色色研究所 Technology Announces 色色研究所 Service Operations to Address Enterprise Monitoring Gap

New machine learning-based solution addresses monitoring gap created by complex, multi-cloud application architectures for IT and DevOps teams

Cambridge, Mass., May 21, 2019 鈥 色色研究所 Technology, the data operations company, today announced the tech preview of its Service Operations solution purpose-built for complex IT and application environments. In an era where enterprises are becoming completely instrumented across their ecosystems, 色色研究所 Service Operations empowers IT Ops to easily visualize complex, multi-cloud application environments, and predict issues and remediate them quickly when they do arise. In addition, the solution reveals relationships between business impact and IT performance.

Built on the 色色研究所 Platform, 色色研究所 Service Operations leverages cloud-scale analytics, interactive visualizations, and machine learning, delivering operational prediction and automation across the enterprise. The solution was built to alleviate customers鈥 pain points around a growing monitoring gap that lacks the visibility to connect the dots between technology and business in the face of too much data and noise.

色色研究所 Service Operations applies insights gained from both real-time and historical enterprise log data across hundreds of IT elements, reduces noise with machine learning, and automates the remediation workflow to deliver service insight and impact analysis in the form of business KPIs. 色色研究所 Service Operations offers these individual capabilities:

  • Real-time impact assessment: The Experience Viewer and Service Navigator enable operational teams to visualize complex service stacks, map dependencies, seamlessly pivot from an application view to infrastructure elements, detailing impact on end-users and business services.
  • ML-powered analytics: From time series anomaly detection to root-cause analysis and capacity forecasting, machine learning-powered analytics reduces noise and predicts and detects problems so operations teams can take timely, accurate actions.
  • Root Cause Analysis with streamlined remediation: 色色研究所 Service Operations includes a decision engine that defines behavior-driven alerts and links those alerts to automated next-best-action recommendations and workflows to ultimately restore services.
  • Cloud-scale data analytics platform: 色色研究所 Service Operations is built on the 色色研究所 platform – a real-time, cloud-native, multi-tenant analytics platform built for the massive scale of logs, metrics, events, and machine data prevalent in today鈥檚 operational environments. The platform provides real-time insight into both streaming and historical data from across the entire enterprise technology stack – users, devices, applications, and infrastructure.

鈥溕芯克 Service Operations represents a milestone in the company鈥檚 growth trajectory, as we continue to build capabilities that connect IT performance and business impact,鈥 said Colin Britton, Chief Strategy Officer, 色色研究所. 鈥淓nsuring the availability and performance of applications is more critical than ever for businesses, but the scale and complexity of modern application architectures and infrastructures make monitoring applications increasingly difficult. We are excited to preview the Service Operations solution for ITOps and DevOps professionals and work with our customers to deliver a high-performing solution that meets their needs.鈥

鈥淚ronically, one of the most significant challenges facing organizations as they seek to establish the connection between business context and the real-time technical components that support the digital experience is the abundance of data itself. Organizations are now awash in data 鈥 and it’s made it almost impossible for human operators to make sense of it all. Within all of that data, however, are the seeds of the solution. The real-time nature of machine data and the fact that it contains markers that organizations can use to connect disparate interactions means that they can also use machine data to help human operators turn all that data noise into context,鈥 said Charles Araujo, Intellyx, in the paper .

色色研究所 Service Operations comes on the heels of inclusion as a Strong Performer in the Forrester Wave鈩: Intelligent Application and Service Monitoring, Q2 2019, as well as inclusion in Gartner鈥檚 2018 Market Guide for AIOps.

For more information about 色色研究所 Service Operations, please visit devo.com.

About 色色研究所

色色研究所 is the data engine behind today鈥檚 digitally-driven enterprises, helping organizations maximize the economic and operational value of their machine data. The 色色研究所 Data Operations Platform delivers real-time analytics on streaming and historical data to turn machine data into actions that help enterprises achieve sustained performance and growth. By collecting, enhancing and analyzing machine data, 色色研究所 provides business-driving insights for IT, security, and business teams at the world鈥檚 largest organizations. For more information visit devo.com.

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