Cloud & Virtualisation Update at the RAL Tier 1 Ian Collier Andrew Lahiff STFC RAL Tier 1 HEPiX, Lincoln, NEBRASKA, 17 th October 2014.

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Presentation transcript:

Cloud & Virtualisation Update at the RAL Tier 1 Ian Collier Andrew Lahiff STFC RAL Tier 1 HEPiX, Lincoln, NEBRASKA, 17 th October 2014

RAL Tier 1 Recap Hyper-V Across STFC Scientific Computing Department Cloud Batch farm related virtualisation

Recap - HyperV at RAL Tier began investigating virtualisation platform Settled on Hyper-V –A challenge for Linux admins Production local storage Hypervisors in 2011 Shared EqualLogic iSCSI storage a year or so later –As Martin mentioned it has recently been problematic Even with some problems, life – and service provisioning - much easier –Matter of minutes to hours to provision new host See previous talks for more detail

Hyper-V Issues Challenge for admins without professional Windows experience to manage –Especially when there are difficult issues –Support from overstretched Windows experts has been limited Recent shared storage issues saw hypervisors losing contact with shared volumes –Our attempts to recover made it worse not better (see above re Windows expertise) –Underlying cause may have been subtle firmware clashes –Rebuilding very carefully –But have just hired someone with specific expertise in this area 20/05/2014HEPiX Spring RAL Site Report

Virtualisation & RAL Context at RAL Hyper-V Across STFC Scientific Computing Department Cloud Batch farm related virtualisation

Context at RAL Tier STFC has run a review of corporate IT services Working group on virtualisation Several separate Hyper-V deployments across organisation –Tier 1 has by far the largest Also some VMWare Little shared effort or experience An intention emerging for common configurations and experience sharing

Virtualisation & RAL Context at RAL Hyper-V Across STFC Scientific Computing Department Cloud Dynamically provisioned worker nodes

Recap - SCD Cloud Began as small experiment 2 1/2 years ago –Initially using StratusLab & old worker nodes –Very quick and easy to get working Deployment until now implemented by graduates on 6 month rotation –Disruptive & variable progress Worked well enough to prove usefulness Something of an exercise in managing expectations

SCD Cloud Future Develop to full supported service to users across STFC IaaS upon which we can offer PaaS –One platform could ultimately be the Tier 1 itself –Integrating cloud resources in to Tier 1 grid work Participation in cloud federations Carrying out fresh technology evaluation. –Things have moved on since we started with StratusLab –Currently favour Opennebula

SCD Cloud March this year secured funding for 30 well specified hypervisors & 30 storage servers –~1000 cores (plus ~800 in old WNs) –~1PB raw storage Using OpenNebula –Collaborating with UGent on configuration tools –Ceph for image store and running images –AD as initial primary authentication 2 staff began work last month one full time, one half time

SCD Cloud Initially private cloud Closely coupled to Tier 1 batch – see later Provide support for Scientific Computing Department projects –Eg Horizon 2020 projects coming on line mid next year Also potential use cases with other STFC departments –Parallel to data services already provided to Diamond & ISIS

SCD Cloud Ceph backend –Been investigating for a couple of years –Have separate test bed (half a generation of standard disk servers (1.7PB raw) being tested for grid data storage –Will use for image store, running images, and possibly a data service Summer student worked on benchmarking & tuning –Investigated moving journals to SSDs –Although OSD benchmarks were much faster, overall performance no different –Turned out it was caches in the raid controllers –Will probably run on those systems with out the journal

Virtualisation & RAL Context at RAL Hyper-V Across STFC Scientific Computing Department Cloud Batch farm related virtualisation

Bursting the batch system into the cloud In Annecy described leveraging HTCondor features designed for power saving to dynamically burst batch work in to our private cloud Aims –Integrate cloud with batch system –First step: allow the batch system to expand into the cloud Avoid running additional third-party and/or complex services Leverage existing functionality in HTCondor as much as possible Proof-of-concept testing carried out with StratusLab cloud –Successfully ran ~11000 jobs from the LHC VOs This allows us to be sure good utilization of our private cloud as LHC VOs can always provide work

The Vacuum Model “Vacuum” model is becoming popular in the UK –Alternative to CE + batch system or clouds –No centrally-submitted pilot job or requests for VMs –VMs appear by “spontaneous production in the vacuum” –VMs run the appropriate pilot framework to pull down jobs –See Andrew McNab’s talk in Annecy Can we incorporate the vacuum model into our existing batch system? –HTCondor has a “VM universe” for managing VMs

The Vacuum Model & HTCondor Considered using fetch work hooks on the worker nodes –Unfortunately fairshares would not be respected Now using a scheduler universe job which runs permanently & submits jobs (VMs) as necessary –One for each VO –If no work or an error, only submit 1-2 VMs every hour –If VMs are running real work, submit more VMs –Fairshares are maintained since the negotiator decides what VMs to run

The Vacuum Model & HTCondor Running VMs using HTCondor –Using the CernVM 3 image ISO image only 15MB in size, CVMFS provides root partition –Using a job hook for: Creating a 20 GB sparse hard disk image file for the CVMFS cache Creating a 40 GB sparse hard disk image file to provide additional disk space mounted as /scratch on the VM Contextualization Setting up NFS so that the pilot log files can be written on the worker node’s disk –Using condor_chirp for: Adding information about the status of the pilot to the job’s ClassAd

The Vacuum Model & HTCondor Testing so far includes –Successfully running regular SAM tests from the GridPP DIRAC instance –ATLAS validation jobs First attempt at running jobs from ATLAS. Need to investigate the cause of the failures: Payload ran out of memory Error in copying the file from job workdir to local SE

Integrating Batch & Cloud All these developments allow us more flexibility in managing & delivering Tier 1 computing services

Virtualisation & RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud Batch farm related virtualisation

Summary Provisioning already much more responsive. Private cloud has developed from a small experiment to the beginning of a real service –With constrained effort - Slower than we would have liked –The prototype platform has been well used Demonstrated transparentl expansion of batch farm into cloud. Proof of concept vacuum model implementation using HTCondor Whole Tier 1 service becoming more flexible

Questions ?