The Cloud Provider’s Blueprint: Navigating Data Localization and DPDP Compliance in India

For Cloud Service Providers (CSPs) operating in India, the financial services ecosystem has shifted. The days when cloud architecture was evaluated purely on uptime, compute pricing, and network latency are over. Today, data governance is the primary architectural driver.

With the framework of the Digital Personal Data Protection (DPDP) Act taking firm hold alongside its operationalized Rules, the compliance environment has entered a new phase. Simultaneously, the Reserve Bank of India (RBI) has doubled down on its digital sovereignty initiatives, explicitly seen in the strict compliance deadlines for digital lending guidelines and updated Master Directions on IT Governance.

This regulatory intersection transforms the role of a CSP. Cloud providers are no longer just passive background utility vendors; they have become active, co-regulatory compliance partners. If your cloud platform hosts workloads for Indian banks, non-banking financial companies (NBFCs), fintech platforms, payment gateways, or insurance firms, you are directly bound by a complex web of localization mandates.

The Dual-Regulator Reality: The Interaction of DPDP and Sectoral Mandates

To build or maintain a compliant financial cloud infrastructure in India, one must first understand the relationship between general privacy legislation and sector-specific financial rules.

The DPDP Act adopts a fundamentally business-friendly, "permissive by default" or "negative list" stance toward international data transfers (Section 16). In theory, personal data can flow across international borders unless the Central Government explicitly places a country or territory on its blacklist.

However, for financial data, this flexibility disappears. The DPDP Act contains a critical conflict clause: if any pre-existing or sectoral regulation imposes stricter data localization requirements, those stricter requirements override the general law. The RBI, the Securities and Exchange Board of India (SEBI), and the Insurance Regulatory and Development Authority of India (IRDAI) enforce absolute localization. For instance, the RBI’s mandate on the Storage of Payment System Data and its strict guidelines for digital lending require financial personal data, transaction records, and credit assessments to be anchored inside India.

For a CSP, this means you cannot rely on the general cross-border allowances of the DPDP Act when handling financial customer data. You must design and deliver an infrastructure that respects the strict boundary fences erected by India's financial regulators.

1. Anchoring Infrastructure: Deep Dive into India-Only Data Residency

The most immediate obligation for any CSP hosting financial workloads is ensuring absolute data residency within the geographic borders of India. This is rarely as simple as checking a box during resource provisioning. It requires a granular review of how data moves across the cloud environment.

Production, Staging, and Microservices

Every component of a financial application must reside locally. This includes not just the primary SQL/NoSQL databases, but also caching layers (like Redis or Memcached clusters), application message queues (such as Kafka or RabbitMQ), and staging or testing environments. A common point of failure occurs when a bank’s production environment is hosted in an India-based cloud region, but its analytics, staging, or QA pipelines pull data into an overseas region. Under current guidelines, this is a severe compliance violation.

The Disaster Recovery (DR) and Cold Storage Trap

 
High availability architectures typically dictate that DR sites be geographically separated from primary regions to survive localized natural disasters. For global CSPs, the instinct might be to replicate an active Mumbai region workload to an offshore region like Singapore or Dubai.

For Indian financial data, this is legally prohibited. Your architecture must offer multi-region or multi-availability-zone topologies entirely within India (e.g., pairing a Mumbai primary region with a Hyderabad or Pune DR region). This restriction applies equally to cold backups, long-term archival storage (like glacier vaults), and machine learning training datasets derived from customer profiles.

Managing Cross-Border Legs and the 24-Hour Purge Rule

The RBI does allow for a temporary exception when a transaction has an explicit international component—such as an Indian resident making a purchase from a foreign merchant or cross-border remittance. In these scenarios, the data may be transmitted and processed outside India.

However, the regulatory clock ticks fast. The RBI Master Directions dictate that the complete end-to-end data must be brought back to local storage, and any copies or traces residing on foreign servers must be permanently deleted within 24 hours.

As a CSP, your network architecture and data pipelines must feature automated, time-bound orchestration tools that guarantee the complete, unrecoverable purging of transient data from foreign edge locations or intermediate nodes inside that strict 24-hour window.

2. Becoming a "Processor-Ready" Partner Under the DPDP Rules

The DPDP Act draws a sharp legal line between the Data Fiduciary (the financial institution determining the purpose of data collection) and the Data Processor (the entity processing data on behalf of the Fiduciary—the CSP).

