SFD15

NetApp & Next Generation Storage Technologies

Chan 2 Comments

There are some exciting technology developments taking place in the storage industry, some behind closed doors but some that are also publicly announced and already commercially available that most of you may already have come across. Some of these are organic developments to build on existing technologies but some are inspired by megascalers like AWS, Azure, GCP and various other cloud platforms. I’ve been lucky enough to be briefed on some of these when I was at SFD12 last year I the Silicon Valley, by SNIA – The Storage and Networking Industry Association that I’ve previously blogged about here.

This time around, I was part of the Storage Filed Day (SFD15) delegate panel that got a chance to visit NetApp at their HQ at Sunnyvale, CA to find out more about some of exciting new product offerings that are in NetApp’s roadmap, either in the works or starting to just come out, incorporating some of these new storage technologies. This post aim to provide a summary of what I learnt there and my respective thoughts.

Introduction

It is no secret that Flash media has changed the dynamics of the storage market over the last decade due to their inherent performance characteristics. While the earliest incarnations of flash media were prohibitively expensive to be used in mass quantities, the invention of SSDs commoditised the use of flash media across the entire storage industry. For example, most tier 1 workloads in the enterprises today are held on a SSD backed storage system where SSD disk drives form the whole or a key part of the storage media stack.

When you look at some of the key storage solutions in use today, there are 2 key, existing flash technologies that stand out, DRAM & SSD. DRAM is the fastest possible flash storage media that is most easily accessible by the data processing compute subsystem while SSD’s fall in to next best place when it comes to speed of access and the level of performance (IOPS & bandwidth). As such, most enterprise storage solutions in the world, be that the ones aimed at the customer data centers or on the megascaler’s cloud platforms utilise one or both of these flash media types to either accelerate (caching) or simply store tier 1 data sets.

It is important to note that, while the SSD’s benefitted from the overall higher performance and lower latency compared to mechanical drives due to the internal architecture of the SSD disks themselves (flash storage cells that don’t require spinning magnetic media), both the SSD drives and classic mechanical (spinning) drives are typically attached & accessed by the compute subsystem via the same SATA or the SaS interface subsystem with the same interface speed & latency. Often the internal performance of an SSD was not fully realised to its maximum potential, especially in an aggregated scenario like that of an enterprise storage array, due to these interface controller access speed and latency limitations, as illustrated in the diagram below.

One of the more recent technology developments in the storage and compute industry, namely “Non-Volatile Memory Express” (NVMe) aims to address these SAS & SATA interface driven performance and the latency limitations through the introduction of new, high performance host controller interface that has been engineered from the ground up to be able to fully utilise flash storage drives. This new NVMe storage architecture is designed to be future proof and would be compatible with various future disk drive technologies that are NAND based as well as non-NAND based storage media.

NVMe SSD drives connected via these NVMe interfaces will not only outperform traditional SSD drives attached via SAS or SATA, but most importantly will enable higher future capabilities such as being able to utilise Remote Direct Memory Address (RDMA) for super high storage performance extending the storage subsystem over a fabric of interconnected storage and compute nodes. A good introduction to the NVMe technology and its benefits over SAS / SATA interfaces can be viewed here.

Another much talked about development on the same front is the subject of the Storage Class Memory (SCM) – Also known as Persistent Memory (PMEM). SCM is an organic successor to the NAND technology based SSD drives that we see in mainstream use in flash accelerated as well as all flash storage arrays today.

At a theoretical level, SCM can come in 2 main types as shown in the above diagram (from a really great IBM research paper published in 2013).

  • M-Type SCM (Synchronous) = Incorporate non-volatile memory based storage in to the memory access subsystem (DDR) rather than SCSI block based storage subsystem through PCIe, achieving DRAM like throughput and latency benefits for persistent storage. Typically take the form of NVDIMM (that is attached to the memory BUS, similar to traditional DRAM) which is the fastest and best performant thing, next to DRAM itself. Uses memory card slots and appear to the system to use as a caching layer or as pooled memory (extended DRAM space) depending on the NVDIMM type (NVDIMMs come in 3 types, NVDIMM-N, NVDIMM-F and NVDIMM-P. A good explanation available here).
  • S-Type SCM (Asynchronous) = Incorporate non-volatile memory based storage but attached via the PCIe connector to the storage subsystem. While this is theoretically slower than the above, it’s still significantly faster than NAND based SSD drives that are in common use today, including those attached via NVMe host controller interface. Intel and Samsung both have already launched S-type SCM drives, Intel with their 3D XPoint architecture and Samsung with Z-SSD respectively but current drive models available are aimed more at consumer / workstation rather than server workloads. Server based implementations of similar SCM drives will likely arrive around 2019. (Along with supported server based software included within operating systems such as Hypervisors – vSphere 7 anyone?)

The idea of the SCM is to address the latency and performance gap that exist in every computer system when it comes to memory and storage since the advent of X86 computing. Typically, access latency for DRAM is around 60ns, and the next best option today, NVMe SSD drives will have a typical latency of around 20-200us and the SCM will fit in between these 2, at a typical latency between 60ns-20uS, depending on the type of the SCM, with a significantly high bandwidth that is incomparable to SSD drives. It is important to note however that most ordinary workloads do not need this type of super latency sensitive, extremely high bandwidth storage performance, the next generation data technologies involving Artificial Intelligence techniques such as machine learning, real-time analytics that relies on processing extremely large swathes of data at super quick time, would absolutely benefit, and in most instance, necessitate the need for these next gen storage technologies to be fully effective.

