OpsRamp Winter 2020 Release Announced with OpsQ Recommend Mode
February 25, 2020
Share this

OpsRamp announced OpsQ Recommend Mode, a capability for first-response and incident remediation, as part of the OpsRamp Winter 2020 Release.

OpsQ Recommend Mode lets digital operations teams use predictive analytics to reduce mean-time-to-resolution (MTTR).

Other artificial intelligence for IT operations (AIOps) innovations in the release include visualization of alert similarity patterns and new alert stats widgets to provide transparency into machine learning-driven decisions.

The OpsRamp Winter 2020 Release also introduces 19 new cloud monitoring integrations for Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), along with dynamic topology maps for Azure and GCP. Highlights of the Winter 2020 Release include:

AIOps: OpsQ is OpsRamp’s intelligent event management, alert correlation, and remediation engine. New AIOps capabilities help IT operations teams ingest, analyze, and extract comprehensive insights for real-time event and incident management:

- OpsQ Recommend Mode. The Winter 2020 Release introduces the OpQ Bot and a new Recommend Mode for alert escalation policies so that IT teams can drive faster incident response with auto-suggested actions. OpsQ Recommend Mode lets IT teams stay in control by using explainable and transparent analytical recommendations for first-response and incident creation.

- Visualization of Alert Seasonality Patterns. Many alerts in IT environments recur at a predictable frequency. OpsRamp OpsQ can learn such seasonality patterns and automatically suppress these recurring alerts. With this release, IT teams can visualize seasonality patterns that OpsQ has learned. This visibility helps IT teams understand the auto-suppress decisions that OpsQ makes and trace recurring alert patterns to underlying IT activity.

- Alert Stats Widget. The Alert Stats widget shows the total number of raw events, correlated alerts, inference alerts, auto-ticketed alerts, and auto-suppressed alerts handled by the OpsQ event management engine. This widget shows how OpsRamp OpsQ reduces event volume at each stage so that IT teams can build more confidence in machine learning-based techniques for alert optimization.

Multi-Cloud Monitoring and Management: OpsRamp currently offers 120+ integrations across leading cloud platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). The OpsRamp Winter 2020 Release drives full-stack visibility for multi-cloud workloads with 19 new cloud monitoring integrations as well as dynamic topology maps for Azure and GCP:

- Deeper Cloud Monitoring. OpsRamp adds monitoring support for 4 AWS, 7 Azure, and 8 GCP cloud services:
AWS – Transit Gateway, AppSync, CloudSearch, and DocumentDB
Azure – Application Insights, Traffic Manager, Virtual Network, Route Table, Virtual Machine Scale Sets, SQL Elastic Pool, and Service Bus
GCP – Cloud BigTable, Cloud Composer, Cloud Filestore, Firebase, Cloud Memorystore for Redis, Cloud Run, Cloud TPU, and Cloud Tasks

- Cloud Topology Maps. In addition to AWS cloud topology maps, OpsRamp now offers automated topology discovery and mapping for Azure and GCP. IT teams can apply cloud topology maps to analyze the impact of changes in their multi-cloud environments. Cloud topology is also applied in OpsQ’s event correlation engine to increase the accuracy of machine learning models.

Hybrid Discovery and Synthetic Monitoring: The OpsRamp Winter 2020 Release introduces new platform capabilities for agentless discovery and synthetic monitoring:

- Agentless Discovery and Monitoring for Windows Servers. While OpsRamp offers agentless discovery for Linux and VMware compute, network, and storage resources, the Winter 2020 Release introduces agentless discovery and monitoring for Windows compute resources. Enterprises with remote offices can manage their distributed Windows infrastructure in a secure and frictionless way with agentless monitoring.

- Synthetic Monitoring. OpsRamp’s enhanced synthetic monitoring provides deeper insights and analysis for troubleshooting multi-step transactions. Application owners can break down each synthetic transaction and gain visibility into the performance of each step in a web transaction.

“While machine learning models for IT operations have generated considerable excitement among technology decision-makers, customers would like to understand how a black box model works before ceding control, ” said Bhanu Singh, SVP of Engineering and DevOps at OpsRamp. “The Winter 2020 Release ensures greater transparency of machine learning models for intelligent event and incident management, along with enhanced monitoring capabilities for leading public cloud platforms.”

Share this

The Latest

January 20, 2021

Following up the list of Application Performance Management Predictions, APMdigest also asked IT industry experts for their 2021 cloud predictions. Part 1 covers multicloud and hybrid cloud ...

January 19, 2021
Given the limitations of the existing IT solutions to manage data, enterprises are leveraging AIOps to undertake a host of activities. These include understanding and predicting customer behavior, detecting anomalies and determining their reasons, and offering prescriptive advice. It helps to detect dependencies responsible for creating issues in an IT infrastructure. Also, with AI having features such as containerization, continuous monitoring, predictive or adaptive cloud management, enterprises can gain a next-gen perspective on their business ...
January 14, 2021

Modernization projects using an incremental and continuous improvement model achieve superior results when compared to other project-based approaches including the ripping and replacing of core business applications, according to the CHAOS2020 Report from Micro Focus and Standish Group ...

January 13, 2021

Enterprise IT infrastructure never ceases to evolve, as companies continually re-examine and reimagine the network to incorporate new technology advancements and meet changing business requirements. But network change initiatives can be costly and time-consuming without a proactive approach to ensuring the right data is available to drive your initiatives ...

January 12, 2021

Data can be hard — knowing where to get it, where to store it, and most importantly, how to use it, are all questions enterprises need to answer. For most companies, this is an ongoing process in which multiple factors and challenges have arisen. In the Actian Datacast 2020: Hybrid Data Trends Snapshot, we shed light on the challenges of cloud migration and how organizations are leveraging data ...

January 11, 2021

With the COVID-19 pandemic causing economic disruptions all over the world, business organizations are further pressed to accelerate their migration to the cloud. As recovery begins and enterprises resume operations, experts expect to see increased spending on cloud services ...

January 07, 2021

Following up the list of Application Performance Management Predictions, APMdigest also asked IT industry experts for their 2021 network performance predictions. The results span 5G, NPM, SD-WAN and more ...

January 06, 2021

Gartner highlighted the six trends that infrastructure and operations (I&O) leaders must start preparing for in the next 12-18 months ...

January 05, 2021

As the global pandemic continues, it has become increasingly clear that companies across every industry are planning the "next normal" of their workplace with a much longer-term view. They have moved from serially extending temporary work-from-home (WFH) arrangements to establishing permanent policies focused on empowering people to WFE — work-from-everywhere ...

January 04, 2021

The New Year means it is time for DEVOPSdigest's annual list of DevOps predictions. Industry experts offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2021 ...