This page is meant to organize the discussion around the virtualization of Fermi Science Analysis Systems software. Some pieces of software today have a long history and there is a clear lack of man power to have these run on recent platforms. Some software are stuck on RHEL5, other on RHEL6, others run on modern platform. A detailed status point has to be made on each piece to understand the way forward: maintenance, VM, container.
Information on this page were first gathered from a number of reference pages:
- Fermi Software Week Winter 2017

Table of content

Task List

Prioritize this task list
Make a detailed status for each of the main software package (Summary table below)
Make a very simple list of use cases: L1Proc, End user, Developer...
Summarize pros and cons of VMs vs Containers (considering use cases)
Summarize pros and cons of Docker vs Singularity (considering use cases)
Summarize Virtualization and Containerization status at SLAC and CC-IN2P3
Can the Release Manager create and track the VM/Containers?

Summary

Here is summary table with the main software packages

see data flow section of the Software Week Meeting notes

created by Johan on Tuesday 6^th 2017, limiting myself to RHEL5, RHEL6 and RHEL7/CentOS7

Name	Build platform	Running platform	Special dependencies	Upgradable?	Existing VM	Existing container	Links	Comments	Date
FastCopy	RHEL5	RHEL5 or RHEL6 ?	?				FASTCopy processing chain	to be reviewed by experts	06 Jun 2017
Halfpipe	RHEL6	RHEL6	Commercial Qt !?	unlikely			Halfpipe	to be reviewed by experts	06 Jun 2017
Isoc Monitoring	RHEL5	RHEL5, works on RHEL6						to be reviewed by Steve T.	06 Jun 2017
GlastRelease	RHEL6	RHEL6	ROOT v5.34	may be with a lot of work and clean up				huge work, including science verification	06 Jun 2017
DataMonitoring	RHEL6	RHEL6	python2, numpy, ROOT	probably if GR is upgraded				svac/monitor is similar to GR, then mostly python code in dataMonitoring	06 Jun 2017
ScienceTools	RHEL7	RHEL7	RHEL7	NA	Giacomo	Sam's / Matt's		there was also one VM for the Fermi Summer school	06 Jun 2017
ASP	RHEL7	RHEL7	RHEL7	NA				should be similar to ScienceTools, ask Jim	06 Jun 2017

What kind of virtualization, VM or Containers?

Many questions to be tackled under this item:
- building vs running
- our software vs 3rd party libraries vs system libraries
- LAT calibrations
- connection to mysql db
Following June 6th 2017 meeting, we'll initially focused on Containers as it's very unlikely that the SLAC farm will move to Virtual Machines (Brian's comment)
- For SLAC farm - docker containers for GlastRelease. Need docker registry
- Use their system run to RHEL6 container, but batch host is RHEL7.
- Johan: VMs might still be useful for code development and debugging, for GR in particular.

Virtualization

Virtual machines running in a cloud environment or on a farm made of virtual nodes
just a simple VM for developers or end users

Containers

a few technologies to consider Docker, Shifter (Nersk for HPC) and Singularity
advantages over a full VM usually are:
- light weight
- better performance
- container has to be carefully built
Docker: the container
Shifter: NERSC container optimized for HPC
Singularity: containers for scientist

Details for main packages

Halfpipe/FastCopy

Halfpipe : runs on RHEL6, but unlikely to move beyond -> virtualize at RHEL6.
- Couple APIs need QT, using commercial version
FastCopy requires RHEL5.
ISOC ops boxes are mostly under RHEL5. Demonstrated that the tools can be run under RHEL6.
Backup ISOC is no longer supported.

GlastRelease

GlastRelease needs virtualizations
- RHEL 6 is last release that we have the personnel to support
- A few people running GlastRelease (Developers) - nice use case for Docker. Getting GlastRelease to run on your laptop is painful.
- GlastRelease carries around Geant4
Is there a distinction between Users and Developers for GlastRelease?
Use Cases
- L1 processing, reprocessing in SLAC batch farm
  - RHEL6 container on a RHEL7 host
  - do FT1, FT2 files go to xrootd? (Warren)
  - separate containers for L1? Maybe not an issue if we can preload batch nodes. We're guessing ~5 GB image.
- Simulations at Lyon, SLAC, GRID
  - maybe the same as for SLAC - check with Samuel for details
- Developers & Users
  - maybe separate versions for debug symbols and source for developers. Could be on-demand production of this version.

