us to deliver products within a faster time frame, yet still retain the high quality and robust features our clients expect. This is especially true when it comes to Python Lambda functions, which enable fast solutions that don’t require any hardware or support on your end at all.
Business Perspective
If you want something that runs smoothly, can be developed quickly, and operates as efficiently as possible, use a Serverless solution coded in Python. The latter’s quick development speed and readability make the most of the former, providing very effective, flexible solutions as a result.