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DZone.com Feed Recent posts on DZone.com Building Your API Gateway From OpenAPI Specs: A Spec-Driven Approach Jul 3rd 2026, 15:00 by sahil arora Generating an API Gateway From OpenAPI Specs Five Key Takeaways When your OpenAPI specification becomes the single source of truth, the gap between your API contract and your gateway configuration simply stops existing. Generating the gateway from the spec scales far better than hand-maintaining per-endpoint configuration as your API surface grows into the hundreds. Generated, human-readable service code keeps day-to-day operations manageable — you can read it, reason about it, and trace failures like ordinary software. The genuinely hard part is not the generation; it's the regeneration workflow and the discipline around where custom logic is allowed to live. Adopt the model on new APIs first, prove it's boring and trustworthy, and only then migrate existing ones. The Quiet Way Gateways Rot Every public API gateway I've worked with started its life clean and, over a few years, quietly accumulated a second universe of hand-written configuration sitting alongside the services it fronts. None of it looked dangerous at the time. A path rewrite here. A parameter rename there. A response transform to make an internal field look the way customers expect it to. A content-type translation to bridge two teams that made different choices years apart. Each individual edit was sensible, small, and well-intentioned. The danger was never any single change — it was the accumulation, and more importantly, the separation. That configuration described how the gateway should behave, but it lived in a different place from the thing it was describing: the API's actual contract. Two artifacts, two repositories, two owners, two review processes, two release cadences — all trying to stay in agreement about the same set of endpoints. Anyone who has run a system like this knows how that story ends. The two drift apart. A backend team renames a field and ships their service. The matching gateway mapping doesn't get updated because it's someone else's pull request in someone else's repo. Nothing fails loudly. A customer-facing response is simply, silently wrong. And the place you now have to go and debug is the gateway — the one component that every single request flows through, and therefore the one component nobody wants to touch under pressure. ‍ OBO SSO in Java Applications: Securely Calling Downstream APIs on Behalf of a User Jul 3rd 2026, 14:00 by Muhammed Harris Kodavath Modern enterprise applications rarely operate in isolation. A user may authenticate through a web or mobile application, invoke a Java-based backend API, and that backend may need to call additional downstream services such as microservices or third-party APIs. In these scenarios, simply using the application's identity is often insufficient. The downstream service may need to know which user initiated the request and enforce authorization based on that user's permissions. This is where the OAuth 2.0 On-Behalf-Of (OBO) flow becomes invaluable. ‍ Building an AI Agent That Responds to Real-Time Events With AWS Bedrock, Kinesis, DynamoDB, and S3 Jul 3rd 2026, 13:00 by Jubin Abhishek Soni Most recommendation systems are batch jobs. They crunch last night's data, write a recommendations table, and serve it all day. That works fine until your user watches three thriller movies in a row at 9 pm and your system is still recommending rom-coms because the batch hasn't run yet. In this post, I'll walk through building an agent system that reacts to streaming user behavior in real time using: ‍ The Software Deployment Failures That Pass Every Pre-Deployment Check Jul 3rd 2026, 12:00 by Sancharini Panda A deployment can pass every gate in a pipeline and still be wrong. This sounds like a contradiction until you look closely at what pre-deployment checks actually verify. Unit tests confirm that individual functions behave as the developer who wrote them intended. Integration tests confirm that components interact the way they were specified to interact. Smoke tests confirm that the application starts and responds. Every one of these checks can pass cleanly while the deployment still introduces a failure that none of them were ever positioned to catch. The failures that slip through this way share a specific characteristic worth naming directly: they are not failures of the code that was just changed. They are failures in how that code now interacts with something else in the system that was not part of the deployment at all. ‍ ‍ You are receiving this email because you subscribed to this feed at blogtrottr.com. By using Blogtrottr, you agree to our terms. If you no longer wish to receive these emails, you can unsubscribe from this feed, edit this subscription, or manage all your subscriptions.