Raam Rosh Hai – Continuous delivery for data science models

Here is the new meta description: "Learn how Raam Rosh Hai enables data scientists and engineers to work together seamlessly, combining expertise to deliver high-performance, scalable, and resilient services with continuous delivery and monitoring."

Key takeaways
  • The concept of “ID” refers to an idea or concept that needs to be turned into a service.
  • Instead of scientists and engineers working on different aspects of a project, they should work together more closely, as separate projects.
  • The “Asaf” platform is designed to help bridge the gap between scientists and engineers by allowing scientists to implement their ideas as services and engineers to focus on deployment and maintenance.
  • The platform uses Docker and Kubernetes to provide continuous delivery of services.
  • The use of message queues (RabbitMQ) allows for asynchronous communication between services.
  • Engineers should focus on deploying and maintaining services, while scientists should focus on creating new services and implementing their ideas.
  • Scientists and engineers should work together to identify and fix bugs, as a single “owner” of the project can cause frustration and delays.
  • Distributed operating systems, such as Kubernetes, make it easier to manage and maintain multiple services.
  • The platform provides observability and monitoring, allowing for easy tracking of service performance.
  • The goal is to make it easy for scientists to implement their ideas as services, and for engineers to deploy and maintain those services.
  • The platform uses Helm charts to simplify the process of deploying and upgrading services.
  • Continuous updates of models can be achieved by using a single library that serves all models.
  • The platform allows for horizontal scaling, making it easy to handle increased traffic.
  • DevOps teams can focus on monitoring and maintenance, rather than tedious tasks such as setting up servers.
  • The platform provides high performance, resilience, and observability out of the box.
  • Engineers should not have to know how to implement models, but rather focus on deploying and maintaining services.
  • The platform allows for easy integration with databases and other tools.
  • By providing a bridge between scientists and engineers, the platform can help reduce the distance between idea and implementation, making the world a better place.