Google Trends for #APIs, #MicroServices & #ServerLess
Serverless, Microservices, and APIs are amongst the hottest technology trends in cloud computing. In this article, we briefly explain what they all represent and discuss their history over time. It is quite interesting to monitor what those buzzwords actually mean for engineering, business, and engineers in general.
In the context of computer programming, an application programming interface which is more widely known as API is a list of underlying definitions, protocols, and the tools which are used for building an application software. A little less technical definition of API would be that it is the defined rules methods by which various components of the software communicates with each other. The quality of a good API will be the provision of all building block for the development of applications, the building blocks are then put together by the programmer. APIs serves various domains it can be for a web-based system, an operating system, a database system, a computer hardware, or a software library. There are many forms an API specification can take, but the most used specifications are for, the data structures, object classes the variables and remote calls. To facilitate smooth usage of API Documentation is usually provided.
Consider using an application on your smartphone, the application sends data to a server by means of an internet connection. The data is retrieved by the server, the server then interprets the data and perform the required necessary functions after which it sends the modified data back to your phone. The data is then again interpreted by the mobile application you are using and presented to you in an understandable way. All the list of function is the definition of an API, this is how API functions.
Microservice architecture simply referred to as microservices, is a well-defined protocol for developing a various software system, it has gained immense popularity in the recent years. There isn’t much known about microservices and a less is known about how the software’s are developed. Nevertheless, it still enjoys the place of being the most preferred software developing tool for many developers. This is due to the scalability microservices offer. This scalable and tailored method is considered the best choice when enabling support for multiple platforms and devices is required, the list includes spanning web, mobile, Internet of Things, and wearables. This tool serves you well even when you are uncertain about the devices you’ll need to support the backdrop of a clouded future.
Microservices cannot be placed into the stencil of one limited definition, but it does possess several distinct characteristics which can help us in the identification of the style. Essentially, microservice architecture is a generalized method that is followed for developing software applications in the context of independently deployable, small in range modular services. In this in each service has the responsibility of running process and communicating through a predefined strategy to achieve a common business goal.
Serverless architectures are the application designs that work with the mediation of third party service providers that includes “Backend as a Service” or BaaS services, or it includes some code generated managed, ephemeral packages on a Functions as a Service or a FaaS platform. By using the mentioned ideas, along with other ideas like single-page applications. These software architectures remove the need for a constant server component. Serverless architectures significantly low the running and operational costs, the complexity associated with operation as well as the and engineering lead time. All these services with an increased reliance on vendor dependencies and the new immature supporting services.
Serverless is increasingly becoming the hot topic in the world of software architecture. The renowned cloud vendors namely Amazon, Google, and Microsoft are investing in serverless in abundance. Not only them there is a flux of book, almanacs, open-source projects, conferences, and various independent software vendors are carrying out massive research on the subject
Graphical Analysis utiling Google Trends:
Google Trends has been around subtly for a long time. It gives you trends based on time or region for a specific item. A time slot can be defined for a specific activity and the ups, downs shifts in the interest can be studies. This also works in site-specific studying; the region can be limited to a country city a particular locality.
This graph shows the shift in the trends of the 3 main software architectures APIs, Microservices, and Serverless. Y-axis of the graph represents the rate of interest; the values have been placed in multiples of 5. The X-axis on the other hand displays time stretched between the span of 2013 to 2018. A bar graph based on this line graph has also been generated where the relative interest of the three topics under the study is clearly depicted.
The region at this specific case is worldwide; which means this graph is representing the development of interest in APIs, Serverless and Microservices in the whole world for 3 year time period starting from June 2013 to May 2018.
Moving on to the shifts and peaks of the interest first high peak is recorded for summer of 2013 i.e. the month of June and July. This peak is followed by episodes of ups and downs until the month of November where a major low peak is recorded for the month of December where APIs touched the value of 40, microservices stays 0 and serverless shows the value which exist somewhere lower than one.
For the year 2014 same trend can be seen where the highest peak can be seen for the month of June while December showing the lowest level of interest. This year the lowest value remained a bit higher when compared to the year 2013. The subsequent year is the depiction of a similar trend where the interest bolsters up in summer and declines in the month of December. Here an anomaly can be seen where APIs shows an extremely low peak whereas the other two services maintain consistency.
Most of the graph the 3 factors under consideration show peaks in accordance with each other which tells us that similar factors determine their interest. There are several exceptions also where one factor achieves a high and the other two does not. The highest peak is recorded in the whole chart for the month of March and year 2017 where API achieves the staggering of 100 points. All the three services went lowest coherently for the month of December and the year 2017 making the year 2017 the most unpredictable of all years.