165 CloudFlare Nodes in 85 of totally 130 Countries
Visit this page regularly as it is updated daily. Last data update: 15-06-2026 07:46:24 UTC
Africa
Algeria (1|4)
Ethiopia (1|5)
Ivory Coast (1|5)
Kenya (2|7)
Mauritius (1|5)
Mozambique (1|2)
Reunion (1|3)
Rwanda (1|1)
South Africa (2|42)
Tanzania (1|6)
Zimbabwe (1|1)Asia
Armenia (1|5)
Azerbaijan (2|5)
Bahrain (1|1)
Bangladesh (1|33)
China (1|470)
Georgia (1|9)
India (4|111)
Indonesia (3|9)
Israel (2|19)
Japan (3|99)
Jordan (1|4)
Kuwait (1|3)
Laos (1|2)
Malaysia (1|35)
Mongolia (1|1)
Nepal (1|15)
Oman (1|9)
Pakistan (2|16)
Philippines (1|5)
Singapore (1|567)
South Korea (1|10)
Sri Lanka (1|1)
Taiwan (2|23)
Thailand (1|21)
Turkey (1|84)
United Arab Emirates (1|4)
Vietnam (2|4)Europe
Albania (1|1)
Austria (1|145)
Belgium (1|27)
Bulgaria (1|75)
Croatia (1|2)
Cyprus (1|9)
Czech Republic (1|45)
Denmark (1|74)
Estonia (1|18)
Finland (1|22)
France (3|550)
Germany (6|623)
Greece (1|38)
Hungary (1|9)
Iceland (1|2)
Ireland (1|18)
Italy (2|167)
Latvia (1|27)
Lithuania (1|7)
Luxembourg (1|2)
Moldova (1|1)
Netherlands (1|528)
Norway (1|29)
Poland (1|184)
Portugal (1|36)
Romania (1|80)
Russia (1|12)
Serbia (1|14)
Slovakia (1|12)
Spain (2|150)
Sweden (1|78)
Switzerland (2|49)
Ukraine (1|10)
United Kingdom (3|535)
Canada (4|115)
Costa Rica (1|3)
Guatemala (1|4)
Mexico (1|1)
United States (29|1741)
Australia (5|157)
French Polynesia (1|1)
New Caledonia (1|3)
New Zealand (1|10)
Argentina (1|24)
Brazil (5|273)
Chile (1|15)
Ecuador (2|9)Nairobi: 1 Node with 6 IP Addresses
| NBO | Nairobi | Kenya (KE) | Kenya (KE) | 162.158.231.139 |
| NBO | Nairobi | Kenya (KE) | Kenya (KE) | 162.158.231.141 |
| NBO | Nairobi | Kenya (KE) | Kenya (KE) | 162.158.231.144 |
| NBO | Nairobi | Kenya (KE) | Kenya (KE) | 172.68.47.132 |
| NBO | Nairobi | Kenya (KE) | Kenya (KE) | 172.68.47.133 |
| NBO | Nairobi | Kenya (KE) | Malawi (MW) | 172.69.170.146 |
Parse Time: 143.843 ms
Is Lazy Loading Always a Net Performance Win?
Lazy loading defers resource loading, but its overall benefit depends on context, rendering behavior, and server characteristics.
The Intended Benefit
Lazy loading reduces initial network payload by deferring offscreen images and assets.This can improve first paint and reduce bandwidth consumption.
Browser Scheduling Complexity
Modern browsers schedule requests dynamically.Aggressive deferral may delay resource discovery or introduce layout shifts.
The benefit is not purely additive; timing interactions matter.
Server-Side Considerations
Lazy loading affects client rendering more than backend generation.If server execution time dominates TTFB, deferring images does not address that root cause.
Edge Cases
Infinite scroll implementations and dynamic galleries sometimes create additional script overhead to manage loading states.That overhead can offset bandwidth savings.
Measuring Impact
Compare total transferred bytes, LCP, and backend latency independently.A holistic view prevents over-crediting a single technique.
Conclusion
Lazy loading is powerful when bandwidth and rendering cost dominate.It is neutral when backend execution is the primary constraint.
Key Takeaways
- Separate frontend gains from backend cost.
- Evaluate layout stability alongside network savings.
- Test under realistic network conditions.
- Use lazy loading selectively rather than universally.