Welcome to hcs-collector, this app will help our customers to collect daily the information from console.redhat.com and generate a report that will reflect some kind of consumption during the month for On-Demand subscriptions.
Disclaimer: This project or the binary files available in the Releases area are NOT delivered and/or released by Red Hat. This is an independent project to help customers and Red Hat Support team to export and/or collect the data from console.redhat.com for counting purposes of HCS or Hybrid Committed Spend Program.
Combined with crhc-cli, this tool will collect the information daily, will keep the data in a place defined by the user and whenever the customer need, they will be able to generate the consumption report. The analysis process will be checking all the local files and will be presenting the max concurrent value of each month. At this moment, this is just a pilot and we are counting only On-demand Physical Node and On-demand Virtual Node
- Here you can see the main menu and some options that we have already
$ ./hcs-collector.py
Usage: hcs-collector.py [OPTIONS] COMMAND [ARGS]...
Command line tool for HCS - Hybrid Commited Spend
Options:
--help Show this message and exit.
Commands:
collect Collect the information using crhc-cli
process Only process the local information with no necessity of download
setup Setup the basic configuration
Basically, you need to configure crhc-cli to be working properly in your environment, after that, you can just download the hcs-collector binary from the release area, and execute the commands below
./hcs-collector setup base-dirto setup where you would like to store the data./hcs-collector setup crhc-clito setup where the crhc-cli binary is located
After that, you can execute
./hcs-collector collectto download daily the files, feel free to add in your cronjob and./hcs-collector process [--tag='tagname']anytime to proceed with the analysis. Specifying a tag will break the analysis down by the values of that tag. Tagging vms can be done with the insights client, by specifying a tag file in /etc/insights-client/tags.yaml
- Here we can see the current configuration. All the information was adde via CLI tool.
$ ./hcs-collector.py setup view
{
"base_dir": "/home/user/hcs_data",
"crhc_cli": "/home/user/demo/crhc"
}
- Here we can see the content of the
hcs_datadirectory
$ pwd
/home/user/hcs_data
$ tree .
.
└── 2022
├── 03
│ ├── CSV
│ │ ├── match_inv_sw_03-12-2022.csv
│ │ ├── match_inv_sw_03-13-2022.csv
│ │ ├── match_inv_sw_03-14-2022.csv
│ │ ├── match_inv_sw_03-15-2022.csv
│ │ ├── match_inv_sw_03-16-2022.csv
│ │ ├── match_inv_sw_03-17-2022.csv
│ │ ├── match_inv_sw_03-18-2022.csv
│ │ ├── match_inv_sw_03-19-2022.csv
│ │ ├── match_inv_sw_03-20-2022.csv
│ │ ├── match_inv_sw_03-21-2022.csv
│ │ ├── match_inv_sw_03-22-2022.csv
│ │ ├── match_inv_sw_03-23-2022.csv
│ │ ├── match_inv_sw_03-24-2022.csv
│ │ ├── match_inv_sw_03-25-2022.csv
│ │ ├── match_inv_sw_03-26-2022.csv
│ │ ├── match_inv_sw_03-27-2022.csv
│ │ ├── match_inv_sw_03-28-2022.csv
│ │ ├── match_inv_sw_03-29-2022.csv
│ │ ├── match_inv_sw_03-30-2022.csv
│ │ └── match_inv_sw_03-31-2022.csv
│ └── JSON
│ ├── inventory_03-12-2022.json
│ ├── inventory_03-13-2022.json
│ ├── inventory_03-14-2022.json
│ ├── inventory_03-15-2022.json
│ ├── inventory_03-16-2022.json
│ ├── inventory_03-17-2022.json
│ ├── inventory_03-18-2022.json
│ ├── inventory_03-19-2022.json
│ ├── inventory_03-20-2022.json
│ ├── inventory_03-21-2022.json
│ ├── inventory_03-22-2022.json
│ ├── inventory_03-23-2022.json
│ ├── inventory_03-24-2022.json
│ ├── inventory_03-25-2022.json
│ ├── inventory_03-26-2022.json
│ ├── inventory_03-27-2022.json
│ ├── inventory_03-28-2022.json
│ ├── inventory_03-29-2022.json
│ ├── inventory_03-30-2022.json
│ ├── inventory_03-31-2022.json
│ ├── swatch_03-12-2022.json
│ ├── swatch_03-13-2022.json
│ ├── swatch_03-14-2022.json
│ ├── swatch_03-15-2022.json
│ ├── swatch_03-16-2022.json
│ ├── swatch_03-17-2022.json
│ ├── swatch_03-18-2022.json
│ ├── swatch_03-19-2022.json
│ ├── swatch_03-20-2022.json
│ ├── swatch_03-21-2022.json
│ ├── swatch_03-22-2022.json
│ ├── swatch_03-23-2022.json
│ ├── swatch_03-24-2022.json
│ ├── swatch_03-25-2022.json
│ ├── swatch_03-26-2022.json
│ ├── swatch_03-27-2022.json
│ ├── swatch_03-28-2022.json
│ ├── swatch_03-29-2022.json
│ ├── swatch_03-30-2022.json
│ └── swatch_03-31-2022.json
└── 04
├── CSV
│ └── match_inv_sw_04-01-2022.csv
└── JSON
├── inventory_04-01-2022.json
└── swatch_04-01-2022.json
7 directories, 63 files
Note. The structure above will be created automatically. No manual intervention is required.
