6 Processes to Automate When Implementing Microsegmentation

Over 95% of security leaders agree microsegmentation is key to strengthening cyber defenses, yet just 5% of organizations are microsegmenting their networks today. Why do so many microsegmentation projects stall or fail outright – if they ever start at all?  

Implementation complexity and costs, disruption to existing operations, dealing with legacy applications, ongoing maintenance, and more top security leaders’ lists of concerns about microsegmentation, creating a long-standing impression that microsegmentation is an unattainable gold standard. 

Legacy segmentation solutions – which rely on network-level controls or agents deployed on endpoints to implement policies – are complex to deploy and maintain, introducing a significant manual burden for security teams. But modern microsegmentation solutions have evolved beyond legacy challenges; today, automation makes it possible to deploy and maintain microsegmentation without the manual burden that historically undermined it. 

We’ll explore how security teams can assess automated capabilities to ensure they’re not trading accuracy for efficiency and outline six processes every organization should automate to implement microsegmentation faster, ease long-term operational debt, and close security gaps – all while cutting costs.

Deterministic, Human-on-the-Loop Automation: How to Cut Complexity When Deploying Microsegmentation at Scale  

We’re intentionally focusing on human-on-the-loop automation because, while artificial intelligence has enormous potential in security, it has to be applied carefully. At Zero, we take a pragmatic approach: we use AI where it improves visibility and user speed, but we do not rely on AI for enforcement decisions that must be precise and deterministic.  

In other words, we believe the most effective use of automation in a microsegmentation project isn’t to replace human judgement like AI would but to operationalize it. Deterministic, human-on-the-loop automation operates on defined logic rather than probabilistic guesswork while keeping security teams in control of outcomes.  

For example, Zero Networks’ automation engine learns allowed network behaviors in order to create dynamic rules for identities and assets. As Chris Boehm, Zero Networks Field CTO, points out, this type of deterministic automation hinges on learning:

In other words, deterministic automation relies on learned realities rather than educated guesses, which are central to probabilistic approaches. Keeping a human on the loop to optionally review, approve, or fine-tune policies in a sandbox environment is a key safeguard for peace of mind while still shrinking manual effort.  

Automation Priorities: How to Implement Microsegmentation Faster and More Accurately 

Automation isn’t just a theoretical benefit for microsegmentation projects – security teams and industry leaders recognize it as key to segmentation success.  

Research from Enterprise Management Associates (EMA) on the maturing microsegmentation market found that security leaders highly value robust automation capabilities in microsegmentation solutions; they’re prioritizing fast, automated asset discovery and tagging that scales with growing environments, as well as automated policy creation and lifecycle management that reduces manual effort and ensures consistent enforcement.  

ViB Tech research echoes the importance of automation, with 88% of security leaders ranking automated policy creation as an important factor when selecting a microsegmentation solution.   

Similarly, CISA’s latest Microsegmentation in Zero Trust guidance reinforces that segmentation policies need to evolve dynamically using contextual data, and Gartner’s 2025 Hype Cycle for Workload and Network Security recommends seeking a microsegmentation solution that maps application paths and makes policy recommendations by leveraging automation.  

Insights like these help clarify a prioritized automation roadmap for security leaders looking to streamline microsegmentation initiatives. To unlock the greatest value from automation, organizations should start by prioritizing these six high-impact automation opportunities.  

1. Comprehensive Environment Discovery  

Before microsegmentation can be enforced, teams need a complete, accurate picture of every network asset, identity, and activity. Manually building this inventory is slow, error-prone, and outdated almost immediately. Any segmentation strategy built on a static or incomplete map starts with structural blind spots baked in. 

Automated discovery changes the starting point entirely. Rather than relying on spreadsheets or periodic audits, real-time network mapping builds a live, comprehensive view of the environment. Even in large environments, this end-to-end visibility can be achieved within hours of deployment thanks to robust automation, replacing weeks of manual effort with a foundation that stays current as the environment evolves. As a result, the “project before the project” that stalls many microsegmentation initiatives is virtually erased.  

2. Monitor and Learn All Network Connections 

After discovering what's in the environment, a microsegmentation solution needs to understand network behavior: which assets communicate, how frequently, and under what conditions? From an identity perspective, what logon activities, account behaviors, and asset access patterns must be preserved to tighten access controls while maintaining user productivity?  

With labor-intensive segmentation approaches, this learning phase requires security teams to reconstruct communication baselines from log data, interview application owners, and piece together flow information from disparate tools. As a result, policies built on stale or incomplete baselines often produce over-permissive rules that leave gaps, or over-restrictive rules that break operations. 

Automated learning replaces manual effort with continuous, structured observation. A real-time learning engine monitors network activity to build a comprehensive knowledge base of actual communication patterns, grounding policy generation in real network behavior.  

