Tarkan Maner Joins Cloudscaling Board of Directors

Posted on by Randy Bias

Today I am extremely pleased to welcome Tarkan Maner, CEO of Nexenta and previously CEO of Wyse technologies, to Cloudscaling’s board of directors. The full press release can be found here.

I met Tarkan during our search for a new CEO and found him to be a passionate entrepreneur with a strong desire to help Cloudscaling succeed. Tarkan and I share similar characteristics. We are both super high energy personalities. We are both intensely keen on cloud. However, we also come from two different worlds: sales/ marketing vs. technology. And that contrast makes all all the difference.

One thing I pride myself on is finding new members of the team who fill in existing capability gaps. Or those who bring completely new capabilities and skills to the table. Here, I think Tarkan’s track record speaks for itself. He has built and led high growth businesses, like Wyse, into the cloud future. I am very much looking forward to learning from Tarkan’s experience and wisdom and his desire to join our board, with so many others courting him is a massive vote of confidence in myself, my co-founder Adam Waters, our business, and the rest of the Cloudscaling team.

Great to have you onboard, Tarkan!

Best,

—Randy

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The 6 Requirements of Enterprise-grade OpenStack, Part 3

Posted on by Randy Bias

In part 1 and part 2 of this series I introduced the core ideas around defining the requirements and then discussed the first four.  Today we’ll discuss the final two requirements and tie it all together.

Onwards and upwards!

Requirement #5 – Scalable, Elastic, and Performant

Enterprise-grade has to mean something. In the past, enterprise-grade related to a certain quality of a system that made it highly reliable, scalable, and performant. More and more, enterprise-grade is beginning to mean “cloud-grade” or “web scale.” What I mean by that is that as the move to next generation applications happens and enterprises adopt a new IT model, we will see major changes in the requirements for delivering a high quality system.

The example I love to use is Hadoop. Hadoop comes with a reference architecture that says: use commodity servers, commodity disk drives, and NO RAID. When is the last time you saw an enterprise infrastructure solution with no data protection at the hardware layer? Of course, it doesn’t make sense to run Hadoop on high end blades attached to a fiber channel SAN, although I have seen it. Even Microsoft Exchange has begun recommending a move towards JBODs from RAID and depending on the application software layer to route around failure.

Let’s talk about these three requirements for enterprise-grade OpenStack.

Scalability & Performance

Scalability is the property of a system to continue to work as it increases in size and workload demands. Performance is the measurement of the throughput of an individual resource of the system rather than the system itself. Perhaps Werner Vogels, CTO of Amazon, said it best:

A service is said to be scalable if when we increase the resources in a system, it results in increased performance in a manner proportional to resources added.

In many ways, OpenStack itself is a highly scalable system. It was designed around a loosely-coupled, message passing architecture — something tried and true for mid to large scale, while also able to scale down to much smaller size deployments. The problem, unfortunately, lies in what design decisions you made when configuring and deploying OpenStack. Some of its default configurations and many of the vendor plugins and solutions have not been designed with scale in mind.[1] When you read the previous installment, you understood that having a reference architecture is critical to delivering hybrid cloud. Make certain you pick an enterprise-grade product with a reference architecture that cares about scale and performance while using well-vetted components and configuration choices.

A complete examination of the scale and performance issues that might arise with OpenStack is beyond the scope of this series; however, let’s tackle the number one issue that most people run into: network performance and scalability.

OpenStack Default Networking is a Bust

OpenStack Compute (Nova) has three built-in default networking models: flat, single_host, and multi_host. All three of these networking models are completely unacceptable for most enterprises. In addition to these default networking models, you have the option of deploying OpenStack Networking (Neutron), which has a highly pluggable architecture that supports a number of different vendor plugins both to manage physical devices and also network virtualization systems (so called Software-defined Networking or SDN).

A very brief explanation of the default networking models shortcomings is in order. I will keep it very simple, but am happy to follow up later with more details. The flat and multi_host networking model requires a single shared VLAN for all elastic (floating) IP addresses. This requires running spanning tree protocol (STP) across your switch fabric, a notoriously dangerous approach if you want high network uptime. I’ve asked the question at multiple conferences to a full room: “How many of you think STP is evil?” and have had nearly everyone in the room raise their hand.

Perhaps more importantly, both flat and multi_host networking models require you to route your public IP addresses from your network edge down to the hypervisor nodes. This is really not an acceptable approach in any modern enterprise. Here’s a diagram showing multi_host mode:

OpenStack multi_host mode

It’s probably also worth noting that if you want multi_host mode, you need to be able to load code on your hypervisor. That means if you like ESX or Hyper-V you are probably out of luck.

By contrast, single_host mode suffers from the singular sin of trying to make a single x86 server the core networking hub through which all traffic between VLANs and the Internet runs.[2] Basically, take your high performance switch fabric and throw it in the trash because your maximum bandwidth is whatever a Linux server can push. Again, this is not an acceptable or even credible approach to networking. To be fair though, OpenStack competitors also took a similar approach to this. Here’s a diagram on single_host mode:

OpenStack single_host mode

All of these approaches have fundamental scalability and performance issues. Which brings us to OpenStack Neutron.

Depending on OpenStack Neutron NOT for the Faint of Heart

As of September 2013, it seems like Neutron still had significant issues as seen in this critical posting from Scott Devoid of Argonne National Labs (ANL) to the OpenStack operators mailing list. As of this writing, OpenStack Neutron supports single_host and flat modes, but not multi_host. Apparently, we may see a replacement for multi_host in the Juno timeframe, although this capability has been missing for a while now.

That being said, Neutron has made a lot of progress and to be honest, many of the issues folks have reported are more likely to stem from poorly written and adapted plugins. What this means is that in order to deliver success with OpenStack Neutron you need a version of Neutron plus accompanying plugins that have been designed for scale and performance.[3] Plus, your cloud operating system vendor should have some proven deployments at scale and have really beaten the crap out of the networking using exhaustive testing frameworks.

I could say much more about the performance and scalability of an enterprise-grade, OpenStack-powered product; however, it should give you a starting point in pinning down your vendors to make sure they have addressed these and related issues.

Most important: regardless of your OpenStack vendor they must be able to provide a detailed, multi-rack reference network architecture.

Without a reference network architecture, your ability to scale past a single rack is purely based on hand-waving and assurances from your vendor that may or may not have any validity.

Elasticity

Infrastructure can’t ever be truly elastic, but its properties can enable elastic applications running on top of it. An elastic cloud is one that has been designed such that individual cost of resources such as VMs, block storage, and objects is as inexpensive as possible. This is directly related to Jevon’s Paradox, which states that as a technology progresses, the increase in efficiency leads towards an increase in the rate of consumption of that technology:

Jevon's Paradox

Simply put, as the relative cost of components in the system reduces, applications can not only consume more, which enables routing around failures, but also consume more for the purposes of scaling application needs up and down based on demand. In essence, you can make the pool larger and buy more capacity if the individual components and resources are as cheap as possible.

Major elastic public clouds like Google, Amazon, and Microsoft are providing these kinds of properties, and it’s what you need to provide inside your four walls to enable hybridization.

