The Greatest Benefit of Observability: Prioritizing and Resolving Issues Faster

The need for real-time, reliable data is increasing, and that data is a necessity to remain competitive in today's business landscape. At the same time, observability has become even more critical with the complexity of a hybrid multi-cloud environment.

"In today's complex hybrid multi-cloud environment, CIOs understand that monitoring of logs, metrics, and traces is no longer sufficient," said Will Schoeppner, Research Director covering application performance management and business intelligence at Enterprise Management Associates (EMA), and author of the a new research report, Driving Observability Through Machine Learning and Predictive Analytics. "Organizations require an observability solution that will provide crucial visibility into the health and performance of the environment and enable predictive solutioning and remediation of critical events prior to impacting customer performance."

To add to the challenges and complexity, the term "observability" has not been clearly defined and can be broad in context. Across the industry, a commonality is that the reach of observability extends well beyond simply the collection of logs, metrics, and traces. Unified observability brings infrastructure monitoring, security, logs, application performance monitoring, and SaaS monitoring into a single platform for complete end-to-end visibility for cross-functional teams, driving streamlined collaboration and faster resolution of issues. Based on this definition, EMA's research explores challenges technology teams face in a complex landscape and how the benefits of observability can have an impact on driving business outcomes and customer success.

This study explored the rapid growth of observability and its critical importance in an organization. It also evaluated how observability that provides predictive analytics developed using machine learning models can make the difference in delivering customer expectations, reducing technology resource cost, and eliminating fatigue within an organization's technology teams.

The research delivered several fascinating key findings detailed throughout the report. Some of these key findings are:

■ 73% of companies indicated they have been data-driven in their decision-making process for three years or more.

■ Only 27% of organizations use the same solution for observability across all IT software development functions.

■ 71% of companies indicated they have been mature in the use of analytics and the use of machine learning in observability for three years or more. However, only 54% of organizations believe their maturity in analytics and the use of machine learning in observability is advanced or superior.

According to respondents, the greatest benefit of observability is being able to prioritize and resolve issues faster, followed by being able to proactively detect issues.

The EMA report was sponsored by Elastic.

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The Greatest Benefit of Observability: Prioritizing and Resolving Issues Faster

The need for real-time, reliable data is increasing, and that data is a necessity to remain competitive in today's business landscape. At the same time, observability has become even more critical with the complexity of a hybrid multi-cloud environment.

"In today's complex hybrid multi-cloud environment, CIOs understand that monitoring of logs, metrics, and traces is no longer sufficient," said Will Schoeppner, Research Director covering application performance management and business intelligence at Enterprise Management Associates (EMA), and author of the a new research report, Driving Observability Through Machine Learning and Predictive Analytics. "Organizations require an observability solution that will provide crucial visibility into the health and performance of the environment and enable predictive solutioning and remediation of critical events prior to impacting customer performance."

To add to the challenges and complexity, the term "observability" has not been clearly defined and can be broad in context. Across the industry, a commonality is that the reach of observability extends well beyond simply the collection of logs, metrics, and traces. Unified observability brings infrastructure monitoring, security, logs, application performance monitoring, and SaaS monitoring into a single platform for complete end-to-end visibility for cross-functional teams, driving streamlined collaboration and faster resolution of issues. Based on this definition, EMA's research explores challenges technology teams face in a complex landscape and how the benefits of observability can have an impact on driving business outcomes and customer success.

This study explored the rapid growth of observability and its critical importance in an organization. It also evaluated how observability that provides predictive analytics developed using machine learning models can make the difference in delivering customer expectations, reducing technology resource cost, and eliminating fatigue within an organization's technology teams.

The research delivered several fascinating key findings detailed throughout the report. Some of these key findings are:

■ 73% of companies indicated they have been data-driven in their decision-making process for three years or more.

■ Only 27% of organizations use the same solution for observability across all IT software development functions.

■ 71% of companies indicated they have been mature in the use of analytics and the use of machine learning in observability for three years or more. However, only 54% of organizations believe their maturity in analytics and the use of machine learning in observability is advanced or superior.

According to respondents, the greatest benefit of observability is being able to prioritize and resolve issues faster, followed by being able to proactively detect issues.

The EMA report was sponsored by Elastic.

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Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

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