Pure//Accelerate 2018 – (Fairly) Full Disclosure

Disclaimer: I recently attended Pure//Accelerate 2018.  My flights, accommodation and conference pass were paid for by Pure Storage via the Analysts and Influencers program. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

Here are my notes on gifts, etc, that I received as a conference attendee at Pure//Accelerate 2018. This is by no stretch an interesting post from a technical perspective, but it’s a way for me to track and publicly disclose what I get and how it looks when I write about various things. I’m going to do this in chronological order, as that was the easiest way for me to take notes during the week. While everyone’s situation is different, I took 5 days of unpaid leave to attend this conference.

 

Saturday

My wife dropped me at the BNE domestic airport and I had some ham and cheese and a few coffees in the Qantas Club. I flew Qantas economy class to SFO via SYD. The flights were paid for by Pure Storage. Plane food was consumed on the flight. It was a generally good experience, and I got myself caught up with Season 3 of Mr. Robot. Pure paid for a car to pick me up at the airport. My driver was the new head coach of the San Francisco City Cats ABA team, so we talked basketball most of the trip. I stayed at a friend’s place until late Monday and then checked in to the Marriott Marquis in downtown San Francisco. The hotel costs were also covered by Pure.

 

Tuesday

When I picked up my conference badge I was given a Pure Storage and Rubrik co-branded backpack. On Tuesday afternoon we kicked off the Analyst and Influencer Experience with a welcome reception at the California Academy of Sciences. I helped myself to a Calicraft Coast Kolsch and 4 Aliciella Bitters. I also availed myself of the charcuterie selection, cheese balls and some fried shrimp. The most enjoyable part of these events is catching up with good folks I haven’t seen in a while, like Vaughn and Craig.

As we left we were each given a shot glass from the Academy of Sciences that was shaped like a small beaker. Pure also had a small box of Sweet 55 chocolate delivered to our hotel rooms. That’s some seriously good stuff. Sorry it didn’t make it home kids.

After the reception I went to dinner with Alastair Cooke, Chris Evans and Matt Leib at M.Y. China in downtown SF. I had the sweet and sour pork and rice and 2 Tsingtao beers. The food was okay. We split the bill 4 ways.

 

Wednesday

We were shuttled to the event venue early in the morning. I had a sausage and egg breakfast biscuit, fruit and coffee in the Analysts and Influencers area for breakfast. I need to remind myself that “biscuits” in their American form are just not really my thing. We were all given an Ember temperature control ceramic mug. I also grabbed 2 Pure-flavoured notepads and pens and a Pure Code t-shirt. Lunch in the A&I room consisted of chicken roulade, salmon, bread roll, pasta and Perrier sparkling spring water. I also grabbed a coffee in between sessions.

Christopher went down to the Solutions Expo and came back with a Quantum sticker (I am protecting data from the dark side) and Veeam 1800mAh keychain USB charger for me. I also grabbed some stickers from Justin Warren and some coffee during another break. No matter how hard I tried I couldn’t trick myself into believing the coffee was good.

There was an A&I function at International Smoke and I helped myself to cheese, charcuterie, shrimp cocktail, ribs, various other finger foods and 3 gin and tonics. I then skipped the conference entertainment (The Goo Goo Dolls) to go with Stephen Foskett and see Terra Lightfoot and The Posies play at The Independent. The car to and from the venue and the tickets were very kindly covered by Stephen. I had two 805 beers while I was there. It was a great gig. 5 stars.

 

Thursday

For breakfast I had fruit, a chocolate croissant and some coffee. Scott Lowe kindly gave me a printed copy of ActualTech’s latest Gorilla Guide to Converged Infrastructure. I also did a whip around the Solutions Expo and grabbed:

  • A Commvault glasses cleaner;
  • 2 plastic Zerto water bottles;
  • A pair of Rubrik socks;
  • A Cisco smart wallet and pen;
  • Veeam webcam cover, retractable charging cable and $5 Starbucks card; and
  • A Catalogic pen.

Lunch was boxed. I had the Carne Asada, consisting of Mexican style rice, flat iron steak, black beans, avocado, crispy tortilla and cilantro. We were all given 1GB USB drives with a copies of the presentations from the A&I Experience on them as well. That was the end of the conference.

I had dinner at ThirstBear Brewing Co with Alastair, Matt Leib and Justin. I had the Thirstyburger, consisting of Richards Ranch grass-fed beef, mahón cheese, chorizo-andalouse sauce, arugula, housemade pickles, panorama bun, and hand-cut fried kennebec patatas. This was washed down with two glasses of The Admiral’s Blend.

 

Friday

As we didn’t fly out until Friday evening, Alastair and I spent some time visiting the Museum of Modern Art. vBrownBag covered my entry to the museum, and the Magritte exhibition was terrific. We then lunched in Chinatown at a place (Maggie’s Cafe) that reminded me a lot of the Chinese places in Brisbane. Before I went to the airport I had a few beers in the hotel bar. This was kindly paid for by Justin Warren. On Friday evening Pure paid for a car to take Justin and I to SFO for our flight back to Australia. Justin gets extra thanks for having me as his plus one in the fancier lounges that I normally don’t have access to.

Big thanks to Pure Storage for having me over for the week, and big thanks to everyone who spent time with me at the event (and after hours) – it’s a big part of why I keep coming back to these types of events.

Pure//Accelerate 2018 – Wednesday – Chat With Charlie Giancarlo

Disclaimer: I recently attended Pure//Accelerate 2018.  My flights, accommodation and conference pass were paid for by Pure Storage via the Analysts and Influencers program. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

Here are my notes from the “Chat with Charlie Giancarlo” session for Analysts and Influencers at Pure//Accelerate.

 

Chat with Charlie Giancarlo

You’ve said culture is important. How do you maintain it? “It’s the difference between hiring missionaries and hiring mercenaries”. People are on a mission, out there to prove something, drive the company forward. There’s not an exact, formulaic way of doing it. Hire people you have experience with in the industry. Pure does have a good interview process. It tends to bring out different sides of the interviewee at the same time. We use objective tests for engineering people. Check on the cultural backgrounds of sales talent.

Are there any acquisitions on the horizon? Gaps you want to fill? We have an acquisition strategy. We’ve decided where we’re going, identified the gaps, looked at buy versus build versus partner. There’s a lot of research to do around strengths and weaknesses, fit, culture. There are different types of companies in the world. Get rich quick, play in your own sandbox, people who are on a mission. We have gaps in our product lines. We could be more cloud, more hyper-converged. FlashBlade is still not 3.0 product.

Other companies are under pressure to be more software or cloud. Given your hardware background, how’s that for you? Our original product was software on commodity hardware. All except one SDS vendor sells hardware. At the end of the day, selling pure software that goes on any box is insanely hard to achieve. Majority of SDS still sell on hardware – one throat to choke. Some customers, at scale, might be able to do this with us. Why build our own hardware? 4RU and 1PB versus 1.5 racks. We understood the limitations of commodity hardware. We’re not wedded to the hardware – we’re wedded to providing more value-add to our customers.

Has anyone taken you up on the offer? Some are enquiring.

