From orphans to open source, data matters

TMF ChildrenMy wife’s day job helps Indian orphans through the Miracle Foundation here in Austin. On the surface, our jobs are very different; however, there is lately more and more intersection in both form and substance. It was not always like that, initially the Miracle Foundation primary engagement had been an emotional appeal: “look, these orphans are sad, they need you. Did we mention that they are orphans?”

Joking aside, there are plenty of kind people who want to help children; however, there are a lots of worthy causes with equally strong appeal. The question is how do you pick which one? Donors/Contributors want one that is both emotionally appealing and effective.

While radically different in human impact, both of raising orphans and building open source rely heavily on personal engagement and passion for success. Just like non-profits, there are many open source projects that want you to invest your time in installing and contributing to their most worthy technology.

About 18 months ago, the Miracle Foundation pivoted their strategy from tending individual children towards cultivating whole orphanages (the “NEST program”, video below). They started tracking things like how much milk and fruit each child ate and if they had been vaccinated. They connected observable data like hemoglobin levels of children to their ability to pay attention in school. They were even aware of additional days girls spent in school just because they got monthly hygiene products.

NEST Spider Graph

Used with Permission, The Miracle Foundation

With this new program, the Miracle Foundation can tell you exactly how much benefit each child will receive from each dollar. These are real results derived from collecting real data, and the results are powerful.

The children the Miracle Foundation nurtures are going from subsistence to flourishing. This is not happening because people care more about these children than before. It is happening because someone is keeping the data and making sure that the support they give gets the results they want. This in turn helps donors (become one) feel confident that their emotional response is delivering tangible improvements. Both are essential to TMF’s mission.

Open source projects have a similar gestalt.

People and companies contributing time and resources to a project want to both believe in the technology and see tangible metrics to validate adoption. Open source transparency makes it easier to find active projects and people are engaged contributors, but it can be harder to determine if the project is having broader impact.

For OpenStack, these tangible metrics began to surface in the last few days. Before the summit, Stephano Muffulli, community manager, launched the OpenStack Activity Board to show commit and quality data for the project. Last Monday, Tim Bell & Ryan Lane presented the results of the first user survey which showed how and what users are adopting for OpenStack.

If you like seeing this type of data driven behavior then vote with your keyboard and become part of an active open source project. For non-profits like the Miracle Foundation, voting is even easier – you just need a credit card to join in their Mothers’ Day campaign. Your mom may not understand anything you add to open source, but she can understand when you help orphans.

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As OpenStack enters rapids with Grizzly, watch for strong currents, hidden rocks & eddies.

White Water

Play Boating From Wikipedia

I enjoy kayaking white water rapids – they are exhilarating and demanding. The water accelerates around obstacles and shows its power. You cannot simply ride the current; you must navigate your way around obstacles, stay clear of eddies that pull you back and watch for hidden rocks. The secret to success is to read the current and make small adjustments as you are carried along – resistance is futile.

After the summit, I see the OpenStack with the Grizzly release like water entering the rapids. The quality and capability of the code base continues to improve while the number of players with offerings in the ecosystem is also increasing rapidly. Until now, there was plenty of room to play together; however, as scope, activity and velocity increase there will more inter-vendor interactions.

As a member of the OpenStack board, I have tremendous enthusiasm for what the OpenStack community has accomplished. There have been some really positive accounts of the summit including CSC “OpenStack gains maturity…“, Silicon Angle “OpenStack has reached a Flash Point”, Randy Bias’ “OpenStack is THE Stack”, Wayne Walls “Hallway Track” and much more on the Planet OpenStack aggregator.

In fact, we’ve created such a love fest for OpenStack that I fear we are drinking our own kool aide.

I have a responsibility to be transparent and honest about challenges facing the us because it’s the Foundation’s job to guide us forward. My positions result from many conversations that I had throughout the week of the Summit. They are also the result of my first hand experiences along with my 14 years of cloud experience.

