Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet.
“As AI and distributed architectures become foundational, reliability can’t stop at the application layer,” said Dritan Suljoti, Catchpoint CTO at LogicMonitor. “The data shows teams are grappling with complexity across the Internet stack, and that’s exactly where modern observability and Internet Performance Monitoring must evolve to keep pace.”
Key findings from the report include:
Slow is the new down, and now the default expectation
Nearly two-thirds of respondents say performance degradations are as serious as outages, reinforcing speed and experience as core reliability outcomes.
Reliability is felt by users, but rarely measured by the business
Only 26% consistently measure whether performance improvements affect business metrics such as revenue or NPS, revealing a persistent gap between what users feel and what organizations track.
AI optimism is surging, while confidence in observing AI lags
60% of respondents express optimism about AI in SRE, and more than half plan to deploy agentic AI systems in production within the next 12 months. While this represents more than double the confidence reported last year, teams report low confidence in monitoring AI reliability, underscoring the need for observability across internal systems and external dependencies.
Toil remains high, even as AI adoption grows
Median toil is 34% of engineers’ time. While 49% report AI has reduced toil, others report no change or increased burden, showing uneven outcomes between leadership expectations and frontline realities.
Resilience maturity remains uneven
Only 17% run chaos or resilience experiments regularly in production, and nearly half report low tolerance for planned failure, pointing to a widening divide between proactive resilience teams and reactive teams.
Learning has become a reliability risk factor
Despite broad agreement that learning matters, just 6% report protected learning time, and most spend only 3–4 hours per month on upskilling, raising concerns about knowledge decay as systems become more AI-driven and Internet-dependent.
As organizations accelerate cloud adoption, distribute architectures across regions and providers, and introduce AI systems into production, the report underscores a pivotal reality: reliability is increasingly a trust and reputation metric, not just an engineering scorecard. The organizations that treat reliability as a shared business language, and instrument it accordingly, will be better positioned to scale AI, protect digital experiences, and sustain customer trust.
Methodology: The 2026 SRE Report is based on insights gathered from the annual SRE Survey, which was open for six weeks during July and August 2025. The survey received 418 responses from professionals across the globe, representing a wide range of roles and levels of managerial responsibility within reliability engineering. Respondents were primarily located in North America (68%), followed by Europe (14%) and Asia (13%). Company sizes varied, with 34% of respondents working at organizations with 1,001–10,000 employees and 19% at companies with 10,001–100,000 employees. This diversity ensures that the report captures a broad and comprehensive perspective on the state of site reliability engineering practices worldwide.