RightScale announced the RightScale Cloud Appliance that integrates RightScale Cloud Portfolio Management and the VMware vSphere virtualization platform.
RightScale users will be able to leverage RightScale Cloud Portfolio Management to manage vSphere resources through a new, lightweight, on-premise RightScale virtual appliance.
With the RightScale Cloud Appliance for vSphere, IT teams can choose whether to deploy workloads to VMware vSphere or any of the leading public or private clouds already supported by RightScale, and will be able to create portable workloads that can move seamlessly between cloud environments and VMware vSphere. Using RightScale, enterprises reduce vendor lock-in and enable infrastructure teams to manage cloud-based workloads from a single pane of glass.
Benefits of using the RightScale Cloud Appliance for vSphere include:
- Single pane of glass across cloud and vSphere environments: Using RightScale, enterprises can enable infrastructure teams to manage cloud-based workloads — including major public clouds, vSphere environments, and OpenStack and CloudStack-based clouds — from a single pane of glass.
- Enhanced vSphere environments with cloud-like capabilities: Cloud environments offer additional capabilities that go beyond the functionality of virtualized environments like vSphere. The RightScale Cloud Appliance adds cloud-like capabilities that expand and streamline access to vSphere. The appliance provides multi-tenancy governance on top of vSphere to allow automated, policy-based sharing of vSphere resource pools by multiple tenants. It also adds standardized instance types to enable developers to quickly pick from a preconfigured set of infrastructure options.
- Self-service access across cloud and virtualized environments: vSphere environments have traditionally been controlled, configured, and managed by IT. With the RightScale Cloud Appliance, new types of users such as application developers, software architects, and DevOps teams will be able to leverage RightScale to deploy and move workloads across cloud and vSphere environments according to the policies set by IT teams.
- Leveraging vCenter and RightScale in parallel: RightScale does not lock users into one management solution. Users can leverage RightScale Cloud Portfolio Management and VMware vCenter Server in parallel. For example, developers can leverage RightScale to deploy workloads in vSphere, while VMWare administrators can leverage vCenter.
Reduced vendor lock-in: RightScale ServerTemplates are dynamic configuration scripts. They provide portability for workloads across vSphere environments and public and private clouds.
- Unified reporting and analytics: With RightScale Cloud Analytics, users can visualize usage and spending across vSphere data centers as well as other clouds.
- Cross-environment professional services: RightScale experts can help enterprises deploy and optimize application portfolios across vSphere virtualized environments as well as public and private clouds.
RightScale offers support for vSphere 5.1 and 5.5 is currently in limited availability. The RightScale Cloud Appliance for vSphere is expected to be generally available in the second quarter of 2014.
The Latest
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 ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...