One of your benefits has been focus, one thing to sell. You just mentioned your competitors don’t have that. Now you’re looking at other stuff? We’re making data easier and more economic to consume. Making the entire stack easier to consume. When I say more HCI, what do I mean? Box with compute, storage and network and you can double it, etc. Another way to look at HCI is a single pane of glass for orchestration, automated discovery, ease of use issue. Customers want us to extend beyond storage.

Single throat to choke and HCI. You provide the total stack, or become an OEM. I have no intention of selling compute. It’s controlled by the semi-conductor company or the OS company.

How about becoming an OEM provider? If they were willing, I’d be all ears. But it’s rare. Dell, Cisco, they’re not OEM companies. Margin models are tough with this.

Developing international sales? Our #2 goal is to scale internationally. Our goals align the company around a few things. It’s not just more sales people. It’s the feature set (eg ActiveCluster). ActiveCluster is more valuable in Europe than anywhere else. US – size is difficult (distance). In Europe they have a lot of 100km apart DCs. Developing support capability. Scaling marketing, legal, finance. It’s a goal for the whole company.

The last company to get to $1B was NetApp. What chance does Pure have to make it to $5B? Well, I hope we do. It’s my job. Storage? That’s a terrible business! Friends in different companies have a lot of different opinions about it. Pure could be the Arista of storage? The people who are engaged in storage don’t believe in storage anymore. They’re not investing in the business. It’s a contrarian model. Compete in business, not just tech. We’re investing 20% in R&D. You need to invest a certain amount in a product line. They have a lot of product lines. We could be bought – we’re a public company. But Dell won’t buy. HPE have bought Nimble. Hitachi don’t really buy people. Who does that leave? I think we have a chance of staying independent.

You could buy somebody. I believe we have a very good sales force. There are a lot of ways to build an acquisition strategy. We have a good sales force.

You’re a public company. You haven’t been doing well. What if Mr Elliott comes into your company? (Activist investor). Generally they like companies with lots of cash. Or companies spending too much on R&D without getting results. We’re growing fast. We just posted 40% profit. Puritans might believe our market cap should be higher. The more we can show that we grow, the more exciting things might be. I don’t think we’re terribly attractive to an activist right now.

Storage is not an interesting place to be. But it’s all about data. Do you see that shifting with investors? What would cause that? I believe we need to innovate too. I think that the investors would need to believe that some of the messages we’re sending today, and over the next year, create an environment where our long term growth path is higher and stronger than it is today. Sometimes its sheer numbers, not storyline. The market believes that NetApp, EMC, etc that they can cause pricing and growth challenges for us for a long time. We need them to believe we’re immune to those challenges.

How about China as a marketplace? China as a competitive threat with new technologies? China is a formidable country in every respect. Competition, market. It’s more difficult than it was 10 years ago as a market. Our administration hasn’t help, China has put a lot of rules and regulations in place. I wish we’d focus on those, not the trade deficit. It’s a market we’re experimenting in. If it only works out as well as our competitors can achieve, it may not be worthwhile. And the issue of competition. I worry about Huawei, particularly in third world countries. Viable, long-lasting commercial concerns. In Europe it’s a bit different. The Chinese are very innovative. The US does well because of a market of 300 million, China has 1.4 billion people.

Joe Tucci said 4-5 years ago that the industry was merging. He said you can’t survive as a small player. How many times have we seen this picture? Huge conglomerates falling apart under their own weight. I hate to disagree with Joe. It’s a misunderstanding of scale. It’s about individual products and capabilities, not the size of the business. If you’re just big, and not growing, you no longer have scale. All you’ve done is create a large company with a lot of under scaled products. Alan Kay “perspective is worth 40 IQ points” [note: it’s apparently 80, maybe I misheard].

Interesting session. 4 stars.

Pure//Accelerate 2018 – Thursday General Session – Rough Notes

Disclaimer: I recently attended Pure//Accelerate 2018.  My flights, accommodation and conference pass were paid for by Pure Storage via the Analysts and Influencers program. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

Here are my rough notes from Thursday’s General Session at Pure//Accelerate 2018.

 

Dave Hatfield

Dave Hatfield takes the stage, reports that there have been over 10000+ viewers and participants for the show. Cast your minds back to the “Summer of love” in 1968. This was also the time of the first big tech demo – “The Mother of All Demos” by Doug Engelbart – and it included the introduction of the mouse, network computing, hypertext linking, collaboration, multiple windows. You can see the clip here.

Pure is about embracing the tools of transformation.

 

Dr Kate Darling

Dr Kate Darling (MIT Media Lab) then takes the stage. She is a researcher with expertise in AI and robotics. She just flew in from Hong Kong. She mentions she had a baby 6 months ago. People say to her “Kate, it must be so interesting to watch your baby develop and compare it to AI development”. She says “[m]y baby is a million times more interesting than anything we’ve developed”.

AI is going to shape the world her baby’s growing up in. Like electricity, we don’t know how it will shape things yet. Some of the applications are really cool. A lot of it is happening behind the scenes. E.g. They took a Lyft to the airport and the driver was using Waze (which uses AI). There’s a bit of hype that goes on, and fear that AI might self-evolve and kill us all. This distracts from the benefits. And the actual problems we face right now (privacy, security, etc). Leads people to over-estimate where we are right now in terms of development.

She works in robotics. We’ve been doing this for centuries. We’re a long way from them taking over the world and killing us all. If you search for AI (via google images) you see human brain / robots pictures. Constantly comparing AI to human intelligence. This image is heavily influenced by sci-fi and pop culture. Automation will have an impact on labour markets. But AI is not like human intelligence. We’ve developed AI that is much smarter than people. But the AI is also a lot dumber. E.g. Siri, I’m bleeding, call me an ambulance. Ok, I’ll call you “an ambulance” from now on.

[image source http://www.derppicz.com/siri-call-me-an-ambulance/]

We’ve been using animals for 1000s of years, and we still use them. E.g., Dolphins for echo-location. Autonomous and unpredictable agents. Their skills are different to ours, and they can partner with us and extend our abilities. We should be thinking outside of the “human replacement” box.

Examples:

  • Japan looks to AI to simplify patent screening
  • Recognise patterns in peoples’ energy consumption
  • Spam filters

Work in human – robot interaction. People’s psychological reactions to physical robots. Treat them like they’re alive, even though they’re machines. Perceive movement in our personal space as intent. The Roomba is really dumb. Military robots – soldiers become attached to bomb disposal robots. Paro Robotics – seal used in nursing homes. A lot of people don’t like the idea of robots for them. But this replaces animal therapy, not human care.

AI can shape how we relate to our tools, and how we relate to each other. The possibilities are endless.

If you’re interested in AI. It’s kind of a “hypey buzzword” thrown around at conferences. It’s not a method and more of a goal. Most of what we do is machine learning. eg. Hot dog example from Silicon Valley. If you’re into AI, you’ll need data scientists. They’re in high demand. If you want to use AI in your business, it’s important to educate yourself.

Need to be aware of some of the pitfalls, check out “Weapons of Math Destruction” by Cathy O’Neill.

There are so many amazing new tools being developed. OSS machine learning libraries. There’s a lot to worry about as a parent, but there’s a lot to look forward to as well. eg. AI that sorts LEGO. Horses replaced by cars. Cars now being replaced by a better version of an autonomous horse.

