cfxEdgeCollector UI

Step 1: Starting cfxEdgeCollector

Start the EdgeCollector by logging into the VM where it is installed using SSH. Once, logged in, start the EdgeCollector using the following command

$ cfxedgecollector --start 

Step 2: Verify cfxEdgeCollector Status

Once the EdgeCollector is started, check the status of the cfxEdgeCollector using the following command

$ cfxedgecollector --status
CloudFabrix Edge Collector

*************************** Edge Collector Environment ************************
JOB_DIR           = /home/macaw/jobs
DATA_DIR          = /home/macaw/data
EXPORTED_DATA_DIR = /home/macaw/exporteddata
BACKUP_DIR        = /home/macaw/backupdir
CONFIG_DIR        = /home/macaw/ConfigDir
SECURE_DIR        = /home/macaw/.cfxcollector
******************************************************************************

Docker installed version is: 18.09.2
+----------------+-------------+-----------------+
|      Name      |    Status   |   Memory/Limit  |
+----------------+-------------+-----------------+
| Edge Collector | UP 14 hours | 80.4 MB/25.1 GB |
+----------------+-------------+-----------------+

Step 3: Accessing the UI

Users will be able to access the cfxEdgeCollector UI and configure job related configuration to perform network discovery. Once the discovery is complete, users can export the data to the AIA system for reporting and further processing as described below.

Using your favorite browser (Chrome / Safari), enter the following URL to access the EdgeCollector UI as shown below screenshot.

https://<ipaddress>:8888

Step 4: Creating a discovery job steps

a. Create new job

b. Provide Job Name (according to network need - e.g. datacenter-network-element-job)

c. Provide seed IP details (i.e starting ip address to collect the data)

d. Add SNMP Credentials to job configuration (this will be used for discovery using SNMP)

e. Add SSH Credentials to job configuration (this will be used for discovery using SSH)

f. Add additional features needed (as shown in the below screenshot as per network requirements -- Advanced)

g. Once the configuration etc are all entered, save the job using the ‘Save’ button as shown below screenshot.

Once the job related parameters are all configured via GUI, users can switch to console using SSH (login to console using SSH via putty) and goto Step 5.

Step 5: Once the configuration etc are all entered, save the job using the UI, users will be able to login to EdgeCollector VM using SSH to perform discovery and collect the details using following command.

$ cfxedgecollector collect  <jobname>