Serverless framework or serverless architecture represents a way of bypassing a suite of server-related delays or complications, which proves extremely useful for businesses dealing with applications and application development. As a professional serverless development and consultancy brand summarizes, this concept does not eliminate servers, but reorganizes the specific processes so that the developers might not have to think about servers anymore and focus exclusively on coding.
In cloud computing, this innovation represents an improvement in PaaS (Platform-as-a-Service) provision. The most common illustrative example (in fact, a road-opener in serverless) would be AWS Lambda, the game-changer service introduced by Amazon in 2014 – defined as “a compute service that runs code in response to events and automatically manages the compute resources needed to run the code”.
From a developer’s point of view, any code can be uploaded into this system and the AWS Lambda would run it based on internal or external triggers – scaling infinitely and only charging the code author for each active run. The developer just needs to focus on its code, while the Lambda takes care of all functionalities. Further services appeared out of the complex need to orchestrate the AWS Lambda functions and the involved resources, aiming to improve even more the developer-lambda interactions.
What does serverless mean for businesses?
For businesses whose products depend on software developing, serverless applications serve in speeding up the development processes – creating and executing serverless applications represents a new level of progress.
The on-premises server hosting is no longer an issue; virtual servers keep the code, micro service or entire application lodged into the hosting cloud and react via an efficient burst whenever there is a need for running them. The costs are computed only for the running (active) moments, whilst the burden of server hosting is taken away from the internal IT department.
Besides AWS Lambda, API Gateway, Google App Engine Cloud and Google Cloud Functions are other similar services. If curious, check the environment and migration specifications by following the previous hyperlinks.
The serverless trend
Once the servereless option became available, some of the most enthusiastic developers took it to an extreme level, abiding by the credo of never using classic servers again.
The system of backup servers, (all of them maintained just in case one of the active servers goes down or high traffic peaks take place), translates in extra costs, continuous updating and the impossibility of granular scaling down – a sum of overly vast operations when small tasks are concerned. It is basically a waste of resources that exceed the ends.
This HighScalabilty article breaks down the serverless architecture for a practical website situation, illustrating the performable processes, as well as the implied costs when using five layers of dev tools (API Gateway, AWS Lambda, DynamoDb, S3 and Cloudfront).
Since the deployment is reduced to milliseconds and going live takes just a few seconds, it is no wonder that some are mesmerized with these tools and see them as a step forward to the threshold of tomorrow’s IoT world. Although the idea of escaping all server worries may seem vague and insufficiently explainable, this innovating model covers well the scenarios where businesses really do not need permanent on-premises servers in order for their coding needs to be fulfilled seamlessly.
One situation involves infrequent actions that do not justify the costs and the operations deriving from full-time private servers. Another situation involves complexity that requires quick infrastructure scaling and deployment. Both instances are brilliantly handled by external serverless services, leaving the app creation to the developers while the support moves outside the premises.
The serverless framework and IoT
The legend has it that Amazon kept acquiring servers with each outage incident until they realized their fleet of servers is large enough to allow a profitable expansion into what became the Amazon Web Services or AWS plethora.
True as it may be, or just a speculative story, their expansion into the serverless (concept) realm comes in handy at the dawn of the IoT era. IoT means connectivity at an exponential level, layers upon layers of communicating hardware, from the micro to the macro level, and correspondingly interdependent applications and software functions.
The pioneers of this future connected world have to solve, among others, the issue of cost-saving architecture and energy-saving infrastructure. Keeping the tech gear dormant while not in active use would be a solution, one that is available right now, as opposed to cutting-edge scalability in both hardware and software, to futuristic materials with different resilience and energy-consuming characteristics, or to intelligent hardware elements that would know to self-regulate their activities. From macro-technology to microelements, configuring the system to consume resources only when firing up is important and increases efficiency.
A single sensor, as a sleep sensor in this source-example, collects data and inputs it into a framework where it is processed and turned into metrics, analytics, and finally results. The processing part is a task pertaining to an AWS Lambda function, configured by the user in this case. Linking the Lambda function to the API Gateway further structures the process and allows the sensor-collected data to reach its final destination. It would not be sustainable to link the sensor data processing to a traditional always-on, private server-supported framework, since the processing needs to be available at demand, yet not continuously active. Therefore, the serverless solution comes in handy and performs the intermittent tasks whenever needed.
In conclusion the idea of a code enabled to run only when required is another way of implementing scalability, making the event-driven scale accessible to any person or business that needs this type of operation, in exchange for subsecond billing. The process includes granular permissions control, logging and monitoring, rapid deployment, customizable configuration and many other tuning capabilities, according to the specific main functions. You may check this slide share example of a user-tracking application and its integration with AWS Lambda for more IoT backend details.