NetApp’s NVMe & SCM vision

NetApp was one of the first classic storage vendors who incorporate flash in to their storage systems, in an efficient manner to accelerate the workloads that is typically stored on spinning disks. This started with the concept of NVRAM that was included in their flagship FAS storage solutions as an acceleration layer. Then came the flash cache (PAM cards) which were flash media attached via the PCIe subsystem to act as a cashing layer for reads which was also popular. Since the advent of all flash storage arrays, NetApp went another step by introducing all flash storage in to their portfolio through the likes of All Flash FAS platform that was engineered and tuned for all flash media as well as the EF series.

NetApp innovation and constant improvement process hasn’t stopped there. During SFD15 event, we were treated to the next step of this technology evolution by NetApp when they discussed how they plan to incorporate the above mentioned NVMe and SCM storage technologies in to their storage portfolio, in order to provide next gen storage capabilities to serve next gen use cases such as AI, big data and real-time analytics. Given below is a holistic roadmap plan of where NetApp see NVMe and SCM technologies fitting in to their roadmap, based on the characteristics, benefits and costs of each technology.

The planned use of NVMe is clearly in 2 different points of the host->storage array communication path.

  • NVMe SSD drives : NVMe SSD drives in a storage array, attached via NVMe host controller interface in order to be able to fully utilise the latency and throughput potential of the SSD drives themselves by the storage processor (in the controllers). This will provide additional performance characteristics to the existing arrays.
  • NVMe-OF : NVMe over fabric which is attached to the storage consumer nodes (Servers) via a ultra-low latency NVMe fabric. NVMe-OF enable the use of RDMA capabilities to reduce the distance between the IO generator and the IO processor thereby significantly reducing the latency. NVMe-OF therefore is widely touted to be the next big thing in storage industry and a number of specialists start-ups like Excelero have already come out to market with specialist solutions and you can find out more about it in my blog here. An example of the NVMe-OF storage solution available from NetApp is the new NetApp EF570 all flash array. This product is already shipping and more details can be found here or here. This platform offers some phenomenal performance numbers at ultra-low latency, built around their trusted, mature, feature rich, yet simple EF storage platform which is also a bonus.

The planned (or experimented) use of SCM is in 2 specific areas of the storage stack, driven primarily by the costs of the media vs the need for acceleration.

  • Storage controller side caching:        NetApp mentioned that some of the experiments they are working on with prototype solutions already built are looking at using SCM media on the storage controllers as a another tier to accelerate performance, in the same way PAM cards or Flash cache was used on the older FAS system. This a relatively straight forward upgrade and would be specially effective in an all flash FAS solution with SSD drives in the back end where a traditional flash cache card based on NAND cells would be less effective.

  • Server (IO generator) side caching:        This use case looks at using the SCM media on the host compute systems that generates the IO to act as a local cache, but most importantly, used in conjunction with the storage controllers rather than in isolation, performing tiering and snapshots from the host cache to a backend storage system like an All Flash FAS.

  • NetApp are experimenting on this front primarily using their recent acquisition of Plexistor and their proprietary software that performs the function of combining DRAM and SCM as a single address space that is byte addressable (via memory semantics which is much faster than scsi / NVMe addressable storage) and presenting that to the applications as a cache while also presenting the backend NetApp storage array such as an All Flash FAS as a persistent storage tier. The applications achieve significantly lower latency and ultra-high throughput this way through caching the hot data using the Plexistor file system which incidentally bypasses the complex Linux IO stack (Comparison below). The Plexistor tech is supposed to provide enterprise grade feature as a part of the same software stack though the specifics of what those enterprise grade features meant were lacking (Guessing the typical availability and management capabilities as natively available within OnTAP?)

Based on some of the initial performance benchmarks, the effect of this is significant, as can be seen below when compared to a normal

My thoughts

As an IT strategist and an Architect at heart with a specific interest in storage who can see super data (read “extremely large quantities of data”) processing becoming a common use case soon across most industries due to the introduction of big data, real-time analytics and the accompanying Machine Learning tech, I can see value in this strategy from NetApp. Most importantly, they are looking at using these advanced technologies in harmony with some the proven, tried and tested data management platforms they already have in the likes of OnTAP software could be a big bonus. The acquisition of Plexistor was a good move for NetApp and integrating their tech and having a shipping product would be super awesome if and when that happens but I would dare say the use cases would be somewhat limited prohibitive initially given the Linux dependency. Others are taking note and the HCI vendor Nutanix’s acquisition of PernixData kind of hints Nutanix also having a similar strategy to that of Plexistor and NetApp.

While the organic growth of current product portfolio with capabilities through incorporating new tech such as NVMe is fairly straight forward and help NetApp stay relevant, it remains to be seen however how well acquisition driven integration such as that of Plexistor with SCM technologies to the NetApp platform would pan out to become a shipping product. NetApp has historically had issues around the efficiency of this integration process which in the past has known to be slow but this time around, under the new CEO George Kurian who brought in a more agile software development methodology and therefore, a more frequent feature & update release cycle, things may well be different this time around. The evidence seen during SFD15 pretty much suggest the same to me which is great.

Slide credit to NetApp!

Thanks

Chan

Cohesity: A secondary storage solution for the Hybrid Cloud?

