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Achieving Intelligent Data Governance

Why It's Better to be Intelligent than High, When it Comes to Data Governance
Don Boxley

High availability's (HA) primary objective has historically been focused on ensuring continuous operations and performance. HA was built on a foundation of redundancy and failover technologies and methodologies to ensure business continuity in the event of workload spikes, planned maintenance, and unplanned downtime.

Today, HA methodologies have been superseded by intelligent workload routing automation (i.e., intelligent availability), in that data and their processing are consistently directed to the proper place at the right time. Intelligent availability partially stems from the distributed realities of the modern data landscape, in that information assets are disbursed on premises, in the cloud, and at the cloud's edge.

Consequently, regulatory compliance has emerged as much a driver for intelligent availability as has performance. With increasing regulations and penalties (such as those for the European Union's General Data Protection Regulation, i.e., GDPR), missteps about where workloads are routed could have dire legal and financial consequences — especially for data in the cloud.

Many countries and industries have stringent regulations about data's location that directly affect cloud deployments. Organizations must know how and where such data is permitted in the cloud before shifting it there for availability and performance issues.

Crafting policies in accordance with these regulations is crucial to leveraging intelligent availability to ensure compliance, and effectively transforms data governance into intelligent data governance.

Cloud Concerns

Cloud deployments have a number of opaque areas in relation to routing workloads for availability. These pertain to the type of cloud involved (public, private, or hybrid), the method of redundancy used, and the nature of the data.

The GDPR, for example, has a number of regulations for personal data, a broad term for "any information related to an identified or identifiable natural person." As such, organizations must be extremely cautious about transporting this type of data, despite the performance gains of doing so. For example, cloud bursting is advantageous for optimizing performance during sudden peaks in network activity, that are common for online transaction processing in finance or manufacturing. Migrating these workloads from local settings to public ones may balance network activity, but can forsake regulations in the process.

Organizations must take similar precautions when strategizing for disaster recovery (DR), one of the chief benefits of intelligent availability. Downtime may be minimized by implementing automatic failovers into the cloud, but can also compromise regulatory compliance.

Cloud compliance issues not only involve where data are stored, but also where (and how) they're processed. GDPR, for example, distinguishes data processors from data controllers. The latter are organizations using data, but the former can involve any assortment of SaaS or SOA options that must adhere to GDPR's personal data regulations. Organizations must assess these measures when cloud brokering among various providers — particularly for transient pricing specials.

Other regulations such as the Payment Card Industry Data Security Standard have rigid stipulations about encrypting data (especially for data in transit) that may apply to workloads spontaneously moved to the cloud. Those in the e-commerce or retail spaces must consider the intricacies of server side or client-side encryption, especially when replicating data between clouds.

The Intelligent Way

Intelligent availability provides the best means of effecting regulatory compliance while dynamically shifting workloads between environments for all of the preceding scenarios. The core of this method is the governance policies devised to meet compliance standards.

Although intelligent availability doesn't determine sensitive information or dictate where it can be routed, it offers portability freedom across settings (including operation systems, physical and virtual infrastructure) that all but forces organizations to identify these factors because of its flexibility. This real-time, on-demand shifting of resources is the catalyst to evaluate workloads through a governance lens, update policies as needed, and leverage them to predetermine optimal routing of data and their processing for availability. Intelligent availability is the means of implementing Intelligent data governance; it's a conduit between performance and regulatory compliance that increases competitive advantage.

Implementing Intelligent Governance

Once those policies are in place, the intelligent availability approach maximizes cloud deployments while maintaining regulatory adherence. Its intelligent algorithms continuously monitor server performance to automatically detect surges, either issuing alerts to organizations or heralding the transfer of workloads to alternative hosts. By already having agreed upon policies conforming to governance practices, prudent organizations can confidently move data to the cloud without violating regulations. Thus, cloud bursting measures can regularly be deployed to minimize network strain during spikes for OLTP (or any other reason) without costly penalties.

Companies also have the benefit of automatic failovers to the cloud to maintain business continuity in the event of natural disasters or failure. This option virtually eliminates downtime, enabling IT to perform maintenance on even the most mission critical infrastructure once data is properly re-routed offsite.

One of the most useful intelligent availability advantages is the capability to span clouds, both among providers and all the variations of clouds available. Although well sourced governance policies are essential to receiving the pricing boons of cloud brokering, intelligent availability's ability to start and stop workloads at the instance level while transporting data between settings is just as valuable.

The data processing issue is a little more complicated but is assisted by intelligent availability's flexibility. Once organizations have researched the various Service Level Agreements of cloud vendors — as well as policies for other types of data processing, including software companies' — they can utilize these platforms in accordance with regulations, transferring their resources where they're permitted. Most encryption concerns are solved with client-side encryption whereby organizations encrypt data before replicating them to the cloud, retaining the sole keys to them. Intelligent availability measures transport this data to the cloud and back as needed.

Adherence

The escalating presence of regulatory mandates isn't likely to soon subside. Compliance standards are just as critical as performance issues, when making workloads available across heterogeneous settings. Intelligent availability's support of versatile storage and processing environments, in conjunction with its low-latency portability, makes it a natural extension of intelligent data governance implementations. These methods ensure data is moved correctly — the first time — to maintain regulatory adherence during an age when it's most difficult to do so.

