Browse past weeks of engineering reads.
Cloudflare's existing server fleet could not keep pace with rapidly growing global traffic demands, requiring a new generation of hardware with significantly higher compute and network throughput.
Cloudflare needed to significantly increase edge compute throughput per server but faced a tradeoff where high-core-count CPUs came with smaller per-core L3 cache, risking latency penalties for cache-dependent workloads.
Customers needed precise control over where their data is processed geographically to meet diverse compliance requirements (e.g., GDPR, data sovereignty laws), but existing pre-defined regional options were too coarse-grained to cover all regulatory and performance needs.
Running large AI models for agent workloads on edge infrastructure was cost-prohibitive and required significant inference stack optimization to serve models like Kimi K2.5 efficiently at scale.
Enterprise SASE (Secure Access Service Edge) migrations traditionally take 18+ months due to architectural complexity, requiring organizations to integrate networking and security across global infrastructure.
The Cloudflare One SASE client's Proxy Mode relied on user-space TCP stacks for tunneling traffic, introducing significant overhead that limited throughput and increased latency for end users.
Tunnel layering in Cloudflare's WARP/One client caused MTU mismatches, leading to silently dropped oversized packets that degraded connectivity and resilience.
Enterprises connecting multiple private networks via tunnels frequently encounter overlapping IP address ranges (e.g., multiple sites using 10.0.0.0/8), making traditional routing tables unable to determine which tunnel should receive return traffic.