Chan 22 Comments

Background

A key part of my typical day job involves staying on top of new technologies and key developments in the world of enterprise IT, with an aim to spot commercially viable, disruptive technologies that are not just cool tech but also have a good business value proposition with a sustainable use case.

To this effect, I’ve been following Cohesity since its arrival to the mainstream market back in 2015, keeping up to date on some of their platform developments with various feature upgrades such as v2.0, v3.0…etc with interest. SFD15 gave me another opportunity to catch up with them and get an up to date view on their latest offerings & the future direction. I liked what I heard from them! Their solution now looks interesting, their marketing message is a little sharper than it was a while ago and I like the direction they are heading in.

Cohesity: Overview


Cohesity claims to be a specialist, software defined, secondary storage vendor who specializes in modernization of the secondary storage tier within the hybrid cloud. Such secondary storage requirements typically include copies of your primary / tier 1 data sets (Such as test & dev VM data and reporting & analytics data) or file shares (CIFS, NFS…etc.). These types of data  tends to be often quite large and therefore typically cost more to store and process. Therefor storing them on the same storage solution as your tier 1 data can be un-necessarily expensive which I can relate to, as an enterprise storage customer as well as a channel SE in my past lives, involved in sizing and designing various storage solutions for my customers. Often, most enterprise customers need separate, dedicated storage solutions to store such data outside of the primary storage cluster but they are stuck with the same, expensive primary storage vendors for choice. Cohesity offers to provide a single, tailor made secondary data platform that spans across both ends of the hybrid cloud to address all these secondary storage requirements. They also provide the ability to act as a hybrid cloud backup storage target too with some added data management capabilities on top so that not only can they store data backups, but also do interesting things with those backup data, across the full Hybrid Cloud spectrum.

With what appears to be decent growth last year (600% revenue growth YoY) and some good customers already onboard, it appears that customers may be taking notice too.

Cohesity: Solution Architecture


A typical Cohesity software defined storage (SDS) solution on-premises comes as an appliance and can start with 3 nodes to form a cluster that provide linear scalable growth. An appliance will typically be a 2U chassis that accommodate 4 nodes and any commodity or an OEM HW platform is supported. Storage itself consist of PCI-e Flash (up to 2TB per node) + capacity disk, which is the typical storage architecture of every SDS manufacturer these days. Again, similar to most other SDS vendors, Cohesity uses Erasure coding or RF2 data sharding across the Cohesity nodes (within each cluster) to provide data redundancy, as a part of the SpanFS file system. Note that given its main purpose as a secondary storage unit, it doesn’t have (or need) an All Flash offering, though they may move in to the primary storage use case, at least indirectly in the future.

Cohesity storage solution can be deployed across to remote and branch office locations as well as to cloud platforms using virtual Cohesity appliances to work hand in hand with the on-premises cluster. Customers can then enable cross cluster data replication and various other integration / interaction activities in a similar way to NetApp Data Fabric works for example for primary data. Note however that Cohesity does not permit the configuration of a single cluster across platforms as of yet (where you can deploy nodes from the same cluster on premises as well as on the cloud enabling Erasure Coding to perform data replication in the way Hedvig storage solution permits for example), but we were hinted that this is in the works for a future release.

Cohesity also have some analytics capabilities built in to the platform which can be handy. The analytics engine uses MapReduce natively within its engine to avoid the need to build external analytic focused compute clusters (such as Hadoop clusters) and having to move (duplicate) data sets to be presented for analysis. The Analytics Workbench on Cohesity platform currently permits external custom code to be injected in to the platform. This can be used to search for contents inside various files held on the Cohesity platform including pattern matching that enables customers to search for social security or credit card numbers which would be quite handy to enforce regulatory compliance. During the SFD15 presentation, we were explained that the capabilities of this platform is being rapidly enhanced to enhance additional regulatory compliance policy enforcements such as those of GDPR. Additional information on Cohesity Analytics capabilities can be found here. Additional video explaining how this works can also be found here.

Outside of these, given the whole Cohesity solution is backed by a distributed file system that is software defined, they naturally have all the software defined goodness expected from any SDS solution such as global deduplication, compression, replication, file indexing, snapshots, multi protocol access, Multi tenancy and QoS within their platform.

My thoughts

I like Cohesity’s current solution and where they are potentially heading. However, the key to their success in my view, would ultimately be their price point which I am yet to see to make sense of where they belong amongst competition.

From a technology and strategy standpoint, Cohesity’s key use cases are very valid and the way they aim to address those is pretty damn good. When you think about the secondary storage use case, cost of serving out less performance hungry, tier 2 data (often large and clunky in size) through an expensive tier 1 storage array (where you have to include larger SAN & NAS storage controllers + additional storage), I cannot help but think that Cohesity’s secondary storage play is quite relevant for many customers. Tier 1 storage solutions, classic SAN /NAS solutions as well HCI solutions such as VMware vSAN or Nutanix, are typically priced to reflect their tier 1 use case. So, a cheaper, more appropriate secondary storage solution such as Cohesity could help save lots of un-necessary SAN / NAS / HCI costs for many customers by being able to now downsize their primary storage solution requirements. This may even further enable more and more customers to embrace HCI solutions for their tier 1 workload too resulting in even less of a need to have expensive, hardware centric SAN / NAS solutions except for when they are genuinely necessary. After all, we are all being taught the importance of rightsizing everything (thanks to the utility computing model introduced by the Public clouds), so perhaps it’s about time that we all look to break down the tier 1 and tier 2 data in to appropriately sized tier 1 and tier 2 storage solutions to benefit from the reduced TCO for the customer? It’s important to note though, that this rightsizing will only likely going to appeal to customers with heavy storage use cases such as typical enterprises and large corporate customers rather than the average small to medium customer who requires a typical multipurpose storage solution to host some VMs + some file data. This is evident in the customer stats provided to us during SFD15, where 70% of their customers are enterprise customers.

