Event Streaming, API and Data Integration: 3 Pillars You Should Master On the Cloud

Event Streaming, API, and Data are the three musketeers that cover all the aspects of mastering integration in the cloud.

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Enterprise Application Integration has been one of the most challenging IT landscape topics since the beginning of time. As soon as the number of systems and applications in big corporations started and grows, this becomes an issue we should address. This process’s efficiency will also define what companies succeed and which ones will fail as the cooperation between applications becomes critical to respond at the pace that the business was demanding.

I usually like to use the “road analogy” to define this:

It doesn’t matter if you have the fastest cars if you don’t have proper roads you will not get anywhere

This situation generates a lot of investments from the companies. Also, a lot of vendors and products were launched to support that situation. Some solutions are starting to emerge: EAI, ESB, SOA, Middleware, Distributed Integration Platforms, Cloud-Native solution, and iPaaS.

Each of the approaches provides a solution for existing challenges. As long as the rest of the industry was evolving, the solutions changed to adapt to the new reality (containers, microservices, DevOps, API-led, Event-Driven..)

So, what is the situation today? Today is extended the misconception that integration is the same as API and also that API is asynchronous HTTP based (REST, gRPC, GraphQL) API. But it is much more than this.

Photo by Tolga Ulkan on Unsplash

1.- API

API-led is key to the integration solution for sure, especially focus on the philosophical approach behind it. Each component that we create today is created with a collaboration in mind to work with existing and future components to benefit the business in an easy and agile way. This transcends the protocol discussion completely.

API covers all different kinds of solutions from existing REST API to AsyncAPI to cover the event-based API.

2.- Event Streaming

Asynchronous communication is needed because the patterns and the requirements when you are talking about big enterprises and different applications make this essential. Requirements like pub-sub approach to increase independence among services and apps, control-flow to manage the execution of high-demanding flows that can exceed the throttling for applications, especially when talking about SaaS solutions.

So, you can think that this is a very opinionated view, but at the same time, this is something that most of the providers in this space have realized based on their actions:

  • AWS release SNS/SQS, its first messaging system, as its only solution.
  • Nov 2017 AWS releases Amazon MQ, another queue messaging system to cover the scenarios that SQS cannot cover.
  • May 2019 AWS releases Amazon MSK, a managed service for Kafka solutions to provide streaming data distribution and processing capabilities.

And that situation is because when we move away from smaller applications when we are migrating from a monolith approach to a micro-service application, more patterns and more requirements are needed, and here is. In contrast, integration solutions have shown in the past,t this is critical for integration solutions.

3.- Data Integration

Usually, when we talk about integration, we talk about Enterprise Application Integration because we have this past bias. Even I use this term to cover this topic, EAI, because we usually refer to these solutions. But since the last years, we are more focused on the data distribution amount the company rather than how applications integrated because what is really important is the data they are exchanging and how we can transform this raw data into insights that we can use to know better our customers or optimize our process or discover new opportunities based on that.

Until recently, this part was handled apart from the integration solutions. You probably rely on a focused ETL (Extract-Transform-Load) that helps to move the data from one database to another or a different kind of storage like a Data Warehouse so your Data Scientist can work with them.

But again, agility has made that this needs to change, and all the principles integration has in terms of providing more agility to the business is also applied to how we exchange data. We try to avoid the data’s technical move and try to ease the access and the right organization on this data. Data Virtualization and Data Streaming are the core capabilities that address and handle those challenges providing an optimized solution for how the data is distributed.

Summary

My main expectation with this article is to make you aware that when you are thinking about integrating your application, this is much more than the REST API that you are exposing, maybe using some API Gateway, and the needs can be very different. The strongest your integration platform is, the stronger your business will be.

Alexandre Vazquez: