Microservice architecture allows for rapid, frequent and reliable delivery of advanced applications. With microservices, an application is structured as a collection of services that are self-contained (versioning, maintenance and testing in one place), independently deployable, scalable and reusable.

By breaking down a skill into its component services and then breaking those down into their component steps, you get sets of pliable, infinitely customizable microservices. Within an intelligent ecosystem, microservices can be pulled from anywhere in the shared library, modified, sequenced, and deployed, creating new automations as well as new microservices that can be continually iterated on, resequenced, and redeployed.

In terms of defining the shape of our ecosystem, microservices map to flows. These flows of sequenced microservices make up the services and skills that an intelligent digital worker (a bot) utilizes. 

Orchestrating hyperautomation requires an open system

• A state of hyperautomation within an organization is achieved when a collection of advanced technologies are sequenced in intelligent ways to create intelligent automations of business processes.
• These innovations, algorithms, and systems that get sewn together suggest that you have a much better chance of achieving general intelligence, or perceived general intelligence, by having access to everybody’s tools. It won’t happen inside some closed system where the tools have to be supplied exclusively by Google or IBM.
• As you can imagine, this distributed development and deployment of microservices gives your entire organization a massive boost.
• You can also create multiple applications/skills concurrently, meaning more developers working on the same app, at the same time, resulting in less time spent in development.

The benefits of microservices can include:

• Ready faster—Since development cycles are shortened, the microservices architecture supports more agile deployment and updates.
• Highly scalable—As demand for certain services grows, you can sequence and deploy microservices across multiple servers and infrastructures to meet your needs.
• Resilient—When constructed properly, independent microservices don’t impact one another. This means that if one piece fails, the whole IDW doesn’t go down.
• Easy to deploy—Because your microservice-based apps are modular and smaller than monolithic apps, the worries that come with traditional deployment are negated. Microservices require more coordination, but the payoffs can be huge.
• Fast and accessible—Because the larger app is broken down into smaller pieces, developers can more easily understand, update, and enhance those pieces, resulting in faster development cycles—especially when combined with agile development methodologies. This also makes it easier to get distributed teams working together.
• Reusability—Microservices can be sequenced in different ways with different sets of other microservices to create new skills and services. They can also be tweaked within existing sequences to produce different outcomes.
• More open—The use of polyglot APIs gives developers the freedom to choose the best language and technology for the necessary function.

Unique challenges that come with microservices architecture

Creating and managing an ecosystem of intelligent digital workers can be an extremely complex undertaking. By making sure you’ve got these bases covered you can focus on enabling non-developers to orchestrate conversational and non-conversational advanced technology quickly and easily.

Prepare for the unique challenges that come with microservices architecture to consider:

• Building—As you organize flows, it’s important to identify dependencies between your services. Be aware that changing one microservice might affect other microservices due to dependencies. You also need to consider the effects that microservices have on your data, and how changes to your data to suit one microservice might affect other microservices that rely on the same data.
• Testing—Integration and end-to-end testing are very important. Depending on how you’ve architected your services and flows to support one another, a failure in one part of the architecture could cause something a few
• Versioning—When you update to new versions, keep in mind that you might break things if there’s no backward compatibility. You can build in conditional logic to handle this, but that can get unwieldy and nasty fast if not managed properly. You can also stand up multiple live versions using different flows, but that can be more complex to maintain and manage.
• Logging—With a distributed system, you need centralized logs to bring everything together. Otherwise, the scale is impossible to manage. A centralized view of the system allows you to pinpoint problems. GSX does much of this for you, but you’ll have to manage occurrences beyond built-in events, errors, and warnings.
• Debugging—When it comes to errors reported through user interaction, it can be difficult to pinpoint the microservice that failed if no error or warning log is reported. Automating simple applications like chatbots, RPAs, or IVRs is relatively easy, but when you take it to the level where you introduce context, memory, and intelligence, identifying bugs beyond errors or warnings can get very complicated.