Section 8(2) of the Act stipulates that a Data Fiduciary can only engage a Data Processor under a valid, legally binding contract—a Data Processing Agreement (DPA). Because the DPDP Act introduces vicarious liability—meaning the financial institution remains legally liable for any privacy failures caused by its vendors—banks and fintechs will enforce rigorous terms down to their CSPs.

Enforcing Purpose Limitation at the Cloud Layer

DPAs must explicitly state the exact scope, duration, and purpose of data processing. For a CSP, this means your platform terms must reassure clients that you will not use their hosted data for any secondary purposes.

Crucially, this prevents cloud providers from utilizing customer data transcripts, financial behavior patterns, or document uploads to train their own internal AI models, LLMs, or optimization algorithms without distinct, explicit authorization.

Architecting for Rule 8: The Erasure and Retention Paradox

The DPDP Rules introduce specific operational challenges regarding data lifecycle management, particularly under Rule 8. Under the privacy framework, when a consumer withdraws consent or the underlying commercial purpose is completed, the Data Fiduciary must erase the data. This requires CSPs to provide erasure-propagation capabilities. When a bank triggers a deletion API, that command must reliably cascade through:

• Block storage volumes and object storage buckets.
• Ephemeral caches and serverless execution logs.
• Read-replicas, snapshots, and immutable backup chains.

However, Rule 8 introduces a counter-requirement: CSPs and Fiduciaries must retain processing logs, system traffic data, and access histories for a minimum of one year from the date of processing to facilitate breach investigations and legal defense.

Your cloud platform must therefore decouple customer data from infrastructure telemetry. While the individual’s personal data must be cleanly deleted, the underlying security, network, and access logs must be safely archived in a localized, tamper-evident repository for at least 12 months.

3. Cryptographic Isolation and Multi-Tenancy Governance

Public cloud infrastructure runs on multi-tenancy—the sharing of physical compute, storage, and network hardware across thousands of disparate customers. For risk-averse financial regulators, multi-tenancy represents a potential attack surface where data could leak across logical boundaries.

To host regulated entities safely, CSPs must implement robust data isolation models.

Advanced Cryptographic Separation (BYOK & HYOK)

Logical separation via software-defined networking (SDN) or hypervisor controls is no longer sufficient on its own. Financial enterprises now demand strict cryptographic isolation. CSPs must provide comprehensive Bring Your Own Key (BYOK) and Hold Your Own Key (HYOK) infrastructures.

By integrating hardware security modules (HSMs) situated within Indian borders, banks can ensure that even if a cloud administrator or a rogue sub-processor accesses the raw storage blocks, the data remains unreadable. If the client holds the master keys externally, the CSP cannot decrypt the underlying financial data under any circumstance.

Tokenization Pipelines at the Edge

For entities processing credit card and debit card transactions, the RBI mandates strict card-on-file tokenization rules. CSPs must offer specialized, compliant edge-computing nodes inside India that intercept raw cardholder data at the point of ingestion, replace it with a secure token, and isolate the vault containing the actual card mapping in a highly restricted, ring-fenced database environment.

4. The 6-Hour Crucible: Incident Response and Forensic Telemetry

When a cybersecurity incident strikes a financial institution, the regulatory pressure intensifies. The RBI’s Master Directions on IT Governance mandate an aggressive timeline: regulated entities must report any cyber incident to the regulator within 6 hours of discovery. Concurrently, Rule 7 of the DPDP framework demands swift notification to both the Data Protection Board of India (DPBI) and affected individuals without undue delay.

Because a financial institution’s application runs on your cloud infrastructure, they cannot meet this 6-hour window unless your internal security operations are fully aligned with theirs.

Real-Time Forensic Provisioning

When a potential breach is flagged, the client's CISO team needs immediate access to system telemetry. CSPs must provide automated "Incident Report Packs" that deliver:

 

• Granular cloud audit trails showing exactly who accessed which object storage keys or database records.
• NetFlow logs indicating whether unauthorized data exfiltration occurred across external internet gateways.
• Snapshot capabilities to freeze compromised virtual machines or container instances for offline forensic analysis.

If your cloud support relies on a standard multi-day ticketing loop to extract and deliver network or access logs, you will directly cause your client to violate the 6-hour regulatory window. This exposure can lead to severe contractual liabilities and significant financial penalties.

