Good observability drives productivity for developer and ops teams

A new report from Splunk looks at the role of observability within today's increasingly complex IT environments.

Based on a survey of 1,850 ITOps and developer professionals, it finds enterprises with good observability resolve issues faster, boost developer productivity, control costs and improve customer satisfaction. Due to such benefits, 86 percent of all respondents plan to increase their observability investments.

The report outlines a new maturity framework that consists of four stages of observability sophistication: foundational visibility; guided insights; proactive response and unified workflows. Based on this framework, respondents were placed into one of four stages of observability maturity: 'Beginning' organizations (45 percent); 'Emerging' organizations (27 percent); 'Evolving' organizations (17 percent); and lastly, 'Leading' organizations (11 percent).

The results show that 68 percent of leading organizations say they're aware of application problems within minutes or seconds of an outage -- 2.8 times faster than the rate of beginning organizations. Leading organizations estimate 80 percent of alerts are legitimate, in contrast to 54 percent from beginning organizations, providing greater certainty and reducing time spent on resolving false alarms.

"Building a leading observability practice means being obsessed with delivering incredible digital experiences to your customers, and embedding that mindset into every decision," says Patrick Lin, senior vice president and general manager, observability at Splunk. "Our report shows this mindset pays off. Leaders not only achieve greater success in mitigating downtime, they also see greater developer innovation and speed."

The report also finds 76 percent of leaders deploy the majority of their application code on demand, in contrast to 30 percent of beginners. In addition, developers in leading organizations spend 38 percent more of their time on innovation than beginning organizations, which means less time spent on toilsome work like troubleshooting and triaging incidents. It's clear that for leading organizations, increased developer productivity and output drive profitability.

Nearly all survey respondents (97 percent) use AI and/or ML-powered systems to enhance their observability operations -- a significant jump from 66 percent of respondents surveyed last year. Through AI and ML's abilities to analyze and process large volumes of data to detect anomalies, identify root causes, recommend actions and automate tasks, teams get the insight they need more rapidly.

Good observability has an effect when it comes to dealing with alerts too, 57 percent of respondents agree the volume of alerts they receive is problematic. Leaders experience far less alert noise, with 85 percent remediating half or more of their alerts due to recommendations from AI/ML. In contrast, only 16 percent of beginning organizations say the same. 65 percent of leaders also use on AIOps to pinpoint and remediate the root cause of incidents with greater
intelligence and automation.

The full report is available from the Splunk site.

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