Why Anycast DNS isn't automatically faster – real-world tests & pitfalls

Anycast DNS sounds like a shortcut to low latency, but real measurements show: Anycast does not automatically deliver the best response time. I explain why anycast DNS often falls short of expectations in tests, what pitfalls arise, and how I realistically evaluate performance—with clear metrics and actionable steps for improvement. Latency.

Key points

I'll summarize the key findings so you know right away what's important. Anycast First, caching dominates perceived DNS speed far more than proximity to the anycast node. Second, BGP does not make geographical decisions but follows policies, which can cause suboptimal paths. Third, more nodes do not automatically solve latency problems, but in some cases increase dispersion. Fourth, measurement methods must combine the end-user view and the server perspective, otherwise blind spots remain. Fifth, true optimization arises from the interplay of routing, caching, monitoring, and clean control of the TTL.

• Caching User latency dominates; root queries are rare.
• BGP can lead to incorrect, longer paths.
• More Nodes sometimes increase misclassifications.
• Measurement requires client and server view.
• TTL and peering beat raw distance.

How Anycast DNS really works

Anycast distributes identical IPs across multiple locations, and BGP directs requests to the „next“ path from a routing perspective, not necessarily to the nearest one. Data Center. In audits, I often see that peering, local provider policies, and prefix lengths have a greater impact on the route than geography. This means that latency shifts noticeably depending on the time of day, utilization, and network events. Those who expect geo-logic are actually looking at policy logic with many variables. A comparison with GeoDNS helps to classify this, as different procedures solve different problems. Problems – a quick overview: GeoDNS vs Anycast – quick routing check.

Caching beats proximity: Root and TLD reality

The effect of the Caches the user experience. Studies by APNIC and RIPE show that TLD records can often be retained for up to two days, and typical users trigger root queries less than once a day. This low frequency minimizes the supposed advantage of minimal anycast latency at root level for everyday use. For large ISP resolvers, this means that the root path does not have a noticeable impact on the majority of traffic. I therefore prioritize measuring latency to authoritative name servers and resolvers, because that is where the really relevant Times.

Why Anycast is not automatically faster

In a series of measurements conducted by an anycast CDN, around 20% of clients ended up on a suboptimal front end, which generated an average of around 25 ms of additional latency; around 10% even saw 100 ms and more, as documented in the IMC study. 2015. These values may seem small, but with many requests or TLS handshakes, the effect adds up significantly. BGP decisions, sudden topology changes, and peering asymmetries drive this dispersion. I have observed that additional locations above a certain number increase the probability of misassignment because routing policies differ. Anycast therefore often performs well in the median, but can be painful in the quantiles. Outliers produce.

Context is key: DNS, CDN, and BGP fine-tuning

CDNs with highly latency-sensitive content invest in BGP fine-tuning, aligning prefixes and communities so that paths with fewer hops and better peering are given priority. Microsoft is often cited as an example of how smart announcements bring users closer to high-performance edges. steer. For DNS services without strict latency requirements, this effort is not always worthwhile; availability and resilience then trump the last millisecond. In addition, the lifetime of DNS responses has a decisive influence on perceived speed. Those who optimal DNS TTL saves users many round trips and reduces latency spikes in the long term – often more effectively than another POP in the Net.

Measurement methods: How I evaluate anycast setups

I don't rely on a single perspective, but combine client view, server view, and active probes on individual Node. The Anycast Efficiency Factor (α) compares the actual latency to the selected Anycast instance with the latency to the best local node; 1.0 would be ideal. I also check the RTT distribution because outliers have a dramatic impact on the user experience. Server-side measurements provide a broad picture of millions of clients, while client probes show the real last mile. Only the comparison shows whether routing policies are working properly or whether policies are proximity beat.

