OpenAI’s ChatGPT recently experienced a major global outage, leaving users unable to access the platform across both web and mobile interfaces. A significant number of users in Asia-Pacific were affected, with around 80% of reporters citing access issues. Specific complaints included messages like “Request is not allowed. Please try again later,” and “Bad Gateway,” suggesting server or gateway-level disruptions. The incident sparked widespread frustration as users relying on ChatGPT for professional and personal tasks found their workflows halted. Despite the widespread reports, OpenAI’s official status page continued to indicate that all systems were operational, further compounding confusion.

This event underscores the critical role of full-stack observability in modern digital operations. True observability, such as using NIKSUN’s end-to-end platform, involves the continuous, real-time collection and correlation of diverse data types - packets, network flows, SNMP, logs, metrics, and telemetry - to form a unified view of system health and performance. By consolidating these inputs, teams can move beyond siloed monitoring tools to detect early anomalies, map service dependencies, and correlate symptoms with root causes faster. When ingested and analyzed together, these data sources enable smarter alerting, faster incident resolution, and proactive capacity or configuration management.

In high-stakes environments - especially those delivering AI services at global scale - this level of observability is not optional. It ensures that outages are not just detected, but understood and mitigated quickly. Observability also feeds into continuous improvement cycles, helping identify architectural weaknesses or bottlenecks before they become service-impacting. Ultimately, by investing in deep, consolidated observability across layers 2 to 7, organizations build resilience, reduce MTTR (mean time to resolution), and deliver more reliable digital experiences. Read more about this story on our LinkedIn page