Category: Software defined storage

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56: GreyBeards talk high performance file storage with Liran Zvibel, CEO & Co-Founder, WekaIO

This month we talk high performance, cluster file systems with Liran Zvibel (@liranzvibel), CEO and Co-Founder of WekaIO, a new software defined, scale-out file system. I first heard of WekaIO when it showed up on SPEC sfs2014 with a new SWBUILD benchmark submission. They had a 60 node EC2-AWS cluster running the benchmark and achieved, at the time, the highest SWBUILD number (500) of any solution.

At the moment, WekaIO are targeting HPC and Media&Entertainment verticals for their solution and it is sold on an annual capacity subscription basis.

By the way, a Wekabyte is 2**100 bytes of storage or ~ 1 trillion exabytes (2**60).

High performance file storage

The challenges with HPC file systems is that they need to handle a large number of files, large amounts of storage with high throughput access to all this data. Where WekaIO comes into the picture is that they do all that plus can support high file IOPS. That is, they can open, read or write a high number of relatively small files at an impressive speed, with low latency. These are becoming more popular with AI-machine learning and life sciences/genomic microscopy image processing.

Most file system developers will tell you that, they can supply high throughput  OR high file IOPS but doing both is a real challenge. WekaIO’s is able to do both while at the same time supporting billions of files per directory and trillions of files in a file system.

WekaIO has support for up to 64K cluster nodes and have tested up to 4000 cluster nodes. WekaIO announced last year an OEM agreement with HPE and are starting to build out bigger clusters.

Media & Entertainment file storage requirements are mostly just high throughput with large (media) file sizes. Here WekaIO has a more competition from other cluster file systems but their ability to support extra-large data repositories with great throughput is another advantage here.

WekaIO cluster file system

WekaIO is a software defined  storage solution. And whereas many HPC cluster file systems have metadata and storage nodes. WekaIO’s cluster nodes are combined meta-data and storage nodes. So as one scale’s capacity (by adding nodes), one not only scales large file throughput (via more IO parallelism) but also scales small file IOPS (via more metadata processing capabilities). There’s also some secret sauce to their metadata sharding (if that’s the right word) that allows WekaIO to support more metadata activity as the cluster grows.

One secret to WekaIO’s ability to support both high throughput and high file IOPS lies in  their performance load balancing across the cluster. Apparently, WekaIO can be configured to constantly monitoring all cluster nodes for performance and can balance all file IO activity (data transfers and metadata services) across the cluster, to insure that no one  node is over burdened with IO.

Liran says that performance load balancing was one reason they were so successful with their EC2 AWS SPEC sfs2014 SWBUILD benchmark. One problem with AWS EC2 nodes is a lot of unpredictability in node performance. When running EC2 instances, “noisy neighbors” impact node performance.  With WekaIO’s performance load balancing running on AWS EC2 node instances, they can  just redirect IO activity around slower nodes to faster nodes that can handle the work, in real time.

WekaIO performance load balancing is a configurable option. The other alternative is for WekaIO to “cryptographically” spread the workload across all the nodes in a cluster.

WekaIO uses a host driver for Posix access to the cluster. WekaIO’s frontend also natively supports (without host driver) NFSv3, SMB3.1, HDFS and AWS S3  protocols.

WekaIO also offers configurable file system data protection that can span 100s of failure domains (racks) supporting from 4 to 16 data stripes with 2 to 4 parity stripes. Liran said this was erasure code like but wouldn’t specifically state what they are doing differently.

They also support high performance storage and inactive storage with automated tiering of inactive data to object storage through policy management.

WekaIO creates a global name space across the cluster, which can be sub-divided into one to thousands  of file systems.

Snapshoting, cloning & moving work

WekaIO also has file system snapshots (readonly) and clones (read-write) using re-direct on write methodology. After the first snapshot/clone, subsequent snapshots/clones are only differential copies.

Another feature Howard and I thought was interesting was their DR as a Service like capability. This is, using an onprem WekaIO cluster to clone a file system/directory, tiering that to an S3 storage object. Then using that S3 storage object with an AWS EC2 WekaIO cluster to import the object(s) and re-constituting that file system/directory in the cloud. Once on AWS, work can occur in the cloud and the process can be reversed to move any updates back to the onprem cluster.

This way if you had work needing more compute than available onprem, you could move the data and workload to AWS, do the work there and then move the data back down to onprem again.

WekaIO’s RtOS, network stack, & NVMeoF

WekaIO runs under Linux as a user space application. WekaIO has implemented their own  Realtime O/S (RtOS) and high performance network stack that runs in user space.

