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Introducing model_poller, a sidecar container for tensorflow/serving.

Home Page: https://hub.docker.com/r/popszer/model_poller

License: MIT License

Python 77.87% Dockerfile 19.48% Shell 2.66%
docker google-cloud-platform publish-subscribe sidecar-container tensorflow-serving

sidecar-pattern_tf-serving's Introduction

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Machine Learning Engineer & Technical Leader

๐Ÿ›  Core Competencies:

  • Machine Learning Workflow Design & Optimization
    • Natural Language Processing (NLP) & Computer Vision (CV)
    • Model training, deployment & monitoring - PyTorch, LabelStudio, MLFlow, DVC
  • Distributed Data Processing & Scalable Architectures (docker, docker-compose, kubernetes)
  • Cloud Computing (Scaleway, AWS, GCP)
  • Full-Stack Development
    • Backend (Python, FastAPI, gRPC)
    • Frontend (Vanilla JS/HTML, React)

๐Ÿ“š Education: Centrale Nantes - Master of Science: Signal Processing & Statistics.

๐Ÿ—‚ Professional Journey:

  • ML Engineer & Eng. manager @ French DoD
  • Freelance ML Engineer
  • ML Engineer @ Schneider Electric, Boston, MA
  • Data Engineer @ Kpler, Paris

๐Ÿ” Learning: Currently looking at Robotics, Evolutionary Computing & Metaheuristics, Conflict-free Replicated Data Types (CRDTs)

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Tech Stack ๐Ÿ› ๏ธ

My favorite tool is the one that's right for the job at hand. Still, I've developed a particular affinity for some.

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Connect ๐Ÿ”—

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Credits

Banner designed using the github profile header generator, octocat shaped with the myOctocat creator.

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sidecar-pattern_tf-serving's Issues

Isn't model polling already a part of TF Serving?

I was reading through the documentation of the TF Serving architecture explicitly. It mentions that utilities for polling a file-system are made available out of the box.

New Sources could support new filesystems, cloud offerings and algorithm backends. TensorFlow Serving provides some common building blocks to make it easy & fast to create new sources. For example, TensorFlow Serving includes a utility to wrap polling behavior around a simple source. Sources are closely related to Loaders for specific algorithms and data hosting servables.

Did you try using these instead of Pub/Sub?

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