Tackle Root Cause Analysis Easier than Ever Before with Skylar Automated RCA

Tackle Root Cause Analysis Easier than Ever Before with Skylar Automated RCA

When service outages happen, the clock starts ticking, not only to restore that service, but also to identify and fix the root cause so the problem doesn’t recur again and again. However, root cause analysis (RCA) can be exceptionally time-consuming for IT teams tasked with combing through massive log files for clues about the underlying problem. Especially when this hunt for root causes relies on excessively manual processes, organizations find themselves wasting both time and money, with the average cost of unplanned downtime falling around $9,000 (or more) per minute.   

However, automation and unsupervised AI are delivering a new normal, one that can now automatically ingest and run machine learning (ML) log analysis across millions of messages from log files across applications to do the heavy lifting RCA requires. Enter: Skylar Automated RCA.  

Leveraging AI to Overcome Key Barriers to Rapid RCA 

Today, the process of uncovering root causes for an IT issue or outage is often hindered by not only the surplus of data and logs to sift through, but also by fragmented insights and limited visibility. While uncovering the root cause and restoring services are critical to maintaining operations, IT teams must also understand exactly what went wrong at the most granular level of an organization’s IT systems and processes in order to effectively resolve it. Achieving this level of understanding is virtually impossible at the scale of a typical enterprise if support teams take a manual approach to problem resolution.  

Fortunately, organizations can now turbocharge their RCA with Skylar Automated RCA – the first of three solutions to be released as part of ScienceLogic’s new suite of advanced AI capabilities, SkylarÔ AI, (which will soon include advanced analytics and an AI advisor). Skylar Automated RCA quickly diagnoses problems, including unknown or novel issues, by analyzing logs in real-time using unsupervised AI coupled with machine learning (ML) algorithms to analyze unlabeled data. 

Skylar Automated RCA delivers insights that help IT teams dramatically accelerate troubleshooting and take proactive steps to avoid future incidents. The process involves real-time analysis of application and environment logs to quickly identify incident details – showing key log lines, plain language summaries, and recommended actions that can save hours, or even days, of manual effort.   

A Closer Look at Capabilities 

Security Operations Center (SOC) teams and incident managers taking a closer look at Skylar Automated RCA’s capabilities will see how the difference is in the details when it comes to understanding its power to accelerate and simplify RCA. Skylar Automated RCA significantly accelerates the diagnostic process, leveraging ML to rapidly sift through hundreds of logs to determine root cause; and because these ML processes are unsupervised, no manual training is required. The AI solution also leverages GenAI to automatically create and deliver problem summary and recommendations in plain language, drastically reducing the time to understand what is actually broken and empowering lower level engineers to act.  

Furthermore, Skylar Automated RCA can proactively uncover new problems without the need for teams to manually build complex rules or scroll through log data. By identifying unusual or novel issues and associated root causes – even when monitoring tools don’t know what to look for – Skylar Automated RCA can then contextualize and correlate that unusual behavior with any recent changes and performance metrics that would indicate potential business or service impacts. 

The Skylar Automated RCA solution is highly intuitive for teams who would otherwise spend hours or days sifting through nuances in log vocabulary and scrutinizing syntax. Because no two logs are alike, looking through logs can be like deciphering a foreign language – even for experienced engineers. Now these experts can leverage Skylar Automated RCA to distill billions of log lines down to the few most critical artifacts that indicate root cause; visualize the most important log keywords that describe the root cause; and generate human-centric GenAI summaries and recommendations that clarify what’s wrong and how to fix it.   

Skylar Automated RCA’s Place in the Larger ScienceLogic Ecosystem 

Skylar Automated RCA is tremendously powerful on its own, but the benefits are multiplied when the solution is situated within the larger ScienceLogic ecosystem. And, the debut of Skylar Automated RCA is just the first of several powerful offerings ScienceLogic is bringing to market as part of the unified Skylar AI suite of advanced capabilities.  

The suite will also feature Skylar Advisor, an AI advisor that delivers persona-based, curated guidance to optimize IT operations and proactively avoid issues; and Skylar Analytics, a proactive analytics platform with advanced AI/ML analytics paired with deep data exploration and visualization tools that facilitate advanced reporting and custom analytics.  

More broadly, the ScienceLogic AI Platform for IT infrastructure management further enhances Skylar Automated RCA’s operation by accelerating creation, enrichment, and routing of service desk tickets for faster resolution; automatically notifying stakeholders of incidents; and facilitating more proactive analytics and auto-remediation capabilities across even the most complex hybrid cloud environments.  

All of this is welcome news to anyone on an IT team who was ever tasked with the manual toil and limited results of traditional RCA tools and methodologies. Learn more about how Skylar Automated RCA can modernize the whole process for transformative gains in the enterprise.