Splunk introduces Splunk AI for enhanced security and observability via generative AI

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Splunk, the leading data analytics and monitoring platform, has unveiled Splunk AI during its recent .conf23 event. This suite of AI-driven solutions aims to enhance the company’s unified security and observability platform, making it easier for organizations to detect and respond to threats while maintaining control over AI implementation.

The centerpiece of Splunk AI is the Splunk AI Assistant, which utilizes generative AI to provide users with an interactive chat experience using natural language. Through this interface, users can create queries using the Splunk Processing Language (SPL) and expand their understanding of the platform.

The AI Assistant is designed to optimize time-to-value and increase accessibility to SPL, democratizing an organization’s access to valuable data insights. It empowers teams such as SecOps, ITOps, and engineering by automating data mining, anomaly detection, and risk assessment. This frees up time for more strategic tasks and reduces errors.

Min Wang, CTO at Splunk, emphasizes that Splunk AI innovations combine automation with human-in-the-loop experiences. The goal is to strengthen human decision-making by increasing speed and effectiveness, rather than replacing it. The AI offerings within Splunk AI surface recommendations based on large amounts of information to enhance and accelerate human decision-making in areas such as detection, investigation, and response.

Splunk AI leverages domain-specific large language models (LLMs) and machine learning (ML) algorithms to improve productivity and cost efficiency. The platform allows organizations to integrate their own AI models or third-party tools, demonstrating Splunk’s commitment to openness and extensibility.

As technology infrastructures become more complex and distributed, and talent shortages persist, organizations need tools that enable swift and efficient action without overwhelming their teams. Splunk AI aims to make the jobs of SecOps, ITOps, and engineering teams easier, allowing them to focus on more strategic work and ensure the resilience of their systems.

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To enhance alerting speed and accuracy, Splunk has introduced several AI-powered capabilities. The app for anomaly detection streamlines and automates the entire operational workflow for anomaly detection. IT Service Intelligence 4.17 service introduces outlier exclusion for adaptive thresholding, which identifies and excludes abnormal data points. ML-assisted thresholding generates dynamic thresholds that mirror the expected workload, reducing false positives and improving alerting accuracy.

The Splunk Machine Learning Toolkit (MLTK) 5.4 provides guided access to ML technology, enabling users of all skill levels to leverage forecasting and predictive analytics. MLTK can be deployed on top of Splunk Enterprise or Cloud platform, extending its capabilities for outlier and anomaly detection, predictive analytics, and clustering.

To further enhance the integration of advanced custom machine learning and deep learning systems, Splunk has introduced the Splunk App for Data Science and Deep Learning (DSDL) 5.1. This offering allows data scientists and machine learning engineers to leverage GPU computing for compute-intensive training tasks and deploy models on CPU or GPU-enabled containers.

Splunk’s AI-powered offerings optimize domain-specific insights derived from real-world experience, ensuring the most effective models tailored to specific use cases. While generative AI tools are valuable for learning curves and generating new insights, deep learning tools are better suited for embedding purpose-built complex anomaly detection algorithms into security offerings.

With Splunk AI, organizations can harness the power of AI to strengthen their security and observability capabilities. By combining automation with human decision-making, Splunk is paving the way for more efficient and effective threat detection, investigation, and response.

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Frequently Asked Questions (FAQs) Related to the Above News

What is Splunk AI?

Splunk AI is a suite of AI-driven solutions introduced by Splunk that aims to enhance the company's unified security and observability platform. It utilizes generative AI to provide users with an interactive chat experience and optimize time-to-value while automating data mining, anomaly detection, and risk assessment.

What is the Splunk AI Assistant?

The Splunk AI Assistant is the centerpiece of Splunk AI. It uses generative AI to provide users with an interactive chat experience using natural language. Users can create queries using the Splunk Processing Language (SPL) and expand their understanding of the platform.

How does the Splunk AI Assistant empower teams?

The Splunk AI Assistant empowers teams such as SecOps, ITOps, and engineering by automating data mining, anomaly detection, and risk assessment. This frees up time for more strategic tasks and reduces errors, optimizing team productivity.

How does Splunk AI enhance human decision-making?

Splunk AI combines automation with human-in-the-loop experiences to strengthen human decision-making. The AI offerings within Splunk AI surface recommendations based on large amounts of information to enhance and accelerate human decision-making in areas such as detection, investigation, and response.

How does Splunk AI leverage AI and machine learning?

Splunk AI leverages domain-specific large language models (LLMs) and machine learning (ML) algorithms to improve productivity and cost efficiency. It allows organizations to integrate their own AI models or third-party tools, demonstrating Splunk's commitment to openness and extensibility.

How does Splunk AI enhance alerting speed and accuracy?

Splunk AI introduces several AI-powered capabilities to enhance alerting speed and accuracy. This includes features like anomaly detection, adaptive thresholding with outlier exclusion, and ML-assisted thresholding to generate dynamic thresholds that reduce false positives and improve alerting accuracy.

What is the role of Splunk Machine Learning Toolkit (MLTK) in Splunk AI?

The Splunk Machine Learning Toolkit (MLTK) provides guided access to ML technology, enabling users of all skill levels to leverage forecasting and predictive analytics. It extends capabilities for outlier and anomaly detection, predictive analytics, and clustering on top of the Splunk Enterprise or Cloud platform.

What is the Splunk App for Data Science and Deep Learning (DSDL)?

The Splunk App for Data Science and Deep Learning (DSDL) allows data scientists and machine learning engineers to leverage GPU computing for compute-intensive training tasks and deploy models on CPU or GPU-enabled containers. It enhances the integration of advanced custom machine learning and deep learning systems.

How does Splunk AI optimize domain-specific insights?

Splunk's AI-powered offerings optimize domain-specific insights derived from real-world experience, ensuring the most effective models tailored to specific use cases. It combines the power of generative AI for learning curves and generating new insights with deep learning tools for embedding complex anomaly detection algorithms into security offerings.

What capabilities does Splunk AI offer for security and observability?

Splunk AI harnesses the power of AI to strengthen security and observability capabilities. It combines automation with human decision-making, paving the way for more efficient and effective threat detection, investigation, and response.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Advait Gupta
Advait Gupta
Advait is our expert writer and manager for the Artificial Intelligence category. His passion for AI research and its advancements drives him to deliver in-depth articles that explore the frontiers of this rapidly evolving field. Advait's articles delve into the latest breakthroughs, trends, and ethical considerations, keeping readers at the forefront of AI knowledge.

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