With their own network stack they have also implemented NVMeoF support for (non-RDMA) Ethernet as well as InfiniBand networks. This is probably another reason they can have such low latency file IO operations.

The podcast runs ~42 minutes. Linar has been around  data storage systems for 20 years and as a result was very knowledgeable and interesting to talk with. Liran almost qualifies as a Greybeard, if not for the fact that he was clean shaven ;/. Listen to the podcast to learn more.

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Linar Zvibel, CEO and Co-Founder, WekaIO

As Co-Founder and CEO, Mr. Liran Zvibel guides long term vision and strategy at WekaIO. Prior to creating the opportunity at WekaIO, he ran engineering at social startup and Fortune 100 organizations including Fusic, where he managed product definition, design and development for a portfolio of rich social media applications.

 

Liran also held principal architectural responsibilities for the hardware platform, clustering infrastructure and overall systems integration for XIV Storage System, acquired by IBM in 2007.

Mr. Zvibel holds a BSc.in Mathematics and Computer Science from Tel Aviv University.

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54: GreyBeards talk scale-out secondary storage with Jonathan Howard, Dir. Tech. Alliances at Commvault

This month we talk scale-out secondary storage with Jonathan Howard,  Director of Technical Alliances at Commvault.  Both Howard and I attended Commvault GO2017 for Tech Field Day, this past month in Washington DC. We had an interesting overview of their Hyperscale secondary storage solution and Jonathan was the one answering most of our questions, so we thought he would make an good guest for our podcast.

Commvault has been providing data protection solutions for a long time, using anyone’s secondary storag, but recently they have released a software defined, scale-out secondary storage solution that runs their software with a clustered file system.

Hyperscale secondary storage

They call their solution, Hyperscale secondary storage and it’s available in both an hardware-software appliance as well as software only configuration on compatible off the shelf commercial hardware. Hyperscale uses the Red Hat Gluster cluster file system and together with the Commvault Data Platform provides a highly scaleable, secondary storage cluster that can meet anyone’s secondary storage needs while providing high availability and high throughput performance.

Commvault’s Hyperscale secondary storage system operates onprem in customer data centers. Hyperscale uses flash storage for system metadata but most secondary storage resides on local server disk.

Combined with Commvault Data Platform

With the sophistication of Commvault Data Platform one can have all the capabilities of a standalone Commvault environment with software defined storage. This allows just about any RTO/RPO needed by today’s enterprise and includes Live Sync secondary storage replication,  Onprem IntelliSnap for on storage snapshot management, Live Mount for instant recovery using secondary storage directly  to boot your VMs without having to wait for data recovery.  , and all the other recovery sophistication available from Commvault.

Hyperscale storage is capable of doing up to 5 Live Mount recoveries simultaneously per node without a problem but more are possible depending on performance requirements.

We also talked about Commvault’s cloud secondary storage solution which can make use of AWS S3 storage to hold backups.

Commvault’s organic growth

Most of the other data protection companies have came about through mergers, acquisitions or spinoffs. Commvault has continued along, enhancing their solution while bashing everything on an underlying centralized metadata database.  So their codebase was grown from the bottom up and supports pretty much any and all data protection requirements.

The podcast runs ~50 minutes. Jonathan was very knowledgeable about the technology and was great to talk with. Listen to the podcast to learn more.

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Jonathan Howard, Director, Technical and Engineering Alliances, Commvault

Jonathan Howard is a Director, Technology & Engineering Alliances for Commvault. A 20-year veteran of the IT industry, Jonathan has worked at Commvault for the past 8 years in various field, product management, and now alliance facing roles.

In his present role with Alliances, Jonathan works with business and technology leaders to design and create numerous joint solutions that have empowered Commvault alliance partners to create and deliver their own new customer solutions.

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52: GreyBeards talk software defined storage with Kiran Sreenivasamurthy, VP Product Management, Maxta

This month we talk with an old friend from Storage Field Day 7 (videos), Kiran Sreenivasamurthy, VP of Product Management for Maxta. Maxta has a software defined storage solution which currently works on VMware vSphere, Red Hat Virtualization and KVM to supply shared, scale out storage and HCI solutions for enterprises across the world.

Maxta is similar to VMware’s vSAN software defined storage whose licenses can be transferred from one server to another, as you upgrade your data center over time. As software defined storage, Maxta runs on any standard Intel X86 hardware. Indeed, Maxta has one customer running two Super Micro servers and one Cisco server in the same cluster.

Maxta advantages

One item that makes Maxta unique is all of its storage properties are assignable at a VM granularity. That is,  replication, deduplication, compression and even blocksize can all be enabled/set at the VMDK-VM level.  This could be useful for environments supporting diverse applications, such as having a 64K block size for Microsoft Exchange and 4K block size for web servers.