Over the next posts, I’ll explore a number of these topics with the goal of helping navigate a path through the potential turbulence. The simple fact is the OpenStack is growing quickly and that creates challenges:

  1. A growing number of new developers are joining. Since our work surface area is expanding, it’s both easier than ever to participate and harder to navigate where to begin. We need to get ahead of the design cycles.
  2. A growing number of non-devs are participating and bringing important contributions and experience. We must include them in the OpenStack meritocracy because they speak for the quality and usability of the project.
  3. A growing number of companies (many “name brands”) who are still trying to figure out how to participate and collaborate in open source projects. Lack of experience increases the risk of divergence (forking) and market confusion.
  4. A growing number of products based on OpenStack also increases forking risk as OpenStack contributors feel compelled to differentiate.
  5. A growing number of core components (compute+block+network+…) that are required to have base functionality.
  6. A growing number of incubated projects that continue to stress innovation and pace of change that challenges the very question of “what is OpenStack?”
  7. A growing number of deployed sites offering OpenStack clouds but the community lacks a way to verify (or really discuss) compatibility between the sites.

This list is a cause for celebration not a cause for alarm – every item is a challenges based on our success. The community and Foundation are already working to address the risks.

While some of us enjoy the chaos and excitement of rapids, other can take comfort from the fact that they are always followed by calm waters. Don’t worry – we’ll navigate through this together.

The Atlantic magazine explains why Lean process rocks (and saves companies $$)

GearsI’m certain that the Atlantic‘s Charles Fishman was not thinking software and DevOps when he wrote the excellent article about “The Insourcing Boom.”  However, I strongly recommend reading this report for anyone who is interested in a practical example of the inefficiencies of software lean process (If you are impatient, jump to page 2 and search for toaster).

It’s important to realize that this article is not about software! It’s an article about industrial manufacturing and the impact that lean process has when you are making stuff.  It’s about how US companies are using Lean to make domestic plants more profitable than Asian ones.  It turns out that how you make something really matters – you can’t really optimize the system if you treat major parts like a black box.

When I talk about Agile and Lean, I am talking about proven processes being applied broadly to companies that want to make profit selling stuff. That’s what this article is about

If you are making software then you are making stuff! Your install and deploy process is your assembly line. Your unreleased code is your inventory.

This article does a good job explaining the benefits of being close to your manufacturing (DevOps) and being flexible in deployment (Agile) and being connected to customers (Lean).  The software industry often acts like it’s inventing everything from scratch. When it comes to manufacturing processes, we can learn a lot from industry.

Unlike software, industry has real costs for scrap and lost inventory. Instead of thinking “old school” perhaps we should be thinking of it as the school of hard knocks.

Bad Premise: Cloud Outages are *not* driving IT back to premises

trapped

I wrote this responding to Lauren Carlson‘s (Software Advice) Blog Post.  Lauren – I’d be more likely to agree with the statement that “SLAs are dead”  Here’s why…

<soapbox>

Recent industry buzz about cloud service level agreements (SLAs) and reliability miss the core point about cloud.  Cloud is about agility, business models, consumerization of software and merciless pursuit of efficiency.

The fact that Amazon EC2 built its base without an “enterprise” SLA is exhibit #1 that the IT world changed and it’s not going back.

Here are my reasons why IT pandoras can’t get cloud back into the box.

#1. Cloud has vastly superior network connectivity

The concept of your users accessing your applications from inside your firewall is so 2005.  Today’s reality is that significant amounts of network access is externally routed means that applications need to live where they have excellent bandwidth to their users and to other applications.

#2. Cloud has elastic consumption of resources

Cloud is not less expensive infrastructure, it is mainly more flexible.  If you’re worried about an outage, then cloud is exactly the investment for you because you position a backup site at another location without having to pay for online resources.  It’s much harder to take down a site that invests the time to design a system that dynamically reallocates load between sites.

#3. Cloud drives more robust architecture

The fact that cloud delivery is more opaque and modular without a five 9s SLA has driven a cloud application architecture revolution (see CAP).  We have shifted the app paradigm from robust scale up hardware to robust scale out software.  Also significant, DevOps innovations have made deployments repeatable and adaptable.