Both their 2 key use cases, Tier 2 data storage as well as backup storage now looks to incorporate cloud capabilities and allows customers to do more than just storing tier 2 data and storing back ups. This is good and is very time relevant indeed. They seem to take a very data centric approach to their use cases and their secret source behind most of the capabilities, the proprietary file system called SpanFS looks and feels very much like NetApp’s cDOT architecture with some enhancements in parts. They are also partnering up with various primary storage solutions such as Pure to enable replication of backup snapshots from Pure to Cohesity, while introducing additional features like built in NAS data protection from NetApp, EMC, Pure, direct integration with VMware vCF for data protection, direct integration with Nutanix for AHV protection kind of moves them closer to Rubrik’s territory which is interesting and ultimately provides customers the choice which is a good thing.

From a hardware & OEM standpoint, Cohesity has partnered up with both HPe and Cisco already and have also made themselves available on HPe pricebook so that customers can order the Cohesity solution using a HPe SKU which is convenient, though I’d personally urge customers to order directly from Cohesity (using your trusted solutions provider) where possible, rather than ordering through an OEM vendor where the pricing may be fixed or engineered to position OEM HW when its not always required.

Given their mixed capabilities of tier 2 data storage, backup storage, and ever-increasing data management capabilities across platforms, they are coopeting if not competing with a number of others such as NetApp who has a similar data management strategy in their “Data pipeline” vision (who also removes the need to have multiple storage silos in the DC for Tier 2 data due to features such as Clustered Data OnTAP & FlexClones), Veeam or even Pure storage. Given their direct integration with various SW & HCI platforms removing the need to have 3rd party backup vendors, they are likely going to be competing directly with Rubrik more and more in the future. Cohesity’s strategy is primarily focused on tier 2 data management and the secondary focus is on data backups and management of that data whereas Rubrik’s strategy appears to be the same but opposite order of priorities (backup 1st, data management 2nd). Personally, I like both vendors and their solution positioning’s as I can see the strategic value in both solutions offerings for customers. But most importantly for Cohesity, there don’t appear to be any other storage vendor, specifically focused on the secondary storage market like they do so I can see a great future for them, as long as their price point remains relevant and that great innovation keeps continuing.

You can watch all the videos from the #SFD15 recorded at the Cohesity HW in Santa Clara here.

If you are an existing Cohesity user, I’d be very keen to get your thoughts, feedback using the comments section below.

A separate post to follow looking at Cohesity’s SmapFS file system and their key use cases!

Chan

A look at the Hedvig distributed Hybrid Cloud storage solution

Chan 4 Comments

During the recently concluded Storage Field Day event (SFD15), I had the chance to travel to the Software Defined Storage company Hedvig in their HQ in Santa Clara where were given a presentation by their engineering team (including the founder) of their solution offering. Now luckily, I knew Hedvig already due to my day job (which involves evaluating new, disruptive tech start-ups to form solutions reseller partnerships – I had already gone through this process with Hedvig a while back). However I learnt about a number of new updates to their solution and this post aims to cover their current solution offering and my thoughts of it, in the current enterprise storage market.

Hedvig: Company Overview

Similar to a number of new storage or backup start-ups came out of stealth in recent times, Hedvig too was founded by an engineer with a technology background, back in 2012. The founder Avinash Lakshman came from a distributed software engineering background, having worked on large scale distributed storage applications such as Amazon Dynamo and Cassandra. While they came out of stealth in 2015, they did not appear to have an aggressive growth strategy backed by an aggressive (read “loud”) marketing effort behind them and looked rather content at natural, organic growth. At least that was my impression seeing how they operated in the UK market anyway. However, during the SFD15 presentation, we found out that they’ve somewhat revamped their logo and related marketing collateral. So perhaps they may well have started to address this already?

Hedvig: Solution Overview


At the outset, they are similar to most other software defined storage start-ups these days that leverages any commodity server hardware on top of their software tier to build a comparatively low cost, software defined storage (SDS) solution. They also have genuine distributed capability to be able to distribute the SDS nodes not just within the data center, but also across data centers as well as cloud platforms, though it’s important to note most SDS vendors these days have got the same capability or are in the process of adding it to their SDS platforms.

Hedvig has positioned themselves as a SDS solution that is a perfect fit for traditional workload such as VMs, backup & DR as well as modern workloads such as Big data, HPC, object storage and various cloud native workloads too. Their solution provides block & file storage capability like most other vendors in their category, as well as object storage which is again another potentially (good) differentiator, especially compared to some of the other HCI solutions out there that often only provide one type or the other.

