ScienceLogic, a leader in context-infused Artificial Intelligence for IT Operations (AIOps) and using data to provide IT operations with actionable insights, announced that the analyst firm, Enterprise Management Associates (EMA), has named ScienceLogic as a top vendor in its “EMA Top 3 Decision Guide for Artificial Intelligence (AI) and Machine Learning (ML) for Optimizing DevOps, IT Operations, and Business.” This recognition is the result of end-user research, market analysis, technical product reviews, and expert interviews to provide enterprise customers with guidance to optimally benefit from AI and ML.
EMA recognized ScienceLogic’s SL1 platform, an AIOps automation engine designed to provide comprehensive, business service visibility across the entire application stack. With today’s ephemeral technological landscape, developers spend approximately 25 percent of their time investigating the root cause of application issues that are related to hybrid IT infrastructures.
“The ability to connect to, ingest, contextualize, normalize, distribute and govern comprehensive IT operations data across data centers and clouds is by far the most important success factor in AIOps,”said Torsten Volk, industry analyst at Enterprise Management Associates. “ScienceLogic SL1 received the EMA Top 3 award for exhibiting the application of ML to create training data essential to AIOps. SL1 can ingest data from any source and establish context through advanced topological graphs across all layers of the application stack, which creates the actionable insights necessary to detect anomalies early, optimize predictive maintenance, and identify root causes without the typical ‘alert storms’.”
Key benefits of SL1 identified by EMA include:
- Comprehensive, real-time insights into full-stack IT operations data
- Continuously updated topology maps provide the required context for AI/ML-driven event noise suppression and anomaly detection
- Auto-discovery of almost any infrastructure component within its individual application and service context
- API-accessible, normalized data lake for contextual data analysis through AI/ML solutions or for automatically updating the corporate CMDB
“Alert floods remain the top pain point among Ops teams, which will only continue to grow with more than a third of enterprises using on average four public cloud providers. As service delivery expectations increase, it becomes far more critical for enterprises to manage and automate processes at machine speed, especially as each of those processes takes place in an increasingly complex, multi-cloud environment,” said Dave Link, founder and CEO at ScienceLogic. “This recognition from EMA is a testament that visibility and context around business service health are critical in solving the industry’s most pressing challenges around IT operations by leveraging the power of AI and ML.”
EMA’s report provides guidance to enterprise influencers and decision makers on the types of AI and ML solutions they should invest in to optimize DevOps, data center operations, and business. It also awards recognition to the top three vendors EMA believes should be included in product evaluations.
