Skip to main content

GDPR and the Need for a Smart Approach to Service Assurance

Michael Segal

Following the introduction of the EU General Data Protection Regulation, or GDPR, on May 25 this year, organizations across the globe with customers and suppliers in the European Union have been working to ensure they are compliant, and bringing the subject of data projection to the front of everyone's mind.

It's little surprise that network security and information assurance are key to complying with the GDPR; the regulation includes a requirement for measures to be put in place that will mitigate the risk associated with assuring the availability and integrity of an organization's information in the event of an attack or outage, for example.

Article 32 is concerned with confidentiality, integrity, availability and resilience of processing systems and data, and with the speed at which availability and access to personal data can be restored in the event of downtime resulting for a breach or network outage. Of course, as the information protected by the GDPR and other similar regulations constantly traverses the network, it's important to assure its availability, reliability and responsiveness. Indeed, not only is this important for regulatory compliance, it should be high on the list of priorities for any business.

Given the size and complexity of today's IT networks, however, it can be almost impossible to detect just when and where a security breach or network failure might occur. It's critical, therefore, that businesses have complete visibility over their IT networks, and any applications and services that run on those networks, in order to protect their customers' information, assure uninterrupted service delivery and, of course, comply with the GDPR.

Insight and Intelligence

The volume of data being produced has exploded in recent years and this is only set to continue, with analysts predicting a tenfold increase within the next decade, 60 percent of which will be generated by enterprises.

Much of this will comprise what the GDPR, and other regulations such as PCI-DSS and HIPAA, define as personal data: the personal email addresses, phone numbers, IP addresses and credit card information that may be collected and recorded by a business. For compliance purposes, it's important that networking teams are able to understand how this data traverses their organization's networks, the paths it will take and where it will be stored.

Keeping track of this information requires full visibility across the entire network, including data centers, applications and the cloud. To comply with regulatory requirements around the processing of data, as well as for service and security assurance, businesses should consider a smart approach to the way they handle data. Such an approach would involve monitoring all "wire data" information, that is every action and transaction that traverses an organization's service delivery infrastructure, and continuously analyzing it and compressing it into metadata at its source. This "smart data" is normalized, organized, and structured in a service and security contextual fashion in real time. The inherent intelligence of the metadata enables analytics tools to clearly understand application performance, infrastructure complexities, service dependencies and, importantly for GDPR compliance, any threats or anomalies.

Essentially, continuous monitoring of this wire data means that businesses can have access to contextualized data that will provide them with the real-time, actionable insights they need for assurance of effective, resilient and secure infrastructure, crucial for complying with the GDPR, not to mention for much of modern business activity.

More at Stake than Ever

The recent implementation of the GDPR means that any organization that processes the personal data of UK citizens, regardless of where in the world that organization is located, is now within the scope of the law. Much has been written over the past year on the eye-watering financial penalties that could be imposed on any company found to be neglectful in fulfilling its duty to protect the privacy of that data. The privacy and protection of personal data have always been considerations for a business, but with the prospect of facing fines of up to €20 million or four percent of annual turnover, there is more at stake for businesses than ever before.

With robust protection in place, and with visibility, insight and intelligence delivering assurance of complete network availability, businesses across the world breathe a little easier that the reliability of their networks, and of the applications that run on those networks, meet the requirements of the GDPR.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

GDPR and the Need for a Smart Approach to Service Assurance

Michael Segal

Following the introduction of the EU General Data Protection Regulation, or GDPR, on May 25 this year, organizations across the globe with customers and suppliers in the European Union have been working to ensure they are compliant, and bringing the subject of data projection to the front of everyone's mind.

It's little surprise that network security and information assurance are key to complying with the GDPR; the regulation includes a requirement for measures to be put in place that will mitigate the risk associated with assuring the availability and integrity of an organization's information in the event of an attack or outage, for example.

Article 32 is concerned with confidentiality, integrity, availability and resilience of processing systems and data, and with the speed at which availability and access to personal data can be restored in the event of downtime resulting for a breach or network outage. Of course, as the information protected by the GDPR and other similar regulations constantly traverses the network, it's important to assure its availability, reliability and responsiveness. Indeed, not only is this important for regulatory compliance, it should be high on the list of priorities for any business.

Given the size and complexity of today's IT networks, however, it can be almost impossible to detect just when and where a security breach or network failure might occur. It's critical, therefore, that businesses have complete visibility over their IT networks, and any applications and services that run on those networks, in order to protect their customers' information, assure uninterrupted service delivery and, of course, comply with the GDPR.

Insight and Intelligence

The volume of data being produced has exploded in recent years and this is only set to continue, with analysts predicting a tenfold increase within the next decade, 60 percent of which will be generated by enterprises.

Much of this will comprise what the GDPR, and other regulations such as PCI-DSS and HIPAA, define as personal data: the personal email addresses, phone numbers, IP addresses and credit card information that may be collected and recorded by a business. For compliance purposes, it's important that networking teams are able to understand how this data traverses their organization's networks, the paths it will take and where it will be stored.

Keeping track of this information requires full visibility across the entire network, including data centers, applications and the cloud. To comply with regulatory requirements around the processing of data, as well as for service and security assurance, businesses should consider a smart approach to the way they handle data. Such an approach would involve monitoring all "wire data" information, that is every action and transaction that traverses an organization's service delivery infrastructure, and continuously analyzing it and compressing it into metadata at its source. This "smart data" is normalized, organized, and structured in a service and security contextual fashion in real time. The inherent intelligence of the metadata enables analytics tools to clearly understand application performance, infrastructure complexities, service dependencies and, importantly for GDPR compliance, any threats or anomalies.

Essentially, continuous monitoring of this wire data means that businesses can have access to contextualized data that will provide them with the real-time, actionable insights they need for assurance of effective, resilient and secure infrastructure, crucial for complying with the GDPR, not to mention for much of modern business activity.

More at Stake than Ever

The recent implementation of the GDPR means that any organization that processes the personal data of UK citizens, regardless of where in the world that organization is located, is now within the scope of the law. Much has been written over the past year on the eye-watering financial penalties that could be imposed on any company found to be neglectful in fulfilling its duty to protect the privacy of that data. The privacy and protection of personal data have always been considerations for a business, but with the prospect of facing fines of up to €20 million or four percent of annual turnover, there is more at stake for businesses than ever before.

With robust protection in place, and with visibility, insight and intelligence delivering assurance of complete network availability, businesses across the world breathe a little easier that the reliability of their networks, and of the applications that run on those networks, meet the requirements of the GDPR.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...