The Hedvig storage platform typically consist of Hedvig SW platform + commodity server hardware with local disks. Each server node can be a physical server or a VM on a cloud platform that runs the Hedvig software. The Hedvig software consist of,

  • Hedvig Storage Proxy
    • This is a piece of software deployed on the compute node (app server, container instance, hypervisor…etc.)
    • Presents file (NFS) & block (iSCSI) storage to compute environments and coverts that to Hedvig proprietary communication protocol with storage service.
    • Also performs caching of reads (writes are redirected).
    • Performs dedupe up front and writes deduped blocks to the back end (storage nodes) only if necessary
    • Each hypervisor runs a proxy appliance VM / VSA (x2 as a HA pair) which will serve all local IO on that hypervisor
  • Hedvig API
    • Presents object storage via S3 or Swift and full RESTful API from the storage nodes to the storage proxy.
    • Runs on the storage nodes
  • Hedvig Storage Services
    • Manages the storage cluster activities and interface with server proxies
    • Runs on the storage nodes and similar to the role of a typical storage processor / SAN or NAS controller
    • Each storage server has 2 parts
      • Data process
        • Local persistence
        • Replication
      • Metadata process
        • Communicate with each other
        • Distributed logic
        • Stored in a proprietary DB on each node
    • Each virtual disk provisioned in the front end is mapped 1:1 to a Hedvig virtual disk in the back end

The Hedvig storage nodes can be commodity or mainstream OEM vendor servers as customer’s chose to use. They will consist of SSD + Mechanical drives which is typical for other SDS vendors too and the storage nodes which runs the Storage services SW will typically be connected to each other using 10Gbe (or higher) standard Ethernet networking.

Like most other SDS solutions, they have typical SDS features and benefits such as dedupe, compression, auto-tiering, caching, snapshots & clones, data replication…etc. Another potentially unique offering they have here is the ability to set storage policies per virtual disk or per container granularity (in the back end), which is nice. The below are some of key storage policy configuration items that can be set per VM / vDisk granularity.

  • Replication Factor (RF) – Number of copies of the data to keep. Range form 1-6. Quorum = (RF/2)+1. This is somewhat similar to the VMware vSAN FTT if you are a vSAN person.
  • Replication policy – Agnostic, Rack aware and DC aware – Kind of similar to the concept of Fault Domains in vSAN for example. Set the scope of data replication for availability
  • Dedupe – Global dedupe across the cluster. Happens at 512B or 4K block size and is done in-line. Important to node that dedupe happens at the storage proxy level which is ensures no un-necessary writes take place in the back end. This is another USP compared to other SDS solution which is also nice.
  • Compression
  • Client caching
  • …etc.

Data replication, availability & IO operations

Hedvig stores data as containers across the cluster nodes to provide redundancy and enforce the policy configuration items regarding availability at container level. Each vDisk is broken down to 16GB chunks and based on the RF level assigned to the vDisk, will ensure the number of RF copies are maintained across a number of nodes (This is somewhat similar to VMware vSAN component size which is set at 256GB). Each of these 16GB chunks is what is known as a container. Within each node, Hedvig SW will group 3 disks in to a logical group called a storage pool and each container that belong to that storage pool will typically stripe the data across that storage pool’s disks. Storage pool and disk rebalancing occurs automatically during less busy times. Data replication will also take in to account the latency considerations if the cluster spans across multiple geo boundaries / DCs / Cloud environments.

Hedvig software maintains an IO locality in order to ensure best performance for read and write IOs where it will prioritise servicing IO from local & less busy nodes. One of the key things to note that during a write, the Hedvig software doesn’t wait for all the acknowledgement from all the storage nodes unlike some of its competitor solutions. As soon as the quorum is met (Quorum = RF/2 + 1, so if the RF is 4, with a remote node on the cloud or on a remote DC over a WAN link, as soon as the data is written locally to 3 local nodes), it will send the ACK back to the sender and the rest of the data writing / offloading can happen in the background. This ensures the faster write response times, and is probably a key architectural element in how they enable truly distributed nodes in a cluster, which can often include remote nodes over a low latency link, without a specific performance hit to a write operation. This is another potential USP for them, at least architecturally on paper, however in reality, will only likely to benefit if you have a higher RF factor in a large cluster.

Reads are also optimised through using a combination of caching at the storage proxy level as well as actual block reads in the back end prioritising local nodes (with a lower cost) to remote nodes. This is markedly different to how VMware vSAN works for example where it avoids the client-side cache locality in order to avoid skewed flash utilisation across the cluster as well as frequent cache re-warning during VMotion…etc. Both architectural decisions have their pros and cons in my view and I like Hedvig’s architecture as it optimises performance which is especially important in a truly distributed cluster.

A deep dive on this subject including the anatomy of a read and a write is available here.

Hedvig: Typical Use Cases

Hedvig, similar to most of its competition, aim to address number of use cases.

Software Defined Primary Storage

Hedvig operates in traditional storage mode (dedicated storage server nodes providing storage to a number of external compute nodes such as VMware ESXi or KVM or even a bare metal application server) or in Hyper-Converged mode where both compute and storage is provided on a single node. They also state that these deployment architectures can be mixed in the same cluster which is pretty cool.

  • Traditional SDS – Agent (storage proxy) running on the application server accessing the storage and speaks storage protocols. Agent also host local metadata and provide local caching amongst other things. Used in a non-hypervisor deployment such as bare metal deployments of app servers.
  • HCI mode – Agent (storage proxy) running on the Hypervisor (as a control VM / VSA – Similar to Nutanix). This is probably their most popular deployment mode.

