Elastic has announced the launch of Elastic AI Assistant for Observability and general availability of Universal Profiling, providing site reliability engineers (SREs), at all levels of expertise, with context-aware, relevant, and actionable operational insights that are specific to their IT environment.
While Artificial Intelligence for IT operations (AIOps) has helped to translate, streamline, and automate problem resolution, Elastic AI Assistant for Observability powered by the advances of generative AI makes it faster and easier. The AI Assistant does this by leveraging generative AI and proprietary data to deliver context-aware and more accurate remediation for SREs which reduces the learning curve and eliminates the need for manual data chasing across silos.
Powered by the Elasticsearch Relevance Engine (ESRE), the Elastic AI Assistant accelerates time to resolution by democratizing understanding of application errors, log message interpretation, alert analysis, and suggestions for optimal code efficiency.
Additionally, Elastic’s AI Assistant interface improves speed and collaboration across teams by allowing users to interactively chat and visualize all relevant telemetry cohesively in one place while also leveraging proprietary data and runbooks for remediation.
“With the Elastic AI Assistant, SREs can quickly and easily turn what might look like machine gibberish into understandable problems that have actionable steps to resolution,” said Ken Exner, chief product officer, Elastic. “Since the Elastic AI Assistant uses the Elasticsearch Relevance Engine on the user’s unique IT environment and proprietary data sets, the responses it generates are relevant and provide richer and more contextualized insight, helping to elevate the expertise of the entire SRE team as they look to drive problem resolution faster in IT environments that will only grow more complex over time.”
“With the proliferation of disparate data, navigating data-driven decision-making and gaining valuable insights can be a formidable task for Indian enterprises. That's why we're excited to introduce Elastic's AI Assistant for Observability, driven by generative AI and the Elasticsearch Relevance Engine. This innovation is a game changer for organizations as it empowers the everyday user, the site reliability engineers (SREs) to tackle complex IT challenges head-on, providing them with tailored insights and actionable solutions. SREs and operations teams will be transformed from operating in manual siloes and chasing the data to being able to intuitively and interactively talk to the data and understand it for solving problems, ensuring faster and more effective problem resolution in our ever-evolving IT landscape. Elastic is committed to supporting India's digital transformation journey with cutting-edge solutions like the Elastic AI Assistant for Observability," said Neeraj Bhatia, Area Vice President, Elastic India & South Asia.
“The impact and value of generative AI dramatically increases when it has access to an enterprise's proprietary data,” said Torsten Volk, analyst at Enterprise Management Associates. “It’s exciting to see how Elastic’s AI Assistant for Observability may help customers achieve a state where generative AI provides role and situation-specific recommendations, problem resolutions, and suggested efficiency enhancements, all based on the customer’s own data sources. At the same time helping keep that information private from the generic AI model that lives in the public cloud.”
Complex cloud-native environments often create blind spots for SRE teams since many components cannot be instrumented. Instrumentation overhead and deployment complexity of traditional monitoring systems are also limiting factors for modern application teams. To address these challenges, Elastic has launched Universal Profiling, with always-on zero instrumentation and low overhead, to pinpoint performance bottlenecks with visibility into third-party libraries, allowing expedited issue resolution while enabling organizations to reduce cloud costs and track and lower the carbon footprint of their infrastructure.
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