Historically, data warehouses have been painful to manage. The legacy, on-premises systems that worked well for the past 40 years have proved to be expensive and they had many challenges around data freshness, scaling, and high costs. Furthermore, they cannot easily provide AI or real-time capabilities that are needed by modern businesses. We even see […]

As deep learning models become more complex and the size of training datasets keeps increasing, training time has become one of the key bottlenecks in the development and deployment of ML systems. Even if you have access to a GPU, with a large dataset it can take days or weeks for a deep learning model […]

Detection and remediation of security vulnerabilities before they reach deployment is critical in a cloud-native world. This makes scanning for vulnerabilities early and often an important part of continuous integration and delivery (CI/CD) processes. The earlier a problem is detected, the fewer downstream issues will occur. The process of checking for vulnerabilities earlier in development […]

One of the biggest challenges when serving machine learning models is delivering predictions in near real-time. Whether you’re a retailer generating recommendations for users shopping on your site, or a food service company estimating delivery time, being able to serve results with low latency is crucial. That’s why we’re excited to announce Private Endpoints on […]