5. Sub-Processor Accountability and Supply Chain Cascading

Modern hyper-scale clouds do not operate in a vacuum. They rely on an ecosystem of specialized sub-processors, third-party software marketplace vendors, and global engineering networks for continuous maintenance. However, under Section 8(1) of the DPDP Act, accountability cannot be offloaded. The primary Data Fiduciary remains liable, meaning they will scrutinize your entire supply chain.

Restricting Global Support Engineering Access

A major point of vulnerability for international CSPs is the "Follow-the-Sun" support model. If a database cluster in Mumbai experiences an outage at 2:00 AM IST, the ticket might automatically route to an on-call site reliability engineer (SRE) based in Europe or the United States.

If that foreign engineer accesses a live production environment containing unencrypted personal financial details, a cross-border data transfer has technically occurred.

To remain compliant, CSPs must offer "Sovereign Support" options. This guarantees that only screened personnel physically located within India can access infrastructure tiers where plain-text financial or personal data could potentially be exposed.

Downstream Sub-Processor Controls

If your cloud platform utilizes third-party SaaS tools or specialized microservices to provide features like automated log indexing, security analysis, or performance monitoring, those vendors are legally classified as sub-processors.

Under the DPDP Rules, you must contractually obligate every sub-processor to maintain equivalent security safeguards (Rule 6). You must also maintain an up-to-date, transparent register of these sub-processors, allowing your financial enterprise clients to review or object to any entity handling their downstream data pipelines.

6. Audit-Ready Foundations and Sovereign Assurances

Indian financial regulators do not operate on an honor system; they require definitive, auditable proof of compliance. Both the RBI and the DPBI reserve the "Right to Inspect" any infrastructure handling local financial data.

Physical and Logical Access for Auditors

Your contractual agreements must explicitly allow regulators or nominated third-party auditors (such as CERT-In empanelled auditors) to inspect your physical data center facilities, security control frameworks, and logical isolation boundaries within India.

Continuous Artifact Delivery

To help clients pass their annual regulatory reviews, CSPs should provide an on-demand compliance portal stocked with verified, localized artifacts:

 

• System Audit Reports (SAR): Specialized audits specifically mapped to RBI’s payment data localization circulars.
• SOC 2 Type II and ISO/IEC 27018 Certifications: Detailed reports confirming operational control over data privacy in public cloud environments.
• Tamper-Evident Logs: Cryptographically signed logs that prove local data retention parameters have been maintained without alteration for the required 12-month window.

Moving Forward: Privacy as a Competitive Advantage 🎯

For Cloud Service Providers in India, data localization and DPDP compliance should not be viewed merely as regulatory hurdles or checklist items handled by the legal department. They represent a fundamental shift in how enterprise software must be architected for the Indian market.

As financial institutions face increasing scrutiny from the RBI and the DPBI, they will naturally migrate toward infrastructure partners that minimize their compliance risk. Cloud providers that design their platforms with data residency by default, absolute cryptographic isolation, rapid forensic telemetry capabilities, and transparent supply chains will establish themselves as trusted operators in India's digital financial economy.

Building a compliant financial cloud requires shifting focus from simply providing raw compute power to establishing a secure, verifiable, and sovereign data perimeter.

Beyond the Sandbox: Navigating Container Runtime Threats and Cyber Resilience

In the fast-moving world of cloud-native development, containers have become the standard unit of deployment. But as we reach 2026, the "honeymoon phase" of simply wrapping applications in Docker images is long gone. We are now in an era where the complexity of our orchestration—Kubernetes, service meshes, and serverless runtimes—has outpaced our ability to secure it using traditional methods.

When we talk about securing containerized workloads, we often focus on the "Shift Left" movement: scanning images in the CI/CD pipeline and signing binaries. While vital, this is only half the battle. The real "Wild West" of security is Runtime. This is where code actually executes, where memory is allocated, and where attackers actively seek to break the "thin glass" of container isolation.

This blog dives deep into the architecture of container isolation, the modern runtime threat landscape of 2026, and the cyber resilience strategies required to satisfy both security engineers and rigorous global regulators.

