Compilation of my live tweets from SNIA’s SDC 2012 (Storage Developer Conference)


Here is a compilation of my live tweets from SNIA’s SDC 2012 (Storage Developers Conference).
You can also read those directly from twitter at https://twitter.com/josebarreto (in reverse order)

Notes and disclaimers

  • These tweets were typed during the talks and they include typos and my own misinterpretations.
  • Text under each talk are quotes from the speaker or text from the speaker slides, not my personal opinion.
  • If you feel that I misquoted you or badly represented the content of a talk, please add a comment to the post.
  • I spent just limited time fixing typos or correcting the text after the event. Just so many hours in a day...
  • I have not attended all sessions (since there are 4 or 5 at a time, that would actually not be possible :-)…
  • SNIA usually posts the actual PDF decks a few weeks after the event. Attendees have access immediately.

Linux CIFS/SMB2 Kernel Clients - A Year In Review by Steven French, IBM

  • SMB3 will be important for Linux, not just Windows #sdc2012
  • Linux kernel supports SMB. Kernel 3.7 (Q4-2012) includes 71 changes related to SMB (including SMB 2.1), 3.6 has 61, 3.5 has 42
  • SMB 2.1 kernel code in Linux enabled as experimental in 3.7. SMB 2.1 will replace CIFS as the default client when stable.
  • SMB3 client (CONFIG_EXPERIMENTAL) expected by Linux kernel 3.8.
  • While implementing Linux client for SMB3, focusing on strengths: clustering, RDMA. Take advantage of great protocol docs

Multiuser CIFS Mounts, Jeff Layton, Red Hat

  • I attended this session, but tweeted just the session title.

How Many IOPS is Enough by Thomas Coughlin, Coughlin Associates

  • 79% of surveyed people said they need between 1K and 1M IOPs. Capacity: from 1GB to 50TB with sweet spot on 500GB.
  • 78% of surveyed people said hardware delivers between 1K and 1M IOPs, with a sweet spot at 100K IOPs. Matches requirements  
  • Minimum latency system hardware (before other bottleneck) ranges between >1sec to <10ns. 35% at 10ms latency.
  • $/GB for SDD and HDD both declining in parallel paths. $/GB roughly follows IOPs.
  • Survey results will be available in October...

SMB 3.0 ( Because 3 > 2 ) - David Kruse, Microsoft

  • Fully packed room to hear David's SMB3 talk. Plus a few standing in the back... pic.twitter.com/TT5mRXiT
  • Time to ponder: When should we recommend disabling SMB1/CIFS by default?

Understanding Hyper-V over SMB 3.0 Through Specific Test Cases with Jose Barreto

  • No tweets during this session. Hard to talk and tweet at the same time 🙂

Continuously Available SMB – Observations and Lessons Learned - David Kruse and Mathew George.

  • I attended this session, but tweeted just the session title.

Status of SMB2/SMB3 Development in Samba, Michael Adam, Samba Team

  • SMB 2.0 officially supported in Samba 3.6 (about a year ago, August 2011)
  • SMB 2.1 work done in Samba for Large MTU, multi-credit, dynamic re-authentication
  • Samba 4.0 will be the release to incorporate SMB 3.0 (encryption and secure negotiate already done)

The Solid State Storage (R-)Evolution, Michael Krause, Hewlett-Packard

  • Storage (especially SSD) performance constrained by SAS interconnects
  • Looking at serviceability from DIMM to PCIe to SATA to SAS. Easy to replace x perfor
  • No need to re-invent SCSI. All OS, hypervisors, file systems, PCIe storage support SCSI.
  • Talking SCSI Express. Potential to take advantage of PCIe capabilities.
  • PCIe has benefits but some challenges: Non optimal DMA "caching", non optimal MMIO performance
  • everything in the world of storage is about to radically change in a few years: SATA, SAS, PCIe, Memory
  • Downstream Port Containment. OS informed of async communications lost.
  • OCuLink: new PCIe cable technology
  • Hardware revolution: stacked media, MCM / On-die, DIMM. Main memory in 1 to 10 TB. Everything in memory?
  • Express Bay (SFF 8639 connector), PCIe CEM (MMIO based semantics), yet to be developed modules
  • Media is going to change. $/bit, power, durability, performance vs. persistence. NAND future bleak.
  • Will every memory become persistent memory? Not sic-fi, this could happen in a few years...
  • Revolutionary changes coming in media. New protocols, new hardware, new software. This is only the beginning