Metrics	Meaning	Good (guideline value)	warning signs
Anycast Efficiency Factor (α)	Ratio of actual RTT vs. best RTT	≤ 1.3 median	≥ 2.0 in many regions
RTT to the nearest site	Lower limit of achievable time	< 20–30 ms regional	> 60 ms without reason
Proportion of suboptimal routes	Incorrect assignment of clients	< 10%	> 20% frequently
Cache hit rate	Percentage answered from cache	> 90% for resolvers	< 70% permanent

Common pitfalls in practice

A classic scenario: BGP policies route traffic to a more distant ASN even though closer paths exist because local policies are the deciding factor. rash . When individual nodes malfunction, traffic sometimes jumps to another continent, which can add 200–300 ms; a publicly reported incident in the resolver environment showed latencies of over 300 ms after an announcement failure. Node affinity also occasionally breaks down, causing clients to see changing nodes and caches to run empty. In regions with weaker connections, a small number of POPs worsen distribution, even though Anycast is active. I therefore specifically test hotspots where real users wait too long, rather than relying solely on global mean values to leave.

Architecture decisions: nodes, prefixes, peering

I plan the number of nodes based on the expected user profile, not on a flat rate. Quote. A few, excellently connected POPs with good peering often significantly outperform many weak locations. Prefix length, communities, and regional splits determine whether policies choose genuine proximity or detours. For projects with strict requirements, I check peering opportunities on site and, if necessary, set smaller prefixes for finer control. The physical location remains central to latency and data protection—this guide helps here. Server location and latency with clear Hints.

Practical guide: Step by step to better latency

I start by taking stock: Where are the authoritative name servers located, what RTT do they deliver from the perspective of real users, and how are the outliers distributed across regions? I then optimize the TTLs for frequently queried zones so that resolvers request responses less frequently and peaks are eliminated. After that, I adjust BGP announcements, test different communities, and analyze how peers actually handle traffic. For conspicuous regions, I implement local improvements—peering, new POP, or alternative paths—until the efficiency metric α clearly decreases. Only then do I check whether another location really brings benefits or, above all, more dispersion generated.

Sample measurement matrix and evaluation

For a global zone operator, I regularly measure the following per region: median RTT, 95th percentile, and α in comparison to the local best node, supplemented by cache hit rates of large Resolver. I contrast these figures with active probes on the internal IPs of individual nodes to see the „physical“ lower limit. If α is high but the single-node RTTs look good, the problem is almost certainly in the routing, not in the server performance. This allows me to identify specifically whether I need to correct peering, prefixes, or location selection. This measurement matrix prevents blind changes and delivers quick wins in the real world. bottlenecks.

Transport protocols and handshakes: UDP, TCP, DoT, DoH, DoQ

Whether Anycast works „fast“ depends heavily on the transport. Classic DNS uses UDP, is therefore handshake-free and usually the fastest—until response sizes or packet loss come into play. If a response is truncated (TC flag) to TCP back, an additional round trip is immediately created; with DoT/DoH (DNS over TLS/HTTPS) adds the TLS handshake. In practice, I see that DoH connections are often reused, which reduces the additional costs after the first few requests. For heavily frequented zones, I therefore plan:

• Dimension the EDNS0 buffer conservatively (e.g., 1232–1400 bytes) to avoid fragmentation.
• Terminate DoT/DoH/DoQ ports identically everywhere so that anycast nodes respond consistently when protocols are mixed.
• Actively check TCP and TLS tuning (initial congestion window, 0-RTT for DoT/DoQ where possible) instead of just optimizing UDP.

A robust DoH/DoQ implementation pays off, especially for mobile access, because packet loss in UDP leads to timeouts more frequently. I measure latency separately for each protocol family and compare the distribution—not just the median—to map real user paths.

Response size, DNSSEC, and fragmentation

Large responses are a latency driver. DNSSEC, SVCB/HTTPS records, and many NS or TXT entries push packets beyond common MTU limits. Fragmented UDP packets are lost more frequently; the subsequent TCP fallback costs time. I plan zones so that responses remain compact:

• Short RRSIGChains (ECDSA/ECDSAP256 instead of long RSA keys) for smaller signatures.
• Meaningful delegation: no unnecessary additional entries in the Authority/Additional Section.
• Use SVCB/HTTPS deliberately and test how often truncation is triggered.

The combination of a smaller EDNS0 buffer and lean responses reduces retransmits and stabilizes the RTTDistribution. In my evaluations, the 95th and 99th percentiles often shrink more than the median—precisely where users feel the delay.