1. The Anatomy of the Isolation Gap: Why Containers Aren't VMs

To secure a container, you must first understand what it actually is. A common misconception is treating a container like a lightweight Virtual Machine (VM). It is not. Containers differ from Virtual Machines (VMs) by operating at the OS level and sharing the host kernel, resulting in weaker, process-level isolation compared to hardware-level isolation. This shared-kernel architecture creates an "isolation gap" where container escapes can compromise the host, though it allows for higher density, faster startup times, and lower overhead.

The Shared Kernel Reality

A VM provides hardware-level virtualization; each VM runs its own full-blown guest Operating System (OS) on top of a hypervisor. If an attacker compromises a VM, they are still trapped within that guest OS.

Containers, conversely, use Operating System Virtualization. They share the host’s Linux kernel. To create the illusion of isolation, the kernel employs two primary features:

 

Namespaces: These provide the "view." They tell a process, "You can only see these files (mount namespace), these users (user namespace), and these network interfaces (network namespace)."

Control Groups (cgroups): These provide the "limits." They dictate how much CPU, memory, and I/O a process can consume.

The "Isolation Gap" exists because the attack surface is the kernel itself. Every container on a host makes system calls (syscalls) to the same kernel. If an attacker can exploit a vulnerability in a syscall (like the infamous "Dirty Pipe" or "Leaky Vessels" of years past), they can potentially escape the container and take control of the entire host node.

2. The Runtime Threat Landscape: Cyber Risks Exploded

The container runtime threat landscape has "exploded" due to the rapid shift toward microservices and cloud-native environments, where containers are often short-lived and share the same host OS kernel. In 2023, approximately 85% of organizations using containers experienced cybersecurity incidents, with 32% occurring specifically during runtime. The primary danger at runtime is that containers are active and operational, making them targets for sophisticated attacks that bypass static security. Here are the primary cyber risks facing containerized workloads today.

A. Container Escape and Kernel Exploitation

The holy grail for an attacker is a Container Breakout. In a multi-tenant environment (like a shared Kubernetes cluster), escaping one container allows an attacker to move laterally to other containers or access sensitive host data. We see attackers using automated fuzzing to find "zero-day" vulnerabilities in the Linux kernel’s namespace implementation, allowing them to bypass seccomp profiles that were once considered "secure enough."

B. The "Poisoned Runtime" (Supply Chain 2.0)

Attackers have realized that scanning a static image is easy to bypass. A "Poisoned Runtime" attack involves an image that looks perfectly clean during a static scan but downloads and executes malicious payloads only once it detects it is running in a production environment (anti-sandboxing techniques). This makes runtime monitoring the only way to detect the threat.

C. Resource Exhaustion and "Side-Channel" Attacks

With the rise of high-density bin-packing in Kubernetes, "noisy neighbor" issues are no longer just a performance problem; they are a security risk. A malicious container can intentionally trigger a Denial of Service (DoS) by exhausting kernel entropy or memory bus bandwidth, affecting all other workloads on the same physical hardware.

D. Credential and Secret Theft via Memory Scraping

Containers often hold sensitive environment variables and secrets (API keys, DB passwords) in memory. Without memory encryption, a compromised process on the host—or even a privileged attacker in a neighboring container—might attempt to scrape the memory of your application to extract these high-value targets.

E. Resource Hijacking

Malicious actors often use compromised containers for unauthorized activities like cryptocurrency mining, which can consume significant compute resources and impact application performance.

3. Advanced Isolation Mechanisms: Hardening the Sandbox

Containers provide lightweight isolation using Linux kernel features like namespaces and cgroups, but because they share the host kernel, they are susceptible to container escape vulnerabilities. Hardening the sandbox involves moving beyond basic containerization to advanced, secure runtime technologies, implementing the principle of least privilege, and utilizing kernel security modules.

Micro-VMs: Kata Containers and Firecracker

Kata uses a lightweight hypervisor to launch each container (or Pod) in its own dedicated kernel. Micro-VMs (like AWS Firecracker) and Kata Containers provide enhanced security over traditional containers by offering hardware-level isolation while maintaining fast startup times. They combine VM security with container speed, using dedicated kernels for each workload to isolate untrusted code, ideal for serverless and multi-tenant applications.

Pro: Strong hardware-level isolation.

Con: Slightly higher memory overhead and slower startup times compared to native containers.

