Operations | Monitoring | ITSM | DevOps | Cloud

The Zero Trust model has fundamentally shifted how organizations secure their applications and infrastructure. Instead of assuming anything inside your network is safe, the Zero Trust security model requires continuous verification of every identity, every device, and every access request across the entire trust model, forcing users and devices to prove that they can access what they are trying to access.

AI’s Operational Complexity Crisis is Real The AI revolution is transforming how we build and operate software, but it’s also creating a perfect storm of operational challenges that are keeping engineering teams up at night.

Managing the cost of foundation models is a critical challenge as AI adoption surges, particularly for teams using powerful models like Anthropic's Claude Opus and Claude Sonnet. Growing teams generate larger prompt volumes and escalating model complexity, making it difficult to have clear visibility, accountability, and control of cloud AI spending.

Automation has transformed incident response within individual teams. Diagnostic scripts, runbooks, and alert systems help engineers troubleshoot and resolve issues more efficiently. Translating those gains across the organization remains a challenge. Most automations are built in silos and not designed to work together. The result: disconnected workflows, inconsistent outcomes, and too much manual effort, leaving teams with less time for the strategic work that drives innovation and resilience.

If your organization is anything like ours, then you’ve probably embraced using large language models like Claude. Just last week, we gave all Honeycomb employees access to Claude. Now, developers can generate AI-assisted code, product managers can perform analysis on customer usage trends, marketers can test messaging, sales can do customer discovery and we are shipping AI-powered features to improve user experience.