Enterprise-grade OpenStack will help lead you into the future by providing scalability and performance while supporting elastic applications. Beware the OpenStack-powered cloud operating system that wants you to use a fiber channel SAN and blade servers. Those days have passed, as we can see with Hadoop.

Requirement #6 – Cloud Support, Training & Services Model for Global Enablement

Chances are you are a global organization and are planning to deliver 24x7x365 next generation, cloud native applications on top of your private, public, and hybrid clouds. You want partners who can support you globally, who have international experience, and most of all who are comfortable with supporting 24x7x365 environments.

Train Your IT Administrators to be the New Cloud Administrators

IT administrators are in the process of transitioning into cloud administrators. This evolution will be a deep and lasting change inside the enterprise. Entirely new sets of skills need to be developed and other skills refreshed and realigned to the new cloud era. When evaluating your enterprise-grade OpenStack partner, you should be looking for one with significant capabilities in training, both on generic OpenStack and on their specific cloud operating system product. Most importantly, when evaluating a partner who can help you upgrade your team’s cloud skills, make certain they aren’t just going to show you how to develop on OpenStack or install OpenStack.

What you really need is operator-centric training that focuses on:

  • Typical OpenStack architectures and specific product architectures
  • Pros and cons of various architecture and plugin/driver choices
  • Scalability, interoperability and performance issues and options
  • Troubleshooting common “full stack” problems
  • Introduction to how your developers will use your cloud
  • Understanding the cloud-native application model

Cloud Support Model

No matter how good your IT team is, you will need a trusted support team to back you up — a team that can support your entire system end-to-end. Make certain you ask your Enterprise-grade OpenStack-powered cloud operating system vendor if their support team has supported high transaction 24×7 environments before. Be certain that they have so-called “full stack” support capabilities. Can they troubleshoot the Linux kernel, your hypervisor of choice, networking architecture and performance issues, and do they understand storage at a deep level? Clouds are integrated systems and compute, storage, and networking all touch each other in fundamental ways. Your vendor needs to know a lot more than how to configure or develop for OpenStack. They need to be cloud experts at all levels of the stack. Demand it.

Global Service Delivery

Delivering a cloud internationally is no small feat, whether large or small.[4] It requires more than just reach. It requires cultural sensitivity and the ability to understand the unique requirements that arise in particular geographies. For example, did you know that while most data centers are more concerned over power than space, in Japan it’s still usually just the opposite. Space winds up being one of the single largest premiums. This space requirement is unique to their particular environment.

Your cloud operating system vendor should have a track record of successful international delivery and a partner network that can assist in a particular location.

Conclusion

OpenStack is an amazing, scalable foundation for building a next generation elastic cloud, but it’s not perfect.  None of the open source solutions it competes with are perfect either.  Instead, each of these tools is really a cloud operating system “kernel” that can be used to deliver a more complete, vetted, Enterprise-grade cloud operating system (cloudOS).  You will need an experienced enterprise vendor to deliver your cloudOS of choice and whether it’s OpenStack or another similar project I hope you will keep these requirements in mind.

I hope you enjoyed this whirlwind tour through the 6 Requirements of Enterprise-grade OpenStack. As a reminder, we covered these SIX requirements:

  1. 99.999% Uptime APIs & Scalable Control Plane
  2. Robust Management & Security Models
  3. Open Architecture
  4. Hybrid Cloud Interoperability
  5. Scalable & Elastic Architecture
  6. Global Support & Services

As you are out there evaluating the right vendor to help with your OpenStack adoption process and the move towards hybrid cloud, make certain you find out how much, if any of these requirements they can meet.

For some related white papers, check out:


[1] It’s also fair to say that some times people are using the messaging systems in an inappropriate manner.  Some times, plain old UDP is still best for fire and forget high throughput systems, like logs.

[2] Before you cry foul, others such as Eucalyptus also went down this unfortunate path.  I believe Eucalyptus 4.0 finally fixes this.  It’s a common mistake for people without networking experience to go down this path.

[3] So far the only one we have tested extensively is OpenContrail, which shows great promise, but we have to get running in some larger deployments before we declare victory.

[4] We know.  Building the KT uCloud in 2010 and 2011 was a huge task for an early stage startup.

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The 6 Requirements of Enterprise-grade OpenStack, Part 2

Posted on by Randy Bias

In part 1 of this series earlier this week, I introduced The 6 Requirements of Enterprise-grade OpenStack.  Today, I’m going to dig into the next two major requirements: Open Architectures and Hybrid Cloud Interoperability.

Let’s get started.

Requirement #3 – Open Architectures & Reducing Vendor Lock-in

We already covered building a robust control plane and cloud management system. One of the attractions of OpenStack is removing vendor lock-in by moving to an open source platform. This is a key value proposition and deserves a complete dialog about what is realistic and what is not in an Enterprise-grade version of OpenStack.

“No Vendor Lock-in” is Snake Oil Salesmanship

Are you being promised that OpenStack provides “no lock-in?” No vendor lock-in is a platonic ideal – something that can be imagined as a perfect form, but never achieved. Any system always has some form of lock-in. For example, many of you probably use RedHat Enterprise Linux (RHEL), a completely 100% open source Linux operating system, as your default Linux within your business. Yet, RHEL is a form of lock-in. RHEL is a specific version of Linux designed for a specific goal. You are locked into their particular reference architecture, packaging systems, installers/bootloaders, etc., even though it is open source.

In fact, with many customers I have seen less of a fear about lock-in and more of a concern about “more lock-in.” For example, one customer, who will remain anonymous, was concerned about adopting our block storage component, even though it was 100% open source due to lock-in concerns. When probed, it became clear that what the customer wanted was to use their existing storage vendors (NetApp and Hitachi Data Systems) and did not want to have to train up their IT teams on a completely new storage offering. Here the lock-in concerns were predominantly about absorbing more lock-in rather than removing it entirely.

What is most important is assessing the risks your business can take. Moving to OpenStack, as with Linux before it, means that you are mitigating certain risks in terms of training your IT teams on the new stack and hedging your bets by being able to get multiple vendors in-house to support your open source software.

In other words, OpenStack can certainly reduce lock-in, but it won’t remove it. So, demand an open architecture, but expect an enterprise product.

Lock-in Happens, Particularly with Enterprise Products

I wish it didn’t, but lock-in does happen, as you can see from above. That means that rather than planning for no lock-in, start planning for what lock-in you are comfortable with. An Enterprise-grade version of OpenStack will provide a variety of options via an open architecture so you can hedge your bets. However, a true cloud operating system and enterprise product cannot ever provide an infinite variety of options. Why not? Because then the support model is not sustainable and that vendor goes out of business.  Not even the largest vendors can provide all options to all people.

If you want to build your own customized cloud operating system[1] built around OpenStack, go ahead, but that isn’t a product. That’s a customized professional services path.  Like those who rolled their own Linux distributions for a while, it leads to a path of chaos and kingdom-building that is bad for your business. Doing it yourself is also resource intensive. You’ll need 20-30 Python developers with a deep knowledge of infrastructure (compute, storage, and network) who can hack full time on your bastardized version of OpenStack.  A team that looks something like this:

Cloud OS Development Team Requirements

So, ultimately, you’re going to have to pick a vendor to bet on if you want enterprise-grade OpenStack-powered cloud solutions.