The only “logical” argument for pulling applications back from the cloud is to assert control over more of the delivery chain for your application.  It the same reason that we think that driving is safer than flying – we’re the ones sitting behind the wheel when we drive.  News flash - driving is NOT safer than flying.

Cloud applications are not about hardware infrastructure, they are about SOFTWARE.  Perhaps one of the greatest disservices foisted on the market was saying cloud is synonymous with “Infrastructure as a Service” and “Virtualization.”  Cloud applications are powerful because we created ways that circumvent the limitations of IaaS and VMs!

</soapbox>

Notes from 2011 Cloud Connect Event Day 2 (#ccevent)

With the OpenStack launch behind me, I have some time to attend the Cloud Connect Event.  I missed all the DevOps sessions, but was getting to geek out on the NoSQL & Big Data sessions.   I jumped to the private cloud track (based on Twitter traffic) and was rewarded for the shift.

I’m surprised at how much focus this cloud conference is dedicated to private cloud.  At other cloud conferences I’ve attended, the focus has been on learning how to use the cloud (specifically the public cloud).  This is the first cloud show I’ve attended that has so much emphasis, dialog and vendor feeding around private.  This was a suits & slacks show with few jeans, t-shirts, and pony tails.  Perhaps private cloud is where the $$$ is being spent now?

It definitely feels like using cloud has become assumed, but the best practices and tools are just emerging.

The twitter #ccevent stream is interesting but temporal.  I’m posting my raw (spelling optional) notes (below the more tag) because there is a lot of great content from the show to support and extend the twitter stream.  I’ll try to italicize some of the better lines.

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Why cloud compute will be free

Today at Dell, I was presenting to our storage teams about cloud storage (aka the “storage banana”) and Dave “Data Gravity” McCrory reminded me that I had not yet posted my epiphany explaining “why cloud compute will be free.”  This realization derives from other topics that he and I have blogged but not stated so simply.

Overlooking that fact that compute is already free at Google and Amazon, you must understand that it’s a cloud eat cloud world out there where losing a customer places your cloud in jeopardy.  Speaking of Jeopardy…

Answer: Something sought by cloud hosts to make profits (and further the agenda of our AI overlords).

Question: What is lock-in?

Hopefully, it’s already obvious to you that clouds are all about data.  Cloud data takes three primary forms:

  1. Data in transformation (compute)
  2. Data in motion (network)
  3. Data at rest (storage)

These three forms combine to create cloud architecture applications (service oriented, externalized state).

The challenge is to find a compelling charge model that both:

  1. Makes it hard to leave your cloud AND
  2. Encourages customers to use your resources effectively (see #1 in Azure Top 20 post)

While compute demands are relatively elastic, storage demand is very consistent, predictable and constantly grows.  Data is easily measured and difficult to move.  In this way, data represents the perfect anchor for cloud customers (model rule #1).  A host with a growing data consumption foot print will have a long-term predictable revenue base.

However, storage consumption along does not encourage model rule #2.  Since storage is the foundation for the cloud, hosts can fairly judge resource use by measuring data egress, ingress and sidegress (attrib @mccrory 2/20/11).  This means tracking not only data in and out of the cloud, but also data transacted between the providers own cloud services.  For example, Azure changes for both data at rest ($0.15/GB/mo) and data in motion ($0.01/10K).

Consequently, the financially healthiest providers are the ones with most customer data.

If hosting success is all about building a larger, persistent storage footprint then service providers will give away services that drive data at rest and/or in motion.  Giving away compute means eliminating the barrier for customers to set up web sites, develop applications, and build their business.  As these accounts grow, they will deposit data in the cloud’s data bank and ultimately deposit dollars in their piggy bank.

However, there is a no-free-lunch caveat:  free compute will not have a meaningful service level agreement (SLA).  The host will continue to charge for customers who need their applications to operate consistently.  I expect that we’ll see free compute (or “spare compute” from the cloud providers perspective) highly used for early life-cycle (development, test, proof-of-concept) and background analytic applications.

