As a security leader, you’re likely familiar with the promise of the cloud: agility, innovation and operational simplicity. But the reality has become a state of profound fatigue. Your teams are navigating a complex patchwork of tools across multiple clouds, providers and accounts. The core issue isn’t a lack of security tooling; it’s the fragmentation of control that is fundamentally breaking legacy security models.

We’ve reached a critical inflection point in cloud security. What we hear consistently from CISOs isn’t just about managing threats—it’s about managing complexity. Even the most capable engineering teams are tired of replatforming, switching consoles, and trying to reconcile risks they can’t fully see. When control is fragmented, risk accelerates. This is the new reality of the cloud, and it’s messy.

The Myth of "Good Enough" Security

In these dynamic environments, many organizations default to the native firewalls their cloud service providers (CSPs) offer, believing the solutions are “good enough.” It’s an understandable choice – they are simple to deploy. But this simplicity creates a dangerous illusion of security, leaving significant gaps that advanced attackers are all too willing to exploit.

These native tools provide only the most basic controls. Specifically, they lack the enterprise-grade capabilities required to stop modern threats. This means:

No Advanced Threat Prevention

They do not provide the deep, Layer 7 inspection or AI-powered analysis needed to stop evasive, zero-day exploits and malware that bypass simple signature-based detection.

No Dynamic or Context-Aware Policy

They rely on static, IP-based rules, which are completely ineffective in dynamic cloud environments where workloads and identities constantly change. They cannot use the cloud’s own language, like tags or application context, for policy enforcement.

No Unified Multicloud Management

Native tools are siloed to a single cloud. This leads to fragmented visibility, inconsistent policies and a dramatic increase in operational complexity for teams trying to secure a multicloud footprint.

No Enterprise AI Security

They are not equipped to protect against emerging AI-specific attacks, such as prompt injection and model theft, leaving your most valuable new workloads exposed.

One recent benchmark found that while Cloud NGFW for AWS from Palo Alto Networks blocked over 95% of exploits, AWS Network firewall blocked just under 4% of those attacks. Similarly, Azure firewall only blocked 18% of exploits while Cloud NGFW for Azure also blocked 95%. These aren’t just statistics; they represent critical, enterprise-level blind spots.

It’s Not a Tooling Problem — It’s an Operating Model Problem

The core issue is that your security model still assumes a static, on-premises infrastructure in a world that is anything but. Workloads are ephemeral. IP addresses shift constantly. Identity, not an IP address, now drives access. You simply cannot enforce a meaningful policy on a moving target with tools built for a stationary target.

This isn’t a problem you can solve by adding another disparate tool to the stack. Doing so only adds to the noise and complexity that is burning out your team.

It requires a new operating model where protection is infrastructure-aware, follows the workload and adapts in real-time. It’s time to move beyond the limitations of native security and build a strategy that aligns with how your cloud actually operates, not the other way around.

In our next post, we’ll explore how a fully managed firewall as a service (FWaaS) provides this new operating model, unifying control and delivering superior security without the operational burden.

Ready to assess your current risk? Run our free, no-obligation Cloud & AI Risk Assessment (CLARA) to identify gaps and exposures across your cloud environments.