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VMware Updates vRealize Cloud Management

VMware announced innovations across its portfolio of VMware vRealize Cloud Management on-premises and software as a service (SaaS) offerings.

The new and enhanced product capabilities combine to further enable customers to consistently deploy and operate their applications, infrastructure, and platform services, from the data center to the cloud to the edge.

“Enterprises face multiple challenges in support of their business in these uncertain times,” said Ajay Singh, SVP and GM, Cloud Management Business Unit, VMware. “They seek to modernize their apps, accelerate hybrid and public cloud innovation, and deliver a modern developer environment. VMware is a trusted partner that enables customers to address those IT challenges head on – allowing them to focus on transforming their business.”

VMware vRealize Cloud Management offers new and innovative capabilities for modern infrastructure automation supporting DevOps principles and self-driving operations. Uniquely available both on-premises and as SaaS, VMware vRealize provides customers with the agility and efficiency of cloud infrastructure at scale, leveraging artificial intelligence (AI), machine learning (ML), and DevOps principles such as Infrastructure as Code (IaC) and GitOps to provision, orchestrate, optimize and govern hybrid and multi-cloud environments. Today, VMware is introducing new releases, capabilities and enhancements spanning VMware vRealize Automation 8.2, VMware vRealize Automation Cloud, VMware vRealize Log Insight 8.2, VMware vRealize Log Insight Cloud, VMware vRealize Operations 8.2, VMware vRealize Operations Cloud, and VMware vRealize Suite Lifecycle Manager 8.2.

VMware vRealize Operations delivers self-driving operations from apps to infrastructure to optimize, plan and scale private, hybrid and multiple public clouds. Powered by AI and predictive analytics, it delivers continuous performance, capacity and cost optimization, proactive planning, intelligent remediation and integrated compliance. VMware vRealize Operations 8.2 and VMware vRealize Operations Cloud will feature:

- Kubernetes Operations: New and enhanced support for Kubernetes via integration with VMware Tanzu Kubernetes Grid and Red Hat OpenShift will enable customers to auto-discover and monitor the health, performance, capacity, cost, and configuration of Kubernetes constructs on-premises and VMware Cloud on AWS.

- App-to-infrastructure Troubleshooting: This latest release will feature integration with popular APM tools such as AppDynamics, Datadog and Dynatrace. It will also include new app discovery via integration with VMware vRealize Network Insight. These two capabilities will help customers predict, prevent and quickly remediate issues in the context of applications.

- Monitoring VMware Cloud and Beyond: Improved metric-correlation and new near real-time monitoring will enable enterprise observability, helping customers detect performance and availability issues up to 15x faster. (1) Enhancements to native AWS management will unlock capacity calculations for EC2 instances and automatically import metrics into VMware vRealize Operations for faster troubleshooting.

- Efficient Capacity and Cost Management: Improvements in pricing and costing engine, including daily virtual machine (VM) cost granularity, enhanced metering capabilities, and pricing support for non-VMware vRealize Automation workloads will help customers to further reduce costs.

Similarly, VMware vRealize Log Insight 8.2 and vRealize Log Insight Cloud will also introduce enhanced Kubernetes support, deeper integration with VMware Cloud on AWS, and overall usability enhancements.

VMware vRealize Automation 8.2 and VMware vRealize Automation Cloud will deliver enhanced capabilities for customers’ most important automation use cases including Modern Automation Platform, DevOps for Infrastructure, Self-Service Cloud and Kubernetes Automation. The new and enhanced VMware vRealize Automation capabilities will include:

- Modern Automation Platform: Enhanced capabilities to increase agility, security and control including granular role-based access control (RBAC), enhanced support for multi-tenant infrastructure, expanded support for Day 2 actions and network automation with NSX policy APIs.

- DevOps for Infrastructure: Enhanced Infrastructure as Code capabilities with the introduction of VMware Cloud Templates as the templating engine for VMware Cloud infrastructure. This also includes management of Terraform configurations from the service catalog.

- Self-Service Cloud: Enhanced integration with VMware Cloud Foundation to further simplify private cloud setup for customers.

- Kubernetes Automation: Self-service provisioning of Kubernetes namespaces via the service catalog with support for VMware Cloud Foundation with Tanzu.

The lifecycle management capabilities of the VMware vRealize Suite help customers speed time to value by automating the deployment, configuration and upgrading of products in the suite. VMware vRealize Suite Lifecycle Manager 8.2 will deploy and manage vRealize Suite products on VMware Cloud on AWS, support vRealize Operations product re-sizing and scaling capabilities as well as continuous availability architecture, and configure single or multiple data sources for vRealize Network Insight. It will also introduce support for compliance certifications including Voluntary Product Accessibility Template (VPAT) 2.0 and Federal Information Processing Standards (FIPS).

VMware vRealize Automation 8.2, VMware vRealize Log Insight 8.2, VMware vRealize Operations 8.2 and VMware vRealize Suite Lifecycle Manager 8.2 are all expected to become available in VMware’s Q3 FY21. Additionally, the new capabilities and enhancements to VMware vRealize Automation Cloud, VMware vRealize Log Insight Cloud and VMware vRealize Operations Cloud are also expected to become available in VMware’s Q3 FY21.

