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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 N. Virginia Washington DC Tel-Aviv Amsterdam Dallas Brisbane Denver Frankfurt Montreal Hong Kong Miami San Francisco London New York Minneapolis
Madrid 1 235 308 41 163 142 145 55 17 227 243 288 244 97 94 84 32 126 255 110 34 100 275 130 134 27 89 119
Beijing 236 1 225 183 178
 
361 189 180 351 363 23 71 242 273 280 173 249 314 232 172 231 45 208 180 169 295 235
Sydney 304 215 1 311 156 157 199 315 283 505 355 147 164 215 229 341 295 195 11 170 298 218 122 228 151 278 215 195
Copenhagen 41 183 311 1 170
 
151 25 22 209 248 228 256 99 94 74 13 128 267 134 16 92 288 118 155 25 92 126
Seattle 164 179 156 170 1
 
264 161 148 331 220 178 133 76 68 198 141 49 187 28 161 69 135 71 20 142 74 58
IPv6 San Franciso
 
 
 
 
 
1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
153
 
 
77
 
 
 
 
Mumbai 146 361 199 150 264
 
1 165 133 306 374 375 131 210 258 176 139 250 205 260 133 229 105 239 255 143 208 238
Warsaw 53 189 315 25 162
 
167 1 39 225 259 247 290 121 111 80 25 148 287 140 29 107 192 135 165 38 106 135
Paris 17 179 283 22 149
 
131 39 1 206 226 237 289 78 85 69 15 110 251 108 13 84 206 107 136 11 74 104
Johannesburg 227 351 505 209 333
 
307 225 207 1 434 456 466 273 274 269 194 307 472 318 211 276 399 304 360 205 268 299
Buenos Aires 243 362 355 248 220
 
371 259 226 429 1 389 309 156 160 287 235 173 363 186 254 178 343 154 203 229 160 177
Shanghai 288 23 147 228 178
 
373 246 237 457 389 1 62 275 203 249 242 273 326 252 264 219 34 214 165 270 223 226
Tokyo 244 82 164 256 133
 
132 290 289 466 310 62 1 167 176 315 246 151 111 113 253 191 63 175 107 249 174 190
N. Virginia 97 243 216 99 75
 
214 112 78 301 156 275 167 1 6 137 83 36 237 36 84 15 210 28 61 75 8 34
Washington DC 94 273 229 94 68 61 263
 
78 274 160 206 175 2 1 138 81 39 301 41 83 15 224 28 63 75 20 26
Tel-Aviv 82 276 341 74 199
 
175 79 70 269 288 248 315 137 138 1 65 168 352 169 66 138 244 182 186 61 136 151
Amsterdam 32 173 295 13 141 134 143 26 15 194 235 267 246 83 81 65 1 112 256 113 9 88 197 116 137 11 88 105
Dallas 126 251 195 128 49 38 253 149 110 307 172 274 151 36 39 166 112 1 200 20 116 45 204 29 37 111 40 31
Brisbane 255 314 15 267 187 163 206 287 251 473 381 323 111 235 297 353 256 200 1 255 262 238 128 226 194 282 237 213
Denver 110 232 170 134 28 28 259 140 109 318 185 252 113 36 41 165 113 20 224 1 118 43 169 52 25 113 42 35
Frankfurt 34 173 298 16 161 153 133 29 13 211 248 265 254 84 83 67 9 116 265 118 1 93 215 121 146 21 83 112
Montreal 101 232 219 93 69
 
229 107 84 276 178 217 191 16 15 142 88 45 238 43 93 1 195 39 77 78 9 36
Hong Kong 274 45 122 287 132
 
105 192 207 400 343 38 63 214 222 244 197 204 128 169 214 194 1 216 166 231 213 206
Miami 130 207 228 118 71 73 240 135 107 304 154 216 175 28 28 182 117 29 226 52 121 39 216 1 76 104 31 42
San Francisco 134 154 151 155 20 1 257 165 134 346 203 173 114 108 73 128 127 40 195 26 146 87 164 76 1 134 63 52
London 26 169 277 25 142 135 143 38 11 205 229 271 249 74 75 66 11 109 282 113 20 78 224 104 147 1 74 99
New York 89 288 215 91 74 63 207 106 73 268 155 208 174 8 8 136 91 40 237 42 83 9 218 32 63 74 1 32
Minneapolis 120 235 195 126 54 52 237 135 104 299 178 226 189 33 26 154 104 32 213 34 112 35 206 42 53 99 30 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.