Rational Survivability

VMotion - Here's Where We Are Today

A lot has been said about the wonders of workload VM portability.

Within the construct of virtualization, and especially VMware, an awful lot of time is spent on VM Mobility but as numerous polls and direct customer engagements have shown, the majority (50% and higher) do not use VMotion.  I talked about this in a post titled “The VM Mobility Myth:”

…the capability to provide for integrated networking and virtualization coupled with governance and autonomics simply isn’t mature at this point. Most people are simply replicating existing zoned/perimertized non-virtualized network topologies in their consolidated virtualized environments and waiting for the platforms to catch up. We’re really still seeing the effects of what virtualization is doing to the classical core/distribution/access design methodology as it relates to how shackled much of this mobility is to critical components like DNS and IP addressing and layer 2 VLANs.  See Greg Ness and Lori Macvittie’s scribblings.

Furthermore, Workload distribution (Ed: today) is simply impractical for anything other than monolithic stacks because the virtualization platforms, the applications and the networks aren’t at a point where from a policy or intelligence perspective they can easily and reliably self-orchestrate.

That last point about “monolithic stacks” described what I talked about in my last post “Virtual Machines Are the Problem, Not the Solution” in which I bemoaned the bloat associated with VM’s and general purpose OS’s included within them and the fact that VMs continue to hinder the notion of being able to achieve true workload portability within the construct of how programmatically one might architect a distributed application using an SOA approach of loosely coupled services.

Combined with the VM bloat — which simply makes these “workloads” too large to practically move in real time — if one couples the annoying laws of physics and current constraints of virtualization driving the return to big, flat layer 2 network architecture — collapsing core/distribution/access designs and dissolving classical n-tier application architectures — one might argue that the proposition of VMotion really is a move backward, not forward, as it relates to true agility.

That’s a little contentious, but in discussions with customers and other Social Media venues, it’s important to think about other designs and options; the fact is that the Metastructure (as it pertains to supporting protocols/services such as DNS which are needed to support this “infrastructure 2.0”) still isn’t where it needs to be in regards to mobility and even with emerging solutions like long-distance VMotion between datacenters, we’re butting up against laws of physics (and costs of the associated bandwidth and infrastructure.)

While we do see advancements in network-driven policy stickiness with the development of elements such as distributed virtual switching, port profiles, software-based vSwitches and virtual appliances (most of which are good solutions in their own right,) this is a network-centric approach.  The policies really ought to be defined by the VM’s themselves (similar to SOA service contracts — see here) and enforced by the network, not the other way around.

Further, what isn’t talked about much is something that @joe_shonk brought up, which is that the SAN volumes/storage from which most of these virtual machines boot, upon which their data is stored and in some cases against which they are archived, don’t move, many times for the same reasons.  In many cases we’re waiting on the maturation of converged networking and advances in networked storage to deliver solutions to some of these challenges.

In the long term, the promise of mobility will be delivered by a split into three four camps which have overlapping and potentially competitive approaches depending upon who is doing the design:

1. The quasi-realtime chunking approach of VMotion via the virtualization platform [virtualization architect,]
2. Integration distribution and “mobility” at the application/OS layer [application architect,] or
3. The more traditional network-based load balancing of traffic to replicated/distributed images [network architect.]
4. Moving or redirecting pointers to large pools of storage where all the images/data(bases) live [Ed. forgot to include this from above]

Depending upon the need and capability of your application(s), virtualization/Cloud platform, and network infrastructure, you’ll likely need a mash-up of all three four.  This model really mimics the differences today in architectural approach between SaaS and IaaS models in Cloud and further suggests that folks need to take a more focused look at PaaS.

Don’t get me wrong, I think VMotion is fantastic and the options it can ultimately delivery intensely useful, but we’re hamstrung by what is really the requirement to forklift — network design, network architecture and the laws of physics.  In many cases we’re fascinated by VM Mobility, but a lot of that romanticization plays on emotion rather than utilization.

So what of it?  How do you use VM mobility today?  Do you?