Requirement #4 – Hybrid Cloud Interoperability

Hybrid is the new cloud. Most customers we talk to acknowledge the reality of needing to provide their developers with the best tool for the job. Needs vary, requirements vary, concerns vary, compliance varies. Every enterprise is a bit unique. Some need to start on public cloud, but then move to private cloud over time. Some need to start on private, but slowly adopt public. Some start on both simultaneously.  RightScale’s recent State of the Cloud 2014 report has some great survey data backing this up:

RightScale-State-of-the-Cloud-2014-hybrid-cloud-strategy

Let’s talk about why your enterprise-grade OpenStack-powered cloud operating system vendor had better have a great hybrid cloud story.

A Hybrid-first Cloud Strategy

Every enterprise needs a hybrid-first cloud strategy. Meaning, hybrid cloud should be your first and primary requirement. Then, plan around hybrid with a single unified governance model that delivers the best of both world’s for your constituencies. Finally, plan on a process where you will triage your apps/needs and determine which cloud is right for the job.  The following diagram highlights this process, but your mileage may vary as criteria are different from business to business:

Triaging and Mapping Apps to the Right Cloud

Understanding Cloud Interoperability & It’s Role In Hybrid Cloud

I have been through quite a number of interoperability efforts, the most painful of which was IPSEC for VPNs. Interoperability between vendors is not free, usually takes a fairly serious effort, and ultimately is worth the pain. Unfortunately, interoperability is deeply misunderstood, particularly as it applies to public/private/hybrid cloud.

The challenge in hybrid cloud is about addressing the issues of application portability. If you want a combination of public and private clouds (hybrid) where an application can be deployed on either cloud, moved between the clouds, or cloudbursted from one cloud to another, then application portability is required. When you pick up and move an app and it’s cloud native automation framework[2] from one cloud to another, a number of key things need to remain the same:

  • Performance must be at relative parity
  • Underlying network, storage, and compute architectures must be the same or similar
  • Your automation framework must support API compatibility with both clouds
  • The TCO of running the app must be within ½-2x of each other
  • There must be behavioral compatibility, meaning non-API “features” are matched
  • You must support API compatibility with the relevant public clouds

Here is a slide I used in a recent webinar to help explain these requirements.

Hybrid Cloud Interoperability Requirements

Of course, you must also have been thoughtful when designing your application and avoided any lock-in features of a particular cloud system, such as a reliance on DynamoDB on AWS, HA/DRS on VMware, iRules on F5 load balancers, etc.

If you don’t meet these requirements, interoperability is not possible and application portability attempts will fail. The application performance will be dramatically different and one cloud will be favored; there will be missing features that cause the app to not function on one cloud or another; and your automation framework may fail if behavioral compatibility doesn’t exist. For example, perhaps it has timers in it that assume a VM comes up in 30 minutes, but on one of your clouds it takes 1-2 hours (I’ve seen this happen).

All of these issues must be addressed in order to achieve hybrid cloud interoperability.

OpenStack Needs a Reference Architecture

The Linux kernel needs a reference architecture. In fact, each major distribution of Linux in essence creates it’s own reference architecture and now we have distinct flavors of Linux OS. For example, there are the RedHat/Fedora/CentOS flavors and the Debian/Ubuntu flavors. These complete x86 operating systems have fully-baked reference architectures and anyone moving within one of the groups will find it relatively trivial to move between them. Whereas a RedHat admin moving to Debian may initially be lost until they come up to speed on the differences. OpenStack is no different.

OpenStack, and in fact most of its open source brethren, has no reference architecture. OpenStack is really the kernel for a cloud operating system. This is actually its strength and weakness. The same holds for Linux. You can get Cray Linux for a supercomputer and you can get Android for an embedded ARM device. Both are Linux, yet both have radically different architectures, making application portability impossible. OpenStack is similar, in that to date most OpenStack clouds are not interoperable, because each has its own reference architecture. Every cloud with its own reference architecture is doomed to be an OpenSnowFlake.

Enterprise-grade cloud operating systems powered by OpenStack must have commonly held reference architectures. That way you can be assured that every deployment is interoperable with every other deployment. These reference architectures have yet to arise. However, given that there is already a single reference architecture in Amazon Web Services (AWS) and Google Cloud Platform (GCP), (we call it “elastic cloud reference architecture”) and given that these two companies will be major forces in public cloud, it’s hard to see how OpenStack can avoid supporting at least one reference architecture that looks like the AWS/GCP model.

To be clear, however, there may be a number of winning reference architectures. I see emerging flavors in high performance computing (HPC) and possibly other verticals like oil & gas.

Enterprise-grade Reference Architecture

Ultimately, you have to place your own bet on where you think OpenStack lands, but existing data says that out of the top 10 public clouds, only a couple are based on OpenStack[3]:

RightScale State of the Cloud 2014 on Top Public Clouds Used by Businesses

If enterprises desire agility, flexibility, and choice, it seems obvious that OpenStack needs to support an enterprise-grade reference architecture that is focused on building hybrid clouds with the ultimate winners in public cloud. It’s just my opinion, but right now that looks like Amazon, Google, and Microsoft.

Enterprise-grade OpenStack means an enterprise-grade reference architecture that enables hybrid cloud interoperability and application portability.

Part 2 Summary

An open architecture designed for hybrid cloud interoperability is a foregone conclusion at this point.  Mostly what folks argue about is how that will be achieved, but for those of us who are pragmatists, it’s certain that public cloud will have a wide variety of winners and that the top 10 public clouds is already dominated by non-OpenStack contenders.  So plan accordingly.

Most importantly, remember to ask for an open architecture, while expecting an enterprise product.

In the next installment we’ll tackle what it means to deliver a performant, scalable, and elastic infrastructure designed for next gen apps.

Next Installment:

UPDATE: Added a clarifying footnote due to some Twitter feedback that seemed unclear on what a “cloud operating system” was and it’s relationship to OpenStack and similar open source projects.


[1] No, Eucalyptus, OpenNebula, CloudStack, <insert your cloud software du jour>, are NOT complete cloud operating systems.  They are all roughly at parity with OpenStack, although certainly you could argue that one is above or below the others.  Why aren’t they complete?  That’s a whole other blog posting series, but suffice it to say that when is the last time you saw an operating system that couldn’t install itself on bare metal?  Or didn’t provide system metrics and logging capabilities?  Or was missing key components (e.g. databases).  A cloud operating system is a non-trivial task and most of these tools have simply handled the easy part of a cloud: placing a VM on a hypervisor (big whoop).

[2] By definition any cloud native next gen app manages itself via an automation framework. It might be a low level approach like Chef, Puppet, SaltStack; it might be a higher order abstraction like Scalr, RightScale, Dell Cloud Manager; it might even be a PaaS framework, but it’s *something*. Or it’s not a cloud-native app.

[3] Be sure to read the caveats on the VMware vCHS data in the actual report itself.

