Let’s dial back the clock before we jump into the whole serverless era, which would include Serverless Computing, Database, Storage, an organisation so much more.
Back in 1989, when Tim Berners-Lee, a British scientist, invented the World Wide Web while working with CERN, it had one sole purpose - to meet the demand for automated information-sharing between scientists and institutes the globe.
Tim wrote the first proposal for the World Wide Web in March 1989 and a second in the following year. And with the assistance of Robert Cailliau, this was formalised as a management proposal in November 1990.
By the end of 1990, Tim had the first server and browser up and running at CERN. He developed the code for his Web server on a NeXT computer. To prevent it from being accidentally turned off, the NeXT computer had a hand-written label in red ink,
Rest is history. Developers were on the idea of being limited because of the limitations of a physical server. Instead of trying to be more efficient with creating and designing code, they had to bottleneck themselves a sizable amount of time caring about the server infrastructure.
We got presented with a diverse set of assets, maintenance on a loop. There was no getting around it.
Say it updating servers, repairing hardware, reliable connectivity, over and under-provisioning with the usage and burning a hole in your pocket and so on. And because of all these reasons, you end up spending the majority or handful of your time maintaining servers and looking after them.
In comes the cloud providers with a solution,
It’s a cloud-based service where the cloud providers - AWS, Azure, Google Cloud Platform and others will manage the servers for you. They dynamically allot the compute and storage resources as needed to execute a particular line of code. So, naturally, servers are still part of the circle. Still, the cloud providers’ catering and life support was handled entirely and were not exposed as physical or virtual machines to the developer running the code.
As far as the user is concerned, a serverless back-end would scale and load balance automatically as the application load fluctuates (high or low) while keeping the application up and running seamlessly.
That would ultimately mean that there is a promise made by reducing the development cycles for a business or organization at any levels with a major hold of how operational costs can be controlled.
Such freedom allows developers to build applications without having the trouble of managing or looking after an infrastructure without:
- Clinching to functionality
- Prolonging server uptime
They ultimately allowed the dev team and assets to keep their hands all in driving the transformation in this modern digital era.
Gone are the days when it was known as “cutting-edge tech”. Serverless is being adopted, and it’s getting more mainstream for business which is established already and for those who are just starting out - Serverless is being adopted by devs discovering the ease and cost-effectiveness of adopting serverless computing, especially if you need speeding up and scaling the process.
The Core Serverless Components
Even though it’s architecture at the very roots, the code is designed to work with FaaS and BaaS from third-party vendors.
All these platforms work based on a pay-as-you-use model. Based on the runtime of the use of functions, and charges the customers accordingly.
Even though Faas and BaaS takes up the significant chunk, you’ll need to be aware of the other components too,
The Serverless Framework is a tool wrapped in a programming framework that can be used to deploy cloud functions and serverless applications to cloud service providers like - AWS, Azure, GCP.
Note: There is a substantial difference between frameworks and platforms when it comes to serverless.
There are many serverless frameworks out there which you can dig into in the year 2023. Each of them has various features that offer so much in terms of multi-cloud development, supporting multiple languages, open-source, automated deployment, etc.
When you are creating or designing an application, one of the vital considerations you need to decide is which database to use for your cloud application. Knowing what’s required can significantly help you choose the right database service, which can help you get started with using the tech stack of today.
Advantages of Using a Serverless Database
Cost Efficiency: Buying or stocking a fixed number of servers takes a lot of your time, and for most cases, it results in underutilisation, and it will be far more expensive than using a serverless database.
There are no operating costs when it comes to licensing, maintenance, installations, support or patching. As the “pay-as-you-go” model states, you are only charged properly upon the used time and memory allocation for running your code.
Scalability, Operations and Functionality: With the introduction to serverless, the developers are greeted with saving their time, not to be worried about the autoscaling system or policies like we had already mentioned in the early segment of this blog. Instead, it’s the cloud service provider’s responsibility. This enables a small developer team to run code by themselves with zero hassle, not to be worried about the need to look out for support of infrastructure or engineers.