Block Storage and Fabric Management Using System Center 2012 Virtual Machine Manager and SMI-S, Madhu Jujare, Microsoft

  • Windows Server 2012 Storage Management APIs are used by VMM 5012. An abstraction of SMI-S APIs.
  • SMAPI Operations: Discovery, Provisioning, Replication, Monitoring, Pass-thru layer
  • Demo of storage discovery and mapping with Virtual Machine Manager 2012.SP1. Using Microsoft iSCSI Target!

Linux Filesystems: Details on Recent Developments in Linux Filesystems and Storage by Chris Mason, Fusion-io

  • Many journaled file systems introduced in Linux 2.4.x in the early 2000s.
  • Linux 2.6.x. Source control at last. Kernel development moved more rapidly. Specially after Git.
  • Backporting to Enterprise. Enterprise kernels are 2-3 years behind mainline. Some distros more than others.
  • Why are there so many filesystems? Why not pick one? Because it's easy and people need specific things.
  • Where Linux is now. Ext4, XFS (great for large files). Btrfs (snapshots, online maintenance). Device Mapper.
  • Where Linux is now. CF (Compact Flash). Block. SCSI (4K, unmap, trim, t10 pi, multipath, Cgroups).
  • NFS. Still THE filesystem for Linux. Revisions introduce new features and complexity. Interoperable.
  • Futures. Atomic writes. Copy offload (block range cloning or new token based standard). Shingled drives (hybrid)
  • Futures. Hinting (tiers, connect blocks, IO priorities). Flash (seems appropriate to end here 🙂

Non-volatile Memory in the Storage Hierarchy: Opportunities and Challenges by Dhruva Chakrabarti, HP

  • Will cover a few technologies coming the near future. From disks to flash and beyond...
  • Flash is a huge leap, but NVRAM presents even bigger opportunities.
  • Comparing density/retention/endurance/latency/cost for hdd/sdd (nand flash)/dram/nvram
  • Talking SCM (Storage Class Memory). Access choices: block interface or byte-addressable model.
  • Architectural model for NVRAM. Coexist with DRAM. Buffers/caches still there. Updates may linger...
  • Failure models. Fail-stop. Byzantine. Arbitrary state corruption. Memory protection.
  • Store to memory must be failure-atomic.
  • NVRAM challenges. Keep persistent data consistent. Programming complexity. Models require flexibility.
  • Visibility ordering requirements. Crash can lead to pointers to uninitialized memory, wild pointers.
  • Potential inconsistencies like persistent memory leaks. There are analogs in multi-threading.
  • Insert a cache line flush to ensure visibility in NVRAM. Reminiscent of a disk cache flush.
  • Many flavors of cache flushes. Intended semantics must be honored red. CPU instruction or API?
  • Fence-based programming has not been well accepted. Higher level abstractions? Wrap in transactions?
  • Conclusion. What is the right API for persistent memory? How much effort? What's the implementation cost?

Building Next Generation Cloud Networks for Big Data Applications by Jayshree Ullal, Arista Networks

  • Agenda: Big Data Trends, Data Analytics, Hadoop.
  • 64-bit CPUs trends, Data storage trends. Moore's law is alive and well.
  • Memory hierarchy is not changing. Hard drives not keeping up, but Flash...
  • Moore's law for Big Data, Digital data doubling every 2 years. DAS/NAS/SAN not keeping up.
  • Variety of data. Raw, unstructured. Not enough minds around to deal with all the issues here.
  • Hadoop means the return of DAS. Racks of servers, DAS, flash cache, non-blocking fabric.
  • Hadoop. 3 copies of the data, one in another rack. Protect you main node, single point of failure.
  • Hadoop. Minimum 10Gb. Shift from north-south communications to east-west. Servers talking to each other.
  • From mainframe, to client/server, to Hadoop clusters.
  • Hadoop pitfalls. Not a layer 2 thing. Highly redundant, many paths, routing. Rack locality. Data integrity
  • Hadoop. File transfers in chunks and blocks. Pipelines replication east-west. Map and Reduce.
  • showing sample 2-rack solution. East-west interconnect is very important. Non-blocking. Buffering.
  • Sample conf. 4000 nodes. 48 servers per cabinet. High speed network backbone. Fault tolerant main node
  • Automating cluster provisioning. Script using DHCP for zero touch provisioning.
  • Buffer challenges. Dynamic allocations, survive micro bursts.
  • Advanced diagnostics and management. Visibility to the queue depth and buffering. Graph historical latency.
  • my power is running out. I gotta speak fast. 🙂