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The 6 Requirements of Enterprise-grade OpenStack, Part 1

Posted on by Randy Bias

Introduction

OpenStack is an amazing foundation for building an enterprise-grade private cloud. The great OpenStack promise is to be the cloud operating system kernel of a new generation. Unfortunately, OpenStack is not a complete cloud operating system, and while it might become one over time, it’s probably best to look at OpenStack as a kernel, not an OS. [1]

In order to become widely adopted by the enterprise, OpenStack must ultimately be delivered via robust, enterprise-grade products that close the gap on the key areas where OpenStack has challenges. These products are delivered today by businesses that can provide support, ease-of-installation, tools for day-to-day management, and all of the other pieces necessary for achieving acceptance. Without these vendors who have a stake in enterprise adoption, OpenStack can never be widely adopted. OpenStack isn’t MySQL. It’s the Linux kernel, and like the Linux kernel, you need a complete operating system to create success.

So what’s required? There are 6 key elements:

  1. 99.999% Uptime APIs & Scalable Control Plane
  2. Robust Management & Security Models
  3. Open Architecture
  4. Hybrid Cloud Interoperability
  5. Scalable & Elastic Architecture
  6. Global Support & Services

6 Requirements for Enterprise-grade OpenStack Supporting Material.002

If your business requires an enterprise-ready OpenStack solution, read on to learn more about what a true enterprise-grade OpenStack-powered private cloud can – and should – offer. Over the next two weeks, I’m going to do a multi-part blog series entitled “6 Requirements of Enterprise-grade OpenStack” – where I will detail these six requirements.

To get started, lets look at OpenStack’s place in the enterprise.

OpenStack in the Enterprise Data Center

Agility is the new watchword for cloud and DevOps is seen as the path to realizing agility. OpenStack provides the ideal platform for delivering a new developer experience inside the enterprise, just as Linux provided a new experience for web applications and Internet adoption. If OpenStack was just a “cheaper VMware,” then it would have little or no real value to the enterprise. Instead, OpenStack provides a shining example of how to build a private elastic cloud like major public clouds such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). Just as Hadoop brought Google’s MapReduce (plus it’s reference architecture) to the masses, OpenStack brings the AWS/GCP-style Infrastructure-as-a-Service (IaaS) offering to everyone. This is what makes DevOps inside the enterprise ultimately shine.

Any discussion about DevOps, like so many of the recent buzzwords, can quickly become mired in semantic arguments. However, the one truism we can all agree on is that the traditional barriers between application developers and IT infrastructure operators need to be broken.

Time after time, I hear a similar story from our customers that goes like this: “We went to the infrastructure teams with our long list of requirements for our new application. They told us it would take 18 months and $10M before it would be ready. So we went to Amazon Web Services. We didn’t get our list of infrastructure requirements and we had to change our application model, but we got to market immediately.” That’s because the inherent value of AWS has less to do with cost and more to do with the on-demand, elastic and developer-centric delivery model.

OpenStack levels the playing field inside the enterprise. Private clouds can be built on the public cloud model, enabling developers while simultaneously giving centralized IT control and governance. In essence, it’s the best of both worlds, which is the true value of OpenStack-powered private clouds.

Why Does Agility Matter?

While I think it’s self-evident that agility is the driving light behind cloud computing, it’s worth a quick refresh. The need for businesses to move now has driven ridiculous growth for AWS (see growth below and notice this is a log chart):

Netcraft AWS Growth Relentless

This growth is all net new applications, or what Microsoft calls next generation applications. The vast majority of these new applications are focused on creating entirely new business value, typically around mobile, social, web applications, and big data. In fact, this category of application is growing so fast that analysts such as IDC and Gartner have started tracking it [2]:

Agility Driven by Next Gen Apps

At its current rate of growth, next generation cloud applications will equal the size of all existing applications by 2018:

Next generation applications are the source for future competitiveness for most enterprises, which has led them to accelerate their cloud adoption process and rethink their cloud strategy.

Observing this phenomenon is what led Forrester analyst Craig Le Clair to say:

Seventy percent of the companies that were on the Fortune 1000 list a mere 10 years ago have now vanished – unable to adapt to change …

We have now entered an adapt or die moment for enterprises, and OpenStack will be key to agility adaptation and the successful support of DevOps.

Over the next few weeks leading up to the OpenStack Summit I’m going to cover all 6 Requirements of Enterprise-grade OpenStack in detail.  Today I am going to handle the first two requirements: high uptime APIs and robust management of your cloud.

Requirement #1 – 99.999% Uptime Control Plane: High Uptime Apps Require a High Uptime API

Continuing our discussion around delivering enterprise-grade OpenStack, let’s discuss how critical API availability and scaling out the cloud control plane are to delivering next gen applications.

Cloud API Uptime & Availability

A critical capability for moving to a new cloud and devops model is the ability of cloud native applications to route around failures in an elastic cloud. These applications know that any given server, disk drive, or network device could fail at any time. They look for these failures and handle them in real-time. That’s how Amazon Web Services (AWS) and Google Cloud Platform (GCP) work and why they can run these services at a low cost structure and with greater flexibility. For an application to adapt in real-time to the normal failures of individual components, the cloud APIs must have higher than normal availability.

Your Cloud Control Plane’s Throughput

API uptime isn’t the only measurement of success. Your cloud’s control plane throughput is also critical. Think of the control plane as the command center of your cloud. It is most of the centralized[3] intelligence and orchestration layer. Your APIs are a subset of the control plane, which for OpenStack also includes all of core OpenStack projects, your day-to-day cloud management software (usually part of a vendor’s Enterprise-grade OpenStack distribution), and all of the ancillary services required such as databases, OpenStack vendor plugins, etc. Your cloud control plane needs to scale-out as your cloud grows bigger. That means that in aggregate, you have more total throughput for API operations (object push/pull, image upload/downloads, metadata updates, etc.).

This is where a proper cloud operating system comes in.

99.999% Uptime APIs and Scale-out Control Plane

In essence, by saying that you can build a four or five 9 app (99.99-99.999%) on a two and a half 9 infrastructure (99.5%), the API that app manages must also have a four or five 9 uptime (99.999%). As most of you know, delivering five 9s of availability is a non-trivial task, as this is only 5.26 minutes of unplanned downtime allowed per year. Typical high availability approaches, such as active/passive or master election systems, can take several minutes to failover, leaving your cloud API endpoints unavailable.

An enterprise-grade cloud operating system can provide guarantees of sub-minute or even sub-second failover and deliver 99.999% or possibly even 99.9999% (that’s six 9s or 31.5 seconds of downtime per year) uptime. This kind of design is achievable at a relatively low price point using classic load balancing style techniques where your control plane and APIs are running active/active/active/active/… to N where N is however many you need as your cloud grows:

Load Balancing vs. Simple HA

Which brings me to the second part of the equation: you need your control plane to grow as your cloud grows. You don’t want to re-architect your system as it grows, and you don’t want to resort to old school scale up techniques for your API endpoints. When you run active/passive or with a master election system for high availability, only one API endpoint is available at a time. That means that you are fundamentally bottlenecked by the total throughput of a single server, which is unacceptable in today’s scale-out cloud world.

Instead, use a load balancing pattern so you can run multi-master (N-way) active API endpoints, scale your control plane horizontally and simultaneously achieve a very high uptime. This is the best of all worlds, allowing your cloud native applications to route around problems in real-time.

Now let’s talk about day-to-day management of and securing your cloud.

