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.

Detailed outage information

This section monitors the NBN link for outages, including planned outages, which currently make up the majority. 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)

1516567560 1516567617     57	 31.579	# 22 January 2018 07:46:00 22 January 2018 07:46:57
1516713821 1516717932   4111	  0.025	# 24 January 2018 00:23:41 24 January 2018 01:32:12
1516718378 1516718459     81	  8.072	# 24 January 2018 01:39:38 24 January 2018 01:40:59
1517113943 1517114786    843	  0.009	# 28 January 2018 15:32:23 28 January 2018 15:46:26
1519216363 1519216639    276	  0.002	# 21 February 2018 23:32:43 21 February 2018 23:37:19
1521060088 1521087056  26968	  0.002	# 15 March 2018 07:41:28 15 March 2018 15:10:56
1522101140 1522127979  26839	  0.004	# 27 March 2018 08:52:20 27 March 2018 16:19:39
1522134661 1522135148    487	  0.539	# 27 March 2018 18:11:01 27 March 2018 18:19:08
1522819704 1522820929   1225	  0.005	#  4 April 2018 15:28:24  4 April 2018 15:48:49
1523241136 1523241239    103	  0.009	#  9 April 2018 12:32:16  9 April 2018 12:33:59
1523241664 1523242689   1025	  8.471	#  9 April 2018 12:41:04  9 April 2018 12:58:09
1523248702 1523248836    134	  0.599	#  9 April 2018 14:38:22  9 April 2018 14:40:36
1523250998 1523252201   1203	  1.665	#  9 April 2018 15:16:38  9 April 2018 15:36:41
1523252625 1523253946   1321	  8.491	#  9 April 2018 15:43:45  9 April 2018 16:05:46
1523254277 1523254426    149	 10.876	#  9 April 2018 16:11:17  9 April 2018 16:13:46
1523555176 1523555279    103	  0.012	# 13 April 2018 03:46:16 13 April 2018 03:47:59
1523555906 1523556346    440	  5.742	# 13 April 2018 03:58:26 13 April 2018 04:05:46
1523556973 1523557076    103	  5.742	# 13 April 2018 04:16:13 13 April 2018 04:17:56
1523558818 1523558921    103	  2.067	# 13 April 2018 04:46:58 13 April 2018 04:48:41
1523561880 1523561981    101	  1.217	# 13 April 2018 05:38:00 13 April 2018 05:39:41

Total 308 outages, total time 695021 seconds (8 days, 01:03:41)
Average time between outages:	428888 seconds (4 days, 23:08:08)
Average duration:		2256 seconds (00:37:36)
Availability:			99.47%
      

“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:

Date        Outages   Duration  Availability    Date
                      (seconds)
1516107600	 15	   797	 99.08%	# 17 January 2018
1516539600	  2	   125	 99.86%	# 22 January 2018
1516712400	  2	  4192	 95.15%	# 24 January 2018
1517058000	  1	   843	 99.02%	# 28 January 2018
1519131600	  1	   276	 99.68%	# 21 February 2018
1521032400	  1	 26968	 68.79%	# 15 March 2018
1522069200	  2	 27326	 68.37%	# 27 March 2018
1522764000	  1	  1225	 98.58%	#  4 April 2018
1523196000	  6	  3935	 95.45%	#  9 April 2018
1523541600	  5	   850	 99.02%	# 13 April 2018
      

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.