 

Dave Hatfield

Dave Hatfield takes the stage again. How can you speed up tasks that are mundane so you can do things that are more impactful? You need a framework and a way to ask the questions about the pitfalls. DevOps – institutionalised knowledge of how to become software businesses. Introduces Jez Humble.

 

Jez Humble

Why does DevOps matter? 

The enterprise is comprised of business, engineering, and operations. The idea for a project occurs, it’s budgeted, delivered and thrown over the wall to ops. Who’s practicing Agile? All about more collaboration. Business people don’t really like that. Now delivering into production all the time and Operations aren’t super happy about that. Operations then create a barrier (through change management), ensuring nothing ever changes.

How does DevOps help?

No real definition. The DevOps Movement is “a cross-functional community of practice dedicated to the study of building, evolving and operating rapidly changing, secure, resilient systems at scale”. There’s some useful reading (Puppet’s State of DevOps Reports) here, here, and here.

Software delivery as a competitive advantage

High performers were more than twice as likely to achieve or exceed the following objectives

  • Quantity of products or services
  • Operating efficiency
  • Customer satisfaction
  • Quality of products or services provided
  • Achieving organisational and mission goals
  • Measures that demonstrate to external parties whether or not the organisation is achieving intended results

IT Performance

  • Lead time for changes
  • Release frequency
  • Time to restore service
  • Change fail rate

We’re used to thinking about throughput and stability and a trade-off – that’s not really the case. High performers do both.

2016 IT performance by Cluster 

(From the 2016 report)

  High IT Performers Medium IT Performers Low IT Performers
Deployment Frequency

For the primary application or service you work on, how often does your organisation deploy code?

On demand (multiple deploys per day) Between once per week and once per month Between once per month and every 6 months
Lead time for changes

For the primary application or service you work on, what is your lead time for changes (i.e. how long does it take to go from code commit to code successfully running in production)?

Less than an hour Between one week and one month Between one month and 6 months
Mean time to recover (MTTR)

For the primary application or service you work on,how long does it generally take to restore service when a service incident occurs (e.g. unplanned outage, service impairment)?

Less than an hour Less than one day Less than one day
Change failure rate

For the primary application or service you work on, what percentage of the changes either result in degraded service or subsequently require remediation (e.g. lead to service impairment, service outage, require a hotfix, rollback, fix forward, patch)?

0-15% 31-45% 16-30%

 

“It’s about culture and architecture”. DevOps isn’t about hiring “DevOps experts”. Go solve the boring problems that no-one wants to do. Help your people grow. Grow your own DevOps experts. Re-orgs sucks the energy out of company. They often don’t produce better outcomes. Have people who need to work together, sit together. The cloud’s great, but you can do continuous delivery with mainframes. Tools are great, but buying “DevOps tools” doesn’t change the outcomes. “Please don’t give developers access to Prod”. DevOps is learning to work in in small batches (product dev and org change). You can’t move fast with water / scrum / fall.

Architectural Outcomes

Can my team …

  • Make large-scale changes to the design of its system without the permission of somebody outside the team or depending on other teams?
  • Complete its work without needing fine-grained communication and coordination with people outside the team?
  • Deploy and release its product or service on demand, independently of other services the product or service depends on?
  • Do most of its testing on demand, without requiring an integrated test environment?
  • Perform deployments during normal business hours with negligible downtime?

Deploying on weekends? We should be able to deploy during the day with negligible downtime

  • DevOps is learning to build quality in. “Cease dependence on mass inspection to achieve quality. Improve the process and build quality into the product in the first place”. W. Edwards Deming.
  • DevOps is enabling cross-functional collaboration through value streams
  • DevOps is developing a culture of experimentation
  • DevOps is continually working to get better

Check out the Accelerate book from Jez.

The Journey

  • Agree and communicate measurable business goals
  • Give teams support and resources to experiment
  • Talk to other teams
  • Achieve quick wins and share learnings
  • Never be satisfied, always keep going

 

Dave Hatfield

Dave Hatfield takes the stage again. Don’t do re-orgs? We had 4 different groups of data scientists pop up in a company of 2300. All doing different things. All the data was in different piggy banks. We got them all to sit together and that made a huge difference. “We need to be the ambassadors of change and transformation. If you don’t do this, one of your competitors will”.

Please buy our stuff. Thanks for your time. Next year the conference will be in September. We’re negotiating the contracts right now and we’ll let you know soon.

Solid session. 4.5 stars.

Pure//Accelerate 2018 – Wednesday General Session – Rough Notes

Disclaimer: I recently attended Pure//Accelerate 2018.  My flights, accommodation and conference pass were paid for by Pure Storage via the Analysts and Influencers program. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

Here are my rough notes from Wednesday’s General Session at Pure//Accelerate 2018.

[A song plays. “NVMe” to the tune of Naughty By Nature’s OPP]

 

Charlie Giancarlo

Charlie Giancarlo (Pure Storage CEO) takes the stage. We share a mission: to power innovation. Storage is really important part of making that mission happen. We’re in the zettabyte era, we don’t even talk about EB anymore. It’s not the silicon age, or the Internet age, or the social age. We’re talking about the original gold rush of 1849. The amount gold in data is unlimited. We need the tools to pick the gold out of the data. The data heroes are us. And we’re announcing a bunch of tools to mine the gold.

Who am I? What has allowed us to get to success? Where are we going?

I’m new here, I’ve just gotten through his 3rd quarter. I’ve been an nngineer, entrepreneur, CTO, equity partner – entirely tech focused. I’ve made a living looking at innovation on the basis of looking at it as a 3-legged stool.

What are the components that advance tech?

  • Networking
  • Compute (Processing)
  • Storage

They advance on their own timelines, and don’t always keep pace, and the industry someitmes gets out of balance. Data centre and system architectures adjust to accommodate this.

Compute

Density has multiplied by a factor of 10 in 10 years (slow down of Moore’s Law), made up for this by massive scale in the DC

Networking

Multiplied by 10 in 8 years, 10Gbps about 10 years ago, and 100Gbps about 2 years ago

Data

  • Multiplied by a factor of 1000
  • Storage vendors just haven’t kept up
  • Storage on white boxes?

Pure came in and bought balance to this picture, allowing storage to keep up with networking and compute.

It’s all about

  • Business model
  • Customer experience
  • Technology

“Data is the most important asset that you have”

Pure Storage became a billion dollar company in revenue last year (8 years in, 5 years after it introduced its first product). It’s cashflow positive and “growing like a bat out of hell” with over 4800 customers. Had less than 500 customers just 4 years ago. And a large chunk of customers are cloud providers. Also in 30% of the Fortune 500.

Software

The software economy sits on top of the compute / network / storage stool. Companies are becoming more digital. Last year they talked about Domino’s, and this year they’re using AI to analyse your phone calls. Your calls are being answered by an AI engine that takes your order. An investment bank has more computer engineers and developers than they have investment bankers. Companies need to feed these apps with data. Data is where the money is.

