AFM based migration provides near-zero downtime and supports migrating EAs/ACLs including immutability attributes (if home is Scale/ESS). I would recommend starting migration in read-only mode, prefetch most of the data and convert the fileset to local-updates (if backup is not needed during the migration) or independent-writer mode before moving the applications to the AFM cache filesets. AFM now supports (from 5.0.2) directory level prefetch with many performance improvements and does not require list-files to be specified.
~Venkat ([email protected]) From: "Oesterlin, Robert" <[email protected]> To: gpfsug main discussion list <[email protected]> Date: 03/06/2019 06:14 PM Subject: [gpfsug-discuss] Follow-up: migrating billions of files Sent by: [email protected] Some of you had questions to my original post. More information: Source: - Files are straight GPFS/Posix - no extended NFSV4 ACLs - A solution that requires $’s to be spent on software (ie, Aspera) isn’t a very viable option - Both source and target clusters are in the same DC - Source is stand-alone NSD servers (bonded 10g-E) and 8gb FC SAN storage - Approx 40 file systems, a few large ones with 300M-400M files each, others smaller - no independent file sets - migration must pose minimal disruption to existing users Target architecture is a small number of file systems (2-3) on ESS with independent filesets - Target (ESS) will have multiple 40gb-E links on each NSD server (GS4) My current thinking is AFM with a pre-populate of the file space and switch the clients over to have them pull data they need (most of the data is older and less active) and them let AFM populate the rest in the background. Bob Oesterlin Sr Principal Storage Engineer, Nuance _______________________________________________ gpfsug-discuss mailing list gpfsug-discuss at spectrumscale.org https://urldefense.proofpoint.com/v2/url?u=http-3A__gpfsug.org_mailman_listinfo_gpfsug-2Ddiscuss&d=DwICAg&c=jf_iaSHvJObTbx-siA1ZOg&r=92LOlNh2yLzrrGTDA7HnfF8LFr55zGxghLZtvZcZD7A&m=YkRmc5bZTZ4O8u_y9PwCjhzuvVXZmhm-_SNQzKhDt0g&s=DUBqVmYz6ycQjkr-PZk4r5hndMIB1-FVzan1CCzlxRg&e=
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