diskover - File system crawler, storage search engine and analytics powered by Elasticsearch
diskover is an open source file system crawler and disk usage software that uses Elasticsearch to index and manage data across heterogeneous storage systems. Using diskover, you are able to more effectively search and organize files and system administrators are able to manage storage infrastructure, efficiently provision storage, monitor and report on storage use, and effectively make decisions about new infrastructure purchases.
As the amount of file data generated by business' continues to expand, the stress on expensive storage infrastructure, users and system administrators, and IT budgets continues to grow.
Using diskover, users can identify old and unused files and give better insights into data change, file duplication and wasted space.
diskover is written and maintained by Chris Park (shirosai) and runs on Linux and OS X/macOS using Python 2/3.
diskover crawler and workerbots running in terminal
diskover-web (diskover's web file manager, analytics app, file system search engine, rest-api)
Kibana dashboards/saved searches/visualizations and support for Gource
diskover Gource videos
Linux or OS X/macOS(tested on OS X 10.11.6, Ubuntu 16.04)
Python 2.7. or Python 3.5./3.6.(tested on Python 2.7.14, 3.5.3, 3.6.4) Python 3 recommended.
Python elasticsearch client module
Python requests module
Python scandir module
Python progressbar2 module
Python redis module
Python rq module
Elasticsearch 5(local or AWS ES Service, tested on Elasticsearch 5.4.2, 5.6.4) Elasticsearch 6 is not supported yet.
Redis(tested on 4.0.8)
Install the above Python modules using pip.
- diskover-web (diskover's web file manager and analytics app)
- Redis RQ Dashboard (for monitoring redis queue)
- sharesniffer (for scanning your network for file shares and auto-mounting for crawls)
- Kibana (for visualizing Elasticsearch data, tested on Kibana 5.4.2, 5.6.4)
- X-Pack (Kibana plugin for graphs, reports, monitoring and http auth)
- Gource (for Gource visualizations of diskover Elasticsearch data, see videos above)
Python qumulo-api module(for using Qumulo storage api, --qumulo cli option, install with pip, Python 2.7. only)
$ git clone https://github.com/shirosaidev/diskover.git $ cd diskover
OVA image file (for vmware, etc)
If you don't want to set up everything yourself, I have an OVA file running the latest version of diskover/diskover-web. Fastest and best way to get up and running with diskover. Contact me for pricing and download link.
You need to have at least Python 2.7. or Python 3.5. and have installed required Python dependencies using
$ pip install -r requirements.txt
Copy diskover config
diskover.cfg and edit for your environment.
Start diskover worker bots (as many as you want, a good number might be cores x 2) with:
$ cd /path/with/diskover $ python diskover_worker_bot.py
Worker bots can be added during a crawl to help with the queue. To run a worker bot in burst mode (quit after all jobs done), use the -b flag. If the queue is empty these bots will die, so use
rq info or
rq-dashboard to see if they are running. Run
diskover-bot-launcher.sh to spawn and kill multiple bots. Bots can be run on any host in the network as long as they have the same nfs/cifs mountpoint as rootdir (-d path) and can connect to ES and Redis (see wiki for more info).
Start diskover main job dispatcher and file tree crawler with:
$ python /path/to/diskover.py -d /rootpath/you/want/to/crawl -i diskover-indexname -a
Defaults for crawl with no flags is to index from . (current directory) and files >0 Bytes and 0 days modified time. Empty files and directores are skipped (unless you use -s 0 and -e flags). Use -h to see cli options.
Read the wiki for more documentation on how to use diskover.
For discussions or questions about diskover, please ask on Google Group.
For bugs about diskover, please use the issues page.
See the license file.