Close the observability gap with agentic observability

When a critical application fails, the last thing an IT team needs is a debate over who's responsible. Yet in complex enterprise environments, network, application, and compute teams often rely on separate legacy monitoring tools, each providing only part of the picture. Identifying the root cause can become a time-consuming exercise while essential services remain unavailable. As organizations expand their use of AI, hybrid infrastructure, and sovereign cloud environments, the challenge is becoming more pressing. The systems supporting critical services are growing more interconnected, while the need for resilience, operational efficiency, and effective governance continues to increase. AI agents are starting to take on some of that operational load, but an agent reasoning from legacy monitoring data sees the same partial picture the humans do. But are enterprise leaders seeing the same risks as the teams responsible for keeping these systems running? …