Cloudflare Redesigned 1.1.1.1 DNS Cache System
The company reduced per-entry memory usage by 56 percent, freeing 100 terabytes of memory across its infrastructure.
Updated on Sept. 23, 2026 in Data Centers

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Cloudflare optimized the in-memory representation of its 1.1.1.1 DNS cache to improve efficiency, completing the rollout on July 6, 2026. This technical redesign reduced memory consumption by 100 terabytes while supporting over 250 billion cache entries.
Why it matters
The upgrade significantly lowers infrastructure overhead by decreasing both memory footprint and lookup latency. These improvements allow for greater cache capacity, which enhances the overall performance and responsiveness of the global DNS service.
Cloudflare reduced p99 resident memory from 9.3 GB to 5.3 GB per instance by replacing Vec and String types with Box structures. Per-entry footprint fell from 953 bytes to 420 bytes, while cache insertion throughput rose by 43 percent.
The players
Cloudflare
Cloudflare is a global technology company that provides content delivery networks, cybersecurity services, and distributed domain name server services.
The details
Engineers optimized the system by packing Booleans into bitflags and storing record data in a contiguous byte buffer using the DNS wire format. These structural changes effectively decreased allocation overhead, leading to a 19 percent reduction in lookup latency.
Timeline
The rollout of memory optimization began on May 18, 2026.
The rollout of memory optimization concluded on July 6, 2026.
The Tech Race
This transition to high-density memory storage reflects a broader industry trend toward maximizing hardware efficiency in large-scale distributed systems. The redesign positions Cloudflare to handle growing internet traffic volumes without requiring proportional increases in physical server footprints.
Users benefit from faster domain lookups due to the 19 percent reduction in latency, resulting in quicker website load times. The increased cache capacity also ensures more consistent service availability during traffic spikes across the global network.
The takeaway
Optimizing data structures remains a critical strategy for managing the massive scale of modern internet services. These efficiency gains demonstrate how technical backend refinements can produce tangible improvements in speed and capacity for global users.
Further reading
For more information on infrastructure scaling and performance, visit Data Centers.
Source note: This article includes information reported by InfoQ.
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