Windows File and Storage Directions by Surendra Verma, Microsoft

  • Landscape: pooled resources, self-service, elasticity, virtualization, usage-based, highly available
  • Industry-standard parts to build very high scale, performing systems. Greater number of less reliable parts.
  • Services influencing hardware. New technologies to address specific needs. Example: Hadoop.
  • OS storage built to address specific needs. Changing that requires significant effort.
  • You have to assume that disks and other parts will fail. Need to address that in software.
  • If you have 1000 disks in a system, some are always failing, you're always reconstructing.
  • ReFS: new file system in Windows 8, assumes that everything is unreliable underneath.
  • Other relevant features in Windows Server 2012: Storage Spaces, Clustered Shared Volumes, SMB Direct.
  • Storage Spaces provides resiliency to media failures. Mirror (2 or 3 way), parity, hot spares.
  • Shared Storage Spaces. Resiliency to node and path failures using shared SAS disks.
  • Storage Spaces is aware of enclosures, can tolerate failure of an entire enclosure.
  • ReFS provides resiliency to media failures. Never write metadata in place. Integrity streams checksum.
  • integrity Streams. User data checksum, validated on every read. Uses Storage Spaces to find a good copy.
  • You own application can use an API to talk to Storage Spaces, find all copies of the data, correct things.
  • Resiliency to latent media errors. Proactively detect and correct, keeping redundancy levels intact.
  • ReFS can detect/correct corrupted data even for data not frequently read. Do it on a regular basis.
  • What if all copies are lost? ReFS will keep the volume online, you can still read what's not corrupted.
  • example configuration with 4 Windows Server 2012 nodes connected to multiple JBODs.

Hyper-V Storage Performance and Scaling with Joe Dai & Liang Yang, Microsoft

Joe Dai:

  • New option in Windows Server 2012: Virtual Fibre Channel. FC to the guest. Uses NPIV. Live migration just works.
  • New in WS2012: SMB 3.0 support in Hyper-V. Enables Shared Nothing Live Migration, Cross-cluster Live Migration.
  • New in WS 2012: Storage Spaces. Pools, Spaces. Thin provisioning. Resiliency.
  • Clustered PCI RAID. Host hardware RAID in a cluster setup.
  • Improved VHD format used by Hyper-V. VHDX. Format specification at http://www.microsoft.com/en-us/download/details.aspx?id=29681 Currently v0.95. 1.0 soon
  • VHDX: Up to 64TB. Internal log for resiliency. MB aligned. Larger blocks for better perf. Custom metadata support.
  • Comparing performance. Pass thru, fixed, dynamic, differencing. VHDX dynamic ~= VHD fixed ~= physical disk.
  • Offloaded Data Transfers (ODX). Reduces times to merge, mirror and create VHD/VHDX. Also works for IO inside the VM.
  • Hyper-V support for UNMAP. Supported on VHDX, Pass-thru. Supported on VHDX Virtual SCSI, Virtual FC, Virtual IDE.
  • UNMAP in Windows Server 2012 can flow from virtual IDE in VM to VHDX to SMB share to block storage behind share.

Laing Yang:

  • My job is to find storage bottlenecks in Hyper-V storage and hand over to Joe to fix them. 🙂
  • Finding scale limits in Hyper-V synthetic SCSI IO path in WS2008R2. 1 VSP thread, 1 VMBus channel per VM, 256 queue depth per
  • WS2012: From 4 VPs per VM to 64 VP per VM. Multi-threaded IO model. 1 channel per 16 VPs. Breaks 1 million IOPs.
  • Huge performance jump in WS2012 Hyper-V. Really close to physical even with high performance storage.
  • Hyper-V Multichannel (not to be confused with SMB Multichannel) enables the jump on performance.
  • Built 1 million IOPs setup for about $10K (excluding server) using SSDs. Demo using IOmeter. Over 1.22M IOPs...

