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OpsRamp Announces Spring 2021 Release

OpsRamp announced the OpsRamp Spring 2021 Release, providing self-service onboarding for faster migration to the public cloud, powerful and customizable dashboards for visualization of hybrid infrastructure performance, and Prometheus metrics ingestion for using homegrown monitoring data within the OpsRamp platform.

OpsRamp’s latest release helps cloud operators achieve faster time-to-value and greater return on investment for their cloud modernization initiatives.

The OpsRamp Spring 2021 Release also introduces new monitoring integrations for Microsoft Azure and Cisco HyperFlex along with enhanced platform navigation for easy access to key product capabilities.

Highlights of the OpsRamp Spring 2021 Release include:

- Rapid Onboarding. OpsRamp’s hybrid cloud wizard delivers a self-contained guide for discovering and monitoring multi-cloud and cloud native infrastructure. Once IT teams provide their cloud infrastructure details, OpsRamp auto-monitoring onboards cloud resources and displays performance metrics within minutes. The platform currently supports auto-monitoring for Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) cloud services along with Kubernetes distributions such as OpenShift and K3s as well as popular Linux distributions.

- Cloud Native Metrics Observability. Kubernetes admins can now ingest Prometheus metrics into OpsRamp for holistic visibility and faster troubleshooting across cloud native infrastructure. Our pull-based mechanism for scraping Prometheus metrics across Kubernetes clusters ensures faster visualization, data federation, and long-term retention of Prometheus insights.

- Data-Driven Insights for Hybrid IT Management. OpsRamp’s new dashboarding model allows cloud operators to visualize any data with a flexible querying framework. Dashboards 2.0 are customizable widgets powered by Prometheus Query Language (PromQL) with the ability to import/export dashboards and customize color palettes and fonts along with out-of-the-box support for a growing number of cloud services.

- Flexible and Centralized Alerting. New alert definition models offer greater flexibility for setting alerts along with streamlined mechanisms to alert on metric data collected by OpsRamp. CloudOps teams can centrally set thresholds to generate alerts for auto-monitored resources and then use relevant insights to keep their IT services up and running.

- Comprehensive Cloud Monitoring. OpsRamp currently offers more than 160 monitoring integrations across leading public cloud providers such as AWS, Azure, and GCP. The OpsRamp Spring 2021 Release offers expanded coverage for Microsoft Azure with metrics support for Blob Storage, Table Storage, File Storage, BatchAI Workspaces, BlockChain, Databox Edge, Logic Integration Service Environment, and Kusto Clusters.

- HyperConverged Infrastructure Monitoring. OpsRamp can not only discover and monitor Cisco HyperFlex components such as cluster nodes, hosts, datastores, and virtual machines but also ingest HyperFlex events into the OpsRamp AIOps platform for faster root cause diagnostics. The platform also supports the discovery and monitoring of physical components of Dell EMC VxRail appliances along with ingestion of VxRail software and hardware events.

“CloudOps teams are shackled by legacy IT operations tools that were never designed to handle the dynamic and ephemeral nature of public cloud infrastructure,” said Ciaran Byrne, VP of Product Management at OpsRamp. “OpsRamp’s digital operations management platform enables faster discovery and monitoring of production workloads across multi-cloud environments along with data-driven insights for managing the health and performance of a distributed infrastructure ecosystem.”

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

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When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

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Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

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In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

OpsRamp Announces Spring 2021 Release

OpsRamp announced the OpsRamp Spring 2021 Release, providing self-service onboarding for faster migration to the public cloud, powerful and customizable dashboards for visualization of hybrid infrastructure performance, and Prometheus metrics ingestion for using homegrown monitoring data within the OpsRamp platform.

OpsRamp’s latest release helps cloud operators achieve faster time-to-value and greater return on investment for their cloud modernization initiatives.

The OpsRamp Spring 2021 Release also introduces new monitoring integrations for Microsoft Azure and Cisco HyperFlex along with enhanced platform navigation for easy access to key product capabilities.

Highlights of the OpsRamp Spring 2021 Release include:

- Rapid Onboarding. OpsRamp’s hybrid cloud wizard delivers a self-contained guide for discovering and monitoring multi-cloud and cloud native infrastructure. Once IT teams provide their cloud infrastructure details, OpsRamp auto-monitoring onboards cloud resources and displays performance metrics within minutes. The platform currently supports auto-monitoring for Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) cloud services along with Kubernetes distributions such as OpenShift and K3s as well as popular Linux distributions.

- Cloud Native Metrics Observability. Kubernetes admins can now ingest Prometheus metrics into OpsRamp for holistic visibility and faster troubleshooting across cloud native infrastructure. Our pull-based mechanism for scraping Prometheus metrics across Kubernetes clusters ensures faster visualization, data federation, and long-term retention of Prometheus insights.

- Data-Driven Insights for Hybrid IT Management. OpsRamp’s new dashboarding model allows cloud operators to visualize any data with a flexible querying framework. Dashboards 2.0 are customizable widgets powered by Prometheus Query Language (PromQL) with the ability to import/export dashboards and customize color palettes and fonts along with out-of-the-box support for a growing number of cloud services.

- Flexible and Centralized Alerting. New alert definition models offer greater flexibility for setting alerts along with streamlined mechanisms to alert on metric data collected by OpsRamp. CloudOps teams can centrally set thresholds to generate alerts for auto-monitored resources and then use relevant insights to keep their IT services up and running.

- Comprehensive Cloud Monitoring. OpsRamp currently offers more than 160 monitoring integrations across leading public cloud providers such as AWS, Azure, and GCP. The OpsRamp Spring 2021 Release offers expanded coverage for Microsoft Azure with metrics support for Blob Storage, Table Storage, File Storage, BatchAI Workspaces, BlockChain, Databox Edge, Logic Integration Service Environment, and Kusto Clusters.

- HyperConverged Infrastructure Monitoring. OpsRamp can not only discover and monitor Cisco HyperFlex components such as cluster nodes, hosts, datastores, and virtual machines but also ingest HyperFlex events into the OpsRamp AIOps platform for faster root cause diagnostics. The platform also supports the discovery and monitoring of physical components of Dell EMC VxRail appliances along with ingestion of VxRail software and hardware events.

“CloudOps teams are shackled by legacy IT operations tools that were never designed to handle the dynamic and ephemeral nature of public cloud infrastructure,” said Ciaran Byrne, VP of Product Management at OpsRamp. “OpsRamp’s digital operations management platform enables faster discovery and monitoring of production workloads across multi-cloud environments along with data-driven insights for managing the health and performance of a distributed infrastructure ecosystem.”

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...