Science Tools

Focus with ScienceTools is just ease of distribution
Would it be useful to distribute the tools in VMs? Containers? Both?
- Joris : I found this VM : Virtual Machine version 3
- Johan : A VM was also setup for the Fermi summer school, should find it somewhere
Are there external dependencies (like xroot-d) that would cause problems with virtualization if backend changes?
- GR uses xrootd ST does not (Eric)
We need automated build system for ST: Release manager vs. manual builds
Use of virtualization is for convenience - which is most useful thing to do? (Richard)
- Don't depend on NFS/AFS if build container right. Stable for data xrootd
- getting files/libraries and also output data.
- Container helps with diffuse model
  - on nodes not on NFS
  - on nodes there's low overhead.
  - Caching image on all of the nodes.
  - Fermi ST image will have the diffuse model in it.
Caching big files (e.g. templates) in container image. Need a strategy with SCS for this for how containers are cached.

Infrastructure and general questions

Release Manager:

Release manager doesn't talk to Oracle - but it does talk to a database. Not user friendly.
Can our Release Manager build containers? (Richard)
- our Release Manager based on Jenkins (here)
- Jenkins has plenty of plugins to facilitate building and testing of Docker containers
  - One plugin
  - Tutorial on how to build container with Jenkins (itself running from a container...)
- Johan: May be just crosscheck with Joanne B. and Max T. , but it should be straightforward

What systems need what kinds of containers?

What is different for developers/users?
Same image for all the GR uses.
Don't want to pull a 3GB image to pull FT1, GR is 3x bigger. Just have 1 image at the moment.
One giant image - good command line interface installed in that image.
Images built such that the top looks the same between GR and ST. Keep same image.
Separate builds for debugging purposes?
GlastRelease is frozen, ST is constantly evolving. Debugging GR is not a problem, debugging ST is important
Giacomo
- Mount code at runtime, container doesn't have debugging tools.
- Container provides environment.
- Compile inside the container.
- run debugger inside container.
- User image has everything - compiled.
Lightweight container for developers then they can compile. Users have full compiled.
Debugging in GR and ST is very different
The computing center will have a cache of docker.
Every project will say what docker images do you want on the batch nodes?
Plan for managing cashed images. Work out allocations for collaborations.
Cost of using docker?

Pipeline

Needs someone that he could show the pipeline code and train to do heavy lifting when it comes to kicking the pipeline
Docker containers for something like the batch system may cause some problems, since
For something like the L1 pipeline, a number of images would need to be launched simultaneously
Would size of the software cause problems with deployment?
We would need a system where you restrict loading images to the batch farm to prevent collisions/problems
There is probably a precedent for this, however, Matt has no experience deploying on this scale
File size of ~1 GB is best, a few is manageable for production.
IT dept supportive of docker@SLAC. There is 1 machine with RHEL7
Lyon is a much larger computing center - likely they will upgrade to Docker first
- Now full support for Docker at Lyon (Fred)
  Joris : Lyon wants to use Singularity because they have security issues with UGE + Docker.

Infrastructure:

Last purchase went into dev cluster
- many nodes @RHEL6, upgrade to RHEL7 and doing docker with this
- Still figuring out NFS/AFS sorted out with RHEL7. GPFS?
It's good to come up with a plan because of security implications if NFS underneath.
- Use right docker (UID issues w/security)
SLAC will give us a few nodes for testing docker. Fall back way to install on user machines. (Brian)
- AFS on RHEL6 docker
- read files if world readable.
- NFS is hardest.
Timeline for RHEL7, 12mo? 2018? (Matt)
- RHEL7 support is dodgy.
- Configuration stuff is hard part

Software dependencies :

GPL_TOOLS (staging and logging)
REPRO common tools
REPRO task scripts
GlastRelease
ScienceTools
GLAST_EXT software (e.g., python, root)
Ftools (KIPAC installation)
ROOT skimmer
FITS skimmer (possibly unnecessary?)
evtClassDefs
calibration and alignment files
diffuse models
xroot tools
xroot /glast/Scratch space
/scratch on local batch machines
data catalog query (FT2 file and current version of FITS files)
mySQL DB (calibration and alignment)
Fermi astrotools (could probably eliminate)

Farms status

Farm	Node OS	Network FS	VMs	Container
SLAC	RHEL6	AFS / NFS	No (never says Brian)	Docker
CC-IN2P3	RHEL6 and CentOS7	AFS to be phased out, CVMFS	A OpenStack Cloud is running but not for production	?
GRID sites	mostly RHEL6, a few CentOS7	many have CVMFS	no	?

Questions

Joris : Is there some security issues with LSF & Docker (https://developer.ibm.com/storage/2017/01/09/running-ibm-spectrum-lsf-jobs-in-docker-containers/ )
Joris : We need to verify the compatibility between Singularity ( Lyon CC ) and Docker
etc.