DC Architectures

  • Monolithic scale-up – client / server (1990s)
  • Virtualised – x86 + virtualisation (2000s)
  • Scale-out  – cloud (2010s)

Previously big compute – apps are rigid, now there’s big data – apps are fluid, data is shared

“Data-centric” architecture

  • Faster
  • 100% shared
  • Simpler
  • Built for rapid innovation

Dedicated storage and stateless compute

Examples

  • Large booking, travel, e-commerce site
  • PAIGE.AI – cancer pathology – digitised samples from the last decade
  • Man AHL – economy and stock market modelling

Behind all these companies is a “data hero”

Over 80% of CxOs believe that the speed of analysing data would be one of their biggest competitive issues, but CIOs worried about not being able to keep up with data coming in to the enterprise.

“We empower innovators to build a better word with data”

Beyond AFA

  • Modern data pipeline
  • A whole new model
  • Pure “on-demand”
  • The AI Era

“New meets Now”

It takes great people to make a great company – the amazing “Puritans”. Pure have a NPS score of 83.7 – best in B2B.

 

Matt Kixmoeller

Matt Kixmoeller takes the stage. We need a new architecture to unlock the value of data. Back in 2009. Michael Jackson died, Obama was in, Fusion-IO had just started. Pure came along and had the idea of building an AFA. Today we’re going to bring you the sequel

  • There’s basically SAN / NAS and DAS (which has seen a resurgence in web scale era)
  • DAS reality – many apps, rigid scaling, either too much storage or too much compute

New technologies to re-wire the DC

  • Diverse, fast compute (CPU, GPU, FPGA)
  • Fast networks and protocols (RoCE, NVMe-oF)
  • Diverse SSD
  • Eliminates the outside the box penalty
  • Gets CPUs totally focussed on applications

What if we can finally unite SAN and DAS into a data-centric architecture?

Gartner have identified “Shared accelerated storage”. “The NVMe-oF protocol … will help balance the performance and simplicity of direct-attached storage (DAS) with the scalability and manageability of shared storage”.

“Tier 0”? – they’re making the same mistake again. Pure are focused on shared accelerated storage available for all.

Tomorrow can look like this

  • Diskless, stateless, elastic compute (continuers, VMs, bare metal)
  • Shared accelerated storage (block, file, object)
  • Fast, converged networks
  • Open, full-stack orchestration

 

Keith Martin

Keith Martin (ServiceNow) takes the stage

  • Dealing with high volumes of data
  • Tremendous growth in net new data
  • 18 months ago, doing basic web scale, DAS architecture
  • Filling up DCs at a very fast clip
  • Stopped and analysed everything there was

What happens in an hour in the DC?

In one hour our customers:

  • 7.5 million performance analytics scores computed
  • 730,000 configuration items added
  • 274,000 notifications sent
  • 76,000 assets added
  • 49,200 live feed messages
  • 36,300 change requests
  • 15,600 workflow activities

Every hour of the day our engineering teams:

  • Develop code across the globe in 9 global develoipment locations (SD, SC, SF, Kirkland, London, Amsterdam, Tel Aviv, Hyderabad, Bangalore)
  • Use 450 copies of ServiceNow for quality engineering testing
  • Run 100,000 automated quality engineering tests

In one hour on our infrastructure

  • 25 billion database queries
  • 112 million HTTP requests
  • 2.5 million emails
  • 25.3 million API calls
  • 493TB of backups

We were going through

  • 30K hard drives
  • 3500+ servers
  • >2000 failed HDDs per year

CPU time was being consumed with backup data movement and restore times were becoming longer and longer. They started to look at the FlashBlade. With its small footprint and low power it was a really interesting option for them. It was really easy to setup and use. They let the engineers out of their cages to play with it in the lab and found it was surprisingly hard to break. So they’ve decided to start using FlashBlade in production as their standard for protection data.

Achieving 3x density now

Each rack has:

  • 30 1RU servers
  • 1000 compute cores
  • 1.5PB effective Flash

Decided to test and implement FlashArray as well and they’re excited about FlashArray//X. ServiceNow cares about uptime. Pure has the best non-disruptive upgrade, expansion and repair model. DAS can prove to be expensive at scale.

 

Matt Kixmoeller

Kix takes the stage again

  • 2016: FlashBlade – the world’s first AFA for big data
  • 2017: FlashArray//X

Introducing the FlashArray//X Family

  • //X10
  • //X20
  • //X50
  • //X70
  • //X90

 

Bill Cerreta

Bill Cerreta takes the stage.

  • The FlashArray was launched in 2012, Purity was built to optimise Flash
  • //M chassis designed for NVMe
  • Deep integration of software and hardware

Where are we going with Flash?

SCM, QLC. We’ve eliminated translation layers. The X//90, for example, has

  • Dual-Protocol controllers – speaks to both SSD and NVMe
  • The 10 through 90 have 25GbE onboard
  • Everything’s NVMe/oF ready and this will be added via software later in the year
  • Double the write bandwidth of //M
  • This year, they’re all in on //X
  • 7 generations of evergreen, non-disruptive upgrades [photo]
  • //X makes everything faster (compared to //M)

Neil Vachharajani takes the stage briefly to talk MongoDB on shared accelerated storage.

Kix continues.

Priced for mainstream adoption

  • Early attempts at NVMe cost 10x more than AFAs
  • //X, when introduced last year, was 25% more than //M
  • $0 premium for //X over //M on an effective capacity basis

[Customer video – Berrios]

 

Jason Nadeau

Jason Nadeau takes the stage. Most infrastructure wasn’t built to allow data to flow freely.

  • 10s of products
  • Complex design
  • Silos, difficult to share

“Data-as-a-Service”

Data-centric Architecture

  • Consolidated and simplified
  • Real-time
  • On-demand and self-driving
  • Ready for tomorrow
  • Multi-cloud

Foundation

  • FlashArray
  • FlashBlade
  • FlashStack
  • AIRI

API-first model and software at the heart of the architecture.

 

Sandeep Singh

Sandeep Singh takes the stage. A lot of companies have managed to virtualise. A lot have managed to “flash-ify”. But a lot of them have yet to automate and “service-ize”, to “container-ize”, or to adopt multi-cloud.

Automate and service-ize – on every cloud platform

  • VMware SDDC – VMware SDDC validated design
  • Open automation – pre-built open full-stack automation toolkits
  • Openshift PaaS – container-based reference architecture

Simon Dodsley takes the stage to talk with Sandeep about MongoDB deployments in less than a minute (down from 5 days).

Sandeep continues. Container adoption is increasing quickly but there’s a lack of storage support for persistent containers. Pure have container plug-ins for Docker, Kubernetes. Containerized apps want to consume storage as-a-service. Introducing Pure Service Orchestrator.

Multi-cloud

Introduced ActiveCluster last year. Snapshots and snapshot mobility (portable snapshots introduced last year) are important.