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VMware Updates vRealize Cloud Management

VMware announced innovations across its portfolio of VMware vRealize Cloud Management on-premises and software as a service (SaaS) offerings.

The new and enhanced product capabilities combine to further enable customers to consistently deploy and operate their applications, infrastructure, and platform services, from the data center to the cloud to the edge.

“Enterprises face multiple challenges in support of their business in these uncertain times,” said Ajay Singh, SVP and GM, Cloud Management Business Unit, VMware. “They seek to modernize their apps, accelerate hybrid and public cloud innovation, and deliver a modern developer environment. VMware is a trusted partner that enables customers to address those IT challenges head on – allowing them to focus on transforming their business.”

VMware vRealize Cloud Management offers new and innovative capabilities for modern infrastructure automation supporting DevOps principles and self-driving operations. Uniquely available both on-premises and as SaaS, VMware vRealize provides customers with the agility and efficiency of cloud infrastructure at scale, leveraging artificial intelligence (AI), machine learning (ML), and DevOps principles such as Infrastructure as Code (IaC) and GitOps to provision, orchestrate, optimize and govern hybrid and multi-cloud environments. Today, VMware is introducing new releases, capabilities and enhancements spanning VMware vRealize Automation 8.2, VMware vRealize Automation Cloud, VMware vRealize Log Insight 8.2, VMware vRealize Log Insight Cloud, VMware vRealize Operations 8.2, VMware vRealize Operations Cloud, and VMware vRealize Suite Lifecycle Manager 8.2.

VMware vRealize Operations delivers self-driving operations from apps to infrastructure to optimize, plan and scale private, hybrid and multiple public clouds. Powered by AI and predictive analytics, it delivers continuous performance, capacity and cost optimization, proactive planning, intelligent remediation and integrated compliance. VMware vRealize Operations 8.2 and VMware vRealize Operations Cloud will feature:

- Kubernetes Operations: New and enhanced support for Kubernetes via integration with VMware Tanzu Kubernetes Grid and Red Hat OpenShift will enable customers to auto-discover and monitor the health, performance, capacity, cost, and configuration of Kubernetes constructs on-premises and VMware Cloud on AWS.

- App-to-infrastructure Troubleshooting: This latest release will feature integration with popular APM tools such as AppDynamics, Datadog and Dynatrace. It will also include new app discovery via integration with VMware vRealize Network Insight. These two capabilities will help customers predict, prevent and quickly remediate issues in the context of applications.

- Monitoring VMware Cloud and Beyond: Improved metric-correlation and new near real-time monitoring will enable enterprise observability, helping customers detect performance and availability issues up to 15x faster. (1) Enhancements to native AWS management will unlock capacity calculations for EC2 instances and automatically import metrics into VMware vRealize Operations for faster troubleshooting.

- Efficient Capacity and Cost Management: Improvements in pricing and costing engine, including daily virtual machine (VM) cost granularity, enhanced metering capabilities, and pricing support for non-VMware vRealize Automation workloads will help customers to further reduce costs.

Similarly, VMware vRealize Log Insight 8.2 and vRealize Log Insight Cloud will also introduce enhanced Kubernetes support, deeper integration with VMware Cloud on AWS, and overall usability enhancements.

VMware vRealize Automation 8.2 and VMware vRealize Automation Cloud will deliver enhanced capabilities for customers’ most important automation use cases including Modern Automation Platform, DevOps for Infrastructure, Self-Service Cloud and Kubernetes Automation. The new and enhanced VMware vRealize Automation capabilities will include:

- Modern Automation Platform: Enhanced capabilities to increase agility, security and control including granular role-based access control (RBAC), enhanced support for multi-tenant infrastructure, expanded support for Day 2 actions and network automation with NSX policy APIs.

- DevOps for Infrastructure: Enhanced Infrastructure as Code capabilities with the introduction of VMware Cloud Templates as the templating engine for VMware Cloud infrastructure. This also includes management of Terraform configurations from the service catalog.

- Self-Service Cloud: Enhanced integration with VMware Cloud Foundation to further simplify private cloud setup for customers.

- Kubernetes Automation: Self-service provisioning of Kubernetes namespaces via the service catalog with support for VMware Cloud Foundation with Tanzu.

The lifecycle management capabilities of the VMware vRealize Suite help customers speed time to value by automating the deployment, configuration and upgrading of products in the suite. VMware vRealize Suite Lifecycle Manager 8.2 will deploy and manage vRealize Suite products on VMware Cloud on AWS, support vRealize Operations product re-sizing and scaling capabilities as well as continuous availability architecture, and configure single or multiple data sources for vRealize Network Insight. It will also introduce support for compliance certifications including Voluntary Product Accessibility Template (VPAT) 2.0 and Federal Information Processing Standards (FIPS).

VMware vRealize Automation 8.2, VMware vRealize Log Insight 8.2, VMware vRealize Operations 8.2 and VMware vRealize Suite Lifecycle Manager 8.2 are all expected to become available in VMware’s Q3 FY21. Additionally, the new capabilities and enhancements to VMware vRealize Automation Cloud, VMware vRealize Log Insight Cloud and VMware vRealize Operations Cloud are also expected to become available in VMware’s Q3 FY21.

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...