The Next Movement to Follow Microservices
Pivotal sponsored this podcast.
If technology affects everyone, shouldn’t technology be for everyone? By everyone? The architecture of distributed systems becomes increasingly complex. And big data, artificial intelligence and machine learning all make things more complicated. Yet we witness a continued pushback to allow more people — even non-IT trained — to be able to access the potential of technology and even create it.
This isn’t just driven by a technological change. More interestingly, it’s a cultural change. And a drive to find a common language so that all key stakeholders can understand the intent behind any digital resource.
At KubeCon+CloudNativeCon last month, The New Stack founder and publisher Alex Williams sat down with Pivotal’s senior vice president James Watters and Pivotal’s global chief technology officer of data-intensive software Sina Sojoodi. They take you on the historical journey from our origins of service-oriented architecture and Waterfall program management through to the microservices architecture, event-driven design and agile practices of today. And they begin to look toward the dependency-oriented and data-centric tomorrow.
The Next Movement To Follow Microservices
Watters said that, as we move from our Infrastructure-as-a-Service world toward a dependency-oriented world, we are switching our focus to how we think about all the data moving through our systems. We are searching for a common architecture to give us more agility and more composability in how we deliver applications.
This has led to trends like event-driven architecture and steam processing, which creates a common language across verticals and allows for data to be more programmable.
Also Listen: Gwen Shapira on the Power of Event-Driven Architecture
The retail space with its logical pathway for events is often used as the example for event-driven architecture. There’s simple logic behind the user behavior that goes from searching, to selecting, to the shopping cart, to the payment model. Each of these services broadcasts out its change of state and the other services respond with a change when appropriate. What Sojoodi points out is that it goes beyond that online store to supply chain management and brick-and-mortar stores. Even the click-and-pickup that most stores have these days creates an incredible complexity.
Event-first approaches unravel some of that entanglement. Build your business state as you’re receiving the immutable events in time — continuously as opposed to request-based. This also enables the reusability that was so lacking with SOA.
But this complexity will only increase with the Internet of Things and everything that is producing hyper-scaled big data.
Sojoodi and Watters talk about how Pivotal-backed Spring Boot — an open source, Java-based framework to create microservices — allows complex architecture to be accessible to any developer. This contrasts with tooling that was popular not that long ago like the Hadoop big data tool that frankly required a Ph.D. to leverage. With Boot, anyone can write a stream process and publish it — instead of having to continually ask the centralized data team for permission all the time.
If there’s one trend that continues, it’s the push for continuous improvement of collaboration. No one’s predicting communication silos being rebuilt and custodial roles being reestablished any time soon.