  • Snap to NFS is generally available now
  • CloudSnap to AWS S3 (available in late 2018)
  • DeltaSnap open API (Veeam, Catalogic, actifiio, CommVault, Rubrik, Cohesity)

 

Jason Nadeau

Jason Nadeau comes back on stage. Data as-a-service consumption. Leases aren’t pay per use and aren’t a service-like experience

Introducing Evergreen Storage Service (ES2)

  • Pay per used GB
  • True open
  • Terms as short as 12 months
  • Always evergreen
  • Onboard in days
  • Always “better-than-cloud” economics

Capex with Evergreen storage, Opex with ES2

[Video on PAIGE.AI]

 

Matt Burr

Matt Burr takes the stage. Unlocking the value of what was once cold data. New era demands a new data mindset.

  • How has the value of data changed?
  • How can you extract that value?
  • How can you get started today?

A robot will replace a human surgeon. A machine has learned to adapt faster than the human brain can. More and more data will live in the hotter tier. What tools can make this valuable? Change in the piggy bank – like data. But data is stuck in silos.

  • Data warehouse
  • Data lake
  • Modern data pipeline
  • AI data pipeline

$/GB used to make sense. We need new metrics. $/flops? $/simulation. Real value is generated by simplifying and accelerating the data flow. Build a data hub on FlashBlade. FlashBlade is 16 months old (GA in January 2016).

Invites NVIDIA’s Rob Ober on stage

 

Rob Ober

“The time has come for GPU computing”

  • Moore’s Law is flattening an awful lot
  • NVIDIA as “the AI computing platform”
  • “The more you buy, the more you save”

Traditional hyper scale cluster – 300 dual-CPU servers, 180KW power, or you can deploy 1 DGX-2, 10KW.

Science fiction is being made possible

  • Ultrasound retrofit
  • 5G beam
  • Molecule modelling 1/10 millionth $

Scaling AI

  • Design guesswork
  • Deployment complexity
  • Multiple points of support

AI scaling is hard, “not like your traditional infrastructure”

AIRI

  • Jointly-validated solution
  • Faster, simplified deployment
  • Trusted expertise and support

 

Matt Kixmoeller

Kix takes the stage again. There’s a big gap in AI infrastructure, with customers spread across varying stages of journey from single server -> scale-out infrastructure. Introduces AIRI Mini and they’re also extending AIRI to Cisco.

 

Data Warehouse pitfalls

  • Performance not keeping up with data
  • Pricing extortions and over-provisioning
  • Inflexible appliances built for a single workload

Progress has to have a foundation.

Customer example of telco in Asia moving from Exadata to FlashBlade

Introducing FlashStack for Oracle Data Warehouse

Set your data free

 

Dave Hatfield

Dave Hatfield takes the stage. Thanks for coming. Over 5000 people in the Bill Graham Civic Auditorium and a lot watching on-line. Customers, partners. Be sure to check out the “petting zoo” (Solutions Pavilion). We wanted to have something that was “not your father’s storage show. Your father’s storage show happened last month”. Anyone been to a Grateful Dead show? It’s a community experience, you don’t know what will happen next.

And that’s a wrap.

Storage Field Day Exclusive at Pure//Accelerate 2017 – FlashBlade 2.0

Disclaimer: I recently attended Storage Field Day 13.  My flights, accommodation and other expenses were paid for by Tech Field Day and Pure Storage. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

 

These are my rough notes from a session I attended on “Day 0” of Pure//Accelerate 2017 (aka Storage Field Day Exclusive at Pure//Accelerate 2017). Videos of the session can be found here and you can grab my raw notes from here. I try to avoid dumping a bunch of dot points in Tech Field Day posts, but as this one covered some key announcements, I thought most of the information was useful presented as is.

 

A Year of FlashBlade

Par Botes spoke to us briefly about the progress made with FlashBlade in the past year. Originally internally codenamed “Wedding Cake” as it was a white box, the performance is “better than you think”, going from 500K IOPS and 15GB/s, to 1.2M IOPS and 15GB/s, to 1.5M IOPS and 16GB/s in the first six months since GA. I first encountered FlashBlade in the flesh at Storage Field Day 10. You can read more about that here.

 

Scaling Beyond 15 Blades

Rob Lee took some time to talk about scaling beyond 15 blades in a chassis.

  • Linear capacity scale – single namespace growing to dozens of PB scale
  • Linear IOPS and throughput – single namespace / IP scales IOPS and throughout with capacity
  • Preserve simplicity – more capacity adds IOPS & throughout with zero administration

 

Logical View

  • Fabric – scale raw bandwidth without adding management
  • Processing – software dynamically schedules processing resources globally
  • Data – place data as a single system across all blades

 

High level Architecture

  • Integrated Networking – combined internal and external networks. Load balance connections across all blades.
  • Distributed control – partition and distribute control of namespace, data, and metadata across all blades
  • Distributed Data – Distribute persistent data across all blades – high-frequency transactions in NVRAM and longer-lived data in N+2 erasure-coded flash

[image courtesy of Pure Storage]

 

FlashBlade Data Distribution

  • Wide-stripe erasure coding with +2 redundancy
  • Scaling past a single chassis
  • External network load balancer, inter-chassis network switching
  • Added external Fabric Module
  • intra-chassis network switching
  • External Flash Module is 2 rackmounted switches

 

Scaling Fabric Bandwidth

32port 100Gbs switch (1.6Tb/s north-south). Here’s a photo of Rob talking about this.

  • Controller load balancing and capacity load balancing
  • East-west traffic
  • NVRAM/Flash data access
  • Metadata coordination
  • 1.6Tbs across chassis, 300Gbs within chassis

 

Control Placement

Adding a blade is straightforward

  • Partitions rebalance to new blade – stops running on old blade and boots on new blade
  • No data movement required, only compute (data stays in-place)
  • Partition load balancing on a per-blade basis – not chassis constrained

 

Data Placement

  • Data erasure coded across n+2 RAID stripes
  • 15 blades – 13-wide stripe (11+2 parity shards)
  • RAID Groups are dynamic – selected as needed
  • RAID Groups can cross chassis boundaries

As you fill the chassis, it becomes beneficial to constrain the RAID group to a chassis. Note also that there’s enhanced resiliency (n+2 per chassis, without additional overhead) and reduced inter-chassis bandwidth requirements for rebuild operations.

 

Takeaways

  • Software creates parallelism and scale; hardware enables access to data
  • Software/hardware integration without tight coupling
  • Simplicity/reliability created by software control of the network fabric

 

Native Objects

Brian Gold presented a section of the session on Why Objects?

Next Generation Apps

  • Cloud-native development
  • Rich metadata databases

Performance

  • Large & streaming: AI training, media serving, analytics
  • Small & random: time-series metrics, real-time streams

Efficiency

  • No visible partitions
  • Unified management

 

Classic Object Gateways

  • Object API gateway -> file system (index to track metadata)
  • File system becomes bottle neck when scaling to billions of object
  • Purity (FlashArray and FlashBlade) – objects at the core

 

Object Read Path

Request Arrival

  • Extract bucket and object names from request
  • Decode bucket and object names
  • Get bucket ID from authority
  • Get object ID from bucket authority
  • Forward read request to object authority

Read data

  • Read object data from flash
  • Forward back to protocol handler
  • Decompress and form response to client

Two takeaways

  • Two phases – metadata lookup and data access; distributed everything
  • Basically identical to how a file is read via NFS

FlashBlade is S3-compatible for the moment. Purity is really a key-value database

 

Looking Forward

The next generation of applications require new storage interfaces. There was a demo using TensorFlow.

