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Omkar Dusane
Omkar Dusane

Posted on Originally published at dev.to

Spotting an architectural paradigm Pioneered by temporal - Durable workflows

I have been noticing something manifesting a massive architectural emergence in software engineering called Durable Execution (or "Code-First Workflows"). It started gaining traction in 2018-19 when I was looking for a declarative workflow writing framework and landed on Apache Cadence, by Maxim Fateev being used at Uber. Talked to Maxim back then and realized I would have to build a full Node.js SDK from scratch to use it, so I took a different path, but kept checking on it. When Uber split Cadence into open-source (similar to how Kafka detached from LinkedIn), I was fascinated by the architecture and kept finding new use cases. By 2022, I was evaluating and adopting Temporal for real production-scale projects, and I personally enjoyed modeling payment and invoicing workflows with it. Recently through 2024 to early 2026, I have been seeing another major use case emerge around evaluation loops and agentic execution. Modeling long-running tasks into discrete pieces remains a fascinating challenge, and how you approach that modeling is the key differentiator between shooting yourself in the foot or seeing immense simplification and benefits.

I will cover why certain engineering organizations rejected Temporal and how those evaluations played out in a separate post. For now, the core takeaway is clear: durable execution has officially crossed over from specialized infrastructure into a standard developer primitive.

This evolution reminds me a lot of how Apache Kafka transformed data pipelines. Just as Kafka became the undisputed open-source standard for event streaming after leaving LinkedIn, I am watching closely to see if Temporal achieves that similar ubiquitous, foundational fate for orchestration. Modern serverless platforms like Inngest are pushing this paradigm even further into everyday web applications, but at its core, the heavy lifting of durable state management traces right back to this fundamental engine.

Whether Temporal becomes the industry-wide default or remains part of a broader ecosystem alongside lighter abstractions, durable execution is here to stay. In upcoming posts, I will dive into real-world production use cases and practical workflow modeling from architecting payment engines to designing resilient AI evaluation loops.

Cheers!!

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