3. Asset Tagging and Grouping  

Raw inventory isn't enough. For microsegmentation to work at scale, assets need to be organized into meaningful groups by function, application, criticality, or business context so that policies can be applied consistently and maintained without becoming unmanageable. 

Manual tagging is a well-known bottleneck in traditional segmentation projects. Teams might spend weeks or months classifying assets, debating taxonomy, and resolving conflicts between IT, security, and application owners. The output is often inconsistent, incomplete, or immediately stale as the environment changes. 

Automated tagging uses observed network behavior to group assets intelligently, mapping them to the communication patterns and business areas they actually serve. This transforms a months-long classification effort into a clear, policy-ready foundation and keeps groupings accurate as workloads evolve, without requiring manual reclassification every time a change occurs.  

4. Policy Creation and Simulation  

After establishing comprehensive network visibility, learning legitimate behavior, and organizing those insights, the next step is translating that knowledge into enforceable policy. But manually writing granular rules for every asset and identity in a large enterprise is an enormous undertaking – and once written, those rules require constant tuning to stay accurate. 

Automated policy generation flips this model. After learning normal communication patterns from observed network behavior, an automated solution uses that baseline to generate precise policies. This approach delivers the tailored, accurate coverage that would take a security team months or years to achieve manually in a fraction of the time. 

Critically, automation here doesn't mean blind enforcement. With a deterministic, human-on-the-loop approach, policies move through simulation and staged rollout before going live. Teams can review proposed rules, test them against real traffic in a sandbox environment, and approve enforcement at their own pace, catching potential disruptions before they impact operations.  

5. Policy Lifecycle Management  

Modern environments change constantly as new applications are deployed, workloads migrate, and communication pathways shift – static rules create gaps and exceptions that accumulate into long-term drift. This is one of the most common reasons microsegmentation efforts fail to yield the promised results, and it doesn’t happen at deployment, but in the months and years that follow. 

Automated lifecycle management keeps policies aligned with reality on a continuous basis. Rather than relying on periodic manual audits or reactive updates triggered by incidents or change requests, the automated solutions maintain visibility into the network and adapt policies as conditions evolve. Access paths that are no longer used are automatically closed, new communication patterns are incorporated, and rule sprawl and privilege creep are structurally prevented rather than periodically cleaned up. 

6. Just-in-Time Access Enforcement 

One of the most persistent vulnerabilities in enterprise networks is always-on access. Admin protocols, privileged pathways, and internal services that are permanently reachable create lateral movement highways that exist regardless of whether they're being actively used. 

Just-in-time (JIT) access enforcement automates the opening and closing of these pathways based on verified identity and context. Rather than leaving privileged access permanently available, access is granted only when explicitly requested, only after identity verification, and only for the duration it's needed. Outside of those verified windows, the paths are closed. 

This ensures the protection of comprehensive microsegmentation can’t be voided by a single compromised credential. An attacker who gains an initial foothold via a valid identity with privileged access still cannot reach sensitive systems or move laterally through admin protocols without hitting another roadblock.  

Automation makes this practical at scale: JIT enforcement that would be operationally impossible to manage manually becomes a consistent, reliable control across the entire environment when network-layer MFA is integrated with automated microsegmentation.  

Real-World Example: How a Global Shipping Leader Automated Segmentation   

Mediterranean Shipping Company (MSC) operates across a global network of 675+ local offices in 155 countries. The organization needed a way to harden its network quickly and comprehensively – without slowing operations or introducing instability across its global footprint. 

But manual segmentation was slow to scale, requiring countless hours of log analysis and manual rule maintenance for only partial coverage. Meanwhile, MSC had limited visibility into internal traffic patterns, which complicated policy creation.  

By adopting granular, automated microsegmentation from Zero Networks, MSC offloaded the manual effort of discovery, learning, and policy management to successfully segment roughly 95% of its servers – after previously spending more than a year on manual-intensive strategies.  

“What once took more than a year of manual work and endless log analysis is now fully automated. We’ve segmented about 95% of our environment, gained complete visibility into network activity, and dramatically strengthened our defenses.” 

- Sergio Fedelini, SVP, IT Infrastructure, MSC 

Automate Microsegmentation to Strengthen Cyber Resilience with Zero 

While microsegmentation was once too slow to deploy, too costly to maintain, and too fragile to sustain under real-world conditions, times have changed – with deterministic, human-on-the-loop automation, Zero Networks’ identity-based microsegmentation solution delivers comprehensive protection in a fraction of the time.  

Zero provides immediate visibility into every identity and asset on the network, then automatically enforces adaptive, identity-aligned policies that prevent lateral movement by default. As a result, the average Zero customer segments 90% of their environment within 90 days.  

Automated, adaptive enforcement also eliminates long-term operational debt while enabling teams to scale protection across production environments. In fact, Zero cuts costs by 87% for the typical enterprise thanks to our advanced automation capabilities.  

Learn how you can automate segmentation with Zero Networks to achieve comprehensive protection in a fraction of the time – request a demo.