  • Converting raw pixels (ultimate in unstructured data) to structured data
  • Now imagine if you’ve got 10s of thousands of cameras
  • Object detection -> message queue -> object indexing, streaming queries, time-series analysis

 

Conclusion

Par wrapped up by talking about:

  • “The big bang of intelligence”
  • Modern Compute – parallel architecture driving performance
  • New Algorithms – modern approaches for superhuman accuracy
  • Big Data – Data is the new oil
  • “Massively parallel is the new normal”
  • 4th Industrial Revolution (2010 – now) – AI, Big Data, Cloud, IoT, Computing, digital to intelligence

I was a bit confused by FlashBlade when I first heard about it, and suggested that the 12 months post Storage Field Day 10 would be critical to the success of the product. Pure have managed to blow me away with the progress they’ve made with the product since GA, the breadth of customers and use cases they’ve lined up, and the overall level of forward thinking that’s gone into the product. You can use it to do some really cool stuff. The biggest problem I’ve had with the “data is the new oil” paradigm is that, unlike real oil, a lot of companies don’t actually know what to do with their data. FlashBlade is not going to magically fix this for you, but it’s going to give you some pretty compelling infrastructure that solves some of the problem of how to do stuff effectively with massive amounts of data.

Object storage is the new hot, and has been for a little while. Putting together a product like FlashBlade has certainly gotten Pure into a bunch of accounts where they weren’t traditionally successful with FlashArray. It’s also given their more traditional customers a different option for tackling big data problems. Pure strike me as being fiendishly focused on delivering something special with FlashBlade, and certainly don’t appear to be slowing down when adding new features to the platform. There’s been some really cool features added, including support for 17TB blades (almost by accident) and increasing scalability to 75 blades. I’m looking forward to seeing what’s next for FlashBlade. You can read the blog post about the FlashBlade 2.0 announcement here.

 

Storage Field Day Exclusive at Pure//Accelerate 2017 – Purity Update

Disclaimer: I recently attended Storage Field Day 13.  My flights, accommodation and other expenses were paid for by Tech Field Day and Pure Storage. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

 

These are my rough notes from a session I attended on “Day 0” of Pure//Accelerate 2017 (aka Storage Field Day Exclusive at Pure//Accelerate 2017). Videos of the session can be found here and you can grab my raw notes from here. I try to avoid dumping a bunch of dot points in Tech Field Day posts, but as this one covered some key announcements, I thought most of the information was useful presented as is.

 

ActiveCluster

Tabriz Holtz and Larry Touchette took us through an overview of ActiveCluster.

 

What do customers really want?

  • Disaster protection
  • Consistent performance
  • Transparent failover
  • Ease of management
  • Subscription to innovation

They don’t want

  • Life to be difficult because they’re running synchronous replication
  • To pay for it

 

Multi-site Active/Active

  • Zero RPO
  • Zero RTO
  • Zero $
  • Zero Additional Hardware

 

Basic Architecture

  • Symmetric Active/Active
  • Pure’s pod management model – container where you can store your volumes
  • Passive Pure1 Cloud Mediator – prevent split brain

 

Pods

  • Simple management model
  • only 1 new command introduced
  • serves as a container and a consistency group
  • keeps metadata with its data

 

4 Steps to Setup

The whole point is that it’s super simple to setup, so much so that you can do it in four steps from the CLI.

1. Connect the arrays

purearray connect --type sync-replication

2. Create a stretched pod

purepod create pod1
purepod add --array arrayB pod1

3. Create a volume

purevol create --size 1T pod1::vol1

4. Connect your hosts

purehost create --preferred-array arrayA host
pure host connect --vol pod1::vol1 host

 

Symmetric Active/Active

I/Os perform symmetrically

  • 1 round trip for writes
  • reads serviced locally

Host ALUA preferences:

  • Active/Optimised
  • Active/Non-optimised

There’s a 5ms RTT limit and it uses TCP/IP between arrays (Ethernet). Independent dedupe runs on both sides.

 

Passive Mediator

  • No split brain … ever!
  • Intelligence is in the arrays
  • Mediator imply records failover
  • No third site needed
  • Arrays alert if they can’t access mediator

There is also the option to deploy a VM that can be used on-premises. While the cloud mediator runs multiple instances behind a load balancer, the on-premises mediator would have to be protected with HA or similar.

So what if I lose comms to the outside world? (both to the outside world and the partner array). Volumes will be taken offline. The mediator is a per pod setting, so you could conceivably use both in your environment.

 

Transparent Recovery

1. Snapshots sent asynchronously until arrays are nearly in sync

2. IOs forwarded synchronously along with final snap are merged into target

3. Arrays are fully in sync with no pause in IO for final sync

The goal is to allow different arrays to replicate with each other. At GA these will be qualified. Purity versions (1 minor version different e.g. 5.1 and 5.2). Every customer gets this feature (yay, Evergreen). Assuming you have the appropriate supporting infrastructure. And there’s support for multiple connection types.

 

DirectFlash Shelf

Pete Kirkpatrick (Chief Hardware Architect) spoke about the recently announced FlashArray//X.

  • 100% NVMe Enterprise AFA
  • “This is just a flash array”
  • The data is the array, the hardware and software comes and goes over time

They were working on the FlashArray//M chassis about 4 years ago, and had gone to some length to future proof the design. “DirectFlash Modules” are now replacing the SAS SSDs. SSDs emulate HDDs – this isn’t ideal.

 

Flash Transition Layer needs Garbage Collection

  • Severely limits sustained throughout
  • Destroys latency distribution
  • Causes excess wear
  • Needs over provisioned capacity

 

Legacy protocols and interfaces

  • Assumed high latency
  • Inherently serialised

 

DirectFlash

Purity has always been designed for Flash, so get disk legacy out of the way. The goal of DirectFlash was to

  • Start with NVMe: efficient, low latency, high throughput, high parallelism,
  • Design an API providing knowledge of the Flash geometry
  • Place data intelligently, and schedule operations with high precision
  • No FTL is required, so GC is eliminated
  • High sustained throughput and low, deterministic latency
  • No over provisioning
  • Extended flash endurance

Here’s a happy snap of one of the 18.3TB (I think) modules.

You can now fit 1PB of useable Flash in 3RU. DirectFlash Shelf is this week’s news. They’re using NVMe/F. It’s over RoCE (RDMA over Converged Ethernet). You can start with 1 shelf at this stage, but Pure are looking to extend that capability.

 

VVols Support

Cody Hosterman took us through VMware Virtual Volumes (VVols) support with Purity//FA 5.0. I enjoy watching Cody present and I wasn’t disappointed by this session. So, VVols eh? Why?

