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. 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)

1730323926 1730352322  28396	  0.002	# 31 October 2024 08:32:06 31 October 2024 16:25:22
1730855658 1730855776    118	  0.007	#  6 November 2024 12:14:18  6 November 2024 12:16:16
1730855832 1730856433    601	 64.286	#  6 November 2024 12:17:12  6 November 2024 12:27:13
1730856734 1730857717    983	 11.960	#  6 November 2024 12:32:14  6 November 2024 12:48:37
1731394871 1731394874      3	  0.007	# 12 November 2024 18:01:11 12 November 2024 18:01:14
1732637415 1732637439     24	  0.003	# 27 November 2024 03:10:15 27 November 2024 03:10:39
1732639970 1732640162    192	  1.422	# 27 November 2024 03:52:50 27 November 2024 03:56:02
1732640289 1732641155    866	 28.346	# 27 November 2024 03:58:09 27 November 2024 04:12:35
1739971876 1739971921     45	  0.000	# 20 February 2025 00:31:16 20 February 2025 00:32:01
1740402651 1740402696     45	  0.008	# 25 February 2025 00:10:51 25 February 2025 00:11:36
1741039433 1741039436      3	  0.006	#  4 March 2025 09:03:53  4 March 2025 09:03:56
1742447270 1742447485    215	  0.003	# 20 March 2025 16:07:50 20 March 2025 16:11:25
1743541232 1743541303     71	  0.003	#  2 April 2025 08:00:32  2 April 2025 08:01:43
1747578887 1747580038   1151	  0.001	# 19 May 2025 00:34:47 19 May 2025 00:53:58
1747584133 1747585091    958	  0.879	# 19 May 2025 02:02:13 19 May 2025 02:18:11
1747586360 1747587443   1083	  2.837	# 19 May 2025 02:39:20 19 May 2025 02:57:23

Summary
Total 593 outages, total time 1337948 seconds (15 days, 11:39:08)
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:	602902 seconds (6 days, 23:28:22)
Average duration:		2256 seconds (00:37:36)
Availability:			99.63%
      

“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)
1730293200	  1	 28396	 67.13%	# 31 October 2024
1730811600	  3	  1702	 98.03%	#  6 November 2024
1731330000	  1	     3	100.00%	# 12 November 2024
1732626000	  3	  1082	 98.75%	# 27 November 2024
1739970000	  1	    45	 99.95%	# 20 February 2025
1740402000	  1	    45	 99.95%	# 25 February 2025
1741006800	  1	     3	100.00%	#  4 March 2025
1742389200	  1	   215	 99.75%	# 20 March 2025
1743512400	  1	    71	 99.92%	#  2 April 2025
1747576800	  3	  3192	 96.31%	# 19 May 2025
      

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.