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Sumo Logic Announces Dynamic Observability

Sumo Logic unveiled its Dynamic Observability prototype to define a new approach based entirely on structured and unstructured log analytics.

Dynamic Observability combines Sumo Logic’s log-based source of truth and a multi-agent LLM architecture to build full application operational context, and recommend root causes and resolution solutions for common performance, reliability and security issues. By determining real-time environment status, correlating events and facts, and dynamically building visualizations and instructions to guide troubleshooters, this new observability foundation will power Sumo Logic’s next generation of products.

Sumo Logic customers can now access a new unified interface that provides a comprehensive view of log data and insights across developer, security and IT operations teams. The new interface makes it easier for teams to share queries and dashboards to promote cross-team collaboration. Features like the new browser functionality and intuitive navigation also speed up troubleshooting and issue resolution.

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Cigniti

Industry experts offer predictions on how Cloud, FinOps and related technologies will evolve and impact business in 2025. Part 3 covers FinOps ...

Sumo Logic Announces Dynamic Observability

Sumo Logic unveiled its Dynamic Observability prototype to define a new approach based entirely on structured and unstructured log analytics.

Dynamic Observability combines Sumo Logic’s log-based source of truth and a multi-agent LLM architecture to build full application operational context, and recommend root causes and resolution solutions for common performance, reliability and security issues. By determining real-time environment status, correlating events and facts, and dynamically building visualizations and instructions to guide troubleshooters, this new observability foundation will power Sumo Logic’s next generation of products.

Sumo Logic customers can now access a new unified interface that provides a comprehensive view of log data and insights across developer, security and IT operations teams. The new interface makes it easier for teams to share queries and dashboards to promote cross-team collaboration. Features like the new browser functionality and intuitive navigation also speed up troubleshooting and issue resolution.

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Industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2025. Part 3 covers data technology ...

Industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2025. Part 2 covers DataOps roles, Data Observability, Business Intelligence and Analytics ...

Industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2025 ...

Gartner highlighted the six trends that will have a significant impact on infrastructure and operations (I&O) for 2025 ...

Since IT costs can consume a significant share of revenue ... enterprises should (but often don't) pay close attention to the efficiency of IT operations at scale. Improving operational cost structures even fractionally can yield major savings for larger organizations, often in the tens of millions of dollars ...

Being able to access the full potential of artificial intelligence (AI) and advanced analytics has become a critical differentiator for businesses. These technologies allow for more informed decision-making, boost operational efficiency, enhance security, and reveal valuable insights hidden within massive data sets. Yet, for organizations to truly harness AI's capabilities, they must first tap into an often-overlooked asset: their mainframe data ...

The global IT skills shortage will persist, and perhaps worsen, over the next few years, carrying a collective price tag of more than $5 trillion. Organizations must search for ways to streamline their IT service management (ITSM) workflows in addition to, or even apart from, hiring more staff. Those who don't find alternative methods of ITSM efficiency will be left behind by their competitors ...

Embedding greater levels of deep learning into enterprise systems demands these deep-learning solutions to be "explainable," conveying to business users why it predicted what it predicted. This "explainability" needs to be communicated in an easy-to-understand and transparent manner to gain the comfort and confidence of users, building trust in the teams using these solutions and driving the adoption of a more responsible approach to development ...

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Image
Cigniti

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