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ScienceLogic Acquires Zebrium

ScienceLogic has acquired machine learning analytics firm Zebrium to automatically find the root cause of complex, modern (i.e., containerized, cloud-native) application problems.

This partnership drastically reduces the time it takes to identify, diagnose and resolve business-service impacting issues, lowering IT costs and delivering superior customer and employee experiences.

With this acquisition, ScienceLogic is combining its AIOps capabilities with the root-cause analysis (RCA) technology of Zebrium to provide enterprises with the ability to comprehensively understand their IT estate, from endpoint devices to SaaS and cloud environments. The solution provides powerful machine learning analytics that draw on both real-time and historical data for a contextual understanding of the service impact and root cause when issues arise so they can be automatically remediated.

“We understand that at the end of the day, customers care about a few core things. Among those are making sense of drastically increased amounts of data, maintaining a quick time to resolution, and focusing on customer experience,” says Mike Nappi, CPO at ScienceLogic. “Our acquisition of Zebrium has its genesis in those customer mandates and stems from years of conversations with partners and clients to understand where the gaps are and how ScienceLogic can help fill them. Combining our capabilities with that of Zebrium creates a whole new level of analytics-driven insights and automation we can bring to bear for our customers.”

What does this mean for IT operations? Drastically reduced hours and resources spent trying to determine what is a potential problem, configuring systems to alert on those problems, and when they occur, combing through large volumes of logs from the application and infrastructure stack to determine the root cause – leaving IT teams the time and capacity to devote to revenue-generating activities.

“This partnership means that ITOps and DevOps teams will have the breathing room to commit time, energy, and resources to improving and supporting infrastructure and analytics standards, all while cutting IT costs,” said Ajay Singh, CEO at Zebrium. “With our machine learning capabilities combined with ScienceLogic’s service context and automation, organizations can greatly reduce the time they spend identifying and remediating issues – leaving them more time to spend on operations that deliver stellar digital experiences for customers and employees alike.”

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ScienceLogic Acquires Zebrium

ScienceLogic has acquired machine learning analytics firm Zebrium to automatically find the root cause of complex, modern (i.e., containerized, cloud-native) application problems.

This partnership drastically reduces the time it takes to identify, diagnose and resolve business-service impacting issues, lowering IT costs and delivering superior customer and employee experiences.

With this acquisition, ScienceLogic is combining its AIOps capabilities with the root-cause analysis (RCA) technology of Zebrium to provide enterprises with the ability to comprehensively understand their IT estate, from endpoint devices to SaaS and cloud environments. The solution provides powerful machine learning analytics that draw on both real-time and historical data for a contextual understanding of the service impact and root cause when issues arise so they can be automatically remediated.

“We understand that at the end of the day, customers care about a few core things. Among those are making sense of drastically increased amounts of data, maintaining a quick time to resolution, and focusing on customer experience,” says Mike Nappi, CPO at ScienceLogic. “Our acquisition of Zebrium has its genesis in those customer mandates and stems from years of conversations with partners and clients to understand where the gaps are and how ScienceLogic can help fill them. Combining our capabilities with that of Zebrium creates a whole new level of analytics-driven insights and automation we can bring to bear for our customers.”

What does this mean for IT operations? Drastically reduced hours and resources spent trying to determine what is a potential problem, configuring systems to alert on those problems, and when they occur, combing through large volumes of logs from the application and infrastructure stack to determine the root cause – leaving IT teams the time and capacity to devote to revenue-generating activities.

“This partnership means that ITOps and DevOps teams will have the breathing room to commit time, energy, and resources to improving and supporting infrastructure and analytics standards, all while cutting IT costs,” said Ajay Singh, CEO at Zebrium. “With our machine learning capabilities combined with ScienceLogic’s service context and automation, organizations can greatly reduce the time they spend identifying and remediating issues – leaving them more time to spend on operations that deliver stellar digital experiences for customers and employees alike.”

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AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...