User-Space Kernels: gVisor

Developed by Google, gVisor acts as a "guest kernel" written in Go. Instead of the container talking directly to the host kernel, it talks to gVisor (the "Sentry"), which filters and handles syscalls in user space. gVisor implements a user-space kernel to provide strong isolation for containerized applications. Unlike standard containers which share the host kernel, gVisor acts as a robust security boundary by intercepting system calls before they reach the host's operating system.

 

Pro: Massive reduction in the host kernel's attack surface.

Con: Significant performance overhead for syscall-heavy applications (like databases).

The Rise of Confidential Containers (CoCo)

Confidential Containers (CoCo) is a Cloud Native Computing Foundation (CNCF) sandbox project that secures sensitive data "in-use" by running containers within hardware-based Trusted Execution Environments (TEEs). It protects workloads from unauthorized access by cloud providers, administrators, or other tenants, making it crucial for cloud-native security, compliance, and hybrid cloud environments.

CoCo is gaining momentum due to the urgent need for "zero-trust" security in cloud-native AI workloads and the increasing focus on data privacy regulations. The project has gained widespread support from major hardware and software vendors including Red Hat, Microsoft, Alibaba, AMD, Intel, ARM, and NVIDIA.

 

Pro: CoCo is vital for industries like BFSI and healthcare to comply with strict regulations (e.g., DPDP, GDPR, DORA) by running workloads on public clouds without exposing customer data to cloud administrators.

Con: CoCo requires specialized hardware that supports confidential computing, which may limit cloud provider options or necessitate hardware upgrades on-premise..

4. Cyber Resilience Strategies: From Detection to Immunity

True cyber resilience isn't just about preventing an attack; it's about how quickly you can detect, contain, and recover from one. Building a cyber-resilient container infrastructure requires moving beyond traditional reactive security towards a "digital immunity" model, where security is integrated into the entire application lifecycle—from coding to runtime. This strategy involves three core pillars: proactive Detection and visibility, Active Defense within pipelines, and Structural Immunity through automation and isolation.

eBPF: The Eyes and Ears of the Kernel

eBPF (extended Berkeley Packet Filter) is the gold standard for runtime observability. It acts as the "eyes and ears" of the Linux kernel, enabling deep, low-overhead observability and security for containers without modifying kernel source code. eBPF allows running sandboxed programs at kernel hooks (e.g., syscalls, network events), providing real-time, tamper-resistant monitoring of file access, network activity, and process execution.

Tools like Falco and Tetragon use eBPF to hook into the kernel and monitor every single syscall, file open, and network connection without significantly slowing down the application.

Strategy: Implement a "Default Deny" syscall policy. If a web server suddenly tries to execute bin/sh or access /etc/shadow, eBPF-based tools can detect it instantly and trigger an automated response.

Zero Trust Architecture for Workloads

Zero Trust Architecture (ZTA) for containers removes implicit trust, enforcing strict authentication, authorization, and continuous validation for every workload, regardless of location. It utilizes micro-segmentation, cryptographic identity (SPIRE), and mTLS to prevent lateral movement. Key approaches include least-privilege policies, behavioral monitoring, and securing the container lifecycle from build to runtime.

Strategy: Implement tools that learn service behavior and automatically create "allow" policies, reducing manual effort and minimizing over-permissioned workloads.

Identity-Based Microsegmentation: Use a CNI (like Cilium) that enforces network policies based on service identity rather than IP addresses.

Short-Lived Credentials: Use tools like HashiCorp Vault or SPIFFE/SPIRE to issue short-lived, mTLS-backed identities to containers, making stolen tokens useless within minutes.

Immutable Infrastructure and Drift Detection

Immutable infrastructure in containerized environments means containers are never modified after deployment; instead, updated versions are redeployed, ensuring consistency and security. This approach mitigates configuration drift, where running containers deviate from their original image, a critical security risk. Drift detection tools, such as Sysdig or Falcon, identify unauthorized file system changes, aiding security.

A resilient system assumes that any change in a running container is an IOC (Indicator of Compromise).

Strategy: Deploy containers with a Read-Only Root Filesystem. If an attacker tries to download a rootkit or modify a config file, the write operation will fail. Pair this with drift detection that alerts you whenever a container's runtime state deviates from its original image manifest.

5. Standards and Regulations: The Compliance Mandate

Securing your workloads is no longer just "best practice"—it's a legal requirement. Container compliance involves adhering to security baselines (NIST, CIS Benchmarks) to protect data, while physical container compliance focuses on structural integrity, safety, and international transport regulations (ISO, CSC).

