Widespread Downtime Found in 99 Percent of Cloud Environments

Downtime and security risks were present in each cloud environment tested, according to 2016 Private Cloud Resiliency Benchmarks, a report from Continuity Software.

The study also found that security and performance risks were found in 99 percent and 97 percent of the environments respectively, with 82 percent of the companies facing data loss risks.

Some of the top risks identified across the private cloud environments include:

■ Configuration drifts between cluster nodes that prevent failover. Examples for such discrepancies range from the most trivial – e.g., a file that is not accessible by all hosts in the cluster – to more complex ones – such as incorrect settings of affinity rules.

■ Virtual networking configuration errors leading to virtual machine isolation and downtime. Examples include incorrect Virtual Machine Port Group configurations and resources misalignment between ESXi cluster hosts leading to a single point of failure.

■ Incorrect storage settings leading to corrupt backups and data store loss. Such risks range from invalid CBT configuration to inconsistent LUN numbering and incorrect UUID settings.

What do these private cloud environments look like?

■ 48 percent of the organizations included in the study run their virtual machines on Windows compared to 7 percent of the organizations that run on Linux. 46 percent of the organizations use a mix of operating systems.

■ Close to three quarters (73 percent) of the organizations use EMC data storage systems. Other storage systems used include NetApp (38 percent), IBM (26 percent), HP (24 percent) and Hitachi (18 percent).

■ 27 percent of the organizations use replication for automated offsite data protection.

■ 12 percent of the organizations utilize active-active failover for continuous availability.

■ Almost all of the organizations (96 percent) use more than one physical path to transfer data between the host and the external storage device.

With a growing level of the complexity, increasing interdependence among infrastructure components, and an escalating pace of change, keeping cloud infrastructure free of risky misconfiguration is becoming a challenge that most organizations fail to meet.

"Sooner or later, every system fails," said Gil Hecht, CEO of Continuity Software. "And when a popular service goes down, it doesn't take long for customers to notice."

Each year enterprises continue to encounter downtime, which currently costs an estimated $740,000 per outage according to Ponemon's most recent report.

"The good news is that most risks lurking in the cloud infrastructure can be identified and corrected before they turn into a service disruption," explained Hecht. "This requires a specialized set of processes and tools, but above all a mindset and strategy focused on early detection and the remediation of risks."

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Widespread Downtime Found in 99 Percent of Cloud Environments

Downtime and security risks were present in each cloud environment tested, according to 2016 Private Cloud Resiliency Benchmarks, a report from Continuity Software.

The study also found that security and performance risks were found in 99 percent and 97 percent of the environments respectively, with 82 percent of the companies facing data loss risks.

Some of the top risks identified across the private cloud environments include:

■ Configuration drifts between cluster nodes that prevent failover. Examples for such discrepancies range from the most trivial – e.g., a file that is not accessible by all hosts in the cluster – to more complex ones – such as incorrect settings of affinity rules.

■ Virtual networking configuration errors leading to virtual machine isolation and downtime. Examples include incorrect Virtual Machine Port Group configurations and resources misalignment between ESXi cluster hosts leading to a single point of failure.

■ Incorrect storage settings leading to corrupt backups and data store loss. Such risks range from invalid CBT configuration to inconsistent LUN numbering and incorrect UUID settings.

What do these private cloud environments look like?

■ 48 percent of the organizations included in the study run their virtual machines on Windows compared to 7 percent of the organizations that run on Linux. 46 percent of the organizations use a mix of operating systems.

■ Close to three quarters (73 percent) of the organizations use EMC data storage systems. Other storage systems used include NetApp (38 percent), IBM (26 percent), HP (24 percent) and Hitachi (18 percent).

■ 27 percent of the organizations use replication for automated offsite data protection.

■ 12 percent of the organizations utilize active-active failover for continuous availability.

■ Almost all of the organizations (96 percent) use more than one physical path to transfer data between the host and the external storage device.

With a growing level of the complexity, increasing interdependence among infrastructure components, and an escalating pace of change, keeping cloud infrastructure free of risky misconfiguration is becoming a challenge that most organizations fail to meet.

"Sooner or later, every system fails," said Gil Hecht, CEO of Continuity Software. "And when a popular service goes down, it doesn't take long for customers to notice."

Each year enterprises continue to encounter downtime, which currently costs an estimated $740,000 per outage according to Ponemon's most recent report.

"The good news is that most risks lurking in the cloud infrastructure can be identified and corrected before they turn into a service disruption," explained Hecht. "This requires a specialized set of processes and tools, but above all a mindset and strategy focused on early detection and the remediation of risks."

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Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

The SRE Report 2026: Reliability Is Being Redefined

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

Why AI Is the Differentiator for Operationally Resilient Organizations

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? ...

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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 ...

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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 ...

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