LnetD v0.2 - new features

Hi all,
V0.2 pushed to git , new things included

- A network weathermap with errors
- A network weathermap with latency , and SPF calculation with total latency along the path
- What if Topology , a basic what if model , change the isis link metric and display it in the model. No link/node remove for now.
- ISIS XR support ( just for links using screen parsing ... while netconf is ready )
- model demand based on netflow

Still can't get proper screenshots but go ahead and clone it and make your own topology

git clone https://github.com/cpmarvin/lnetd.git

Model Demand:

Save layout:

LnetD v0.1 - network inventory based on ISIS

Hi again, Finally manage to find time and put all the code in an web application. There are two project that i want to thank for offering all the tools required to build this. https://github.com/afourmy/eNMS/ https://github.com/afourmy/flask-gentelella Now back to the topology map and inventory based on ISIS.

•  Login screen

• Dashboard

• Inventory

• D3js Topology and Map

As always code on github: https://github.com/cpmarvin/lnetd

Dijkstra - Networkx, d3.js weathermap based on ISIS topology

Based on previous posts the code is extended with couple of new features.

First the parallel link algorithm is enhanced using http://webiks.com/d3-js-force-layout-straight-parallel-links/ calculation, please see the link for more details. I have parallel links support and 'half links' to support displaying in/out link utilisation.

Same as before I'm using py ez to parse the isis database from a juniper device. This creates a json with all the links in the topology. The json also contains information about current 5 minutes utilisation and snmp ifindex for each link.

The weathermap function is based on snmp data collected by telegraf and stored in influxdb. The py ez script will populate the json with information from influxdb. Basically for each link we have the IP address, based on this we query influxdb to get the snmp ifindex. Then I do a second query to get the last 5 minutes util and the link capacity.

The resulting json has the following information:

Source, target, local ip, remote ip, util, capacity, local_ip_remote_ip, ifindex.

[{"r_ip": "x.x.x.x", "l_int": 49, "capacity": 10000, "target": "PE1-CPT", "metric": "145", "l_ip_r_ip": ["x.x.x.x", "y.y.y.y"], "util": 1491081683, "source": "PE1-GSW", "r_int": 0, "l_ip": "y.y.y.y"}

After the d3js topology is displayed, clicking on an link will create a plotly graph with last 24h utilisation. This is done via ajax query to the api. The request argument is host + ifindex. The api will query influxdb and get the snmp information.

The last piece of the puzzle is the dijkstra algorithm to find shortest path between nodes.

This is achieved using networkx python library and works on top of flask. The js code sends a request with all links array, source and destination. The api will return all links id for all ecmp paths between nodes. Based on link Id d3js will colour the links with dotted lines.

Demo time: 

Topology:

Plotly graph on link click:

Dijkstra's spf between two nodes:

Code on https://github.com/cpmarvin/lnetd

Leave a message if you have a hard time replicating this. This project started as a learning exercise and the code is not very clean.