If, as the saying goes, two’s company and three’s a crowd, then, as of today, consider our Disaster Recovery trophy case standing room only. The unfortunate reality of today’s cybersecurity landscape is this: It’s not a matter of when, but if, your organization’s defenses will be tested. Success in these tense moments, when your adrenaline is pumping and time and attention are at a premium, requires more than just the right technology.
Today, we’re excited to announce a new integration with Amazon SageMaker! SageMaker helps companies build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. By leveraging JFrog Artifactory and Amazon SageMaker together, ML models can be delivered alongside all other software development components in a modern DevSecOps workflow, making each model immutable, traceable, secure, and validated as it matures for release.
As applications and their software supply chains become more complex, designing an AppSec program that is agile enough to keep pace, while still providing a clear, enterprise-wide view of risk requires a deep understanding of applications — depth that covers every line of code and package from development all the way to their live, running state.
This week at the World Economic Forum Annual Meeting, SecurityScorecard published the first Cyber Resilience Scorecard, offering leaders and decision-makers a comprehensive and global view of global cyber risk. SecurityScorecard identified a strong correlation between a country’s cyber risk exposure and GDP, which underscores that a nation’s economic prosperity is deeply intertwined with its ability to navigate the complex landscape of cyber threats.