LogicMonitor announced the launch of Dexda, an AI solution for Hybrid Observability.
Using machine learning and Natural Language Processing (NLP) to automate insights and deliver a contextualized experience, LogicMonitor's Dexda empowers ITOps teams to effortlessly identify problems, determine the root cause of those problems faster than ever before, and prevent events from exploding into business-critical incidents.
"Being on the bleeding edge of technology requires shifting the organizational mindset from reactive responses to proactive insights, getting comfortable with humans leveraging machines for greater agility and innovation," said Christina Kosmowski, CEO, LogicMonitor. "Our users crave superior anomaly detection, predictive analytics, and intelligent alerting - where we are best in class. Dexda is the latest step in the evolution of our AIOps technologies. Now, we are advancing Generative AI for solving customer challenges, making LogicMonitor even more user-friendly as a co-pilot."
With Dexda, LogicMonitor offers:
- Robust AI capabilities through the application of sophisticated algorithms on historical and real-time data to provide purpose-built, layered intelligence for faster resolutions. LogicMonitor first introduced AI into its platform with its LM Intelligence feature within the LM Envision platform.
- Using AI machine learning, LM Intelligence acts as an "early warning system" for IT and Cloud operations by providing dynamic thresholding, anomaly detection, forecasting and more, empowering teams to reach a significantly lower mean time to resolution (MTTR) and reduce risks to the business.
Dexda ingests events from LM Envision to transform them into contextualized insights. The advanced machine learning techniques automatically correlate data to identify and alert based on time, resources, and pattern disruption. Dexda users can resolve critical issues faster than their competitors with these capabilities:
- Reduced Alert Noise - Advanced machine learning techniques, contextual enrichment capabilities, and deduplication efforts filter through thousands of daily events to produce succinct alerts for the most critical incidents, and drive down MTTR
- ServiceNow Ready – Includes a seamless bi-directional integration with ServiceNow Incident module to fit correlated insights into standard IT workflows. ServiceNow CMDB data automatically enriches Dexda alerts to drive additional context for alert correlations
- Adaptive correlation – Avoid delays in escalating insights to ServiceNow by automatically re-clustering alerts into new insights when a more optimal clustering option is found
- Extensible correlation – Customizable user-defined correlation models target both the alert and enriched CMDB data, based on what makes sense for the business
- MSP Ready – Now supports multi-tenancy with correlations scoped to each tenant
The Latest
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
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 ...