The Virtual Desktop Infrastructure Storage Behaviors and Requirements with Spencer Shepler, Microsoft

  • Storage for Hyper-V in Windows Server 2012: VHDX, NTFS, CSV, SMB 3.0.
  • Review of SMB 3.0 advantages for Hyper-V: active recovery, Multichannel, RDMA.
  • Showing results for SMB Multichannel with four traditional 10GbE. Line rate with 64KB IOs. CPU bound with 8KB.
  • Files used by Hyper-V. XML, BIN, CSV, VHD, VHDX, AVHDX. Gold, diff and snapshot disk relationships.
  • improvements in VHDX. Up to 64TB size. 4KB logical sector size, 1MB alignment for allocations. UNMAP. TRIM.
  • VDI: Personal desktops vs. Pooled desktops. Pros and cons.
  • Test environment. WS2012 servers. Win7 desktops. Login VSI http://www.loginvsi.com - 48 10K rpm HDD.
  • Workload. Copy, word, print pdf, find/replace, zip, outlook e-mail, ppt, browsing, freemind. Realistic!
  • Login VSI fairly complex to setup. Login frequency 30 seconds. Workload started "randomly" after login.
  • Example output from Login VSI. Showing VSI Max.
  • Reading of BIN file during VM restore is sequential. IO size varies.
  • Gold VHDX activity. 77GB over 1 hour. Only reads, 512 bytes to 1MB size IOs. 25KB average. 88% are <=32KB
  • Distribution for all IO. Reads are 90% 64KB or less. Writes mostly 20KB or less.
  • AVHD activity 1/10 read to write ratio. Flush/write is 1/10. Range 512 bytes to 1MB. 90% are 64KB or less.
  • At the end of test run for 1 hour with 85 desktops. 2000 IOPs from all 85 VMs, 2:1 read/write ratio.

SQL Server: Understanding the Data Workload by Gunter Zink, Microsoft (original title did not fit a tweet)

  • Looking at OLTP and data warehousing workloads. What's new in SQL Server 2012.
  • Understanding SQL Server. Store and retrieve structured data, Relation, ACID, using schema.
  • Data organized in tables. tables have columns. Tables stored in 8KB pages. Page size fixed, not configurable.
  • SQL Server Datafile. Header, GAM page (bitmap for 4GB of pages), 4GB of pages, GAM page, 4GB of pages, etc...
  • SQL Server file space allocated in extents. An extent is 8 pages or 64KB. Parameter for larger extent size.
  • SQL Server log file: Hreader, log records (512 bytes to 60KB). Checkpoint markers. truncated after backup.
  • If your storage reports 4KB sector size, minimum log write for SQL Server is 4KB. Records are padded.
  • 2/3 of SQL Servers run OLTP workloads. Many active users, lightweight transactions.
  • Going over what happens when you run OLTP. Read cache or read disk, write log to disk and mark page as dirty
  • Log buffer. Circular buffer, no fixed size. One buffer written to disk, another being filled with changes.
  • If storage is not fast enough, writing log takes longer and buffer changes grows larger.
  • Lazy writer. Writes dirty pages to disk (memory pressure). Checkpoint: Writes pages, marks log file (time limit)
  • Checkpoint modes: Automatic, Indirect, Manual. Write rate reduced if latency reaches 20ms (can be configured)
  • Automatic SQL Checkpoint. Write intensity controlled by recovery interval. Default is 0 = every two minutes.
  • New in SQL Server 2012. Target_Recovery_Time. Makes checkpoint less spikey by constantly writing dirty pages.
  • SQL Server log file. Change records in sequence. Mostly just writes. Except in recovery or transaction rollback.
  • Data file IO. 8KB random reads, buffered (based on number of user queries). Can be done in 64KB at SQL start up.
  • Log file IO: unbuffered small sequential writes (depends on how many inserts/updates/deletes).
  • About 80% of SQL Server performance problems are storage performance problems. Not enough spindles or memory.
  • SQL Server problems. 20ms threshold too high for SSDs. Use -k parameter to limit (specified in MB/sec)
  • Issues. Checkpoint floods array cache (20ms). Cache de-staging causes log drive write performance.
  • Log writes must go to disk, no buffering. Data writes can be buffered, since it can recover from the log.
  • SQL Server and Tiered Storage. We probably won't read what we've just written.
  • Data warehouse. Read large amounts of data, mostly no index, table scans. Hourly or daily updates (from OLTP).
  • Understanding a data warehouse query. Lots of large reads. Table scans and range scans. Reads: 64KB up to 512KB.
  • DW. Uses TempDB to handle intermediate results, sort. Mostly 64KB writes, 8KB reads. SSDs are good for this.
  • DW common problems: Not enough IO bandwidth. 2P server can ingest 10Gbytes/sec. Careful with TP, pooled LUNs.
  • DW common problems. Arrays don't read from multiple mirror copies.
  • SMB file server and SQL Server. Limited support in SQL Server 2008 R2. Fully supported with SQL Server 2012.
  • I got my fastest data warehouse performance using SMB 3.0 with RDMA. Also simpler to manage.
  • Comparing steps to update SQL Server with Fibre Channel and SMB 3.0 (many more steps using FC).
  • SQL Server - FC vs. SMB 3.0 connectivity cost comparison. Comparing $/MB/sec with 1GbE, 10GbE, QDR IB, 8G FC.

