Conquering Complexity with New Rules for Application Delivery in the AI Era

The tangled web of legacy application delivery strategies and siloed approaches creates challenges so universal they’ve become the status quo. Here’s the reality of today’s hybrid, multicloud world:

• Too many point solutions: Every problem gets its own tool, and none of them talk to each other.
• Multiple management consoles: Fragmented interfaces lead to operational headaches.
• Policy inconsistency nightmares: Policies differ across environments, creating gaps in security and governance.
• Manual complexity: Over-reliance on human intervention slows everything down.
• Lack of interoperability: Siloed systems create a Tower of Babel effect.
• Incomplete observability: Monitoring tools live in isolation, leaving visibility gaps across the delivery chain.

These challenges are so widespread they’ve been codified in "The Application Delivery Top 10." Tackling these issues demands a new playbook. 

The next generation of Application Delivery Controllers (ADCs) isn’t about incremental improvements—it’s about resetting the foundation. These six principles don’t just address the challenges; they cancel out complexity at its core. 

Hybrid, multicloud environments demand end-to-end security baked into every aspect of delivery. Modern ADCs integrate security at every layer, protecting applications against modern threats while ensuring smooth delivery.

• Policy inconsistency nightmares: Unified security ensures policies are consistent across all environments.
• Incomplete observability: Integrated security provides insights into application performance and potential vulnerabilities.
• Too many point solutions: Combining security and delivery eliminates the need for separate tools.

Example: An ADC with built-in distributed denial-of-service (DDoS) protection, web application firewall (WAF), and API security ensures that apps are secure and efficiently delivered—everywhere.

Hybrid multicloud demands flexibility. ADCs must operate seamlessly across hardware, software, containers, and cloud-native environments. This adaptability reduces silos and aligns with dynamic strategies.

• Multiple management consoles: Unified form factors reduce the need for disparate tools.
• Lack of interoperability: ADCs compatible with diverse environments eliminate friction.
• Manual complexity: Consistency across deployments streamlines management.

Example: A containerized ADC deployed in Kubernetes clusters ensures consistent app delivery across on-prem and cloud setups without extra overhead.

Consistent controls eliminate policy fragmentation and simplify governance. A consistent management interface provides a reliable, familiar way to manage multiple points of control. 

• Policy inconsistency nightmares: Consistent policy management ensures alignment across all clouds.
• Manual complexity: Familiar tools and APIs reduce configuration errors and speed up operations.
• Too many point solutions: A single interface for controls minimizes the need for disparate tools.

Example: A consistent interface for traffic policies, security rules, and analytics empowers teams to deliver applications faster and more securely with tools and APIs they already know. This isn’t the old “single pane of glass” vision; it’s about achieving consistency in controls, policies, and APIs across every environment.

Visibility is non-negotiable in hybrid, multicloud. Advanced analytics offer real-time insights into performance, user experience, and security.

• Incomplete observability: Centralized analytics fill visibility gaps across environments.
• Policy inconsistency nightmares: Analytics identify and address policy enforcement gaps.
• Manual complexity: Automated insights streamline troubleshooting and decision-making.

Example: An ADC with real-time dashboards reveals traffic patterns, app performance, and potential security threats in near-real time while insights provide potential actions to mitigate issues before they become problems.

Programmable ADCs allow for deep customization, from traffic handling to security policies. This flexibility is essential for modern hybrid workloads.

• Too many point solutions: Programmable data planes consolidate functionality into one platform.
• Lack of interoperability: Customization ensures compatibility across diverse systems.
• Manual complexity: Automation of repetitive tasks reduces operational effort.

Example: Custom routing logic for AI-driven workloads optimizes delivery without additional infrastructure.

Automation is the antidote to manual complexity. From deployment to scaling, automation simplifies application delivery across distributed environments.

• Manual complexity: Automation eliminates human error and accelerates processes.
• Policy inconsistency nightmares: Automated enforcement ensures compliance everywhere.
• Incomplete observability: Continuous monitoring and automated responses close the loop.

Example: Automatically provisioning ADCs during app deployment speeds up delivery and reduces admin workload.