  • Virtual disk granularity on array – use array-based technology on a virtual disk basis
  • Automatic volume creation and configuration
  • Storage Policy Based Provisioning

 

Virtual Volumes – The Full Picture

[image via Pure Storage]

 

VVols

Every VM has individual volumes on the array:

  • Config VVol—4 GB—holds the configuration information of the VM. Created automatically when a VM is provisioned
  • Swap VVol—is for the VM swap file. Sized according to the VM memory. Created automatically when the VM is powered-on and deleted when powered-off
  • Data VVol—for every virtual disk added to the virtual machine there is a new data VVol. Sized by the requested size of the virtual disk

 

VVol Snapshots

  • VMware snapshot and array-snapshot is created automatically – no performance penalty

 

The Data Plane

Protocol Endpoints

  • A mount-point for VVols
  • Presented in a traditional fashion via iSCSI or FC as LUN
  • VVols are sub-LUNs to a PE. IO goes to the PE on the array, the array distributes.
  • FlashArray automatically “binds” VVols to the appropriate PE

 

The Management Plane

  • How does vCenter manage the FlashArray? Through a VASA provider

FlashArray VASA Provider

  • VASA version 3 (includes replication)
  • Redundant service on both controllers
  • Automatically configured during Purity upgrade
  • Active-active configuration
  • Entirely stateless – no configuration is tied to /stored on the hardware of the controllers (no special VASA database on the array, it is part of the array configuration)

 

Policy Based Management

Create VMs and individual virtual disks (VVols) independently

Use customised capabilities advertised by VASA provider to configure volumes

  • Replication
  • Snapshot policy
  • QoS
  • Etc.

Are VVols Special Volumes? On the FlashArray, not really. Just normal volumes with special metadata tags. So if you want to present a VVol to a physical server for instance? You can just connect it as a standard LUN.

 

Conclusion

I’m enthusiastic as all get out about ActiveCluster. There have been rumblings in the market about this type of capability for some time, so it’s great to see Pure deliver. I need to dig a bit deeper into it, but it feels a lot like it has the cross-site capability of Dell EMC’s VPLEX without a lot of the palaver traditionally associated with that product (which to be fair, does more than just cross-site volumes). The great thing is that it’s available to existing customers without additional expense (at least on the Pure side) or messing about. This has always been a big selling point for Pure, and it’s great to see it continue here.

I think the DirectFlash shelf is certainly a step in the right direction and the appetite is there for this kind of solution. I’ll be interested to see how many shelves they end up adding, as the scale and speed possibilities here are potentially pretty tremendous. It will also be interesting to see the uptake of the solution over the next 12 months.

I liked a lot of what I saw with Cody’s presentation on VVols support. It certainly appeared fairly straightforward. I remain underwhelmed by VVols in general though. I know there needed to be a change in the way we presented storage to VMs but it feels like we’ve somehow missed the boat with this solution. In another year it might just be that everything sits on VVols by default but I feel like that’s been the feeling for the past five years and it hasn’t yet transformed to the extent we expected. I am more than happy to be proven wrong on this point though, and my surliness regarding VVols shouldn’t be taken as criticism of what Pure have managed to deliver here. Also, it’s worth checking out Cody’s post on Virtual Volumes support here – he covers it way better than I do.

Storage Field Day Exclusive at Pure//Accelerate 2017 – General Session Notes

Disclaimer: I recently attended Storage Field Day 13.  My flights, accommodation and other expenses were paid for by Tech Field Day and Pure Storage. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

 

Here are my General Session notes from Day 1 of Pure//Accelerate 2017. I’ll be digging into some of the announcements in the very near future so this is just a rough teaser. I call it death by dot point.

 

David Hatfield

David Hatfield in a Dubs cap. Sorry about the traffic, but it can be hard “[w]hen you setup an event for 3000 people in kind of a crack area?.” He then talks about Game 5 of the NBA Finals. Thanks to people for coming a long way (some travelled around 36 hours). 227800 square feet of space. Used for manufacture of iron originally. This will be the last event ever in this building. Will be knocked down soon. There’s also a 110 feet wide screen, 420 million pixels, FlashBlade helps to render.

“New and Possible”

  • 25 new software capabilities, new hardware, new cloud capabilities, new partners (friendships?)
  • “The new possible” – Help you break free from legacy way of doing things.
  • New – look around and identify what real innovation looks like.

Partner and sponsor shoutout

  • It takes an ecosystem of partners to help too, and sponsors as well.
  • Shoutout to Veeam – will be directly integrating Veeam and Pure Storage in next release of Availability Suite (v10?)
  • Cisco – FlashStack (over 1400 customers together). 7 CVDs in place at the moment. 2 new offers – NVMe over Fabric to the host, Cisco Capital – full offering for FlashStack

 

Scott Dietzen

Scott Dietzen (CEO) takes the stage, and reclaims his Dubs cap. Am I in the right place? I knew I was when I got inside. Blue is the colour of so many of our competitors, but it’s a Warriors cap, so it’s okay.

This is our second //Accelerate conference. Thanks to 3300 customers (and partners).

“The world’s most valuable resource is data”

  • Companies are competing to amass huge datasets (are they doing useful things with it though?)
  • AI rates only behind cloud and mobile in terms of impact people think it will have
  • “Massively parallel AI demands massively parallel storage”

“By the year 2020 the amount of data created will be 50+ zettabytes”

  • Capacity of the Internet will only be 2.5 zettabytes
  • It’s going to stored close to where it’s generated

A new model for DCs

  • Multi-cloud
  • Core
  • Edge

Pure uses tonnes of SaaS to run its business, but it also has its own DCs. Believes Edge is going to be larger than multi-cloud and core together because of IoT, etc.

 

Disruptors? (based on a recent survey)

  • The digital gold rush
  • The great workload debate
  • Cloud: migrations and mistakes
  • Data: taking back control

Multi-cloud = photo of Snoop Dogg blazing. Pure are looking to deliver “The data platform for the cloud era”.

 

Differentiators?

  • Big data bandwidth
  • Performance for deep learning
  • ultra-density
  • Uptime
  • Subscription to innovation

 

Tomorrow’s cloud block:

  • 1300 cores
  • 2.6PB Flash
  • 2x density and 5x performance improvement (for leading SaaS company)
  • 100x reduction in space for enterprise DC (20 racks -> 4RU)

$1B revenue and cash flow positive, 6th year in selling

All the new software updates are given to customers for free

 

Liz Centoni

Liz Centoni (Cisco SVP and GM, Computing Systems Product Group) takes the stage to talk with Scott Dietzen.

Every DC was built to do one thing: run applications. But these applications are changing – how they’re built, where they reside, etc. They’re a lot more distributed. A lot more endpoints to manage and secure.

How does FlashStack help?

  • Helps customers build their private cloud infrastructure
  • This year – adding hybrid cloud (via Cisco CloudCenter)

FlightStats example

Servers existed before DCs or cloud. Customers want any workload, anywhere

  • Compute is moving closer to the data.
  • Security is top of mind for everyone.
  • UCS is a “system” – fabric-centric design, 100% programmable, 60K customers.
  • Start small and scale

What about the impact of NVMe?

  • SSDs changed the storage bottleneck, but NVMe really puts it back on the network. Cisco is happy about having the opportunity to improve the performance of the whole stack.

 

Kelli Zielinski

Kelli Zielinski, Domino’s takes the stage. Traditional arrays just weren’t keeping up. Invested in Pure Storage FlashStack. Now “[t]he application gets what it needs”.

 

Matt Kixmoeller

Matt Kixmoeller takes the stage. It’s the “dawn of a new cloud era – yet the old never really disappears”.