The Future of Protocol and SMB2/3 Analysis with Paul Long, Microsoft

  • We'll talk about Message Analyzer. David is helping.
  • Protocol Engineering Framework
  • Like Network Monitor. Modern message analysis tool built on the Protocol Engineering Framework
  • Source for Message Analyzer can be network packets, ETW events, text logs, other sources. Can validate messages.
  • Browse for message sources, Select a subset of messages, View using a viewer like a grid..
  • New way of viewing starting from the top down, instead of the bottom up in NetMon.
  • Unlike NetMon, you can group by any field or message property. Also payload rendering (like JPG)
  • Switching to demo mode...
  • Guidance shipped online. Starting with a the "Capture/Trace" option.
  • Trace scenarios: NDIS, Firewall, Web Proxy, LAN , WLAN, Wifi. Trace filter as well.
  • Doing a link layer capture (just like old NetMon). Start capture. Generate some web traffic.
  • Stop the trace. Group by module. Look at all protocols. Like HTTP. Drill in to see operations.
  • Looking at operations. HTTP GET. Look at the details. High level stack view.
  • Now grouping on both protocol and content type. Easily spots pictures over HTTP. Image preview.
  • Easier to see time elapsed per operation when you group messages. You dig to individual messages
  • Now looking at SMB trace. Trace of a file copy. Group on the file name (search for the property)
  • Now grouped on SMB.Filename. You can see all SB operations to copy a specific file.
  • Now looking at a trace of SMB file copy to an encrypted file share.
  • Built in traces to capture from the client side or server side. Can do full PDU or header.only
  • This can also be used to capture SMB Direct data, using the SMB client trace.
  • Showing the trace now with both network traffic and SMB client trace data (unencrypted).
  • Want to associate the wire capture with the SMB client ETW trace? Use the message ID
  • Showing mix of firewall trace and SMB client ETW trace. You see it both encrypted and not.
  • SMB team at Microsoft is the first to add native protocol unit tracing. Very useful...
  • Most providers have ETW debug logging but not the actual messages.
  • You can also get the trace with just NetSh or LogMan and load the trace in the tool later.
  • We also can deploy the tool and use PowerShell to start/stop capture.
  • If the event provider offers them, you can specify level and keywords during the capture.
  • Add some files (log file and wireshark trace). Narrow down the time. Add selection filter.
  • Mixing wireshark trace with a Samba text log file (pattern matching text log).
  • Audience: As a Samba hacker, Message Analyzer is one of the most interesting tools I have seen!
  • Jaws are dropping as Paul demos analyzing a trace from WireShark + Samba taken on Linux.
  • Next demo: visualizations. Two separate file copies. Showing summary view for SMB reads/writes
  • Looking at a graph of bytes/second for SMB reads and writes. Zooming into a specific time.
  • From any viewer you should be any to do any kind of selection and then launch another viewer.
  • If you're a developer, you can create a very sophisticated viewer.
  • Next demo: showing the protocol dashboard viewer. Charts with protocol bars. Drills into HTTP.

