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Network Latency

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This grid displays the network latency of pings between each monitoring location in the Dotcom-Monitor cloud network. With over two dozen monitoring locations throughout the world, the Dotcom-Monitor network serves as a standard baseline for detecting trends in backbone latency communication issues as well as regional outages and slowdowns.

  Madrid Beijing Sydney Copenhagen Seattle IPv6 San Franciso Mumbai Warsaw Paris Johannesburg Buenos Aires Shanghai Tokyo AWS US-East Washington DC Tel-Aviv Amsterdam Dallas Brisbane Denver Frankfurt Montreal Hong Kong Miami San Francisco London New York Minneapolis
Madrid 1 341 327 41 163 154 218 55 17 156 260 296 272 108 94 80 35 118 379 102 35 106 273 138 135 27 99 121
Beijing
 
1 222 170 188
 
502 287 263
 
356 26 113 223 241 304 241 213 355 184 171 233 41 220 183 229 242 207
Sydney 327 223 1 328 157 147 176 314 289 458 352 186 140 209 234 335 292 188 12 175 306 217 232 225 147 284 251 231
Copenhagen 41 169 328 1 171 165 161 25 22 173 248 277 209 104 108 76 18 138 330 145 16 97 279 121 168 25 96 130
Seattle 163 189 157 171 1
 
276 175 148 288 206 166 142 80 64 188 132 53 168 30 174 78 153 71 23 147 75 54
IPv6 San Franciso
 
 
 
 
 
1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mumbai 246 502 176 170 276
 
1 319 169 297 441 427 142 313 320 326 145 284 181 280 140 334 114 295 272 281 219 312
Warsaw 54 240 314 25 175
 
318 1 39 172 251 211 263 107 105 89 26 145 344 139 31 107 206 132 166 36 99 150
Paris 17 263 290 22 148
 
168 40 1 166 224 248 255 86 78 68 15 112 300 110 12 84 246 114 134 10 78 105
Johannesburg 176
 
458 173 288
 
298 172 158 1 373
 
412 225 228 213 145 281 463 278 157 216 344 243 302 143 212 252
Buenos Aires 260 356 351 249 208
 
441 251 222 373 1 394 310 155 154 283 226 166 369 180 239 157 342 149 207 223 149 169
Shanghai 281 26 186 276 166
 
402 211 249
 
365 1 41 222 232 277 195 189 351 162 189 249 34 231 174 256 239 189
Tokyo 272
 
140 209 142
 
141 263 254 412 310 41 1 164 171 316 254 134 124 112 261 191 54 174 109 286 174 146
AWS US-East 108 221 210 104 80
 
311 107 86 224 155 223 164 1 2 130 79 34 241 48 83 14 221 25 64 75 6 29
Washington DC 99 241 234 108 64 68 320 106 81 228 150 233 171 2 1 140 80 38 300 38 94 14 229 27 68 101 24 31
Tel-Aviv 80 306 336 76 188
 
326 89 68 213 283 276 315 130 164 1 75 168 354 161 62 135 241 161 193 67 130 160
Amsterdam 36 241 292 18 132 138 153 26 15 145 226 194 254 79 80 75 1 122 383 113 9 82 202 125 138 11 76 107
Dallas 132 213 188 138 53 37 287 146 112 285 174 192 135 34 38 168 122 1 197 22 116 43 209 35 36 107 42 33
Brisbane 318 355 12 330 168 227 179 344 300 463 368 350 124 241 296 355 383 197 1 181 304 232 126 223 162 322 225 208
Denver 109 206 177 145 30 25 306 139 110 282 179 168 112 47 38 161 113 22 181 1 119 42 179 47 25 110 41 43
Frankfurt 50 171 306 16 173 152 139 29 13 157 239 208 261 83 95 62 9 116 304 119 1 94 208 126 145 17 80 114
Montreal 101 233 217 97 78
 
334 107 84 216 156 249 191 14 14 135 82 43 232 42 96 1 228 39 80 78 11 43
Hong Kong 195 41 232 285 153
 
113 197 246 324 350 49 55 221 238 240 202 183 126 179 209 228 1 208 156 197 207 195
Miami 138 219 225 121 71 67 293 132 115 243 187 213 174 25 27 161 137 35 223 47 126 39 208 1 74 100 30 40
San Francisco 134 183 148 167 20 31 272 165 134 302 208 168 110 62 68 198 137 38 162 25 145 80 190 74 1 134 63 51
London 27 225 284 25 147 133 280 36 10 143 223 256 286 75 101 67 11 107 322 110 17 78 197 100 134 1 69 102
New York 99 243 252 96 75 64 219 99 78 212 149 228 172 6 24 129 76 42 225 39 79 9 207 30 63 69 1 32
Minneapolis 121 207 232 130 54 49 300 150 105 252 169 188 146 30 30 160 106
 
207 43 114 41 194 40 51 102 32 1

What is Network Latency?

Network latency is the delay in time it takes information (packets) to travel from one node or location to another. This grid reveals any locations that are consistently performing slower that the average locations. Each monitoring location is situated in a Tier 3 data center with multiple pipelines connected directly to the backbone internet providers in that geographic region. Dotcom-Monitor performs thousands of tests to websites, servers and other online systems around the world each minute, so we understand the importance of backbone latency as well as the broader network latency in between the many different nodes along the path of internet traffic.

Test Network Latency

There are several interesting observations when you begin to study the network latency grid. The first to stand out is the stream of 1s diagonally down the page - this is because there is never any lag between a host and itself. You can see a similar result on your local machine by opening a command line and typing: ping localhost. The result should be <1ms which means that it takes less than one millisecond to ping itself.

You may also notice gaps in the grid, particularly between the IPv6 only locations and the locations that are IPv4 only - if the node is unable to communicate using IPv6 or does not have an IPv6 address, then no results will be shown.

Feel free to bookmark this page to come back and perform a quick check of overall internet backbone health.

Great Firewall of China

You may notice that most of the network latency results to and from the Shanghai China monitoring location are orders of magnitude higher than the rest of the locations. This is due to the amount of filtering on internet traffic by the Chinese government. In fact, there are many public websites such as Google, YouTube and Facebook that are completely blocked by the Great Firewall of China. Another reason for higher latency is due to a poorer infrastructure in China than other Western countries.

Additional Network Tools

For additional analytics feel free to navigate to the free tools section of Dotcom-Monitor where you can perform custom ping, traceroute or website speed tests. If you're here troubleshooting network latency issues with a website or server that you manage, please sign up for a free trial for 30 days and gain complete access to the entire suite of Dotcom-Monitor tools to help troubleshoot issues with your network, website availability and much more.