The vast majority of technology projects (and other areas) begin with planning and predictable use of the channels, products or services that will be marketed. These estimates are the base parameter for the foundation of the entire architecture, and according to the expected volume, the components are provisioned based on a need, even considering contingency for peak consumption.
It is known that the advancement of cloud infrastructures allows for self-scalability and a very satisfactory elasticity for most scenarios, however, when the human factor enters the variables, it is evidently uncertain the proportion that this volume can take in case of an increase seasonally motivated by an unpredictable cause during project planning.
Behavioral changes in the way of consuming products and/or services have an impact not only on stocks and service availability, but also in the channels that provide these offers.
This change in habits directly impacts the pattern with which companies work with their offers and products, as well as the way they are structured to meet the usual demand. Taking this scenario to the world of technology, we have architectures defined to support a certain type of behavior and load, and a drastic change in this pattern can lead to a breakdown in the excellence of the final customer service.
For instance, a seasonal increase in orders on a company's digital channels (websites and mobile applications), permeate through all architectural layers until it reaches the actual product or service. Once these requests increase in the input channel, there is a long way to go until this interaction is completed, and that means that not only the applications need to be refactored, but also the integration mechanisms that guarantee that the customer will arrive even the product or service that this digital company is offering.
These integrations are represented, in most cases, by APIs, which make the interface between the digital channels and the systems that process the orders of these customers. For all this flow to be supported, it is essential that there are pieces of technological architecture that guarantee the stability and scalability of this solution, and it is in this context that an API management platform enters.
Evidently this is not an innovative and disruptive technology, which was created to stem seasonal demands, this is an already consolidated technology that can contribute a lot in this scenario, if used properly.
And how can you take advantage of such a tool quickly and efficiently to prevent an outage caused by a seasonal increase?
There are some simple measures that can help in the stability and scalability of the services that an API platform supports, such as the use of Rate Limit, which acts as a traffic controller for requests that arrive and leave through a network with integrated applications.
Another important component in an availability and efficiency strategy is the cache, which can considerably reduce the number of requests (repeated and of low volatility) that are processed in the internal systems, before returning the information to the digital channel.
In addition to these preventive components of unwanted behaviors such as falling or sluggish sites and applications, an API platform can also assist in monitoring and alerting potential problems, through analytical data that is worked in real-time and can serve as input for business strategy decision, such as the withdrawal of a product or service that is having a negative impact on the application's behavior, in addition to sending alerts to operations teams before a serious incident occurs.
These and other measures, properly applied in your integration layer, can prevent a breakdown in your internal systems, in addition to sustaining the availability of digital channels that are often the only way to your business. And you, already use these or other practices in your integration layer? Leave a comment!