Tag: Coho Data

Coho Data, hyperloglog and the quest for IO performance

Posted on by Ray in Clustered storage, Data analytics, File Storage, SSD storage, Storage, Storage performance, System effectiveness, Visionary leadershp

We were at SFD6, last month and Coho Data‘s CTO & Co-Founder, Andy Warfield got up to tell us what’s happening at Coho. (We also met with Andy at SFD4, check out the videolinks to learn more.)

What’s new at Coho Data

Coho Data has been shipping GA product for about 3 quarters and is a simple to use, scale-out, hybrid (SSD & disk) storage system for VMware NFS datastores. Coho Data storage uses Software Defined Networking (SDN) switches to perform faster networking handoffs and optimized data flow across storage nodes. They use standard servers and a SDN switch that can scale from two nodes (micro-arrays) to lots (100 or more?).

Version 2.0 will add remote asynch replication and enhanced API enhancements. We won’t discuss the update anymore but if you want your storage to tweet its messages/alerts check it out. Thank Chris Wahl when you start seeing storage system tweets pollute your  twitter feed.

The highlight of the session, was Andy’s discussion of HyperLogLog, a new approach to understanding customer workloads.

HyperLogLog

Coho Data was designed from the start using Microsoft IO traces (1-week of MSR Cambridge datacenter block IO traces available at SNIA IO Trace repository).  [bold italics added later, ed.] which recorded all IO from 10 But Coho also recorded linux developers developer desktop IO activity for a year, amounting to ~ 1B 7.6B IOs and multi-TBs of data. I just got a call looking for some file activity tracing, so everybody in storage could use more IO traces. But detailed IO traces take up CPU cycles and lot’s of space. HyperLogLogs can solve a portion of this.

Before we go there, a little background. For instance, with a Bloom Filter you can tell whether a block has been referenced or not. In a bloom filter you hash a key, term or whatever multiple times and then OR them into separate bitfields, one per hash. Bloom filters have a small possibility of a false positive (block-id present in filter but was not really in IO stream) but no possibility of a false negative (block-id NOT present in filter but it really was in IO stream). However, bloom filters tells us nothing about how frequently blocks were read.

With a HyperLogLog, one can approximate (within ~2%) how many times a block was referenced. By capturing multiple HyperLogLogs pictures over time, one can determine block access frequency during application processing. Each HyperLogLog trace only occupies ~2 KB, so recording one/hour takes ~50KB/day. The math is beyond me but there’s plenty info online (e.g. here).

HyperLogLog functionality will be included in a future Coho Data update. Coho Data will be implementing what they call “Counter Stacks” which makes use of hyperloglogs in a future release (see Jake Wire’s Usenix Session video/PDF). Once present, Coho Data will save hyperloglog counter stack data, analyze it, and use it to better characterize customer IO with the goal of better optimizing their storage system to actual workloads

For more info please see other SFD6 blogger posts on Coho Data:

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Now if someone could just develop a super efficient algorithm/storage structure to record block sequences I think we have this licked.

Disclosure statement: I have done work for Coho Data over the last year.

Picture credits: (Lego) Me holding a Coho (Data) Salmon 🙂

Fall SNWUSA 2013

Posted on by Ray in Cloud services, Crowdsourcing, Data grid, File Storage, Object storage, Software Defined Network, Storage, Storage architecture, Strategic Inflection Points, Strategy, System effectiveness, Systems, Visionary leadershp

Here’s my thoughts on SNWUSA which occurred this past week in the Long Beach Convention Center.

First, it was a great location. I saw a number of users I haven’t seen at SNWUSA ever before, some of which I have known for years from other (non-storage) venues.

Second, the exhibit hall was scantly populated. There were no major storage vendors at the show at all. Gold sponsors included NEC, Riverbed, & Sepaton, representing the largest exhibiters presenn. Making up the next (Contributing) tier were Western Digital, Toshiba, Active Archive Alliance, and LTO consortium with a smattering of smaller companies.  Finally, there were another 12 vendors with kiosks around the floor, with the largest there being Veeam Software.

I suspect VMWorld Europe happening the same time in Barcelona might have had something to do with the sparse exhibit floor but the trend has been present for the past few shows.

That being said there were still a few surprises in store, at least for me.  Two of the most interesting ones were:

  • Coho Data who came out of stealth with a scale out, RAIN (Redundant array of independent nodes) based storage cluster, with distributed, mirrored customer data across nodes and software defined networking. They currently support NFS for VMware with a management UI reminiscent of IOS 7 sans touch support. The product comes as a series of nodes with SSDs, disk storage and SDN. The SDN allows Coho Data to relocate front-end (client) connections to where the customer data lies. The distributed, mirrored backend storage provides redundancy in the case of a node/disk failure, at which time the system understands what data is now at risk and rebuilds the now-mirorless data onto other nodes. It reminds me a lot of Bycast/Archivas like architectures, with SDN and NFS support. I suppose the reason they are supporting VMware VMDKs is that the files are fairly large and thus easier to supply.
  • Cloud Physics was not exhibiting but they sponsored a break. As such, they were there talking with analysts and the press about their product. Their product installs as a VMware VM service and propagates VMware management agents to ESX servers which then pipe information back to their app about how your VMware environment is running, how VMs are performing, how your network and storage are performing for the VMs running, etc. This data is then sent to the cloud, where it’s anonymized. In the cloud, customers can use apps (called Cards) to analyze this data in the cloud, which can help them understand problem areas, predict what configuration changes can do for them, show them how VMs are performing, etc. It essentially is logging all this information to the cloud and providing ways to analyze the data to optimize your VMware environment.

Coming in just behind these two was Jeda Networks with their Software Defined Storage Network (SDSN). They use commodity (OpenFlow compatible) 10GbE switches to support a software FCoE storage SAN. Jeda Networks say that over the past two years,  most 10GbE switch hardware have started to support DCB in hardware and with that in place, plus OpenFlow compatibility, they can provide a SDSN on top of them just by emulating a control layer for FCoE switches. Of course one would still need FCoE storage and CNAs but with that in place one could use much cheaper switches to support FCoE.

CloudPhysics has a subscription based pricing model which offers three tiers:

  • Free where you get their Vapp, the management agents and a defined set of Free Card Apps for no cost;
  • Standard level where you get all the above plus a set of Card Apps which provide more VMware managability for $50/ESX server/Month; and
  • Enterprise level where you get all the above plus all the Card Apps presently available for $150/ESX server/Month.

Jeda networks and Coho Data are still developing their pricing and had none they were willing to disclose.

One of the CloudPhysics Card apps could predict how certain VMs would benefit from host based (PCIe or SSD) IO caching. They had a chart which showed working set inflection points for (I think) one VM running an OLTP application.  I have asked for this chart to discuss further in a future post.  But although CloudPhysics has the data to produce such a chart, the application shows three potential break points where say adding 500MB, 2000MB or 10000MB of SSD cache can speed up application performance by 10%, 30% or 50% (numbers here made up for example purposes and not off the chart they showed me).

A few other companies made announcements at the show. For example, Sepaton announced their new VirtuoSO, scale out hybrid reduplication appliance.

That’s about it. I would have to say that SNW needs to rethink their business model, frequency of stows or what they are trying to do at their conferences. However, on the plust side, most of the users I talked with came away with a lot of information and thought the show was worthwhile and I came away with a few surprises.

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