Software Defined Hybrid Cloud Storage

Given the truly distributed nature of Hedvig solution platform, they provide a nice Hybrid cloud use case for the complete solution to extend the storage cluster across geographical boundaries including cloud platforms (IaaS instances). Currently supported cloud platforms by Hedvig include AWS, Azure and GCP. Stretching a cluster over to a cloud platform would involve IaaS VMs from the cloud platform being used as cluster nodes with available block storage from the cloud platform providing virtual disks as local drives for each cloud node. When you define Hedvig virtual disks, you get specify the data replication topology across the hybrid cloud. Important to note though that the client accessing those disks will be advised to be run within the same data center / cloud platform / region for obvious performance reasons.

Hedvig also now supports integrating with Docker for containerised workloads through their Docker volume plugin & integration with Kubernetes volume integration framework, similar to most of the other SDS solutions.

Hyper-Converged Backup

This is a something they’ve recently introduced but unless I’ve misunderstood, this is not so much a complete backup solution including offsite backups, but more of a snapshot capability at the array level (within the Hedvig layer). Again, this is similar to most other array level snapshots from other vendor’s solutions and can be used for immediate restores without having to rely on a hypervisor snapshot which would be inefficient. An external backup solution using a backup partner (such as Veeam for example) to offsite those snapshot backups is highly recommended as with any other SDS solution.

My thoughts

I like the Hedvig solution and some of its neat littles tricks such as the clever use of the storage proxy agent to offload some of the backend storage operations to the front end (i.e. dedupe) and therefore potentially reduce back end IO as well as network performance penalty to a minimum between the compute and storage layers. They are a good hybrid SDS solution that can cater for a mixed workload across the private data center as well as public cloud platforms. It’s NOT a specialised solution for a specific workload and doesn’t claim to provide a sub millisecond latency solution and instead, provide a good all-around storage solution that is architected from ground up to be truly distributed. Despite its ability to be used in a traditional storage as well as HCI mode, most of the real-life applications of its technology however, would likely be in a HCI world, with some kind of a Hyper-visor like vSphere ESXi or KVM.

Looking at the organisation itself and their core solution, it’s obvious that they’ve tried to solve a number of hardware defined storage issues that were prevalent in the industry at the time of their inception (2012), through the clever use of software. That act is commendable. However, the sad truth is that, since then, a lot has happened in the industry and a number of other start-ups and established vendors have also attempted to do the same, some with perhaps an unfair advantage due to having their own hypervisor too, which is a critical factor when it comes to your capabilities. Nutanix and VMware vSAN for example, developed similar SDx design principles and tried to address most of the same technical challenges. I fear that those vendors and their solutions were little aggressive in their plans and managed to get their go to market process right in my view, at a much bigger scale as well. Nutanix pioneered in creating a new SDS use case (HCI) in the industry and capitalised on it before everyone else did and VMware vSAN came out as a credible, and potentially better challenger to dominate this space. While Hedvig is independent from a hypervisor platform and therefore provide same capabilities across multiple platforms, the reality is that not many customers would need that capability as they’d be happy with a single Hypervisor & a storage platform. I also think Hedvig potentially missed a trick in their solution positioning in the market to create a differentiated message and win market share. As a result, their growth is nowhere near comparable to that of VMware vSAN or Nutanix for example.

As much as I like the Hedvig technology, I fear for their future and their future survival. Without some significant innovation and some business leadership involved in setting a differentiated strategy for their business, life would be somewhat be difficult, especially if they are to make a commercial success out of the as a company. Their technology is good and engineering team seems credible, but the competition is high and the market is somewhat saturated with so many general purpose SDS solutions as well as specialist SDS solutions aimed at specific workloads. Most of their competition also have much more resources at their disposal to throw at their solution, including more comprehensive marketing engines too. For these reasons, I fear that Hedvig may struggle to survive in their current path of generalised SDS solution and would potentially be better off in focusing on a specific use case / vertical …etc and focusing all their innovation efforts on that.

The founder and the CEO of the company still appears to be very much an engineer at heart still and having an externally sourced business leader with start-up experience to lead Hedvig in to the future may not be a bad thing for them in the long run either, in my view.

Keen to get your thoughts, especially if you are an existing Hedvig customer – Please comment below.

Slide credit goes to Hedvig and Tech Field Day team.

P.S. You can find all the TFD and SFD presentations about Hedvig via the link here.

Chan

Dropbox’s Magic Pocket: Power of Software Defined Storage

Chan 5 Comments

Background

Dropbox is one of the poster boys of the modern-day tech start-ups, similar to the Uber’s and the Netflix’s of the world that was founded by engineers using their engineering prowess to help consumers around the world address various day to day challenges using technologies in a novel way. So, when I was informed that not only Dropbox would be presenting at the SFD15, but we’d also get to tour their state of the art data center, I was ecstatic. (perhaps ecstatic is an understatement!). I work with various technology vendors, from large vendors like Microsoft, Amazon, VMware, Cisco, NetApp…. etc to little known start-ups and Dropbox’s name is often mentioned in event keynote speeches, case studies…etc by most of these vendors as a perfect example of how a born in the cloud organisation can use modern technology efficiently. Heck, they are even referenced in some of the AWS training courses I’ve come across on Pluralsight that talk about Drobox’s ingenious way of using AWS S3 storage behind the scene to store file data content.