Requirement #2 – Robust Management: Managing and Securing Your Cloud is Not Free

You probably know this already, but building a robust, manageable, and secure infrastructure in the enterprise isn’t easy. The notion that an enterprise-grade private cloud can be delivered in an afternoon and in production that evening doesn’t wash with the realities of the datacenter. Still, time is of the essence and if you want a cloud that doesn’t suck and you want it (relatively) fast, then it will help if the version of OpenStack you choose has been designed with deployment, daily management, and security in mind. Let’s take a deeper look at what that entails.

Robust Management

Installation is only the beginning when it comes to managing OpenStack. A true cloud operating system provides a suite of operator-centric cloud management tools designed to allow the infrastructure team to be successful at service delivery. These management tools provide:

  • Repeatable architectural model, preferably using pods or blocks wired together with a reference network architecture
  • Initial cloud installation & deployment
  • Typical day-to-day cloud operator tools for logging, system metrics, and correlation
  • Cloud operator command line interface (CLI) and API for integration and automation
  • Cloud operator GUI for visualization and analysis

Many attempts to solve the private cloud management challenges stop at installation. Installation is just the beginning of your journey, and how easy it is doesn’t matter if your cloud is then hard to manage on a daily basis. As we all know, running a production system is not easy. In fact, private clouds are significantly more complex than traditional infrastructure approaches in many aspects. To simplify the issue, at scale, the cloud pioneers, such as Google, Amazon, and Facebook have all adopted a pod, cluster, or block based approach to designing, deploying, and managing their cloud. Google has clusters; Facebook has triplets; but it’s all ultimately the same: a Lego brick-like repeatable approach to building your cloud and datacenter.[4] Enterprise-grade OpenStack-powered cloud operating systems will need to provide a similar approach to cloud organization.

Once the cloud is up and running, cloud operators need a variety of tools to maintain the cloud on a regular basis, including event logs and system metrics. Sure, in an elastic cloud events that used to be critical (e.g. server or switch failure) are no longer high priority. However, your cloud can’t be a black box. You need information on how it’s operating on a daily basis so you can troubleshoot specific issues as required and most importantly keep an eye out for recurring issues using correlation tools. An individual server failure might not be a problem, but any kind of common issue that is effective large amounts of resources needs to be sought out and quickly addressed.

What is your cloud doing? Not only do you need to know, but your other tools and groups may need to know as well. Integration to existing systems is critical to broad adoption. Any complete solution will have an API and command line interface (CLI) to allow you integrate and automate. A CLI and API for just OpenStack administrative needs is not enough. What about your physical server plant or management of your blocks or pods? How about being able to retrieve system metrics and logging data on demand from not only OpenStack, but Linux and other non-OpenStack applications? You need a single, unified interface for cloud operations and management. Obviously, if you have this API, a GUI should also be provided for those unique cloud operator tasks that require visualizations such as looking for patterns in system and network metrics.

Security Model

Cloud turns the security model on its head. A complete discussion of this topic is far beyond the scope of this blog, but I do know one thing: enterprises want a private cloud with an understandable security model, particularly for the control plane. As I covered in the previous installment of this series, your cloud control plane’s API uptime and throughput is critical to allowing next generation applications to route around trouble. Similarly, the security of your cloud’s control plane should not be taken for granted.

It can be easy to get caught up in the move towards a decentralized model, but decentralized and scale-out are not the same thing. You can actually mix centralization and scale-out techniques and this is the default model that cloud pioneer Google uses. Keeping your cloud control plane in one place allows you to:

  • Have a single go-to location for troubleshooting
  • Always know where your control plane is located rather than having to guess
  • Apply security policies/zones to your control plane
  • Keep your control plane data (the system of record) completely separated from data plane data

This last item is perhaps most important. You don’t want your OpenStack database to reside on the same storage system as your virtual machines. What if someone breaks into a VM through the hypervisor? Or, conversely, what happens if someone breaks into the control plane via an API?

Best practices in the enterprise have long comprised an approach of zoning (usually with VLANs) of different components into different security areas with differing policies applied. Zoning slows an attacker down, gives you time to detect them, and to respond. Being able to take a similar approach to your private cloud security model is vital to making certain your cloud is secure.

Cloud Management and Security

As I said, your journey begins with the installation of the cloud. After that, you need a set of tools and a security model that allows you to confidently manage your cloud day by day. An Enterprise-grade, OpenStack-powered cloud operating system should deliver as much of these capabilities as possible.

Part 1 Summary

OpenStack is a strong foundation for building a next generation private cloud designed for next generation cloud applications.  Unfortunately, it isn’t a complete cloud operating system and you will need a partner to provide you with that solution.  This series is covering The 6 Requirements of Enterprise-grade OpenStack and in today’s blog posting I covered the need for a high uptime, scale-out control plane and robust, secure management tools.

In the next installment I will cover building around an open architecture and reducing vendor lock-in.  That will be followed by the closing posting covering the need for filling in the gaps around scalability and performance and choosing a partner who can provide global services & support.

Second Installment:

Final Installment:

UPDATE: Added references for the growth of new net new apps.


[1] In fact, even the OpenStack Foundation is about to refresh it’s messaging to help clarify this.

[2] The original source for this is EMC, both at this blog posting and via a private presentation by Joe Tucci, CEO of EMC, at a Research Board event.

[3] Yes, centralized. Something can be centralized and still scale-out. Centralization is necessary for proper security policies and zones to be enforced.

[4] Google’s cluster architecture has quite a bit of detail here.

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The Top Three Things To Bookmark for the Juno Summit

Posted on by Azmir Mohamed

I can’t believe that it’s less than a month before the the upcoming Juno Summit.  As you start putting together your plans for the Summit, I wanted to highlight some items to look forward to from the Cloudscaling team.

#1: Four Cloudscaling sessions have been selected for the Summit.

We appreciate the explicit endorsement from the community – the topics reflect on our experience and leadership in the space – and we are very excited to share! Here is a recap of the four Cloudscaling sessions – you can simply add them to your Summit schedule by clicking on the links:

  • Hybrid Cloud Landmines: Architecting Apps to Avoid Problems (Randy Bias & Drew Smith): Application portability? Cross-cloud replication and bursting? These are hard issues with serious implications that we’ll examine in detail, digging into the subtleties between simply implementing a cross-cloud API and actually using it to get real work done. We’ll provide a set of recommendations on how to architect your application from the ground up to be hybrid cloud friendly.

  • Open Cloud System: OpenStack Architected Like AWS (Randy Bias): At Cloudscaling, we spend a great deal of effort operationalizing OpenStack for customers and ensuring it’s compatible with leading public clouds. In this session, we’ll detail the configuration and design decisions we make in real world OpenStack deployments.

  • OpenStack Block Storage: Performance vs. Reliability (Randy Bias & Joseph Glanville): In this presentation, we’ll talk about selecting and designing the right kind of storage for your use case. We’ll also walk you through how we built our block storage solution in Open Cloud System, its design principles, and explain why it is a better version of AWS Elastic Block Storage (EBS) in several key ways. (I regret we have to pull the plug on this presentation due to time constraints!  Hopefully in fall.  Best, –Randy)

#2: For the second Summit in a row, we are sharing our booth space with Quanta.

