| Greg's network link statistics |
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This page shows my network availability and performance statistics connected to the Australian National Broadband Network. It bases on earlier pages that I wrote for the DSL and satellite connections.
I had hoped that with the advent of the NBN, this page would no longer be needed. Unfortunately, this has proven not to be the case. While I don't have issues with throughput, the availability has been the worst I have ever experienced, with outages of up to 48 hours. It's not clear where the problem lies, but I have observed serious issues with the DHCP authentication that my ISP uses. More here when I understand the situation better.
The graphs show:
Network status. This is the number of remote systems responding to a ICMP echo (ping) packet at the same time as the link status ping. I currently ping 5 systems which I frequently access: freefall.freebsd.org (now somewhere in New York state), www.lemis.com, my external web server in Raleigh NC, ffm.lemis.com, located in Frankfurt am Main, ozlabs.org, located in Canberra, and ftp.netbsd.org, located somewhere in the USA. Normally this value should be 5. If it's less, the script retries every second until full connectivity is restored.
Link packet loss, which has proven to be a significant issue since early 2018. I send 20 ICMP ping messages to the other end of the network link and count how many are lost.
I previously had parameters "link status" and "TCP speed”, but they no longer seem to make much sense.
The graphs were made with gnuplot, and I'm not very happy with the smoothing. In particular, the right-hand side of smoothed graphs has too much influence, and it's easy to get the false impression that the link status or TCP speed have changed significantly in the last few minutes. If anybody can point me at a way to fix this problem, I'd be grateful.
Click on the graphs for a 1600x1200 version.
This section monitors the NBN link for outages, including planned outages. I have manually edited the data to remove false positives, such as when moving house. I have a program that evaluates the outage information and produces detailed outage information. Here's the information on the past 20 outages, along with the overall statistics:
Start time End time Duration Badness from to
(seconds)
1644437903 1644437973 70 14.694 # 10 February 2022 07:18:23 10 February 2022 07:19:33
1644519268 1644519349 81 0.044 # 11 February 2022 05:54:28 11 February 2022 05:55:49
1644598961 1644598965 4 0.045 # 12 February 2022 04:02:41 12 February 2022 04:02:45
1644789211 1644789391 180 0.019 # 14 February 2022 08:53:31 14 February 2022 08:56:31
1644849074 1644849077 3 0.060 # 15 February 2022 01:31:14 15 February 2022 01:31:17
1645030936 1645032158 1222 0.020 # 17 February 2022 04:02:16 17 February 2022 04:22:38
1645192327 1645192507 180 0.022 # 19 February 2022 00:52:07 19 February 2022 00:55:07
1645546584 1645547001 417 0.010 # 23 February 2022 03:16:24 23 February 2022 03:23:21
1645631129 1645631153 24 0.043 # 24 February 2022 02:45:29 24 February 2022 02:45:53
1649795093 1649799454 4361 0.001 # 13 April 2022 06:24:53 13 April 2022 07:37:34
1649800745 1649800959 214 2.789 # 13 April 2022 07:59:05 13 April 2022 08:02:39
1649801168 1649801731 563 17.225 # 13 April 2022 08:06:08 13 April 2022 08:15:31
1650430130 1650430456 326 0.006 # 20 April 2022 14:48:50 20 April 2022 14:54:16
1652292259 1652292361 102 0.002 # 12 May 2022 04:04:19 12 May 2022 04:06:01
1652293810 1652296705 2895 2.484 # 12 May 2022 04:30:10 12 May 2022 05:18:25
1653273231 1653273287 56 0.004 # 23 May 2022 12:33:51 23 May 2022 12:34:47
Summary
Total 500 outages, total time 1168419 seconds (13 days, 12:33:39)
Longest outage: 192150 seconds (2 days, 05:22:30)
Start: 21 February 2015 04:36:54
End: 23 February 2015 09:59:24
Average time between outages: 522030 seconds (6 days, 01:00:30)
Average duration: 2336 seconds (00:38:56)
Availability: 99.55%
“Badness” is an attempt to quantify the effect. It's the reciprocal of the number of seconds per hour that the link was up between failures (i.e. 3600 / uptime).
And here is the summary information for the past 10 days with a less than 100% record:
Timestamp Outages Duration Availability Date
(seconds)
1644757200 1 180 99.79% # 14 February 2022
1644843600 1 3 100.00% # 15 February 2022
1645016400 1 1222 98.59% # 17 February 2022
1645189200 1 180 99.79% # 19 February 2022
1645534800 1 417 99.52% # 23 February 2022
1645621200 1 24 99.97% # 24 February 2022
1649772000 3 5138 94.05% # 13 April 2022
1650376800 1 326 99.62% # 20 April 2022
1652277600 2 2997 96.53% # 12 May 2022
1653228000 1 56 99.90% # 23 May 2022
The dates in the left columns are in UNIX time_t format to ease further processing. I also have lists of all individual outages, or summaries per day.
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