Engineering Security Data Lakes for Cloud & Hybrid Environments

For today’s cloud-native enterprises, “security by default” is a dangerously misleading concept. Many digital-native organizations, whose entire operations are built and run in the cloud, may assume that the inherent security of cloud platforms is sufficient to protect their business. But the reality is far more nuanced, and the risks are significant for those who overlook foundational security responsibilities.

For businesses born in the cloud, security gaps are amplified. Operating entirely in cloud environments introduces new challenges that traditional security models were never designed to address. As these organizations scale and innovate at cloud speed, they face a landscape where security must be engineered into every layer, not simply inherited from the infrastructure provider.

The Cloud Security Myth

At the heart of many cloud breaches is a misunderstanding of the shared responsibility model. Cloud providers like AWS, Azure, and Google Cloud are responsible for securing the infrastructure - the servers, networks, and physical data centers. But securing what lives in the cloud - applications, configurations, workloads, and data - is the customer’s responsibility.

For enterprises operating in hybrid or multi-cloud environments, this blurred line becomes a risk vector in itself. Without direct control over the underlying infrastructure, organizations must rethink how they monitor, detect, and respond to threats. And they need to do it in real-time, across environments that are constantly scaling, shifting, and evolving.

This is where the traditional playbook falls apart.

Challenges with Traditional Cloud Security Approaches

Fragmented Visibility

Too often, cloud security is siloed from traditional SecOps. Different tools, different teams, and different telemetry streams result in disjointed workflows and inconsistent threat detection. A cloud-native workload might be invisible to the legacy SIEM, while on-prem alerts remain untouched by cloud-centric tools.

This fragmentation creates blind spots - making it harder for CISOs to answer fundamental questions like:

• Where are our most valuable assets?
• Who’s accessing them?
• Are we under attack right now?

Limitations of Legacy Tools

Legacy SIEMs weren’t designed to handle today’s velocity or volume of data. They’re expensive to scale, inefficient at processing unstructured telemetry, and often lack real-time analytics. Most struggle to support:

• Petabyte-scale telemetry
• Streaming data sources
• Multi-cloud architectures
• Extended data retention for compliance or forensics
• In the era of containers, APIs, and distributed microservices, these limitations are no longer tolerable.

The Role of Data Lakes in Securing Cloud Environments

To address these challenges, forward-thinking organizations are turning to security data lakes as a foundational element of their cloud security strategy.

Data Lakes as the Foundation

A security data lake is a centralized repository that allows organizations to store vast amounts of structured and unstructured data at scale. They ingest, normalize, correlate, and store massive volumes of telemetry - spanning on-prem systems, multi-cloud infrastructure, SaaS platforms, and third-party threat intel.

Unlike legacy SIEMs, which are optimized for ingestion cost and short-term storage, data lakes are built for scale, flexibility, and long-term value. Here's how they secure your environment:

• Normalization: Bring disparate data formats (syslogs, flow logs, EDR data, cloud audit logs, etc.) into a unified schema.
• Correlation: Connect events across environments and layers (e.g., identity, network, workload) to identify advanced threats.
• Retention: Store historical data for months or years to support compliance, root cause analysis, and machine learning.
• Analytics: Leverage AI/ML to identify anomalies, accelerate investigations, and surface previously undetectable risks.

By centralizing telemetry and enabling intelligent analytics, data lakes give CISOs a single source of truth for both reactive and proactive security operations.

Best Practices for Building a Cloud-First Security Data Lake

To maximize value from a security data lake, consider these key architectural and operational best practices:

Centralized Visibility

Ensure your lake aggregates telemetry across all environments - cloud, on-prem, containers, SaaS apps, identity systems, IoT devices, and more. True visibility means nothing is left out. To achieve this:

• Integrate telemetry from all sources into the data lake using APIs or agents.
• Use dashboards or visualization tools to present actionable insights in real time.
• Ensure that all stakeholders - security analysts, DevOps teams, compliance officers - have access to relevant insights tailored to their roles.

Integration with Managed Detection and Response (MDR) Workflows

Security doesn’t stop at visibility; it requires continuous monitoring and proactive threat management. Integrate your data lake with Managed Detection and Response (MDR) workflows to:

• Automate threat detection using pre-built ML models.
• Enable rapid incident response through automated playbooks.
• Continuously update detection rules based on emerging threat intelligence.

This integration ensures that your organization stays ahead of adversaries while minimizing manual intervention.

Flexible Data Ingestion & Orchestration

Use data engineering to control what you ingest, transform it as needed, and route it to the right tools - reducing costs and enabling agile response.

How Netenrich Empowers Organizations

Enter Netenrich - a cybersecurity firm that brings an engineering-led approach to building and operating security data lakes for modern enterprises.

Rather than relying on outdated tools, Netenrich combines cloud-scale telemetry with intelligent analytics and workflow automation to create a next-generation security architecture.

Take Back Control of Your Data

Netenrich enables organizations to orchestrate telemetry collection at scale, applying cost-aware data ingestion strategies that prioritize high-value signals. You get control over what to keep, where to store it, and how to use it.

Customize Without Compromise

Ingest petabytes of data from any source - cloud platforms, endpoints, OT/IoT devices - and build custom integrations aligned with your business objectives and risk tolerance.

Automate Efficiently

Leverage centralized, automated case management to help SOC teams respond faster and more consistently. Playbooks are enriched with context from across your telemetry to reduce triage time and increase impact.

Netenrich’s Solution

Netenrich merges the capabilities of security data lakes with a data-driven strategy for threat detection and response. It’s not just about storage - it’s about insight, efficiency, and actionability.

Integration with Google BigQuery

Through its partnership with Google Cloud, Netenrich integrates with BigQuery, delivering cloud-native analytics at scale. This allows security teams to:

• Run high-speed queries across petabytes of data
• Leverage Google Threat Intelligence
• Correlate real-time signals across cloud and hybrid environments
• Accelerate detection, triage, and response

Case Study: Cloud Software Group’s Transformation

Cloud Software Group (CSG) provides a powerful example of how Netenrich + BigQuery can transform security operations.

The challenge: CSG was struggling with fragmented visibility, siloed workflows, and slow response times across a sprawling hybrid infrastructure.

The solution: Implement Netenrich’s Adaptive MDR platform powered by a centralized data lake and BigQuery analytics.

The results:

• Playbook consolidation: From 40+ to just three streamlined workflows
• Detection coverage: Improved by over 140%
• MTTR: Reduced by up to 70%

This transformation illustrates the power of bringing together data, automation, and analytics in a cohesive architecture.

Get the case story here: https://netenrich.com/citrix-splunk-to-netenrich-mdr-case-study

Future-Proofing Cloud Security

In the world of hybrid and multi-cloud operations, yesterday’s tools and approaches won’t cut it. CISOs need centralized visibility, real-time analytics, and automation-ready platforms that evolve as fast as their environments. Netenrich offers a compelling path forward with an engineering-led approach to cloud security.

As a top-tier certified Google Services Delivery Partner, Netenrich brings deep expertise across the Google SecOps ecosystem. Netenrich’s capabilities span:

• Google Threat Intelligence
• Google Chrome Enterprise
• Mandiant
• Google Cloud Security Command Center
• SIEM
• SOAR
• Google Hunt
• Gemini AI for SecOps
• Universal Data Models (BigQuery, UDM)

By uniting these advanced tools and services, Netenrich empowers organizations to operationalize cloud-scale security, accelerate threat detection and response, and maximize the value of their security data lake investments-all on a foundation built for the future.