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Docker and Kubernetes for Data Science
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#datascience #kubernetes #docker
Docker is the most popular container environment and kubernetes platform for orchestrating containers. There are 3 major areas where Docker and Kubernetes can help accelerate data science initiatives
1.Infrastructure
2.Tooling and Reproducible
3.Deployment and Scaling
Benefits for Data Science project include
- Efficient usage of infrastructure
- Bring in parity between development and production
- Manage multiple versions of tools efficiently
- Seamless scaling to meet business demand
- Ease of migration of models to production
- Zero downtime deployment
Docker is the most popular container environment and kubernetes platform for orchestrating containers. There are 3 major areas where Docker and Kubernetes can help accelerate data science initiatives
1.Infrastructure
2.Tooling and Reproducible
3.Deployment and Scaling
Benefits for Data Science project include
- Efficient usage of infrastructure
- Bring in parity between development and production
- Manage multiple versions of tools efficiently
- Seamless scaling to meet business demand
- Ease of migration of models to production
- Zero downtime deployment
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