Purity

  • Reduce
  • Assure
  • Protect
  • Secure
  • Direct Flash

Pure1

  • Manage
  • Analyse
  • Support
  • Meta

FlashBlade for big data, FlashArray//X for low latency/high IOPS apps

It’s time for software to take centre stage – 25 new features (delivered in an Evergreen fashion)

 

Tier 1

  • “no one ever got fired for buying [blue]”.
  • You want reliability and innovation (dedupe, compression, simple, automated, open cloud integration, NVMe, NVMe/F)
  • Delivered 2 years of 6 9s since GA

Metro Stretch Cluster – 1994 – EMC launched SRDF – 20 years later – still hard and expensive.

 

Purity//FA 5.0

Purity ActiveCluster.

Steve Hodgson (Software Architect) does a brief demo on setup.

 

Jason Nadeau

Jason Nadeau takes the stage.

  • Compression 2.0 – 25% improvement – self-selecting compression engines
  • Simplest VVols implementation in the industry
  • Granular VM-level operations and transparency
  • Cloud automation and security compliance

 

Purity//FA Snap and CloudSnap

“Portable snapshot”

  • Snap Local
  • Snap to FlashArray
  • Snap to FlashBlade
  • Snap to NFS
  • CloudSnap to AWS
  • DeltaSnap to API

So now you can:

  • Native, two-way cloud connection
  • Backup, restore, migrate, and DR
  • Fully leverage all PaaS services

 

Purity //Run

  • Run VMs and Containers Directly on Purity
  • Ideal for Edge Analytics, Custom protocols
  • Flexible, open, secure, HA platform

 

Windows File Services for Purity

  • Best of Breed – FlashArray meets MS File services

 

DirectFlash Shelf

  • Native NVMe/F expansion shelf (photo)

 

“The new Tier 1 is Evergreen”

 

Arthur Riel

Arthur Riel (Director, The World Bank) takes the stage. The World Bank is neither Wall Street nor Main Street. Their job is to decrease poverty. When he got there, they were a risk-averse organisation (“Let’s keep doing what we’re doing because it works”).

  • But “[i]f I save money and can’t deliver my services what good is that?”.
  • “Slow storage covers up a lot of sins up the stack”

 

Sumit Dhawan

Sumit Dhawan (runs EUC at VMware) talks with Scott Dietzen.

“Tech is going out of tech” you need a more platform-centric approach (?)

Dietzen: Is it hard to work with us when your parent company is Dell? (I’m paraphrasing).

 

Par Botes and Rob Lee

Par Botes and Rob Lee take the stage to talk about FlashBlade.

  • “The big bang of intelligence”
  • Medium blade – 17TB (fits in between 8TB and 52TB)
  • 75 blade-scale FlashBlade (start as small as 7 blades, scale 1 at a time)

 

Why Object Storage?

  • Cloud-native applications use object storage
  • Next-generation developers code with object
  • Cloud primary storage is object
  • >10x faster time to first byte vs S3
  • >100x faster indexing image objects vs existing solution at leading web scale company

Brian Gold joins them on stage – it’s about AI from edge to cloud

 

Rob Ober

Rob Ober (Tesla Chief Platform Architect, Nvidia) takes the stage with Scott Dietzen.

Deep learning (about 5 years ago) has taken off because of:

  • Neural nets (this have been around a while)
  • Massive amounts of data (tremendous volumes)
  • Computation

“You need good data”

 

Sandeep Singh

Sandeep Singh on stage to talk about self-driving storage

  • Automate and simplify
  • Sense and model world around
  • Constantly learn and re-train
  • Global effect

 

>7PB telemetry data

> 1 trillion data points per day

 

Pure1

>500 Sev1 incidents avoided to date

 

Performance sizing has been the final frontier

  • Too many variables
  • Complex interaction and inter-dependencies
  • Over provisioning = wasted expense
  • under-provisioning = downtime

This is a perfect problem for AI and machine learning.

 

Pure1 Meta

  • Global sensor network
  • real-time scanning
  • data lake
  • AI engine

 

Sergey Zhuravlev, Chief Data Scientist

  • >1000 measures
  • “workload DNA”
  • Meta learns from everyone’s workloads to make better predictions
  • Meta Workload Planner

 

David Hatfield takes the stage to wrap up. Here’s a summary of today’s announcements.

 

Purity//FA 5.0

  • ActiveCluster
  • Snap to FlashBlade
  • Windows File Services for FlashArray (SMB and NFS)
  • Policy QoS
  • Snap to NFS
  • Compression 2.0
  • VVols
  • Hybrid Cloud for AWS
  • Microsoft ODX
  • CloudSnap to AWS
  • Purity /Run
  • Docker Persistent Volumes

 

Purity//FB 2.0

  • Object / S3
  • SMB
  • Snapshots
  • Scale to 75 Blades
  • HTTP
  • REST
  • LDAP
  • IPv6
  • NFS NLM

 

Pure1

  • Pure1 Meta
  • Workload Planner
  • Cloud Mediator
  • Global Dashboard
  • Workload DNA
  • Cloud REST

 

Good session. 4 stars. Stephen did a nice live blog as well – you can read it here.

 

Storage Field Day – I’ll Be At Storage Field Day 13 and Pure Accelerate

Storage Field Day 13

In what can only be considered excellent news, I’ll be heading to the US in early June for another Storage Field Day event. If you haven’t heard of the very excellent Tech Field Day events, you should check them out. I’m looking forward to time travel and spending time with some really smart people for a few days. It’s also worth checking back on the Storage Field Day 13 website during the event (June 14 – 16) as there’ll be video streaming and updated links to additional content. You can also see the list of delegates and event-related articles that have been published.

I think it’s a great line-up of presenting companies this time around. There are a few I’m very familiar with and some I’ve not seen in action before.

*Update – NetApp have now taken the place of Seagate. I’ll update the schedule when I know more.

 

I won’t do the delegate rundown, but having met a number of these people I can assure the videos will be worth watching.

Here’s the rough schedule (all times are ‘Merican Pacific and may change).

Wednesday, Jun 14 09:30-10:30 StorageCraft Presents at Storage Field Day 13
Wednesday, Jun 14 16:00-17:30 NetApp Presents at Storage Field Day 13
Thursday, Jun 15 08:00-12:00 Dell EMC Presents at Storage Field Day 13
Thursday, Jun 15 13:00-14:00 SNIA Presents at Storage Field Day 13
Thursday, Jun 15 15:00-17:00 Primary Data Presents at Storage Field Day 13
Friday, Jun 16 10:30-12:30 X-IO Technologies Presents at Storage Field Day 13

 

Storage Field Day Exclusive at Pure Accelerate 2017

You may have also noticed that I’ll be participating in the Storage Field Day Exclusive at Pure Accelerate 2017. This will be running from June 12 – 14 in San Francisco and promises to be a whole lot of fun. Check the landing page here for more details of the event and delegates in attendance.

I’d like to publicly thank in advance the nice folks from Tech Field Day who’ve seen fit to have me back, as well as Pure Storage for having me along to their event as well. Also big thanks to the companies presenting. It’s going to be a lot of fun. Seriously.