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OpsRamp Releases Summer Release

OpsRamp announced its Summer Release which includes alert predictions for preventing outages and incidents, alert enrichment policies for faster incident troubleshooting, and auto monitoring enhancements for Alibaba Cloud and Prometheus metrics ingestion.

OpsRamp’s latest release helps IT teams avoid outages and prevent reputational damages with predictive alerting, alert enrichment, and dynamic workflows. The OpsRamp Summer 2021 Release also introduces new monitoring integrations for Alibaba Cloud, Prometheus metrics ingestion, Hitachi, VMware, Dell EMC, and Poly.

Highlights of the OpsRamp Summer 2021 Release include:

- Predictive Alerting. Alert prediction policies help IT teams anticipate which alerts repeat regularly and turn into performance-impacting incidents. With AIOps, operators can reduce service degradations by identifying seasonal alert patterns as well as lower incident volumes by forecasting repetitive alerts.

- Alert Enrichment. Organizations can accelerate incident troubleshooting by enriching the ‘problem area’ field in the alert description subject. IT operators can use regular expressions to populate alert context details so that they can identify problems faster with relevant information.

- Auto Monitoring. IT operators can now rapidly onboard and monitor their Windows infrastructure, including Windows Server, Active Directory, Exchange, IIS, and SQL Server through auto monitoring. Cloud engineers can ensure centralized data storage and retention of Prometheus metrics with support for Prometheus instances running on bare metal and virtualized infrastructure.

- Alibaba Cloud Monitoring. CloudOps engineers can now onboard and monitor their services running in Alibaba Cloud. They can visualize, alert, and perform root cause analysis on ECS instances, Auto Scaling, RDS, Load Balancer, EMR, and VPC services within Alibaba Cloud and accelerate troubleshooting for multicloud infrastructure within a single platform.

- Datacenter Monitoring. System administrators can now monitor the performance and health of popular datacenter infrastructure such as Hitachi VSP OpsCenter, NAS and HCI, VMware vSAN, NSX-T and NSX-V, Dell EMC PowerScale, PowerStore and PowerMax, and Poly Trio, VVX/CCX and Group.

- Dynamic Workflows (Beta). Instead of building a number of different automation workflows, IT operators can maintain a single decision table to address specific operational scenarios at scale. Dynamic workflows ensure faster incident response by invoking diagnostic actions for distinct scenarios.

- Mobile Application. IT teams can now respond to alerts and incidents through the OpsRamp mobile application with support for both Android and iOS devices. Operators can view, sort, search, filter, comment, and take action on alerts while also being able to access, edit, sort, filter, and reassign incidents from anywhere.

- Powerful Visualizations. Operators can now clearly visualize metric values that can arbitrarily increase or decrease within a fixed range using Gauge charts. For network operations teams that work in 24/7 shifts, dark mode reduces eye strain, improves readability, and offers ergonomic comfort.
OpsRamp Dark Mode reduces blue-light fatigue for ops teams that troubleshoot during late hours or are accustomed to darkened UIs.

“Modern IT teams have to deal with escalating customer expectations, constant toil, technical debt, and an overwhelming amount of operational data to process and analyze,” said Sheen Khoury, Chief Revenue Officer at OpsRamp. “OpsRamp’s digital operations management platform transforms reactive incidents workflows to proactive and preventive operations for faster incident prediction, recognition, and remediation.”

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OpsRamp Releases Summer Release

OpsRamp announced its Summer Release which includes alert predictions for preventing outages and incidents, alert enrichment policies for faster incident troubleshooting, and auto monitoring enhancements for Alibaba Cloud and Prometheus metrics ingestion.

OpsRamp’s latest release helps IT teams avoid outages and prevent reputational damages with predictive alerting, alert enrichment, and dynamic workflows. The OpsRamp Summer 2021 Release also introduces new monitoring integrations for Alibaba Cloud, Prometheus metrics ingestion, Hitachi, VMware, Dell EMC, and Poly.

Highlights of the OpsRamp Summer 2021 Release include:

- Predictive Alerting. Alert prediction policies help IT teams anticipate which alerts repeat regularly and turn into performance-impacting incidents. With AIOps, operators can reduce service degradations by identifying seasonal alert patterns as well as lower incident volumes by forecasting repetitive alerts.

- Alert Enrichment. Organizations can accelerate incident troubleshooting by enriching the ‘problem area’ field in the alert description subject. IT operators can use regular expressions to populate alert context details so that they can identify problems faster with relevant information.

- Auto Monitoring. IT operators can now rapidly onboard and monitor their Windows infrastructure, including Windows Server, Active Directory, Exchange, IIS, and SQL Server through auto monitoring. Cloud engineers can ensure centralized data storage and retention of Prometheus metrics with support for Prometheus instances running on bare metal and virtualized infrastructure.

- Alibaba Cloud Monitoring. CloudOps engineers can now onboard and monitor their services running in Alibaba Cloud. They can visualize, alert, and perform root cause analysis on ECS instances, Auto Scaling, RDS, Load Balancer, EMR, and VPC services within Alibaba Cloud and accelerate troubleshooting for multicloud infrastructure within a single platform.

- Datacenter Monitoring. System administrators can now monitor the performance and health of popular datacenter infrastructure such as Hitachi VSP OpsCenter, NAS and HCI, VMware vSAN, NSX-T and NSX-V, Dell EMC PowerScale, PowerStore and PowerMax, and Poly Trio, VVX/CCX and Group.

- Dynamic Workflows (Beta). Instead of building a number of different automation workflows, IT operators can maintain a single decision table to address specific operational scenarios at scale. Dynamic workflows ensure faster incident response by invoking diagnostic actions for distinct scenarios.

- Mobile Application. IT teams can now respond to alerts and incidents through the OpsRamp mobile application with support for both Android and iOS devices. Operators can view, sort, search, filter, comment, and take action on alerts while also being able to access, edit, sort, filter, and reassign incidents from anywhere.

- Powerful Visualizations. Operators can now clearly visualize metric values that can arbitrarily increase or decrease within a fixed range using Gauge charts. For network operations teams that work in 24/7 shifts, dark mode reduces eye strain, improves readability, and offers ergonomic comfort.
OpsRamp Dark Mode reduces blue-light fatigue for ops teams that troubleshoot during late hours or are accustomed to darkened UIs.

“Modern IT teams have to deal with escalating customer expectations, constant toil, technical debt, and an overwhelming amount of operational data to process and analyze,” said Sheen Khoury, Chief Revenue Officer at OpsRamp. “OpsRamp’s digital operations management platform transforms reactive incidents workflows to proactive and preventive operations for faster incident prediction, recognition, and remediation.”

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Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...