The reason is simple – a significant majority of Cloudscaling customers use Quanta servers and storage equipment for their OpenStack powered clouds (and did I mentioned what such a great team they are to work with?). While OpenStack’s role is to ultimately abstract the underlying physical infrastructure, we have found Quanta hardware to be a perfect complement to elastic OpenStack-powered clouds. The Quanta team will be bringing a few racks of their datacenter products that are most optimized for building modern OpenStack clouds. Stop by our booth!

#3:Open Cloud System (OCS) product announcement.

OK, I know it’s a teaser. But it should be no surprise that Icehouse will be central to the OCS announcement but we have a few additional items up our sleeves to share including

  • New OCS management capabilities

  • Additional AWS compatible features

So, it’s an understatement to say that we will be busy between now and the Summit. But any opportunity to meaningfully interact with the community, our customers and our partners is worth its weight in gold. We look forward to seeing you in Atlanta!

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A Concierge in the Cloud

Posted on by Azmir Mohamed

Today at Interop in Las Vegas, Cloudscaling introduced our new Cloud Concierge Services. The idea for Cloud Concierge came about as we watched enterprises struggle to understand where to start implementing an OpenStack cloud solution. Between public clouds, private clouds and legacy technology, there were many interrelated and complex decisions companies have to make.

Cloud Concierge aims to reduce complexities and accelerate adoption of enterprise OpenStack cloud implementations. We achieve this by:

  • Building all-inclusive offerings catered to fixed budgets and timeframes,

  • Grouping the Cloud Concierge offerings in logical phases of OpenStack adoption,

  • Addressing the needs of key stakeholders in the enterprise, such as the infrastructure and application teams, who are transforming  IT.

More importantly, our Cloud Concierge Solution Architects will train IT professionals on new skills and guide them to insights needed to operate in a modern cloud era. In addition to getting the IT team started in the short-term, they’ll gain new learnings that will allow them to better serve their organizations for the long-term.

Adopting a cloud strategy is a must in today’s business world. An OpenStack decision will give companies greater agility, transform IT service delivery and create differentiated business value. Cloud Concierge will help you go from “Zero to Cloud” on time and on budget.

Get in touch, and let us know how we can help you get started. Learn more about our Cloud Concierge Services at www.cloudscaling.com/services/cloud-concierge-services/.

 

Posted in OpenStack | Leave a comment

Cloud Just Got Real – The Race Begins

Posted on by Randy Bias

This week, Google hosted its Cloud Platform Live event. Some people were a little surprised at my enthusiastic live twitter coverage for a number of Google’s announcements. I have been waiting for them to “go big or go home” for a while now. My biggest surprise was how long it took Google to get up to speed. My fundamental belief is that they waited so long because they realized what they needed to do to succeed had little to do with initial speed, but was more about long term momentum.

Let me explain.

There are Three Ways to be #1

I wish I could claim this is my original thought, but I heard it from someone else[1]. If you know a more canonical source, I would very much like to have it. Please send it along via twitter or comments.

The saying goes like this:

There are three ways to be #1 in a market:

  1. Being first
  2. Being best
  3. Being cheapest

Ideally, you would be two or more of these things, leading to market dominance.

If you were Google, entering into this market years after AWS has launched and gained the market traction they have, you might reflect on what your best strategy is. Maybe you know the above truism or maybe you just have good instincts. If you are playing to win and you can’t be first that means you need to be best or cheapest, but preferably both.

And that, in essence, I think boils down why Google took a while to get “in market” and really tried to nail the technology before getting very serious as we saw this week.

Public Cloud is A Development Engine Game

I have always thought that public cloud was less about technical features (e.g. VMs on demand, object storage, etc.) and more about building a world class development engine. As I noted on previous occasions, businesses like Amazon actually increase in feature velocity as they get bigger, not decrease. This is a relatively new phenomena only seen in web-scale businesses (and Apple).

Building velocity like this is less about technology and more about culture and organizational structure. I’m sure you have read the seminal The Mythical Man Month, which essentially says that as a development team gets larger your overhead on communication increases to the point where you actually move slower. The answer to this is typically moving to an agile model, but that’s only a partial fix. It is far more effective to make your development organization look like a set of loosely coupled independent startups with clear targets for success and clear accountability. In that way teams run their own business.

This also maps to the actual underlying technology structure of the business and is the general “a-ha” moment that large scale web businesses collectively had. Here’s a 2007 ZDnet article talking about Amazon.com’s (the retail site) services oriented architecture.

Google Cloud Platform’s Announcements

I don’t really need to recap the various announcements this week. You can find that in various places. What I do want to highlight is the two underlying trends that these announcements represent:

Google thinks this is a game for the hearts and minds of developers of new apps
Google is doubling down on it’s own development engineering might first

This is reflected in the Wired article that came out yesterday entitled Google’s Bold Plan to Overthrow Amazon as King of Cloud.

The key quote is here:

“We will spend the majority of our development efforts on this New World,” wrote [Urs] Hölzle. “Every developer will want to live in this world…and it’s our job to build it.”

More succinctly what Urs is saying is that Google’s strategy is to build a developer advantage inside Google in order to enable developers outside of Google to have cloud services (platform and infrastructure) that they will love.

Hints of this can be found in the more nuanced technical announcements yesterday such as the support of integrated build/test pipelines through a combination of Google Compute Engine (GCE) + Google App Engine (GAE) using the GAE Managed VMs offering.

Being Best AND Cheapest

Google’s approach to their Cloud Platform has been the slow and steady buildup of a hard-hitting, quick-firing development engine that is capable of increasing the velocity of feature releases over time. That development engine has now reached escape velocity. There are only two other public clouds like this: Amazon Web Services and Microsoft Azure [2].

Google’s development engine shows they are targeting being Best AND Cheapest. There are a number of good reasons why they can accomplish those goals and perhaps I will deep dive into them in a future blog posting.

Consider this … If it’s a three way horse race in public cloud with OpenStack for the private cloud then we need to accept that we are now living in a multi-cloud world. For me, this is a sure indicator of a rapidly maturing marketplace that delivers maximum choice to developers and enterprises.

To paraphrase: Cloud just got real.


[1] Marc Andreesen I think, but I can’t find the blog posting where I thought he laid it out. BTW, if you haven’t read Marc’s original blog postings on entrepreneurism and startups, you are really missing out. The archive is here.
[2] HP might develop this capability over time, but they need to seriously commit to the path, so there are significant question marks about their possibilities for success until their business is more stable.

 

Posted in Cloud Computing | Leave a comment

Pets vs. Cattle: The Elastic Cloud Story

Posted on by Randy Bias

Last night I presented at the Chicago DevOps Meetup along with @mattokeefe and @mfdii.  The presentation went very well and was warmly received.  It’s a bit of a revisit of some topics I have covered before, such as Pets vs. Cattle, the new kind of elastic cloud, and the architectural patterns involved with building these new kinds of clouds.  I did a major refresh though and am weaving the threads a bit differently than before.

I hope you enjoy it.

