Architectural shift	Key characteristics	Why legacy security struggles	Consequence
Monolith → Microservices	Hundreds of independently deployed services; each exposes its own API, often using REST/JSON, gRPC, or GraphQL; services communicate east–west inside a cluster	Perimeter‑based WAFs see only the gateway/edge traffic and can’t inspect internal service‑to‑service calls; static rules can’t keep up with frequent changes and dynamic endpoints	Explosion in attack surface; blind spots inside service mesh; rule drift leading to high false negatives and noisy false positives
On‑prem → Cloud & Hybrid	Elastic containers and functions spin up and down; workloads spread across multiple clouds, regions, and AZs; all traffic is encrypted end‑to‑end	Traditional appliances expect fixed IPs and a defined perimeter; they can’t see traffic inside zero‑trust networks or across clouds; sending all traffic to a central sensor adds latency and costs	Coverage gaps across clouds, inconsistent policies, runaway egress costs, and missed attacks hidden inside encrypted east–west flows
Traditional code → AI‑native	LLM‑driven agents and autonomous services make decisions and call APIs and MCP tools on behalf of users; behaviour is non‑deterministic, and input can contain adversarial prompts	Signature‑based tools don’t understand prompts or model outputs; ACLs allow machine‑to‑machine calls without checking context; hard to baseline “normal” for an AI agent	Emergence of new attack vectors (prompt injection, data‑poisoning, AI‑assisted exfiltration) that go undetected; legitimate AI actions misclassified or vice versa, causing business disruption