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We’re excited to unveil lakeFS 1.59.0, a release that brings a completely revamped user interface designed to make your data versioning experience more intuitive, elegant,
- Oz Katz
Today’s organizations don’t just use a single data storage solution – they operate across on-prem servers, multiple cloud providers, and hybrid environments. This distributed approach
- Tal Sofer
Supercharging Machine Learning Machine learning (ML) is essential in driving critical business decisions and innovation across various industries. To maintain competitive advantages, organizations continually refine
- Barak Amar
One of the capabilities of lakeFS is that you can use it to create isolated environments for experimentation or development. Let’s say we want to
- Oz Katz
Reproducibility is a fundamental challenge in building reliable machine learning (ML) models and AI applications. It’s not just about debugging a model when it fails
- Oz Katz
Introduction Role-Based Access Control (RBAC) is an effective way to minimize the risk of data breaches by ensuring users only have access to the data
- Amit Kesarwani
The General Data Protection Regulation (GDPR) imposes strict requirements on how organizations collect, store, and manage personal data. Businesses must ensure data security, auditability, and
- Iddo Avneri
As a user of lakeFS, you probably started by using its web interface. But as an object store, lakeFS is also a server that uses
- Ariel Shaqed (Scolnicov)
AI projects require not only advanced algorithms but also robust infrastructure to manage datasets, ensure reproducibility, and streamline deployments. By combining lakeFS, the Git-like version
- Iddo Avneri
What is lakeFS Enterprise? lakeFS Enterprise is a commercially-supported version of lakeFS, offering additional features and functionalities that meet the needs of organizations from a
- Amit Kesarwani
In the landscape of ML and AI, metadata is essential for building accurate, trustworthy models. By providing context around data, metadata supports efficient data discovery,
- Tal Sofer
When working with large datasets stored in object stores (such as Amazon S3, Google Cloud Storage, Azure Blob Storage on the cloud, or MinIO or
- Iddo Avneri