Pets vs. Cattle: The Elastic Cloud Story from Cloudscaling, Inc.
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The Case for Tiered Storage in Private Clouds

Posted on by Randy Bias

Fall of last year I wrote a controversial whitepaper detailing my concerns about how distributed storage was being marketed.  The blog introduction and the whitepaper were both entitled Converged Storage, Wishful Thinking, and Reality.  There was a certain amount of expected blowback from folks at RedHat and Ceph as well as more thoughtful replies from Dreamhost and Solidfire.  Some of the feedback was pure screed, some was worthy of considered thought, and much of it missed the mark.  I realized however that it was *my* failure to communicate clearly that caused a considerable amount of the feedback to be erroneous.

So I wrote an update to that whitepaper that I think helps clarify my thinking in this area.  Fortuitously, the recent Google outage really helps to emphasize what I am talking about.  If you haven’t been paying attention, you can find out more about it here and from Google themselves.  In a nutshell, Google, who runs a 3-4 nine operation for most services (meaning 99.9-99.99% uptime), had a 35-minute outage due to a software bug.  It’s noteworthy that an event like this is so heavily scrutinized given that the vast majority of businesses struggle to achieve three nines of uptime.

More importantly, this outage highlights what I was trying to say in my original paper, which is that large homogeneous software systems are inherently dangerous to uptime.  Systems fail because of hardware failure, operator error, or software bugs.  Traditional high availability (HA) pairs solve for the hardware failure problem, but typically ignore operator error or software bugs.  Newer distributed software systems *still* predominantly solve for hardware failure, ignoring the more likely failure scenarios of operator error and software bugs.  This is a major problem.

There are a number of ways to solve these problems, including but not limited to: running more than one kind of software system (i.e. moving to a more heterogeneous set of systems), using sharding techniques, and applying disaster recovery techniques.  All of these approaches are essentially doing the same thing, which is limiting the failure domain size.  Not having fault isolation means you will see cascading failures as AWS has seen several times when it violated some of these basic principles. Operator errors combined with software bugs caused massive EBS failures, which spilled across Availability Zones because the EBS control plane spanned the AZes.

This is my problem with how distributed storage systems are being marketed.  I love distributed storage.  I think it has a place in the datacenter.  Cloudscaling is currently evaluating our options for integrating open source distributed storage software in our product.  The problem is that it’s place is not to run everywhere in the datacenter and the marketeers at various storage startups who believe so and market so-called “unified” storage solutions are really setting everyone up for failure.  There is no spoon.

For more details, here is my updated storage whitepaper, now entitled The Case for Tiered Storage in Private Clouds, that hopefully furthers the conversation on the appropriate best practices and patterns to use for deploying storage in private clouds today.

In the interest of transparency, I will say that this new revision was kindly reviewed by the team at SolidFire, who have a similar viewpoint to mine.  Much thanks to Dave Wright, Dave Cahill, and John Griffith (PTL for OpenStack Cinder) for their feedback.

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Vote Now: Awesome Proposals for the Spring OpenStack Summit

Posted on by Randy Bias

Voting is now open for the Spring 2014 OpenStack Summit in Atlanta!

Cloudscaling (and our friends at Mirantis) have submitted a variety of great session abstracts, from Randy Bias’ walkthrough of hybrid cloud landmines to avoid when architecting applications to Boris Renski’s discussion on updating the OpenStack mission statement to disrupt large player competitive barriers and keep the stack open for innovation.

Below, we’ve summarized each talk and provided a link to its page on the voting site. As always, you must be a member of the OpenStack Foundation to vote. If you’re not already a member, just click here to join as an individual member for free. You get to shape the OpenStack Summit agenda by voting up the sessions that you’d like to see.

We look forward to seeing you in Atlanta!

Cloudscaling Session Proposals

  • (Vote Here) Open Cloud System 3.0: OpenStack Architected Like AWS (Azmir Mohamed) - At Cloudscaling, we spend a great deal of effort operationalizing OpenStack for customers and ensuring it’s compatible with leading public clouds. In this session, we’ll detail the configuration and design decisions we make in real world OpenStack deployments.

  • (Vote Here) OpenStack Scale-out High Availability: Scaling to 1,000+ servers without Neutron (JC Smith + Randy Bias) - The default OpenStack networking models don’t make sense in a modern datacenter. Similar to the approach taken by HP, CERN and other deployments, we’ll detail how we replace the default networking model through standard plugins in order to deploy a fully scale-out networking model that can support 100s of racks with incredibly high performance.

  • (Vote Here) For Cloud Operators: Hands-on With OpenStack for Elastic Clouds (Sean Winn) - In this session, we will provide a condensed version of our 2-day OpenStack Bootcamp workshop with an operator-centric, hands-on approach.

  • (Vote Here) ZFS on Linux + OpenStack: Flash Performance at Spinning Disk Prices (Joseph Glanville) - Join us for this walkthrough of ZFS on Linux (ZoL) where we’ll cover the state of ZoL along with the related OpenStack plugins and drivers. You’ll leave with a clear understanding of why multi-tenant cloud workloads are perfect for ZFS as well as how to measure and tune performance.

  • (Vote Here) Voice of the User: Running OpenStack in Production (Drew Smith + Ryan Lane) - Join us for an analysis and interactive discussion of real world OpenStack deployment issues. Along with guest speaker, Ryan Lane, who is running an OpenStack based cloud, we’re going to combine a review of data from our field and support requests with war story examples of “when it goes wrong”.

  • (Vote Here) OpenStack Block Storage: Performance vs. Reliability (Randy Bias + Joseph Glanville) - In this presentation, we’ll talk about selecting and designing the right kind of storage for your use case. We’ll also walk you through how we built our block storage solution in Open Cloud System, its design principles, and explain why it is a better version of AWS Elastic Block Storage (EBS) in several key ways.

  • (Vote Here) iSCSI Performance Testing & Tuning (Joseph Glanville) - In this session, we’ll explore the pros and cons of different iSCSI implementations within OpenStack Cinder deployments. We’ll then look at performance tuning options for iSCSI as well as the effects of related architecture components such as using jumbo frames in the network, flash storage, hybrid storage pools and iSCSI multi-pathing.

  • (Vote Here) Emulating A Large Scale, Multi-Rack Cloud on One Server (Mike Lang) - In this presentation we’ll introduce a new open source tool that allows us to emulate a multi-rack, multi-server, OpenStack deployment on a single server, allowing complete cloud architectures to be tested. We’ll also recommend how this tool can be used to expand the OpenStack continuous integration system and possibly serve as a mechanism for testing a variety of OpenStack reference architectures within complex, multi-rack deployments.

  • (Vote Here) Hybrid Cloud Landmines: Architecting Apps to Avoid Problems (Drew Smith + Randy Bias) - Application portability? Cross-cloud replication and bursting? These are hard issues with serious implications that we’ll examine in detail, digging into the subtleties between simply implementing a cross-cloud API and actually using it to get real work done. We’ll provide a set of recommendations on how to architect your application from the ground up to be hybrid cloud friendly.

  • (Vote Here) Tinker: A Tool for Network Configuration Management at Cloud Scale (Abhishek Chanda) - Managing network configuration in a cloud deployment can be a major pain. In this session, we will introduce tinker, a tool to generate and manage network device configuration using existing metadata to automatically and reliably generate configurations for all network devices in a cloud.