So, when I learned that they have designed and built their own Software Defined Storage solution to bring back most of their data storage from AWS on to their on data centres, I was quite curious to find out more details of the said platform and the reasoning behind the move back to on-premises. Given it’s the first time their engineering team openly discussed things, I was looking forward to talking their engineering team at the event.

This post summarises what I learnt from the Dropbox team.

Introduction

I don’t think it’s necessary to introduce Dropbox to anyone these days. If, however you’ve been under a rock for the past 4 years, Dropbox is the pioneering tech organisation from the Silicon Valley that built an online content sharing and a collaboration platform that allows you to synchronise content between various end user devices automatically while letting you access them on any device, anywhere. During this process of data synchronisation and content sharing, they are dealing with,

  • 500+ million users
  • 500+ Petabytes of data storage
  • 750+ billion API calls handled

When they first went live, Dropbox used AWS’s S3 storage (PaaS) to store the actual user file data behind the scene, while their own web servers were used to host the metadata about those files and users. However, as their data storage requirements grew, the necessity to change this architecture was starting to outweigh the benefits such as the agility and ease provided by leveraging AWS cloud storage. As such, Dropbox decided to bring this file storage back in to their own data center on-premises. Dropbox states 2 unique reasons behind this decision: Performance requirements and the raw storage costs. Given the unique use case they have for block storage at extremely high scale, by designing a tailor-made cloud storage solution of their own engineered to provide maximum performance at the lowest unit cost, Dropbox was planning on saving a significant amount of operational costs. As a private company that is about to go in to a public IPO, saving costs was obviously high on their agenda.

Magic Pocket: Software Architecture

While the original name came from an old internal nick name to Dropbox itself, Magic Pocket (MP) now refers to their custom built, internally hosted, software defined, cloud storage infrastructure that is now used by Dropbox to host majority of their user’s file data. This is multi-exabytes in size, with data being fully replicated for availability and has a high data durability (12 x 9’s) and high availability (4 x 9’s).

Within the MP architecture, files are stored in to blocks and replicated across their geo boundaries within their internal infrastructure (back end storage nodes) for durability and availability. The data stored in the MP infrastructure consist of 4mb blocks that are immutable by design. Changes to the data in the blocks are tracked through a File Journal that is part of the metadata held on the Dropbox application servers. Due to the temporal locality of the data, bulk of the static data that are cold, are stored on high capacity, high latency but cheap spinning drives while meta data, cache data & DB’s are kept on high performance low latency, but expensive SSDs.

Unlike most enterprise focused Software Defined Storage (SDS) solutions that utilises some kind of quorum style consensus or distributed coordination to ensure data availability and integrity, MP utilises a simple, centralised, sharded MySQL cluster which is a bit of surprise. Data redundancy is made available through…yeah you guessed it! Customised Erasure coding, similar to many other enterprise SDS solutions however. Data is typically replicated at 1GB chunks (known as buckets) that consist of random, often contiguous 4K blocks. A bucket would replicate or Erasure coded across multiple physical servers (storage nodes) and a set of 1 or more buckets replicated to a set of nodes makes up a volume. This architecture is somewhat similar to how the enterprise SDS vendor Hedvig store their data in the back end.

In Dropbox’s SDS architecture, a pocket is similar to a fault domain in other enterprise SDS solutions and is a geographical zone (US east, US west & US Central for example). Each zone has a cluster of storage servers and other application servers and data blocks are replicated across multiple zones for availability. Pretty standard stuff so far.

Dropbox has a comprehensive Edge network which is geographically dispersed across the world to funnel all customer Drobox application’s connectivities through. The client connectivity path is Application (on user device) -> local pop (proxy servers in an edge location) > Block server > Magic Pocket infrastructure servers > Storage nodes. While the proxy servers in edge locations don’t store any caching of data and can almost be thought of as typical Web servers the clients connect through, the other servers such as Block/MP/Storage nodes servers are ordinary X86 servers stores within Dropbox’s own DCs. These servers are multi sourced as per best practise, and somewhat customised for Dropbox’s specific requirements, especially when it comes to storage node servers. Storage nodes are customised, high density, storage nodes with a capacity to have around 1PB of raw data in each server using local disks. All servers run a generic version of Ubuntu and runs bare metal rather than as VM’s.

Inside each zone, application servers such as Block & Magic Pocket app & db servers act as gateways for storage requests coming through the edge servers. These also hosts the meta data mapping for block placement (block index) in the backend and runs sharded MySQL clusters to store this information (running on SSD storage). Cross zone replication is also initiated in an asynchronous manner within this tier.

A cell is a logical entity of physical storage servers (a cluster of storage nodes) and that defines the core of the Dropbox’s proprietary storage backend which is worth a closer look. These have very large local disks and each storage server (node) consist of around 1PB of storage. These nodes are used as dumb nodes for block level data storage. Replication table, which runs in memory as a small MySQL DB stores the mapping of logical Bucket <-> Volume <-> Storage nodes. This is also part of the metadata stack and is stored on app / db servers with SSD storage.

Master is the software component within each cell that is acting as a janitor and performs back end tasks such as storage node monitoring, creating storage buckets, and other background maintenance operations. However the Master is not on the data plane so doesn’t affect the immediate data read / write operations. There’s a 1:1 mapping between master : Cell. Volume manager (another software component) can be thought of as the data movers / heavy lifters responsible for handling instructions from Master and performing operations accordingly on the storage nodes. Volume manager runs on the actual storage nodes (Storage servers) in the back end.

