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author | Dimitri Staessens <dimitri@ouroboros.rocks> | 2021-07-25 12:42:59 +0200 |
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committer | Dimitri Staessens <dimitri@ouroboros.rocks> | 2021-07-25 12:42:59 +0200 |
commit | e5fff042c0af949afe5904d4138641841b504cb8 (patch) | |
tree | a1ba4ee692f524cb13a6068cd943ca8b265785bf /content/en/docs/Tools | |
parent | b22970134f538af6ec3483fbb3c910d1ccbecc22 (diff) | |
download | website-e5fff042c0af949afe5904d4138641841b504cb8.tar.gz website-e5fff042c0af949afe5904d4138641841b504cb8.zip |
content: Add metrics exporter description
Diffstat (limited to 'content/en/docs/Tools')
15 files changed, 285 insertions, 0 deletions
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Consult the +InfluxDB documentation on how to do this, +https://docs.influxdata.com/influxdb/v2.0/get-started/#set-up-influxdb. + +To use grafana, install and run grafana open source, +https://grafana.com/grafana/download +https://grafana.com/docs/grafana/latest/?pg=graf-resources&plcmt=get-started + +Go to the grafana UI (usually http://localhost:3000) and set up +InfluxDB as your datasource: +Go to Configuration -> Datasources -> Add datasource and select InfluxDB +Set "flux" as the Query Language, and +under "InfluxDB Details" set your Organization as in InfluxDB and set +the copy/paste the token for the bucket to the Token field. + +To add the Ouroboros dashboard, +select Dashboards -> Manage -> Import + +and then either upload the json file from this repository in + +dashboards-grafana/general.json + +or copy the contents of that file to the "Import via panel json" +textbox and click "Load". + +### Run the exporter: + +Clone this repository and go to the pyExporter directory. + +Edit the config.ini.example file and fill out the InfluxDB +information (token, org). Save it as config.ini. + +and run oexport.py + +``` +cd exporters-influxdb/pyExporter/ +python oexport.py +``` + +## Overview of Grafana general dashboard for Ouroboros + +The grafana dashboard allows you to explore various aspects of +Ouroboros running on your local or remote systems. As the prototype +matures, more and more metrics will become available. + +### Variables + +At the top, you can set a number of variables to restrict what is seen +on the dashboard: + +{{<figure width="30%" src="/docs/Tools/grafana-variables.png">}} + +* System allows you to specify a set of host/node/devices in the network: + +{{<figure width="30%" src="/docs/Tools/grafana-variables-system.png">}} + +The list will contain all hosts that put metrics in the InfluxDB +database in the last 5 days (Unfortunaly there seems to be no current +option to restrict this to the current selected time range). + +* Type allows you to select metrics for a certain IPCP type + +{{<figure width="30%" src="/docs/Tools/grafana-variables-type.png">}} + +As you can see, all Ouroboros IPCP types are there, with unclusion of +an UNKNOWN type. This may briefly pop up when the metric is misread by +the exporter. + +* Layer allows you to restrict the metrics to a certain layer + +* IPCP allows to restrict metrics to a certain IPCP + +* Interval allows to select a window in which metrics are aggregated. + +{{<figure width="30%" src="/docs/Tools/grafana-variables-interval.png">}} + +Metrics will be aggregated from the actual exporter values (e.g. mean +or last value) that fall in this interval. This interval should thus +be larger than the exporter interval to ensure that each window has +enough raw data. + +### Panels + +As you can see in the image above, the dashboard is subdivided in a +bunch of panels, each of which focuses on some aspect of the +prototype. + +#### System + +{{<figure width="80%" src="/docs/Tools/grafana-system.png">}} + +The system panel shows the number of IPCPs and known IPCP flows in all +monitored systems as a stacked series. This system is running a small +test with 3 IPCPs (2 unicast IPCPs and a local IPCP) with a single +flow between oping server/client(which has one endpoint in each IPCP, +so it shows 2 because this small test runs on a single host). The +colors on the graphs are sometimes not matching the labels, which is a +grafana issue that I hope will get fixed soon. + +#### Link State Database + +{{<figure width="80%" src="/docs/Tools/grafana-lsdb.png">}} + +The Link State Database panel shows the knowledge each IPCP has about +the network routing area(s) it is in. The example has 2 IPCPs that are +directly connected, so each knows 1 neighbor (the other IPCP), 2 +nodes, and two links (each unidirectional arc in the topology graph is +counted). + +#### Process N-1 flows + +{{<figure width="80%" src="/docs/Tools/grafana-frcp.png">}} + +This is the first panel that deals with the [Flow-and-Retransmission +Control +Protocol](/docs/concepts/protocols##flow-and-retransmission-control-protocol-frcp) +(FRCP). It shows metrics for the flows between the applications (this +is not the same flow as the data transfer flow above, which is between +the IPCPs). This panel shows metrics relating to retransmission. The +first is the current retransmission timeout, i.e. the time after which +a packet will be retranmitted. This is calculated from the smoothed +round-trip time and its estimated deviation (well below 1ms), as +estimated by FRCP. + +The flow is created by the oping application that is pinging at a 10ms +interval with packet retransmission enabled (so basically a service +equivalent as running ping over TCP). The main difference with TCP is +that Ouroboros flows are between the applications themselves. The +oping server immediately responds to the client, so the client sees a +response time well below 1 ms[^1]. The server, however, sees the +client sending a packet only every 10ms and its RTO is a bit over +10ms. The ACKs from the perspective of the server are piggybacked on +the client's next ping. (This is similar to TCP "delayed ACK", the +timer in Ouroboros is set to 10ms, so if I would ping at 1 second +intervals over a flow with FRCP enabled, the server would also see a +10ms Round-trip time). + +#### Delta-t constants + +The second panel to do with FRCP are the Delta-t constants. Delta-t is +the protocol on which FRCP is based. Right now, they are only +configurable at compile time, but in the future they will probably be +configurable using fccntl(). + +{{<figure width="80%" src="/docs/Tools/grafana-frcp-constants.png">}} + +A quick refresher on these Delta-t timers: + +* **Maximum Packet Lifetime** (MPL) is the maximum time a packet can + live in the network, default is 1 minute. + +* **Retransmission timer** (R) is the maximum time which a + retransmission for a packet may be sent by the sender. The default + is 2 minutes. The first retransmission will happen after RTO, + then 2 * RTO, 4* RTO and so on with an exponential back-off, but + no packets will be sent after R has expired. If this happens, the + flow is considered failed / down. + +* **Acknowledgment timer** (A) is the maximum time which an packet may + be acknowledged by the receiver. Default is 10 seconds. So a + packet may be acknowledged immediately, or after 10 milliseconds, + or after 4 seconds, but not any more after 10 seconds. + +#### Delta-t window + +{{<figure width="80%" src="/docs/Tools/grafana-frcp-window.png">}} + +The third and (at least at this point) last panel related to FRCP is +the window panel that shows information regarding Flow Control. FRCP +flow control tracks the number of packets in flight. These are the +packets that were sent by the sender, but have not been +read/acknowledged yet by the receiver. Each packet is numbered +sequentially starting from a random value. The default maximum window +size is currently 256 packets. + +#### IPCP N+1 flows + +{{<figure width="80%" src="/docs/Tools/grafana-ipcp-np1.png">}} + +These graphs show basic statistics from the point of view of the IPCP +that is serving the application flow. It shows upstream and downstream +bandwidth and packet rates, and total sent and received packets/bytes. + +#### N+1 Flow Management + +{{<figure width="60%" src="/docs/Tools/grafana-ipcp-np1-fu.png">}} + +These 4 panels show the management traffic sent by the flow +allocators. Currently this traffic is only related to congestion +avoidance. The example here is taken from a jFed experiment during a +period of congestion. The receiver IPCP monitors packets for +congestion markers and it will send an update to the source IPCP to +inform it to slow down. It shows the rate of flow updates for +multi-bit Explicit Congestion Notification. As you can see, there is +still an issue where the receiver is not receiving all the flow +updates and there is a lot of jitter and burstiness at the receiver +side for these (small) packets. I'm working on fixing this. + +#### Congestion Avoidance + +{{<figure width="80%" src="/docs/Tools/grafana-ipcp-np1-cc.png">}} + +This is a more detailed panel that shows the internals of the MB-ECN +congestion avoidance algorithm. + +The left side shows the congestion window width, which is the +timeframe over which the algorithm is averaging bandwidth. This scales +with the packet rate, as there have to be enough packets in the window +to make a reasonable measurement. Biggest change compared to TCP is +that this window width is independent of RTT. The congestion +algorithm then sets a target for the maximum number of bytes to send +within this window (congestion window size). The division of the +number of bytes that can be sent and the size of the windows yields +the target bandwidth. The congestion was caused by a 100Mbit link, and +the target set by the algorithm is quite near this value. The +congestion level is a quantity that controls the rate at which the +window scales down when there is congestion. This upstream/downstream +view should be as close as possible to identical, the reason they are +not is because of the jitter and loss in the flow updates as observed +above. Work in progress. + +The graphs also show the number of packets and bytes in the current +congestion window. The default target is set to min 8 and max 64 +packets within the congestion window before it scales up/down. + +And finally, the upstream packet counters shows the number of packets +sent without receiving a congestion update from the receiver, and the +downstream packet counter shows the number of packets received since +the last time there was no congestion. + +#### Data transfer local components + +The last panel shows the (management) traffic sent and received by the +IPCP internal as measured by the forwarding engine (Data transfer). + +{{<figure width="80%" src="/docs/Tools/grafana-ipcp-dt-dht.png">}} + +The components that are current shown on this panel are the DHT and +the Flow Allocator. As you can see, the DHT didn't do much during this +interval. That's because it is only needed for name-to-address +resolution and it will only send/receive packets when an address is +resolved or when it needs to refresh its state, which happens only +once every 15 minutes or so. + +{{<figure width="80%" src="/docs/Tools/grafana-ipcp-dt-fa.png">}} + +The bottom part of the local components is dedicated to the flow +allocator. During the monitoring period, only flow updates were sent, +so this is the same data as shown in the flow management traffic, but +from the viewpoint of the forwarding element in the IPCP, so it shows +actual bandwidth in addition to the packet rates. + +[^1]: If this still seems high, disabling CPU "C-states" and tuning + the kernel for low latency can reduce this to a few + microseconds. |