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Quick takeaways
- Go was chosen as the programming language for the ML pipeline project due to its simplicity, reliability, and support for building distributed microservices.
- The team implemented a wait strategy for service dependencies using the 'wait for it' Go package and contributed back to its repository.
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Overview of the podcast episode
This podcast episode discusses a specific project developed by members of the Go community at Intel, focusing on their ML pipeline healthcare solution microservices. The project involved building an ML pipeline for image processing and automated image comparisons in healthcare use cases, utilizing microservices and containerization. The hosts interviewed Samantha Coyle and Anita Elizabeth Simon, who shared insights on the challenges they faced and the decision to use Go as the programming language of choice. They also discussed the wait strategy for their services and the open-source package they incorporated into the project. Overall, the episode highlights the importance of open-source contributions and the benefits of using Go for developing scalable, distributed systems.
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highlights
Listen to the best highlights from the podcasts you love and dive into the full episode