Stability vs. speed: health checks and failover

Anycast is unforgiving when health checks are poorly configured. Overly aggressive withdrawal logic generates flaps, overly conservative checks keep faulty nodes in the routing for too long. I rely on:

• Combined health signals (local probes, external checks, service status), not just ICMP.
• Hysteresis and damping for BGP announcements, so that brief disruptions do not trigger global switches.
• Fast detection via BFD, but controlled return to the cluster (graceful return) to maintain cache affinity.

During maintenance, I announce prefixes with reduced local prefix length, allow traffic to flow out, and only then take the node offline. This keeps user paths stable and avoids cache cold starts.

Consistency, TTL strategies, and cache behavior

Speed arises in the Cache – Consistency determines how stable it remains. For updates, I balance TTLs against change frequency. Frequently requested, rarely modified records receive higher TTLs; I use dynamic entries with moderate TTLs and active advance warning (NOTIFY) to secondaries. The following have also proven effective:

• serve staleResolvers may temporarily provide outdated responses in the event of upstream disruptions—better than timeouts.
• Prefetch close to TTL end, so that popular entries remain fresh in the cache.
• Conscious Negative caching (NXDOMAIN TTL) to relieve popular but incorrect queries.

I check whether updates arrive promptly via all Anycast nodes (serial monitoring via SOA) and compare the time to convergence. Latency optimization without clean data distribution otherwise leads to inconsistent responses and subsequent errors.

IPv6, dual stack, and asymmetric routing

In many networks, IPv4 and IPv6 paths differ significantly. I measure dual stack Always separate: α, median RTT, and outliers per IP family. It is not uncommon for v6 to have poorer connectivity or follow different policies. I remedy this with identical announcements, coordinated communities, and targeted v6 peering. On the client side, Happy Eyeballs comes into play—good v6 performance is therefore not just „nice to have,“ but directly influences the user experience.

Avoiding measurement errors: What I don't do

ICMP ping on anycast IPs often fails to reflect reality: firewalls, rate limits, and ICMP policies separate from DNS distort results. Equally problematic are single locations in cloud monitoring that hide entire continents. I therefore rate:

• UDP/53, TCP/53, and DoH/DoT RTTs with real queries (A/AAAA, NXDOMAIN, DNSSEC-validated).
• Client-side probes in ISP and mobile networks, not just data centers.
• Long runs over weeks to see effects of time of day and day of the week.

Only by comparing synthetic probes and server-side logs can you determine whether a problem is local, regional, or global—and whether time is being lost in routing or application.

BGP fine-tuning in practice

Fine control often decides within 10–50 ms. I work with regional communities For Local Pref, use selective de-aggregation (within clean ROAs) if necessary and avoid prefix lengths that are dropped by large carriers. Important: Announce IPv4/IPv6 consistently and verify the policy effect for all transits. If α remains high in individual regions, I temporarily split prefixes, measure again, and make a data-driven decision as to whether the split can remain or whether better peering is the more sustainable solution.

Operations Playbook: Repeatable Steps

To ensure that optimization does not become a one-off project, I keep a lean playbook handy:

• Monthly α review per region and IP family; outlier lists with specific ISPs.
• Quarterly chaos drills (Node withdrawal, link down) with metric comparison before/after drill.
• Release checklist for zone changes: response size, DNSSEC impact, fragmentation risk, TTL consequences.
• Peering audits: cost/benefit, capacity, packet loss, jitter; clear thresholds and escalation paths.
• Transparent health check policies with hysteresis and documented thresholds.

These routines keep latency, stability, and consistency in balance—and Anycast delivers what it can: robust accessibility with good, but not automatically perfect, performance. Performance.

Summary: My advice to operators

Anycast DNS provides solid availability and mostly good times, but it does not automatically accelerate a zone without clean Tuning. Measure efficiency with α, check the median and outliers, and actively test against individual nodes. Prioritize the cache: appropriate TTLs often reduce round trips more than an additional POP. Make data-driven decisions about new nodes and question BGP policies before rolling out further. This way, you can benefit from Anycast without incurring avoidable wrong routes to run.