  • (Vote Here) OpenStack and the Google Compute Engine APIs (Alex Levine + Randy Bias) - It’s a hybrid cloud world and OpenStack powered public clouds won’t be everywhere, so it makes sense that we have a rich ecosystem of compatibility APIs in addition to the native OpenStack APIs. Come learn about the Google Compute Engine (GCE) APIs we recently built and submitted back to StackForge, including how they were built, how to add them to your own OpenStack deployment, and how to test them.

Mirantis Session Proposals

  • (Vote Here) Configuring Live Migrations for Workload Transitions (Damian Igbe) – This talk will review approaches to three fundamentally different live migration methodologies: block migration, shared storage migration, and migrating instances booted from Cinder volumes (i.e., volume booted migration). It will compare these three approaches and discuss factors to consider when deciding which methodology to use in different scenarios. We will also review practical (and sometimes critical) steps to ensure that both the cloud and its workloads are properly configured for live migration, along with important factors that can make or break smooth implementation and operation of live migration.

  • (Vote Here) Step One, Launch Openstack; Step Zero, Pick your hardware (Gregory Elkinbard) – The power of OpenStack software implementation, deployment and operations all cross the critical path of hardware selection. In this presentation, we’ll present a distillation of the key factors we have applied at Mirantis through dozens of highly successful OpenStack deployments on how to select an optimal hardware platform for your OpenStack cloud.

  • (Vote Here) Source Based Packaging: The Missing Ingredient of Continuous Delivery? (Dmitry Borodaenko) – This talk will explore the gap between source-based CI used by the OpenStack community and package-oriented deployment favored by OpenStack distributions, and examine the state of tools aiming to bridge that gap. Attend and you’ll learn how to tick the OpenStack CI/CD checkbox without leaving the comfort of the package-config-service pattern and the safety of security updates from your favorite distro.

  • (Vote Here) Is it time to update the OpenStack mission statement? (Boris Renski) – This talk will take a closer look at various OpenStack community initiatives and projects that disrupt competitive barriers established by large infrastructure players. We’ll also examine how the OpenStack community is making OpenStack distribution vendors in their present form irrelevant in many respects.

  • (Vote Here) Preparing and Publishing an Application in the Openstack Application Catalog (Alexander Tivelkov) – This workshop will walk you through the steps required to prepare an application for publication. The presenters will pick a real-life application and demonstrate how to publish it in the Catalog. Attendees will see how to define the configuration parameters and dependencies, build the deployment and maintenance workflows, construct a user-friendly UI to control these workflows – and, eventually, how to publish all of it in the Catalog. And all of this without writing a single line of Python code or modifying a single bit of the application itself.

  • (Vote Here) How to Avoid Picking Problems that Openstack Can’t Solve (Evgeniya Shumakher) – To be effective promoters and developers of OpenStack, we need to be able to identify these cases (not all edge-cases, either) and have the firmness of conviction to guide prospective users away from OpenStack, when risks are so high that their results will be marginal or unsatisfactory. (And we need to look at these gaps, where they exist, and think hard about filling them.) Attendees will leave this presentation with a fuller understanding of how to pilot their organizations away from what may become lackluster OpenStack engagements, and towards opportunities that take best advantage of OpenStack as it now exists.

  • (Vote Here) Extending the Fuel Project to Accelerate and Simplify Deployment of OpenStack Drivers and Components (David Easter) – In this session, we’ll fully familiarize attendees with the (relatively simple) process of becoming an OpenStack contributor. We’ll go over the process roadmap, account registration, security and authentication, connecting with community online resources and documentation, OpenStack and related code repositories, projects and their taxonomies, configuring Git to work within OpenStack’s code-review process and committing changes, review and approvals. And we’ll also cover details of how and where to best patch Fuel and describe the Fuel API timetable, imminent component releases and Fuel’s project roadmap. Attendees – particularly developers – should come away from this session ready to join the OpenStack project, find resources, pick goals and quickly be productive, especially where contributing to Fuel is concerned.

  • (Vote Here)  Rally – Benchmarking OpenStack at Scale Using Your Own Hardware (Boris Pavlovic) – Benchmarking a huge distributed system like OpenStack raises the complexity bar significantly. Add to that the fact that OpenStack may be a moving target – with Continuous Integration/Continuous Deployment (CI/CD) keeping things in flux – and benchmarking becomes, as Spock might say, “a non-trivial problem.” This session will explore Rally’s high level architecture, the current state of the Rally project, and the Rally Roadmap. We’ll also cover how to use Rally to improve the quality of OpenStack (Dev case), to ensure that OpenStack clouds pass SLA (QA/DevOps case) and to help build CI/CD. Attendees should leave this session with a solid understanding of Rally and most of the info they need to begin integrating Rally to existing OpenStacks and architecting it into new deployments.

  • (Vote Here)  How Community can make OpenStack Customer Centric (Alex Freedland) – As a major OpenStack vendor, Mirantis has developed a set of best practices for welcoming and working with end-user customers, extending to them the benefits of OpenStack community participation, and conversely, obtaining from them guidance and actionable market intelligence. By discussing these best-practices, we hope to 1) help the OpenStack community reach out more consistently, and with better results, to real end-user customers 2) develop beneficial (but also non-burdensome) roles in the community, enabling and shaping participation by a range of parties whose main motive is to use rather than build the product and 3) explore structural tweaks that will enable better exchange of information between ‘style: end-user’ participants and members of the community who participate in more fundamental ways.

  • (Vote Here) Bare Metal Peer-to-Peer Provisioning at Scale (Herman Narkaytis) – In this talk, we’ll review the current state of bare metal provisioning in TripleO / Ironic and Fuel and model the scalability limits of alternate approaches and architectures. We will discuss the state of things in Icehouse, including what use cases are covered, the algorithm, and limitations. We will also explore whether plans for Juno can reverse diminishing scalability and drive bare metal provisioning closer to linear performance. Bare metal provisioning (versus creating virtual machines) has its own challenges, and after attending this talk, you’ll not only have a better understanding of the differences, you’ll also have a feel for possible ways to mitigate those challenges.

  • (Vote Here) Breaking the East-West Barrier: How to Combine a Flat Network, Security, Manageability and Killer Performance in Openstack (Pedro Marques, Przemyslaw Grygiel) – In this talk, we’ll outline a practical, step-by-step method for configuring and provisioning a 200-node OpenStack cluster using Fuel. Using a fully-functional physical infrastructure, we broke through very real bottlenecks in Openstack defaults and in tooling (the proof of a real bottleneck is that when you resolve it, it exposes the next bottleneck). In addition, we will enumerate typical mistakes and pitfalls.

  • (Vote Here) Securing OpenStack with Intel Trusted Computing (Christian Huebner) – Intel Trusted Computing allows comparing the current state of a compute host with a previously stored good state. This presentation will contain a general overview of Trusted Computing, OpenAttestation server and client deployment on Red Hat Enterprise Linux, the inner workings of trusted_filter.py and its attestation procedure against an OpenAttestation server and configuration and testing of OpenStack controllers and compute nodes for trusted execution. The presentation is based on a recent deployment of OpenAttestation with both trusted and untrusted compute nodes using RedHat Enterprise Linux 6.5 and OpenAttestation 1.6.

Posted in OpenStack | Leave a comment

 

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