Storage Systems for Shingled Disks, with Garth Gibson, Panasas

  • Talking about disk technology. Reaction of HDD to what's going with SSDs.
  • Kryder's law for magnetic disks. Expectation is that disks will cost next to nothing.
  • High capacity disk. As bits get smaller, the bit might not hold it's orientation 10 years later.
  • Heat assisted to make it possible to write, then keep it longer when cold. Need to aim that laser precisely..
  • New technology. Shingled writing. Write head is wider than read head. Density defined by read head, not write head.
  • As you write, you overwrite a portion of what you wrote before, but you can still read it.
  • Shingled can be done with today's heads with minor changes, no need to wait for heat assisted technology.
  • Shingled disks. Large sequential writes. Disks becomes tape!!
  • Hard to see just the one bit. Safe plan is to see the bit from slightly different angles and use signal processing.
  • if aiming at 3x the density: cross talk. Signal processing using 2 dimensions TMDR. 3-5 revs to to read a track.
  • Shingled disks. Initial multiplier will be a factor of 2. Seek 10nm instead of 30 nm. Wider band with sharp edges.
  • Write head edge needs to be sharp on one side, where the tracks will overlap. Looking at different widths.
  • Aerial density favors large bands that overlap. Looking at some math that proves this.
  • You could have a special place in the disk with no shingles for good random write performance, mixed with shingled.
  • Lots of question on shingled disks. How to handle performance, errors, etc.
  • Shingled disks. Same problem for Flash. Shingled disks - same algorithms as Flash.
  • modify software to avoid or minimize read, modify, write. Log structured file systems are 20 years old.
  • Key idea is that disk attribute says "sequential writing". T13 and t10 standards.
  • Shingled disks. Hadoop as initial target. Project with mix of shingled and unshingled disks. Could also be SSD+HDD.
  • Prototype banded disk API. Write forward or move back to 0. Showing test results with new file system.
  • future work. Move beyond hadoop to general workloads, hurts with lots of small files. Large files ok.
  • future work. Pack metadata. All of the metadata into tables, backed on disk by large blob of changes.
  • Summary of status. Appropriate for Big Data. One file = one band. Hadoop is write once. Next steps: pack metadata.

The Big Deal of Big Data to Big Storage with Benjamin Woo, Neuralytix

  • Can't project to both screens because laptop does not have VGA. Ah, technology... Will use just right screen.
  • Even Batman is into big data. ?!
  • What's the big picture for big data. Eye chart with lots of companies, grouped into areas...
  • We have a problem with storage/data processing today. Way too many hops. (comparing to airline routes ?!)
  • Sample path: Oracle to Informatica to Microstategy and Hadoop. Bring them together. Single copy of "the truth".
  • Eliminate the process of ETL. Eliminate the need for exports. Help customers to find stuff in the single copy.
  • You are developers. You need to find a solution for this problem. Do you buy into this?
  • Multiple copies OK for redundancy or performance, but shouldn't it all be same source of truth?
  • Single copy of the truth better for discovery. Don't sample, don't summarize. You will find more than you expect.
  • We're always thinking about the infrastructure. Remove yourself from the hardware and think about the data!
  • The challenge is how to think about the data. Storage developers can map that to the hardware.
  • Send complaints to /dev/null. Tweet at @BenWooNY
  • Should we drop RDBMS altogether? Should we add more metadata to them? Maybe.
  • Our abstractions are already far removed from the hardware. Think virtual disks in VM to file system to SAN array.
  • Software Defined Storage is something we've been doing for years in silicon.
  • Remember what we're here for. It's about the data. Otherwise there is no point in doing storage.
  • Is there more complexity in having a single copy of the truth? Yes, but that is part of what we do! We thrive there!
  • Think about Hadoop. They take on all the complexity and use dumb hardware. That's how they create value!

