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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Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

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The Real Enterprise AI Risk Isn't Hallucinations

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

IT Leaders Must Establish a Network Data Architecture Practice

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

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Enterprise Cloud Observability: Choosing the Right Starting Point

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...