Blog posts on ADC Top 10
Application Delivery Top 10
ADC Top 10 blog posts(6)
AI App Delivery Top 10: Inability to handle latency
AI makes latency a trust problem, not just performance: slow “assistant” responses feel like hesitation or failure, and token-heavy prompts/outputs expand work even on healthy systems.
By Lori Mac Vittie
AI App Delivery Top 10: Unoptimized traffic steering
AI breaks traditional traffic steering assumptions: backends aren’t interchangeable, costs vary, and agents fan out unpredictably—so routing must account for model, GPU health, and data locality.
By Lori Mac Vittie
AI App Delivery Top 10: Insufficient Traffic Controls
Traditional rate limits and throttles miss the real blast radius. AI workloads fan out across models, vector stores, and services, driving latency spikes, cascading failures, and retries.
By Lori Mac Vittie
AI App Delivery Top 10: Incomplete observability
AI won’t scale by itself. Without a unified control plane that collapses tooling and ownership boundaries, inference becomes the most brittle and coordination-heavy tier.
By Lori Mac Vittie
AI App Delivery Top 10: Lack of fault tolerance and resiliency
AI makes classic resiliency gaps far more costly: single GPU or dependency failures cascade through synchronous inference chains, compounding latency and degrading outputs.
By Lori Mac Vittie
AI App Delivery Top 10: Weak DNS practices
For inference and agentic systems, DNS resilience is critical to availability and performance—bad resolution means misrouting, latency spikes, and service blackouts across regions.
By Lori Mac Vittie