Unified Storage for the Private Cloud with Dennis Chapman, NetApp

  • 10th anniversary of SMI-S. Also 10th anniversary of pirate day. Arghhh...
  • application silos to virtualization to private clouds (plus public and hybrid clouds)
  • Focusing on the network. Fundamentally clients talking to storage in some way...
  • storage choices for physical servers. Local (DAS) and remote (FC, iSCSI, SMB). Local for OS, remote for data.
  • Linux pretty much the same as Windows. Difference is NFS instead of SMB. Talking storage affinities.
  • Windows OS. Limited booting from iSCSI and FC. Mostly local.
  • Windows. Data mostly on FC and iSCSI, SMB still limited (NFS more well established on Linux).
  • shifting to virtualized workloads on Windows. Opts for local and remote. More choices, storage to the guest.
  • Virtualized workloads are the #1 configuration we provide storage for.
  • Looking at options for Windows and Linux guests, hosted on both VMware and Hyper-V hosts. Table shows options
  • FC to the guest. Primary on Linux, secondary on Windows. Jose: FC to the guest new in WS2012.
  • File storage (NFS) primary on Linux, but secondary on Windows (SMB). Jose: again, SMB support new in WS2012.
  • iSCSI secondary for Linux guest, but primary for Windows guests.
  • SMB still limited right now, expect it to grow. Interested on how it will play, maybe as high as NFS on Linux
  • Distributed workload state. Workload domain, hypervisors domain, storage domain.
  • Guest point in time consistency. Crash consistency or application consistency. OS easier, applications harder
  • Hibernation consistency. Put the guest to sleep and snapshot. Works well for Windows VMs. Costs time.
  • Application consistency. Specific APIs. VSS for Windows. I love this! Including remote VSS for SMB shares.
  • Application consistency for Linux. Missing VSS. We have to do specific things to make it work. Not easy.
  • hypervisors PIT consistency. VMware, cluster file system VMFS. Can store files on NFS as well.
  • Hypervisors PIT for Hyper-V. Similar choices with VHD on CSV. Also now option for SMB in WS2012.
  • Affinities and consistency. Workload domain, Hypervisors domain and Storage domain backups. Choices.
  • VSS is the major difference between Windows and Linux in terms of backup and consistency.
  • Moving to the Storage domain. Data ONTAP 8 Clustering. Showing 6-node filer cluster diagram.
  • NetApp Vservers owns a set of Flexvols, with contain close objects (either LUN or file).
  • Sample workflow with NetApp with remote SMB storage. Using remote VSS to create a backup using clones.
  • Sample workflow. App consistent backup from a guest using an iSCSI LUN.
  • Showing eye charts with integration with VMware and Microsoft.
  • Talking up the use of PowerShell, SMB when integrating with Microsoft.
  • Talk multiple protocols, rich services, deep management integration, highly available and reliable.

SNIA SSSI PCIe SSD Round Table. Moderator + four members.

  • Introductions, overview of SSSI PCIe task force and committee.
  • 62 companies in the last conference. Presentations available for download. http://www.snia.org/forums/sssi/pcie
  • Covering standards, sites and tools available from the group. See link posted
  • difference between PCIE SSDs look just other drives, but there are differences. Bandwidth is one of them.
  • Looking at random 4KB write IOPs and response time for different types of disks: HDD, MLC, SLC, PCIe.
  • Different SSD tech offer similar response rates. Some high latencies due to garbage collection.
  • comparing now DRAM, PCIe, SAS and SATA. Lower latencies in first two.
  • Comparing CPU utilization. From less than 10% to over 50%. What CPU utilization to achieve IOPs...
  • Other system factors. Looking at CPU affinity effect on random 4KB writes... Wide variation.
  • Performance measurement. Response time is key when testing PCIe SSDs. Power mgmt? Heat mgmt? Protocol effect on perf?
  • Extending the SCSI platform for performance. SCSI is everywhere in storage.
  • Looking at server attached SSDs and how much is SATA, SAS, PCIe, boot drive. Power envelope is a consideration.
  • SCSI is everywhere. SCSI Express protocol for standard path to PCIe. SoP (SCSI over PCIe). Hardware and software.
  • SCSI Express: Controllers, Drive/Device, Drivers. Express bay connector. 25 watts of power.
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