Top Trends in Observability: The 2025 Forecast is Here

We just launched the fifth annual Observability Forecast, a report based on a survey of 1,700 engineering and IT leaders worldwide. This report explores the capabilities, business outcomes, and operational challenges that will define success in the upcoming era of technology.

The Rise of Intelligent Observability and AI 

The tech world is on the brink of another major shift as AI becomes embedded in everything we do. This new era demands a move from basic monitoring to Intelligent Observability. This means preparing for a massive expansion of software where anyone—from experienced engineers to non-IT domain experts—can build and deploy applications quickly. The scale and complexity of what's coming will be unprecedented, and traditional observability won't be enough. Observability itself will need to be usable for everyone.

Our survey results show that the adoption of AI monitoring capabilities grew from 42% in 2024 to 54% in 2025. This double-digit growth pushes AI monitoring into the majority of organizations for the first time. Organizations are moving beyond simple experimentation with AI and are deploying it in live, customer-facing environments. This shift is fueling a demand for deeper observability, as organizations need real-time insight into how complex, distributed systems behave and interact to avoid hidden failures.

AI-powered observability platforms are becoming essential. This is because probabilistic AI models depend on dynamic, distributed environments and can fail in ways that are opaque to traditional monitoring. For organizations adopting AI at scale, a deeper level of system insight is needed, one that goes beyond just tracing code or monitoring infrastructure. In some cases, this requires deploying AI to monitor AI. The report found that the adoption of AI technologies was the top driver of observability demand, cited by 45% of executive leaders.

Leaders also identified the most impactful AI capabilities for improving incident response. The top three were:

• AI-assisted troubleshooting (38%)
• Automatic root cause analysis (RCA) (33%)
• Predictive analytics (32%)

These capabilities help teams diagnose and prevent issues before they impact users. By detecting issues earlier and automating responses, AI can reduce downtime and speed up recovery. This allows teams to shift from reacting to outages to resolving problems proactively.

The Tangible Business Value of Observability

The report clearly shows that observability delivers real business impact. High-impact outages carry a median cost of $2 million USD per hour, or about $33,333 USD per minute. For organizations with full-stack observability (FSO), this median cost drops to $1 million per hour.

Observability directly improves system stability and availability. The survey revealed that 75% of businesses report a positive return on their observability investments. Nearly one in five (18%) say they are realizing a 3-10x return on investment. For businesses, the top benefits of observability are:

• Reduced unplanned downtime (55% of leaders)
• Improved overall operational efficiency (50%)
• Reduced security risk (46%)

Engineering Efficiency

Observability also improves engineering productivity and satisfaction by reducing the time engineers spend on reactive tasks. Engineers spend 33% of their time on "firefighting" or addressing disruptions. When you add in the 33% spent on maintenance and technical debt, more than two-thirds of an engineer's time is spent on tasks other than developing new features or coding innovations.

For practitioners (SREs, IT, DevOps), the top benefits of observability are:

• Reduced alert fatigue (59%)
• Faster troubleshooting and root cause analysis (58%)
• Improved collaboration across teams (52%)

Streamlined observability workflows, especially with AI assistance, allow engineers to quickly pinpoint issues, which reduces cognitive load and frustration. This frees up teams to focus on building new features and innovating, which contributes to higher job satisfaction and lower turnover.

Challenges and Solutions: Full-Stack Observability and Tool Consolidation 

Despite the benefits, many organizations struggle to achieve true full-stack observability (FSO). A staggering 73% of organizations surveyed lack FSO, leaving large parts of their tech stack without comprehensive monitoring. This gap exposes them to both operational and financial risks. FSO is defined as having visibility across five key categories: infrastructure, applications and services, security monitoring, digital experience monitoring, and log management.

The main challenges to achieving full-stack observability are:

• Complex technology stacks (cited by 36% of leaders)
• Too many monitoring tools or siloed data (cited by 29%)

These issues often go hand-in-hand, as new services and frameworks introduce more telemetry that ends up scattered across disconnected tools. This fragmented view of system health forces engineers to switch between dashboards to piece together incident narratives, while valuable data remains hidden. Inconsistent telemetry also limits the effectiveness of AI-driven capabilities.

The good news is that organizations are actively addressing this issue. The average number of observability tools per organization has declined by 27% over two years, from 6 to 4.4. This trend reflects a recognition that too many tools create problems like fragmented data, higher overhead, and slower incident response.

A majority of organizations (52%) plan to consolidate their observability tools onto unified platforms in the next 12-24 months. This highlights a strong industry trend away from point solutions and toward unified platforms that provide a single, holistic view of system health.

Strategic Imperatives for 2025 and Beyond 🚀

Based on the survey findings, three clear strategic imperatives emerge for IT and data leaders:

1. Prioritize unified platforms with one view of system health. This addresses tool sprawl and provides comprehensive insights.
2. Cultivate an observability-driven culture. This makes reliability a shared responsibility.
3. Embrace AI for proactive operations. This moves teams from a reactive to a predictive stance, preventing issues before they occur.

The future of observability is about predictive action, AI, and resilience. As AI applications become central to business, a unified observability approach is non-negotiable for this new era. 

To truly prepare your business for the next wave of innovation, download the full 2025 Observability Forecast.