Another advantage is their multi-hypervisor support. Maxta’s support for RH Virtualization, VMware and KVM offers the unique ability to migrate storage and even powered off VMs, from one hypervisor to another. Maxta’s file system is the same for both VMware and KVM clusters.

Maxta clusters

Their software must be licensed on all servers in a vSphere or KVM cluster with access to Maxta storage. The minimum Maxta cluster size is 3 nodes for 2-way replication and 5 nodes for 3-way replication.  Most Maxta systems run on 8 to 12 server node clusters. But Maxta has installations with 20 to 24 nodes in customer deployments.

Maxta supports SSD only as well as SSD-disk hybrid storage. And SSDs can be NVMe as well as SATA SSD storage. In hybrid configurations, Maxta SSDs are used as read and write back caches for disk storage.

Maxta supports compute only nodes, compute-storage nodes and witness only nodes (node with 1 storage device). In addition, besides heterogeneous server support, Maxta clusters can have nodes with different storage capacities. Maxta will optimize VM data placement to balance IO activity across heterogeneous nodes.

Maxta provides a vCenter plugin so VMware admins can manage and monitor their storage inside vSphere environment. Maxta also offers a Cloud Connect MX which is a cloud based system allowing for management of all your Maxta clusters through out an enterprise, wherever they reside.

Even HCI, through partners

For customers wanting an HCI solution, Maxta partners can supply pre-tested, HCI appliances or can configure Maxta software with servers at customer data centers. Maxta has done well OEMing their solution, and one significant success has been their OEM deal with Lenovo in China and East Asia, where they sell HCI appliances with Maxta software.

Maxta has also found success with managed service providers (that want to deploy the software on their own hardware), and SME & ROBO environments. Also Maxta seems to be doing very well in Latin America as well as previously mentioned China.

The podcast runs ~42 minutes. Kiran is knowledgeable individual and has worked with some of the leading storage companies of the last two decades.  Listen to the podcast to learn more.

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Kiran Sreenivasamurthy, VP Product Management, Maxta

Kiran Sreenivasamurthy is the Vice President of Product Management for Maxta Inc. He has developed and managed storage hardware and software products for more than 20 years with leading storage companies and startups including HP 3PAR, NetApp and Mendocino Software.

Kiran Manages all aspects of Maxta’s hyperconvergence product portfolio from inception through revenue.

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51: GreyBeards talk hyper convergence with Lee Caswell, VP Product, Storage & Availability BU, VMware

Sponsored by:

VMware

In this episode we talk with Lee Caswell (@LeeCaswell), Vice President of Product, Storage and Availability Business Unit, VMware.  This is the second time Lee’s been on our show, the previous one back in April of last year when he was with his prior employer. Lee’s been at VMware for a little over a year now and has helped lead some significant changes in their HCI offering, vSAN.

VMware vSAN/HCI business

Many customers struggle to modernize their data centers with funding being the primary issue. This is very similar to what happened in the early 2000s as customers started virtualizing servers and consolidating storage. But today, there’s a new option, server based/software defined storage like VMware’s vSAN, which can be deployed for little expense and grown incrementally as needed. VMware’s vSAN customer base is currently growing by 150% CAGR, and VMware is adding over 100 new vSAN customers a week.

Many companies say they offer HCI, but few have adopted the software-only business model this entails. The transition from a hardware-software, appliance-based business model to a software-only business model is difficult and means a move from a high revenue-lower margin business to a lower revenue-higher margin business. VMware, from its very beginnings, has built a sustainable software-only business model that extends to vSAN today.

The software business model means that VMware can partner easily with a wide variety of server OEM partners to supply vSAN ReadyNodes that are pre-certified and jointly supported in the field. There are currently 14 server partners for vSAN ReadyNodes. In addition, VMware has co-designed the VxRail HCI Appliance with Dell EMC, which adds integrated life-cycle management as well as Dell EMC data protection software licenses.

As a result, customers can adopt vSAN as a build or a buy option for on-prem use and can also leverage vSAN in the cloud from a variety of cloud providers, including AWS very soon. It’s the software-only business model that sets the stage for this common data management across the hybrid cloud.

VMware vSAN software defined storage (SDS)

The advent of Intel Xeon processors and plentiful, relatively cheap SSD storage has made vSAN an easy storage solution for most virtualized data centers today. SSDs removed any performance concerns that customers had with hybrid HCI configurations. And with Intel’s latest Xeon Scalable processors, there’s more than enough power to handle both application compute and storage compute workloads.