NIST SP 800-190: The North Star

NIST Special Publication 800-190, titled the Application Container Security Guide, is widely regarded as the "North Star" or foundational framework for securing containerized applications and their associated infrastructure. Released in 2017, it provides practical, actionable recommendations for addressing security risks across the entire container lifecycle—from development to production runtime.

The NIST Application Container Security Guide remains the definitive framework. It breaks container security into five tiers:

 

1. Image Security: Focuses on preventing compromised images, scanning for vulnerabilities, ensuring source authenticity, and avoiding embedded secrets.
2. Registry Security: Recommends using private registries, secure communication (TLS/SSL), and strict authentication/authorization for image access.
3. Orchestrator Security: Emphasizes limiting administrative privileges, network segmentation, and hardening nodes.
4. Container Runtime Security: Requires monitoring for anomalous behavior, limiting container privileges (e.g., non-root), and using immutable infrastructure.
5. Host OS Security: Advises using container-specific host operating systems (e.g., Bottlerocket, Talos, Red Hat CoreOS) rather than general-purpose OSs to minimize the attack surface.

CIS Benchmarks

CIS Benchmarks for containers provide industry-consensus, best-practice security configuration guidelines for technologies like Docker and Kubernetes. They help harden container environments by securing host OS, daemons, and container runtimes, reducing attack surfaces to meet audit requirements. Key standards include Benchmarks for Docker and Kubernetes.

The Center for Internet Security (CIS) released major updates in early 2026 for Docker and Kubernetes. These benchmarks now include specific mandates for:

 

• Enabling User Namespaces by default to prevent root-privilege escalation.
• Strict requirements for seccomp and AppArmor/SELinux profiles for all production workloads.

EU Regulations: NIS2 and DORA

NIS2 (Directive (EU) 2022/2555) and DORA (Regulation (EU) 2022/2554) are critical EU regulations strengthening digital resilience, applying to containerized environments by enforcing strict security, risk management, and incident reporting. NIS2 requires implementation by Oct 17, 2024, for broad sectors, while DORA, effective Jan 17, 2025, specifically mandates financial entities to manage ICT risks, including third-party cloud providers.

For those operating in or with Europe, the NIS2 Directive and the Digital Operational Resilience Act (DORA) have set a high bar.

 

• NIS2: Requires "essential" and "important" entities to manage supply chain risks and implement robust incident response.
• DORA: Specifically targets the financial sector, demanding that containerized financial applications pass "Threat-Led Penetration Testing" (TLPT) to prove they can withstand sophisticated runtime attacks.

Regulatory Requirements in India:

Cloud computing and containerization in India are governed by a rapidly evolving framework designed to secure digital infrastructure, ensure data localization, and standardize performance, particularly as the nation scales its AI-ready data center capacity. The regulatory environment is primarily driven by the Ministry of Electronics and Information Technology (MeitY), the Bureau of Indian Standards (BIS), and CERT-In.

Some of the Key requirements relevant to Containerized workloads are:

• KSPM (Kubernetes Security Posture Management): Organizations must conduct quarterly audits of cluster configurations, including Role-Based Access Control (RBAC) and network policies.
• Image Security: Mandates scanning container images for vulnerabilities before deployment to ensure only signed, verified images are used.
• Least Privilege: Strict enforcement of the principle of least privilege across all containerized workloads, using tools to revoke excessive permissions.

Conclusion: The "Immune System" Mindset

The goal of container security has shifted. We are moving away from trying to build an "impenetrable fortress" and toward building a digital immune system.

By combining Hardened Isolation (like Kata or gVisor) with Runtime Observability (eBPF) and Confidential Computing, we create an environment where threats are not just blocked, but are identified and neutralized with surgical precision.

The future of securing containerized workloads lies in acknowledging that the runtime is volatile. By embracing cyber resilience—informed by standards like NIST and enforced by modern isolation technology—you can ensure your workloads remain secure even when the "glass" of the container is under pressure.

Key Takeaways

• Don't rely on runc for high-risk workloads: Explore sandboxed runtimes.
• Make eBPF your foundation: It provides the visibility you need to satisfy NIS2/DORA.
• Automate your response: Detection is useless if you have to wait for a human to wake up and "kubectl delete pod."
• Hardware matters: Look into Confidential Containers for your most sensitive data processing.