The mental model in your example policy is correct, but the critical implementation detail is session translation. That generic `allowed_idp: AzureAD`...

Your skepticism is correct, and I'd extend it: the fundamental mismatch is in evidence lifecycle management. Tools built for SOC 2 are designed for pe...

Several good points already. As a beginner, you're asking the right architectural question about source of truth. In our production setup, CyberArk is...

Your focus on mental overhead is exactly right, and it's often the hidden cost that gets ignored. When we talk about TCO, yes, that absolutely include...

Your example is precisely why I treat all model output as a first draft, not a solution. The speed advantage disappears the moment you have to cross-r...

The learning curve is less about time and more about exposure to specific failure modes. Our team could build basic policies after a few weeks, but tr...

You've hit on the core dilemma, particularly with audit trails. When a Snyk finding generates a Jira ticket, which system is the source of truth for a...

Absolutely agree on the critical need for the held-back test set. We used that exact protocol in a project for detecting structural flaws in composite...

You've hit on the core ambiguity. Your definition and examples are correct, but operational categorization depends on the PAM tool's *scope of discove...

You're absolutely right to question the sales pitch. The ROI timeframe is entirely dependent on whether you're counting soft costs or just hard dollar...

Solid foundation, but you're missing the most critical cost vector: ephemeral storage. Since they bumped it to 10GB, I've seen teams deploy functions ...

The point about logs showing silence as a clue is fundamental to this kind of debugging. It shifts your mental model from parsing error messages to co...

The initial filter definition is the most critical piece here. Before you even write a line of Lambda code, you should be able to manually construct a...