House all your ML orchestration needs
ML orchestration can be complex and involve heterogeneous workflows. Your orchestration platform should be a backbone for all your ML workflows. Flyte lets you customize and extend workflows however you want with a heavy dose of infrastructure abstraction.
“One of the biggest reasons we picked Flyte was because it is ideologically aligned with what we think all MLOps systems should have: strong lineage guarantees.”
— Jake Neyer, Software Engineer at Striveworks
Model development made easy
Onboarding your ML workflows on an orchestration platform shouldn’t be a struggle. Flyte has out-of-the-box integrations to ease your way into managing them. It supports distributed training using Horovod and Kubeflow operators; data processing with Spark; ML monitoring through whylogs; and more integrations for simplifying model development. Flyte also bridges the gap between data science and low-level infrastructure setup to make model development a breeze.
Break down ML silos
Development of ML models often requires collaboration among teams. It may involve working on different parts of the model training process as a team or managing multiple models simultaneously. A centralized orchestration platform like Flyte enables data and ML engineers to work in isolated environments while still facilitating collaboration. That’s essential to smooth progress with no communication breakdowns.
Build reproducible ML models
ML models often exhibit non-deterministic behavior. Flyte lets you serialize your models and store them on cloud so you can associate them with different versions of your runs. Track the lineage of all your ML experiments and those of your team members, and rerun them as needed for reproducibility.
Features to improve your ML workflow
Map tasks
Parallelize hyperparameter tuning
Intra-task checkpointing
Checkpoint your executions to avoid rerunning them from scratch
Spot or Preemptible instances
Cut costs for model training
GPU acceleration
Schedule your runs on GPUs when needed
Allocate resources dynamically
Mitigate resource overuse and underuse
Recover from failures
Avoid rerunning successful tasks when an execution fails
Enhance your ML workflows. Just the way you need.
A platform for every orchestration use case
Flyte is a versatile solution that can help you address any custom orchestration challenge, not just those related to machine learning.
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Generate biological insights faster by collaborating on a centralized platform.
Learn more🙋 Your Use Case
Build Flyte workflows to effectively address your orchestration challenge.
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