From Lee’s perspective, there’s still a place for traditional SAN storage, but he sees it more for cold storage that is scaled independently from servers or for bare metal/non-virtualized storage environments. But for everyone else using virtualized data centers, they really need to give vSAN a look.

Storage vendors shifting sales

It used to be that major storage vendor sales teams would lead with hardware appliance storage solutions and then move to HCI when pushed. The problem was that a typical SAN storage sale takes 9 months to complete and then 3 years of limited additional sales.

To address this, some vendors have taken the approach where they lead with HCI and only move to legacy storage when it’s a better fit. With VMware vSAN, it’s a quicker sales cycle than legacy storage because HCI costs less up front and there’s no need to buy the final storage configuration with the first purchase. VMware vSAN HCI can grow as the customer applications needs dictate, generating additional incremental sales over time.

VMware vSAN in AWS

Recently, VMware has announced VMware Cloud in AWS.What this means is that you can have vSAN storage operating in an AWS cloud just like you would on-prem. In this case, workloads could migrate from cloud to on-prem and back again with almost no changes. How the data gets from on-prem to cloud is another question.

Also the pricing model for VMware Cloud in AWS moves to a consumption based model, where you pay for just what you use on a monthly basis. This way VMware Cloud in AWS and vSAN is billed monthly, consistent with other AWS offerings.

VMware vs. Microsoft on cloud

There’s a subtle difference in how Microsoft and VMware are adopting cloud. VMware came from an infrastructure platform and is now implementing their infrastructure on cloud. Microsoft started as a development platform and is taking their cloud development platform/stack and bringing it to on-prem.

It’s really two different philosophies in action. We now see VMware doing more for the development community with vSphere Integrated Containers (VIC), Docker Containers, Kubernetes, and Pivotal Cloud foundry. Meanwhile Microsoft is looking to implement the Azure stack for on-prem environments, and they are focusing more on infrastructure. In the end, enterprises will have terrific choices as the software defined data center frees up customers dollars and management time.

The podcast runs ~25 minutes. Lee is a very knowledgeable individual and although he doesn’t qualify as a Greybeard (just yet), he has been in and around the data center and flash storage environments throughout most of his career. From his diverse history, Lee has developed a very business like perspective on data center and storage technologies and it’s always a pleasure talking with him.  Listen to the podcast to learn more.

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Lee Caswell, V.P. of Product, Storage & Availability Business Unit, VMware

Lee Caswell leads the VMware storage marketing team driving vSAN products, partnerships, and integrations. Lee joined VMware in 2016 and has extensive experience in executive leadership within the storage, flash and virtualization markets.

Prior to VMware, Lee was vice president of Marketing at NetApp and vice president of Solution Marketing at Fusion-IO (now SanDisk). Lee was a founding member of Pivot3, a company widely considered to be the founder of hyper-converged systems, where he served as the CEO and CMO. Earlier in his career, Lee held marketing leadership positions at Adaptec, and SEEQ Technology, a pioneer in non-volatile memory. He started his career at General Electric in Corporate Consulting.

Lee holds a bachelor of arts degree in economics from Carleton College and a master of business administration degree from Dartmouth College. Lee is a New York native and has lived in northern California for many years. He and his wife live in Palo Alto and have two children. In his spare time Lee enjoys cycling, playing guitar, and hiking the local hills.

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48: Greybeards talk object storage with Enrico Signoretti, Head of Product Strategy, OpenIO

In this episode we talk with Enrico Signoretti, Head of Product Strategy for OpenIO, a software defined, object storage startup out of Europe. Enrico is an old friend, having been a member of many Storage Field Day events (SFD) in the past which both Howard and I attended and we wanted to hear what he was up to nowadays.

OpenIO open source SDS

It turns out that OpenIO is an open source object storage project that’s been around since 2008 and has recently (2015) been re-launched as a new storage startup. The open source, community version is still available and OpenIO has links to downloads to try it out. There’s even one for a Raspberry PI (Raspbian 8, I believe) on their website.

As everyone should recall object storage is meant for multi-PB data storage environments. Objects are assigned an ID and are stored in containers or buckets. Object storage has a flat hierarchy unlike file systems that have a multi-tiered hierarchy.

Currently, OpenIO is in a number of customer sites running 15-20PB storage environments. OpenIO supports AWS S3 compatible protocol and OpenStack Swift object storage API.

OpenIO is based on open source but customer service and usability are built into the product they license to end customers  on a usable capacity basis. Minimum license is for 100TB and can go into the multiPB range. There doesn’t appear to be any charge for enhancements of additional features or additional cluster nodes.

