Transforming Cloud Security Through AI and Data Fabric

Daniel Deeney, CEO and co-founder of Paladin Cloud, joins John Richards to explore how artificial intelligence is revolutionizing cloud security. With extensive experience as an enterprise software CEO and venture capitalist, Deeney brings unique insights from his successful track record of building and scaling cybersecurity companies. After his previous company's acquisition by VMware in 2019, he launched Paladin Cloud to address the growing challenges of managing security across multiple cloud environments.

The episode delves deep into the concept of data fabric and its crucial role in modern cybersecurity. Richards and Deeney discuss how organizations struggle with tool proliferation and data overload in cloud security. They explore how Paladin Cloud's innovative approach uses data fabric to unify risk assessment across various security tools while leveraging generative AI for enhanced threat intelligence. The conversation highlights practical solutions for teams dealing with overwhelming security alerts and the challenge of prioritizing threats effectively.

Questions we answer in this episode:

• How can organizations handle the overwhelming amount of security data from multiple tools?
• What role does generative AI play in modern cloud security?
• How can teams better prioritize security risks across different environments?

Key Takeaways:

• Data fabric technology enables unified risk assessment across multiple security tools
• AI-powered risk scoring helps teams prioritize threats more effectively
• Security teams need both technological solutions and services support to manage modern threats

This episode offers invaluable insights for security professionals, DevOps teams, and technology leaders grappling with cloud security challenges. Whether you're dealing with alert fatigue, struggling to prioritize security risks, or looking to understand how AI can enhance your security operations, this discussion provides practical guidance and strategic perspectives on navigating the complex landscape of modern cloud security.

Links & Notes

• Learn more about Paladin Cloud
• Got a question? Ask us here!

• (00:00) - Welcome to Cyber Sentries
• (01:05) - Meet Daniel Deeney
• (01:25) - Starting Paladin Cloud
• (02:53) - The Approach
• (04:54) - Data Fabric Layer
• (09:39) - Addressing Pain Points
• (15:54) - Bringing Data Together and Normalizing
• (18:52) - Users
• (20:37) - Other Models
• (26:02) - Prioritization
• (29:19) - Customer Service
• (31:16) - Wrap Up

Diving into the Rise of On-Prem AI and Cloud Security

In this episode of Cyber Sentries, host John Richards is joined by Doron Caspin, a Senior Manager of Product Management at Red Hat, and Christopher Nuland, a Technical Marketing Manager at Red Hat. They explore the growing trend of on-premise open source models for running AI and the unique benefits and challenges that come with it. The conversation also touches on how DeepSeek has challenged the big players and validated the value of smaller agentic models.

John, Doron, and Christopher dive into the shifting landscape of AI and cloud security. They discuss the trends Red Hat is seeing in the industry, such as the move towards smaller, domain-specific language models and the importance of securing AI workloads in hybrid cloud environments. The guests share insights on the key considerations organizations face when deciding to run AI models on-premises, including compliance requirements and the need to treat AI models with the same level of security as databases.

Questions we answer in this episode:

• What are the benefits and challenges of running AI on-premises?
• How can organizations secure their AI workloads in hybrid cloud environments?
• What impact has DeepSeek had on the AI industry?

Key Takeaways:

• On-prem AI offers unique advantages for industries with strict compliance requirements
• Treating AI models like databases is crucial for ensuring robust security
• The future of AI is likely to be open source, with smaller, domain-specific models gaining traction

This episode is a must-listen for anyone interested in the intersection of AI and cloud security. John, Doron, and Christopher provide valuable insights and practical advice for organizations navigating this rapidly evolving landscape. Whether you're a security professional, data engineer, or business leader, you'll come away with a deeper understanding of the trends shaping the future of AI and the steps you can take to secure your AI workloads.

Links & Notes

• Try Red Hat Advanced Cluster Security Cloud Service
• Red Hat Advanced Cluster Security for Kubernetes
• Training an AI to Conquer Double Dragon: Reinforcement Learning Demo
• Learn more about Paladin Cloud
• Got a question? Ask us here!

• (00:00) - Welcome to Cyber Sentries
• (00:31) - Red Hat
• (01:04) - Meet Christopher and Doron
• (05:26) - Past to Present
• (07:54) - Trends in the Approach
• (12:24) - The Security Side
• (16:15) - Key Considerations
• (19:26) - Training and Models
• (22:33) - Iterations and Shifts
• (25:36) - Importance of Security Foundations
• (28:35) - Security in Agent Space
• (30:00) - Wrap Up

Navigating AI Adoption: From Exploration to Implementation

In this illuminating episode of Cyber Sentries, John Richards sits down with Jim Wilt, distinguished chief architect at Weave and veteran security practitioner. With decades of experience in emerging technologies since the mainframe era, Jim brings unique insights into how organizations can successfully integrate AI while maintaining robust security practices.

The conversation delves deep into a three-phase approach for AI adoption: learning, growing, and landing. Jim emphasizes the importance of experimentation before commitment, challenging the common rush to define use cases before understanding the technology's capabilities. He shares practical examples of how organizations can progress from internal testing to external deployment, while maintaining security at each stage. The discussion explores how AI isn't about replacement but enhancement - whether for individual roles or organizational processes - and why adaptability in implementation is crucial for success.

Questions we answer in this episode:

• How should organizations approach their initial AI adoption?
• What's the optimal timeline for moving from experimentation to implementation?
• When and how should security measures be integrated into AI initiatives?

Key Takeaways:

• "Replaceable architecture" is becoming more critical than "reusable architecture" in the AI era
• Organizations need 9-18 months of internal testing before external AI deployment
• Security measures should scale up gradually, from minimal during learning to comprehensive in production

This episode provides invaluable guidance for any organization navigating AI adoption. Jim's practical, experience-based insights cut through the hype, offering a clear roadmap for sustainable AI integration while maintaining security integrity. Whether you're just starting your AI journey or looking to refine your existing approach, this discussion offers actionable strategies for success.

Links & Notes

• ‘What Air Canada Lost In ‘Remarkable’ Lying AI Chatbot Case’
• CIO.com: From risk to reward: Mastering the art of adopting emerging technologies
• Generative AI (GenAI) – A Primer
• GenAI and the Human Experience
• Replaceable is the New Reusable
• Applied AI
• Connect with Jim on LinkedIn
• Learn more about Paladin Cloud
• Got a question? Ask us here!

• (00:04) - Welcome to Cyber Sentries
• (00:55) - Meet Jim Wilt
• (01:46) - Jim’s Background
• (03:59) - Where to Start
• (13:28) - Public vs. Private Models
• (17:52) - Time in Growth Period
• (18:48) - Use Cases
• (21:57) - Transitioning to External Use
• (29:06) - Scaling from Personal to Organizational
• (31:52) - Safeguarding
• (37:21) - Flexibility
• (38:34) - Wrap Up