Drawbacks of Using a Serverless Architecture
Resource and Performance Limitations: Serverless computing may not be suitable for some workloads which might require high-performance, and the reason being cloud providers who impose those resource limits. Another reason is that it would probably be a lot more cost-efficient to bulk-provision the number of servers that you require at any given period.
Debugging and Monitoring: The takeaway here is that environments in which a serverless application is built and run are not often open-source, implying that its performance traits aren’t easy to monitor or replicate in a local environment. But we do have many debugging and monitoring tools that are making giant leaps in the serverless space.
Serverless Use Cases
There are diverse sample size use cases when it comes to serverless based on the characteristics, commonly used practices and further impact made by serverless.
Here are some of the key findings made by Arixv:
- AWS currently dominates the platform for serverless applications (80%). The dominating application domain is web services (33%), with 40% of the analysed workloads being business-critical and at least 55% of them in production already.
- The reduced operation cost of serverless platforms (33%), the reduced operation effort (24%), the scalability (24%), and performance gains (13%) are the main drivers of serverless adoption. In comparison, cost savings seems to be a stronger motivator than performance benefits. At the same time, 58% of use cases have latency requirements, 2% even have real-time demands, while only 36% are latency insensitive. Locality requirements are only relevant for 21% of the total use cases.
- 81% of the analysed use cases exhibit bursty workloads. This highlights the overall trend of serverless workloads to feature unpredictable on-demand workloads, typically triggered through lightweight (<1MB) HTTP requests.
- Although workflows are already sizable (31% of the use cases), most workflows are of simple structure, small, and short-lived. This is likely to change as demand follows natural trends and orchestration methods move toward (cloud-native) workflow engines.
There are many use cases when it comes to Serverless applications. Take a look at how it’s being used across the domains.
This can imply that designing, building, and implementing serverless can be materialised across a wide variety of domains.
Organisations Using Serverless Technology
Whether you are new to the whole idea of going serverless or having already explored the space, let’s take a look at some of the prominent organisations leveraging serverless tech in their gambit.
1. Netflix & AWS Lambda Synergy
Being one of the largest OTT providers, delivering seven billion+ hours of video content to more than 50 million users in 60+ countries per quarter, there’s a demand to be met. It’s being delivered with maximum efficiency, reducing the rate of errors and saving precious time using AWS Lambda to help manage its complex, dynamic infrastructure using event-based triggers.
Lambda is the moderator of handling the massive Netflix library modified in 24 hours to validate their entire content library to make sure they are delivered to their users seamlessly.
Case Study: Netflix and Lambda Case Study
2. Shamrock’s Billion Dollar Serverless Blueprint
Shamrock Trading Corporation is the parent company for a family of brands in transportation services, finance and technology. From fleet software, invoicing systems, financial services, logistics handling, they have many wings for modern digital systems.
All these services are 100% serverless. Shamrock moved their entire business strategy to serverless to reduce their costs and reduce operational scaling risks. They effectively managed to cut their expenses from 30,000 USD to just 3,000 by shifting their Docker app to a serverless workload.
3. IndieHackers’ Revenue Forecasting with Serverless
Known for its ever so popular community forum for the tech industry. They decided to join hands with DataBlade to leverage a serverless web application to interact with an accessible, on-demand standalone implementation of the forecasting model for their business needs. IndieHackers needed to forecast their plan for resource and budget allocations.
Their solution was two-fold, deploying a standalone implementation of the model to be accessible on-demand and creating a web application that can interact with the model, including managing versions, executing runs with different inputs, and downloading results.
Takeaways and Trends in Serverless
Most serverless use cases are already in production, with AWS as the most popular platform and web services being the most common application domain. It would be interesting to see how other players in the market can develop something to tilt the market in their favour to make it a broader playground.
Most cloud functions (67%) are short-running, with running times in the order of milliseconds or seconds, thus requiring serverless frameworks that impose small overheads when running functions in them.
Cost savings (both in terms of infrastructure and operation costs) are a more significant driver for adopting cost than the offered performance and scalability gains.
There are an increasing trend toward ever-larger, ever more complex workflows, indicating the need to move toward (cloud-native) workflow engines.
While a serverless approach may not work for every scenario, it can certainly free up resources and provide greater flexibility in the proper context for years to come.