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Jan 17, 2020   |  By Polly Traylor
IT spending remains solid, with a nod to Azure, AI, edge. January is the month to plan ahead which often means taking a closer look at budgets. Spiceworks surveyed more than 1,000 technology buyers in companies across North America and Europe, finding that 44% of businesses plan to increase tech spend in 2020, up from 38% in 2019; an equal number (44%) said that spending would stay the same.
Jan 15, 2020   |  By Polly Traylor
Large retailers today have more applications, networks, and systems to monitor than ever before: emerging trends including “extended reality” and robots that help customers find merchandise, keep shelves stocked and fulfill orders faster in warehouses.
Jan 14, 2020   |  By Aaditya Aravamudhan
In December, OpsRamp was at two major industry events: Gartner IT Infrastructure, Operations & Cloud Strategies and AWS re:Invent. The team demonstrated how hybrid cloud management, multi-cloud monitoring, and machine learning can proactively maintain business services, reduce alert floods, and consolidate point tools across a fragmented enterprise IT environment. Here’s a quick snapshot of the other news milestones from December.
Jan 10, 2020   |  By Polly Traylor
The world of IT operations management, DevOps, AIOps, and cloud is always changing. That’s why there’s The OpsRamp Monitor: OpsRamp’s top weekly review of interesting developments and emerging trends in digital operations. Subscribe to our blog for the latest and greatest. And stay on top of everything Ops.
Jan 9, 2020   |  By Jiayi Hoffman
Traditional enterprise application platforms are usually built with Java Enterprise technologies and this is the case as well for OpsRamp. However, in machine learning (ML) world, Python is the most commonly used language, with Java rarely used. To develop ML components within enterprise platforms, such as the AIOps capabilities in OpsRamp, we have to run ML components as Python microservices and they communicate with Java microservices in the platform.
Mar 24, 2019   |  By OpsRamp
Read the eBook to understand why and how IT operations should move forward.
Mar 24, 2019   |  By OpsRamp
Learn how service-centric AIOps can simplify incident management at scale.
Mar 1, 2019   |  By OpsRamp
Learn the 5 requirements to embrace a focus on service intelligence and digital transformation.
Mar 1, 2019   |  By OpsRamp
Learn how to use the right processes and tools to manage risk across project execution, budgets, staffing, and timelines for a cloud migration initiative.
Feb 15, 2019   |  By OpsRamp
Read the 451 Research report to learn how OpsRamp is transforming hybrid operations with service-centric AIOps.
Oct 10, 2019   |  By OpsRamp, Inc
More control. More flexibility. Less chaos. The OpsRamp Fall Release includes enhancements to OpsQ, the OpsRamp artificial intelligence inference engine, that improves event management capabilities and intelligent correlation machine learning models, along with improved multi-cloud monitoring and much more.
Aug 23, 2019   |  By OpsRamp, Inc
Artificial intelligence for IT operations (AIOps), with its promises of smarter automation, data ingestion, and actionable insights, is all the rage in the world of IT infrastructure monitoring and management. But how do you fundamentally implement it in an organization that is simultaneously balancing the demands of legacy, cloud, and hyperconverged digital infrastructure?
Jul 12, 2019   |  By OpsRamp
Artificial intelligence for IT Operations is purpose-built to ingest large sources of data from infrastructure and point tools, and produce actionable insights on root-cause analysis and incident remediation. How do you bring these innovations to an enterprise ecosystem that’s also in the middle of cloud migration and overall digital transformation?
Jul 2, 2019   |  By OpsRamp
Hear Bhanu Singh's presentation at Cloud Expo Santa Clara on how to build a data-driven organization for better operational agility in the face of overwhelming data.
Jun 4, 2019   |  By OpsRamp
The Summer 2019 Release introduces OpsQ Observed Mode to build confidence in machine learning models for IT event and performance analysis. It also includes automated alert suppression to reduce human time spent on first-response to alerts, continuous learning-based alert escalation using live event data, and new infrastructure monitoring capabilities for cloud native environments.