What is the best way to handle large datasets in CI/CD?
We have massive datasets and our current CI/CD process is hitting a wall trying to pull them for testing. How do large organizations handle this? Do they use data snapshots, synthetic data, or some so...
How should I handle feature drift in an automated deployment pipeline?
We have a stable training pipeline, but our production models start degrading within weeks due to feature drift. Since we are moving toward an agile deployment model, I need a way to integrate drift d...
What is the best way to handle library updates in production?
We are constantly getting blocked by library updates (e.g., PyTorch, Scikit-learn). Upgrading often breaks our training scripts or our production models. In an agile setup, what is the best policy? Sh...
How to test models with synthetic data?
We cannot always get real production data for our testing pipeline because of privacy reasons. Is it common to use synthetic data for unit testing models? How do you ensure the synthetic data is reali...
How to design a feedback loop for continuous model improvement?
The core of agile MLOps seems to be the feedback loop. Once our model is in production, how do we systematically collect user feedback or ground truth to feed back into the training data? I am not loo...
What is the best way to handle batch inference for large models?
We have models that take a long time to run and cannot be served in real-time. We are looking at a batch inference strategy. How do we fit this into an agile pipeline? Does it require different CI/CD ...
How to handle distributed training in an agile pipeline?
Our datasets are getting huge, and single-node training is no longer an option. How do we incorporate distributed training into our automated pipelines without adding massive complexity? Is it better ...
How to automate the data labeling process?
Labeling data is the biggest bottleneck in our process. We want to move towards active learning or some form of weak supervision. How do you integrate these into an agile MLOps system? Does the labeli...
What to look for in an MLOps interview candidate?
I am now the one hiring for our ML team, and I am struggling to find candidates who understand both the data science and the engineering sides. What questions can I ask to see if someone really unders...
What should be included in an MLOps documentation suite?
I am building a new ML pipeline and I want to ensure it stays maintainable for future team members. Beyond the code, what documentation is absolutely mandatory for an agile MLOps system? I am thinking...