The front end (interface to the SDS platform) supports simple operations such as Put, Get and Repair. (Details of how this works can be found here)

Magic Pocket: Storage Servers

Dropbox’s customized, high density storage servers make up the actual back end storage infrastructure. Typically each server has a 40GB NIC, around 90 x high capacity enterprise SATA drives as local disks totalling up to around 1PB of raw space per node, runs a bare metal Ubuntu Linux with the Magic Pocket SDS application code and their life cycle management is heavily automated using proprietary and custom built tools. This set up provides a significantly large fault domain per each storage node given the huge capacity of each, but the wider SDS application and network load balancing capabilities architected in the application itself ensure mitigate or design against a complete failures of each server or a cell. We were treated to a scene of observing how this works in action when these engineering team decided to randomly pull the networking cables out while we were touring the DC, and then also cut the power to a full rack which had zero impact on the normal operations of Dropbox’s service. That was pretty cool to see.

My thoughts

Companies like Dropbox inspire me to think outside of the box when it comes to what is possible and how to address modern day business requirements using innovative ways using technology. Similar to the session on Open19 project (part of the Open Compute Project) from the LinkedIn engineering team during SFD12 event last year, this session has also hugely inspired me about the power of software & Hardware engineering and, the impact initiatives like this can have on the wider IT community at large, that we all live and breathe.

As for the Magic pocket SDS & HW architecture… I am a big fan and its great to see organisations such as Dropbox and Netflix (CDN architecture) who epitomises extreme ends of certain use cases, publicly opening up about the backend IT infrastructure that are powering their solutions so that 99% of the other enterprise IT folks can learn and adapt from those blueprints where relevant.

It is also important to remember though, for normal organisations with typical enterprise IT requirements, such custom-built solutions will not be practical nor would they be required and often, the best they’d need can be met with a similarly architected, commercially available Software Defined Storage solution and tailor to meet their requirements. The most important part here though is to realise the power of Software Defined Storage here. If Dropbox can meet their extreme storage requirements through a Software Defined Storage solution that operate on a lower cost premium than a proprietary storage solution, the average corporate or enterprise storage use cases do not have any excuse to keep buying expensive SAN / NAS hardware with a premium price tag. Most enterprise SDS storage solutions (VMware vSAN, Nutanix, Hedvig, Scality…etc.) all have a very similar software and a hardware architecture to that of Dropbox’s and carries a lower cost price point compared to expensive hardware centric storage solutions from the big vendors like EMC, NetApp, HPe, IBM…etc. So why not look in to a SDS solution to if your SAN / NAS is up for a renewal? You can very likely save significant costs and at the same time, benefit from a software defined innovation which tends to comes quicker when there’s no proprietary hardware baggage.

Given Dropbox’s unique scale and storage size, they’ve made a conscious decision to move away for the majority of their storage requirements from AWS (S3 storage) as it they’ve gone past the point where using cloud storage was not economical nor performant enough. But it is also important to remember that they only got to that point through the growth of their business which at the beginning, was only enabled by the agility provided by the very same AWS S3 cloud storage platform they decided to move away from. Most organisations out there are nowhere near the level of scale like Dropbox and therefore its important to remember that for your typical requirements, you can benefit significantly through the clever use of cloud technologies, especially PaaS technologies such as AWS S3, AWS Lambda, Microsoft O365, Azure SQL that provide a ready to use technology solutions platform without you having to build it all from the scratch. In most cases, that freedom and the speed of access can be a worthy trade-off for a slightly higher cost.

Keen to get your thoughts – get involved via comments button below!

Image credit goes to Dropbox!

Chan

Storage Field Day 15 – Watch Live Here

Chan 2 Comments

Following on from my previous post about the vendor line-up and my plans during the event, this post is to share the exact vendor presentation schedule and some additional details.

Watch LIVE!

Below is the live streaming link to the event on the day if you’d like to join us LIVE. While the time difference might make it a little tricky for some, it is well worth taking part in as all the viewers will also have the chance to ask questions from the vendors live, similar to the delegates onset. Just do it, you won’t be disappointed!

Session Schedule

Given below is the session schedule throughout the event, starting from Wednesday the 7th. All times are in Pacific time (-8 hours from UK time)

Wednesday the 7th of March

    • 09:30 – 11:30 (5:30-7:30pm UK time) – WekaIO presents
    • 13:00 – 15:00 (9-11pm UK time) – IBM presents
    • 16:00 – 18:00 (12-2am 8th of March, UK time) Dropbox presents

Thursday the 8th of March

  • 08:00-10:00 (4-6pm UK time) – Hedvig presents from their Santa Clara offices
  • 10:30-12:30 (6:30-8:30pm UK time) NetApp presents from their Santa Clara offices
  • 13:30-15:30 (9:30-11:30pm UK time) – Western Digital/Tegile presents from Levi’s Stadium
  • 16:00-18:00 (12-2am 9th of March, UK time) – Datrium presents from Levi’s Stadium

Friday the 9th of March

  • 08:00-10:00 (4-6pm UK time) – StarWinds presents in the Seattle Room
  • 11:00-13:00 (7-9pm UK time) – Cohesity presents at their San Jose offices
  • 14:00-16:00 (10pm-12am UK time) – Huawei presents at their Santa Clara offices