Good afternoon or good morning everyone. I'm Google B Nation, and I'm thrilled to be here at Con 42 to talk about something close to all our hearts enterprise integrations today. The talk is titled Beyond Rest Exploding Modern A PA, paradigms for Enhanced Enterprise Integration. As integration architects and developers, we know that traditional rest model has served us well, but the digital ecosystem is changing fast and it's time to explore what's next. Let's start with the bigger picture. Over the few last few years, we have seen the shift in how enterprise approach. A PA design and rest is no longer the default. Organizations are exploring graph ql, event driven models, a PA misses, serverless, APAs, and even hypermedia driven designs. Why? Because our integration challenges are getting more complex and rest isn't always the most efficient way to solve the problem. Why? Why move beyond the risk? So what are the pain points? Such slow development with risk complex data often means multiple endpoints, multiple calls, and a lot of developer frustrations. Then there's a data overhead risk. A PA tend to over deliver data leading to inefficiencies, especially for mobile or bandwidth sensitive clients. We also run into breaking changes as systems scale versioning. Rest points become a nightmare, and of course, scaling risk wasn't designed for a high throughput. Event, high end heavy enrollment, and that shows under peak loads. So graph ql, data efficiency breakthrough. Let's talk about the graph ql. It's a major leap forward in how we query the data. Rather than juggling multiple endpoint or getting too much or too little data, GraphQL gives the client control. A single query returns exactly what's needed. Nothing more or nothing less. And the impact is some companies have seen 60 to 70 percentage reduction in the data transfer volume and significantly faster development cycles. It's not just about speed, it's about developer experience and maintainability. So next, let's start with event driven architecture. Now onto the real time needs. Enter the event driven architectures. Instead of pulling or relying on a synchronous call, services publish events when state change occur, these events are streamed and consumed as synchronously. Allowing systems to react in near real time. This is also a loose coupling, which helps to build a build system more scalable and resilient, especially in microservice landscapes. So a PA based, so one big challenge in the modern architecture is EXPLO explosion of point to point integration. That's where a PA mesh comes in. It offers a unified gateway that can route, compose, secure, and cast records across the multiple microservices. Instead of having a individual team built ad hoc integrations, the mes abstract and simplifies architecture. Think of it as an orchestrator and a er. So next, the serverless APIs scale on demand. Now let's talk on scale. So imagine the infrastructure that scales exactly what as you need it and disappears when you don't. So that's the promise of serverless a p. They bring up to 78 percentage cost reduction with cold stats averaging over just three seconds and warm responses as fast as two 50 milliseconds. It's the ultimate pay as you go model for your compute. a enhanced APIs. So we are also seeing a big leap forward with a enhanced APIs. So these APIs use special learning or intent recognition, anomaly detection, and even predictive caching. So the systems start serving. Serving when user will need, not just what you ask for. It's smarter, more active, and even it's. It's the direction many enterprise platforms are heading towards. So hypermedia APIs are self-documenting systems, so unless finally it's not a overlooked hypermedia api. These might seem old school, but the idea about idea of APAs that are self-documenting and guide the client through resource discovery is powerful. The, they reduce breaking changes by 65 percentage occurring to some studies and make client site development much more intuitive. Now let's zoom out. choosing the right a PA paradigm isn't just a technical discussion, it's a strategic. You need to know, you need to look at your business goals, data patterns, consumer expectations, and scalability needs. Know one size fits everything, but the best architecture often blends multiple paradigms to match the specific use cases. So let's discuss the key takeaways here. So if you remember nothing else from this session, let it be this. No single solution fits all. Blend strategies, apps needed, evaluate, trade off. Every model has a pros and cons. Start smile, find a pain Point, implement and learn. Impact. Always try your architecture to outcomes. Thanks so much for joining me. I hope I gave you a first lens to look into integration, not just as a technical hurdle, but as a powerful, driver for business agility and innovation. I am happy to take your questions, to shoot me, if you have any questions, and thank you for giving the opportunity to present this. Thank you so much.