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Achieving Intelligent Data Governance

Why It's Better to be Intelligent than High, When it Comes to Data Governance
Don Boxley

High availability's (HA) primary objective has historically been focused on ensuring continuous operations and performance. HA was built on a foundation of redundancy and failover technologies and methodologies to ensure business continuity in the event of workload spikes, planned maintenance, and unplanned downtime.

Today, HA methodologies have been superseded by intelligent workload routing automation (i.e., intelligent availability), in that data and their processing are consistently directed to the proper place at the right time. Intelligent availability partially stems from the distributed realities of the modern data landscape, in that information assets are disbursed on premises, in the cloud, and at the cloud's edge.

Consequently, regulatory compliance has emerged as much a driver for intelligent availability as has performance. With increasing regulations and penalties (such as those for the European Union's General Data Protection Regulation, i.e., GDPR), missteps about where workloads are routed could have dire legal and financial consequences — especially for data in the cloud.

Many countries and industries have stringent regulations about data's location that directly affect cloud deployments. Organizations must know how and where such data is permitted in the cloud before shifting it there for availability and performance issues.

Crafting policies in accordance with these regulations is crucial to leveraging intelligent availability to ensure compliance, and effectively transforms data governance into intelligent data governance.

Cloud Concerns

Cloud deployments have a number of opaque areas in relation to routing workloads for availability. These pertain to the type of cloud involved (public, private, or hybrid), the method of redundancy used, and the nature of the data.

The GDPR, for example, has a number of regulations for personal data, a broad term for "any information related to an identified or identifiable natural person." As such, organizations must be extremely cautious about transporting this type of data, despite the performance gains of doing so. For example, cloud bursting is advantageous for optimizing performance during sudden peaks in network activity, that are common for online transaction processing in finance or manufacturing. Migrating these workloads from local settings to public ones may balance network activity, but can forsake regulations in the process.

Organizations must take similar precautions when strategizing for disaster recovery (DR), one of the chief benefits of intelligent availability. Downtime may be minimized by implementing automatic failovers into the cloud, but can also compromise regulatory compliance.

Cloud compliance issues not only involve where data are stored, but also where (and how) they're processed. GDPR, for example, distinguishes data processors from data controllers. The latter are organizations using data, but the former can involve any assortment of SaaS or SOA options that must adhere to GDPR's personal data regulations. Organizations must assess these measures when cloud brokering among various providers — particularly for transient pricing specials.

Other regulations such as the Payment Card Industry Data Security Standard have rigid stipulations about encrypting data (especially for data in transit) that may apply to workloads spontaneously moved to the cloud. Those in the e-commerce or retail spaces must consider the intricacies of server side or client-side encryption, especially when replicating data between clouds.

The Intelligent Way

Intelligent availability provides the best means of effecting regulatory compliance while dynamically shifting workloads between environments for all of the preceding scenarios. The core of this method is the governance policies devised to meet compliance standards.

Although intelligent availability doesn't determine sensitive information or dictate where it can be routed, it offers portability freedom across settings (including operation systems, physical and virtual infrastructure) that all but forces organizations to identify these factors because of its flexibility. This real-time, on-demand shifting of resources is the catalyst to evaluate workloads through a governance lens, update policies as needed, and leverage them to predetermine optimal routing of data and their processing for availability. Intelligent availability is the means of implementing Intelligent data governance; it's a conduit between performance and regulatory compliance that increases competitive advantage.

Implementing Intelligent Governance

Once those policies are in place, the intelligent availability approach maximizes cloud deployments while maintaining regulatory adherence. Its intelligent algorithms continuously monitor server performance to automatically detect surges, either issuing alerts to organizations or heralding the transfer of workloads to alternative hosts. By already having agreed upon policies conforming to governance practices, prudent organizations can confidently move data to the cloud without violating regulations. Thus, cloud bursting measures can regularly be deployed to minimize network strain during spikes for OLTP (or any other reason) without costly penalties.

Companies also have the benefit of automatic failovers to the cloud to maintain business continuity in the event of natural disasters or failure. This option virtually eliminates downtime, enabling IT to perform maintenance on even the most mission critical infrastructure once data is properly re-routed offsite.

One of the most useful intelligent availability advantages is the capability to span clouds, both among providers and all the variations of clouds available. Although well sourced governance policies are essential to receiving the pricing boons of cloud brokering, intelligent availability's ability to start and stop workloads at the instance level while transporting data between settings is just as valuable.

The data processing issue is a little more complicated but is assisted by intelligent availability's flexibility. Once organizations have researched the various Service Level Agreements of cloud vendors — as well as policies for other types of data processing, including software companies' — they can utilize these platforms in accordance with regulations, transferring their resources where they're permitted. Most encryption concerns are solved with client-side encryption whereby organizations encrypt data before replicating them to the cloud, retaining the sole keys to them. Intelligent availability measures transport this data to the cloud and back as needed.

Adherence

The escalating presence of regulatory mandates isn't likely to soon subside. Compliance standards are just as critical as performance issues, when making workloads available across heterogeneous settings. Intelligent availability's support of versatile storage and processing environments, in conjunction with its low-latency portability, makes it a natural extension of intelligent data governance implementations. These methods ensure data is moved correctly — the first time — to maintain regulatory adherence during an age when it's most difficult to do so.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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