- And here we can see the output of
processoption
$ ./hcs-collector.py process
## RHEL On-Demand
Max Concurrent RHEL On-Demand, referrent to ..: 2022-03
On-Demand, Physical Node .....................: 973
On-Demand, Virtual Node ......................: 5092
Virtual Data Center, Virtual Node ............: 3742
Unknown ......................................: 0
## RHEL Add-ons
On-Demand, High Availability, Physical Node...: 0
On-Demand, High Availability, Virtual Node....: 12
On-Demand, Directory Server Node .............: 20
## Virtualization
On-Demand, Virtualization Sockets ............: 192
## Middleware
On-Demand, JBoss EAP Cores ...................: 312
On-Demand, JWS Cores .........................: 474
## RHEL Virtual Data Center
Virtual Data Center, Hypervisor ..............: 198
Virtual Data Center, Hypervisor Sockets ......: 766
## RHEL On-Demand
Max Concurrent RHEL On-Demand, referrent to ..: 2022-04
On-Demand, Physical Node .....................: 978
On-Demand, Virtual Node ......................: 5500
Virtual Data Center, Virtual Node ............: 3787
Unknown ......................................: 0
## RHEL Add-ons
On-Demand, High Availability, Physical Node...: 0
On-Demand, High Availability, Virtual Node....: 12
On-Demand, Directory Server Node .............: 20
## Virtualization
On-Demand, Virtualization Sockets ............: 192
## Middleware
On-Demand, JBoss EAP Cores ...................: 324
On-Demand, JWS Cores .........................: 496
## RHEL Virtual Data Center
Virtual Data Center, Hypervisor ..............: 198
Virtual Data Center, Hypervisor Sockets ......: 766
Another option is to use the --tag to break down the overall usage by tag. This is so that you can break down your usage by environment, or business unit or any other criteria, and can help with internal cross charging.
Tags can be defined by creating the file /etc/insights-client/tags.yaml. The contents of the file are a set of named value pairs - e.g. environment=Dev, or environment=Prod. After creating the file, when the insights-client next runs, the tags will be uploaded to insights and then you can break down the usages based on those tags. Systems which are not tagged will be counted in the overall number, but not in the breakdown. You can find out more about how to set custom tags on your systems here.
Here's an example of using --tag=environment to break down the usage by environment.
$ ./hcs-collector.py process --tag=environment
## RHEL On-Demand
Max Concurrent RHEL On-Demand, referrent to ..: 2022-04
On-Demand, Physical Node .....................: 978
Dev ........................................: 278
Prod .......................................: 700
On-Demand, Virtual Node ......................: 5500
Dev ........................................: 1500
Prod .......................................: 4000
Unknown ......................................: 0
## RHEL Add-ons
On-Demand, HA Node ...........................: 12
Dev ........................................: 2
Prod .......................................: 10
On-Demand, Directory Server Node .............: 20
Dev ........................................: 0
Prod .......................................: 20
## Virtualization
On-Demand, Virtualization Sockets ............: 192
Dev ........................................: 0
Prod .......................................: 192
## Middleware
On-Demand, JBoss EAP Cores ...................: 324
Dev ........................................: 120
Prod .......................................: 204
On-Demand, JWS Cores .........................: 196
Dev ........................................: 68
Prod .......................................: 128
Ps.: This pilot is still very recent, Please, if you get any issue or improvements that you would like to share, feel free to submit a new Issue
Thank you!
Waldirio ([email protected])
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