The market is starting to wake up to the idea that cloud is not about IaaS – it’s about who has the data and the networks.

Oh, dem golden spindles!  Oh, dem golden spindles!

32nd rule to measure complexity + 6 hyperscale network design rules

If you’ve studied computer science then you know there are algorithms that calculate “complexity.” Unfortunately, these have little practical use for data center operators.  My complexity rule does not require a PhD:

The 32nd rule: If it takes more than 30 seconds to pick out what would be impacted by a device failure then your design is too complex.

6 Hyperscale Network Design Rules

  1. Cost Matters
  2. Keep Networks Flat
  3. Filter at the Edge
  4. Design Fault Zones
  5. Plan for Local Traffic
  6. Offer load balancers (to your users)

Sorry for the teaser… I’ll be able to release more substance behind this list soon.   Until then comments are (as always) welcome!

 

 

 

Jevon’s Paradox

I’ve been finding it necessary to quote Jevon’s paradox several times lately and realized that I have NOT referenced it here.  Quite simply, understanding Jevon’s paradox is essential to understanding cloud.

The concept of the paradox is that when we make something more efficient (for example gas in cars), the demand for that resource goes up (we move further into the exurbs because driving is cheaper).  Notably, as Moore’s law drives computer efficiency up, we are using more and more computers.  Specifically, I have more computers in my house every year even though the efficiency of just one smart phone far (far) exceeds power of my son’s Sinclair 1000.

In cloud computing, Jevon’s paradox points us to the expectation that the rush of applications and activity in the cloud will continue to accelerate.  Since I expect competition and Moore’s law to drive increasing gains in cloud efficiency (and therefore customer advantageous price signals) the market will happily convert these utilization improvements into more and more interesting capabilities.

The cloud expansion means that we can sustain more providers entering the market.  In fact, Jevon would tell us that more providers will likely INCREASE demand for cloud as competition and capacity put downward pressure on prices.  [Q: where will they make up the margin?   A: Adjacent Services]

The loser in cloud’s exploration of Jevon’s paradox are non-cloud deployments (Dell strategists are you listening?).  These systems suffer because their ability to improve their efficiency is limited.

As I look down the road on cloud, I can see many opportunities for current applications to take advantage of cheaper cloud resources to provide even more value.  For example, adding map-reduce analytics to scan a customer’s data can provide tremendous insights.  Today, it’s a luxury like flying on the Concorde.  Tomorrow, it will be part like hopping the Nerd Bird from San Jose to Austin – just a normal part of our daily lives.

 

Note: A shout out to Dave McCrory who introduced me to Jevon’s Paradox.

Cloud Culture Clash Creates Opportunities

In my opinion, one of the biggest challenges facing companies like Dell, my employer, is how to help package and deliver this thing called cloud into the market.  I recently had the opportunity to watch and listen to customers try to digest the concept of PaaS.

While not surprising, the technology professionals in the room split into across four major cultural camps: enterprise vs. start-up and dev vs. ops.  Because I have a passing infatuation with pastel cloud shaped quadrant graphs, I was able to analyze the camps for some interesting insights.

The camps are:

  1. Imperialists:  These enterprise type developers are responsible for adapting their existing business to meet the market.  They prefer process oriented tools like Microsoft .Net and Java that have proven scale and supportability.
  2. MacGyvers: These startup type developers are under the gun to create marketable solutions before their cash runs out.  They prefer tools that adapt quick, minimize development time and community extensions.
  3. Crown Jewels: These enterprise type IT workers have to keep the email and critical systems humming.  When they screw up everyone notices.  They prefer systems where they can maintain control, visibility, or (better) both.
  4. Legos: These start-up type operations jugglers are required to be nimble and responsive with shoestring budgets.   They prefer systems that they can change and adapt quickly.  They welcome automation as long as they can maintain control, visibility, or (better) both.

This graph is deceiving because it underplays the psychological break caused by willingness to take risks.  This break creates a cloud culture chasm. 