The original code was developed for a big email service provider and supported a massive user community. So it was originally developed for small objects, with fast access and many cluster nodes. Nowadays, it can also support very large objects as well.

OpenIO functionality

Each disk device in the OpenIO cluster is a dedicated service. By setting it up this way,  load balancing across the cluster can be at the disk level. Load balancing in OpenIO, is also a dynamic operation. That is, every time a object is created all node’s current capacity is used to determine the node with the least used capacity, which is then allocated to hold that object. This way there’s no static allocation of object IDs to nodes.

Data protection in OpenIO supports erasure coding as well as mirroring (replication{. This can be set by policy and can vary depending on object size. For example, if an object is say under 100MB it can be replicated 3 times but if it’s over 100MB it uses erasure coding.

OpenIO supports hybrid tiering today. This means that an object can move from OpenIO residency to public cloud (AWS S3 or BackBlaze B2) residency over time if the customer wishes. In a future release they will support replication to public cloud as well as tiering.  Many larger customers don’t use tiering because of the expense. Enrico says S3 is cheap as long as you don’t access the data.

OpenIO provides compression of objects. Although many object storage customers already compress and encrypt their data so may not use this. For those customers who don’t, compression can often double the amount of effective storage.

Metadata is just another service in the OpenIO cluster. This means it can be assigned to a number of nodes or all nodes on a configuration basis. OpenIO keeps their metadata on SSDs, which are replicated for data protection rather than in memory. This allows OpenIO to have a light weight footprint. They call their solution “serverless” but what I take from that is that it doesn’t use a lot of server resources to run.

OpenIO offers a number of adjunct services besides pure object storage such as video transcoding or streaming that can be invoked automatically on objects.

They also offer stretched clusters where an OpenIO cluster exists across multiple locations. Objects can have dispersal-like erasure coding for multi-site environments so that if one site goes down you still have access to the data. But Enrico said you have to have a minimum of 3 sites for this.

Enrico mentioned one media & entertainment customer stored only one version of a video in the object storage but when requested in another format automatically transcoded it in realtime. They kept this newly transcoded version in a CDN for future availability, until it aged out.

There seems to be a lot of policy and procedural flexibility available with OpenIO but that may just be an artifact of running in Linux.

They currently support RedHat, Ubuntu and CentOS. They also have a Docker container in Beta test for persistent objects, which is expected to ship later this year.

OpenIO hardware requirements

OpenIO has minimal hardware requirements for cluster nodes. The only thing I saw on their website was the need for at least 2GB of RAM on each node.  And metadata services seem to require SSDs on multiple nodes.

As discussed above, OpenIO has a uniquely light weight footprint (which is why it can run on Raspberry PI) and only seems to need about 500MB of DRAM and 1 core to run effectively.

OpenIO supports heterogeneous nodes. That is nodes can have different numbers and types of disks/SSDs on them, different processor, memory configurations and OSs. We talked about the possibility of having a node go down or disks going down and operating without them for a month, at the end of which admins could go through and fix them/replacing them as needed. Enrico also mentioned it was very easy to add and decommission nodes.

OpenIO supports a nano-node, which is just an (ARM) CPU, ram and a disk drive. Sort of like Seagate Kinetic and other vendor Open Ethernet drive solutions. These drives have a lightweight processor with small memory running Linux accessing an attached disk drive.

Also, OpenIO nodes can offer different services. Some cluster nodes can offer metadata and object storage services and others only object storage services. This seems configurable on a server basis. There’s probably some minimum number of metadata and object services required in a cluster. Enrico mentioned three nodes as a minimum cluster.

The podcast runs ~42 minutes but Enrico is a very knowledgeable, industry expert and a great friend from multiple SFD/TFD events. Howard and I had fun talking with him again. Listen to the podcast to learn more.

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Enrico Signoretti, Head of Product Strategy at OpenIO.

In his role as head of product strategy, Enrico is responsible for the planning design and execution of OpenIO product strategy. With the support of his team, he develops product roadmaps from the planning stages to development to ensure their market fit.

Enrico promotes OpenIO products and represent the company and its products at several industry events, conferences and association meetings across different geographies. He actively participates in the company’s sales effort with key accounts as well as by exploring opportunities for developing new partnerships and innovative channel activities.

Prior to joining OpenIO, Enrico worked as an independent IT analyst, blogger and advisor for six years, serving clients among primary storage vendors, startups and end users in Europe and the US.

Enrico is constantly keeping an eye on how the market evolves and continuously looking for new ideas and innovative solutions.

Enrico is also a great sailor and an unsuccessful fisherman.