On one side, the reliable Imperialists want will mount a Royal Navy flotilla to protect the Crown Jewels in a massive show of strength.  They are concerned about the security and reliability of cloud technologies.

On the other side, the MacGyvers are working against a ticking time bomb to build a stealth helicopter from Legos they recovered from Happy Meals™.  They are concerned about getting out of their current jam to compile another day.

Normally Imperialists simply ignore the MacGyvers or run down the slow ones like yesterday’s flotsam.  The cloud is changing that dynamic because it’s proving to be a dramatic force multiplier in several ways:

  1. Lower cost of entry – the latest cloud options (e.g. GAE) do not charge anything unless you generate traffic.  The only barrier to entry is an idea and time.
  2. Rapid scale – companies can fund growth incrementally based on success while also being able to grow dramatically with minimal advanced planning.
  3. Faster pace of innovation – new platforms, architectures and community development has accelerated development.  Shared infrastructure means less work on back office and more time on revenue focused innovation.
  4. Easier access to customers – social media and piggy backing on huge SaaS companies like Facebook, Google or SalesForce bring customers to new companies’ front doors.  This means less work on marketing and sales and more time on revenue focused innovation.

The bottom line is that the cloud is allowing the MacGyvers to be faster, stronger, and more innovative than ever before.  And we can expect them to be spending even less time polishing the brass in the back office because current SaaS companies are working hard to help make them faster and more innovative.

For example, Facebook is highly incented for 3rd party applications to be innovative and popular not only because they get a part of the take, but because it increases the market strength of their own SaaS application.

So the opportunity for Imperialists is to find a way for employee and empower the MacGyvers.  This is not just a matter of buying a box of Legos: the strategy requires tolerating enabling embracing a culture of revenue focused innovation that eliminates process drag.  My vision does not suggest a full replacement because the Imperialists are process specialists.  The goal is to incubate and encapsulate cloud technologies and cultures.

So our challenge is more than picking up cloud technologies, it’s understanding the cloud communities and cultures that we are enabling.

Cloud Gravity & Shards

This post is the final post laying out a rethinking of how we view user and buyer motivations for public and private clouds.

In part 1, I laid out the “magic cube” that showed a more discrete technological breakdown of cloud deployments (see that for the MSH, MDH, MDO, UDO key).  In part 2, I piled higher and deeper business vectors onto the cube showing that the cost value of the vertices was not linear.  The costs were so unequal that they pulled our nice isometric cube into a cone.

The Cloud Gravity Well

To help make sense of cloud gravity, I’m adding a qualitative measure of friction.

Friction represents the cloud consumer’s willingness to adopt the requirements of our cloud vertices.  I commonly hear people say they are not willing to put sensitive data “in the cloud” or they are worried about a “lack of security.”  These practical concerns create significant friction against cloud adoption; meanwhile, being able to just “throw up” servers (yuck!) and avoiding IT restrictions make it easy (low friction) to use clouds.

Historically, it was easy to plot friction vs. cost.  There was a nice linear trend where providers simply lowered cost to overcome friction.  This has been fueling the current cloud boom.

The magic cube analysis shows another dynamic emerging because of competing drivers from management and isolation.  The dramatic saving from outsource management are inhibited by the high friction for giving up data protection, isolation, control, and performance minimums.  I believe that my figure, while pretty, dramatically understates the friction gap between dedicated and shared hosting.  This tension creates a non-linear trend in which substantial customer traction will follow the more expensive offerings.  In fact, it may be impossible to overcome this friction with pricing pressure.

I believe this analysis shows that there’s a significant market opportunity for clouds that have dedicated resources yet are still managed and hosted by a trusted 3rd party.  On the other hand, this gravity well could turn out to be a black hole money pit.  Like all cloud revolutions, the timid need not apply.

Post Script: Like any marketing trend, there must be a name.  These clouds are not “private” in the conventional sense and I cringe at using “hybrid” for anything anymore.  If current public clouds are like hotels (or hostels) then these clouds are more like condos or managed community McMansions.  I think calling them “cloud shards” is very crisp, but my marketing crystal ball says “try again.”  Suggestions?