/Hoff

Greg Ness touched off an interesting discussion when he asked “Will Virtualization Undermine Network Equipment Vendors?”  It’s a great read summarizing how virtualization (and Cloud) are really beginning to accelerate how classical networking equipment vendors are re-evaluating their portfolios in order to come to terms with these disruptive innovations.

I’ve written so much about this over the last three years and my response is short and sweet:

Virtualization has actually long been an enabler for network equipment vendors — not server virtualization, mind you, but network virtualization.  The same goes in the security space. The disruption caused by server virtualization is only acting as an accelerant — pushing the limits of scale, redefining organizational and operational boundaries, and acting as a forcing function causing wholesale reconsideration of archetypal network (and security) topologies.

The compressed timeframe associated with the disruption caused by virtualization and its adoption in conjunction with the arrival of Cloud Computing may seem unnatural given the relatively short window associated with its arrival, but when one takes the longer-term view, it’s quite natural.  We’ve seen it before in vignettes across the evolution of computing, but the convergence of economics, culture, technology and consumerism have amplified its relevance.

To answer Greg’s question, Virtualization will only undermine those network equipment vendors who were not prepared for it in the first place.  Those that were building highly virtualized, context-enabled routing, switching and security products will embrace this swing in the hardware/software pendulum and develop hybrid solutions that span the physical and virtual manifestations of what the “network” has become.

As I mentioned in my blog titled “Quick Bit: Virtual & Cloud Networking – Where It ISN’T Going…”

Specifically, as it comes to understanding how the network plays in virtual and Cloud architectures, it’s not where the network *is* in the increasingly complex virtualized, converged and unified computing architectures, it’s where networking *isn’t.*

Where ISN'T The Network?

Take a look at your network equipment vendors.  Where do they play in that stack above?  Compare and contrast that with what is going on with vendors like Citrix/Xen with the Open vSwitch, Vyatta, Arista with vEOS and Cisco with the Nexus 1000v*…interesting times for sure.

/Hoff

*Disclosure: I work for Cisco.

For those of you who are not in the security space and may not have read the Cloud Security Alliance’s “Guidance for Critical Areas of Focus,” you may have missed the “Cloud Architectural Framework” section I wrote as a contribution.

We are working on improving the entire guide, but I thought I would re-publish the Cloud Architectural Framework section and solicit comments here as well as “set it free” as a stand-alone reference document.

Please keep in mind, I wrote this before many of the other papers such as NIST’s were officially published, so the normal churn in the blogosphere and general Cloud space may mean that  some of the terms and definitions have settled down.

I hope it proves useful, even in its current form (I have many updates to make as part of the v2 Guidance document.)

/Hoff

Cloud Computing (“Cloud”) is a catch-all term that describes the evolutionary development of many existing technologies and approaches to computing that at its most basic, separates application and information resources from the underlying infrastructure and mechanisms used to deliver them with the addition of elastic scale and the utility model of allocation.  Cloud computing enhances collaboration, agility, scale, availability and provides the potential for cost reduction through optimized and efficient computing.

More specifically, Cloud describes the use of a collection of distributed services, applications, information and infrastructure comprised of pools of compute, network, information and storage resources.  These components can be rapidly orchestrated, provisioned, implemented and decommissioned using an on-demand utility-like model of allocation and consumption.  Cloud services are most often, but not always, utilized in conjunction with and enabled by virtualization technologies to provide dynamic integration, provisioning, orchestration, mobility and scale.

While the very definition of Cloud suggests the decoupling of resources from the physical affinity to and location of the infrastructure that delivers them, many descriptions of Cloud go to one extreme or another by either exaggerating or artificially limiting the many attributes of Cloud.  This is often purposely done in an attempt to inflate or marginalize its scope.  Some examples include the suggestions that for a service to be Cloud-based, that the Internet must be used as a transport, a web browser must be used as an access modality or that the resources are always shared in a multi-tenant environment outside of the “perimeter.”  What is missing in these definitions is context.

From an architectural perspective given this abstracted evolution of technology, there is much confusion surrounding how Cloud is both similar and differs from existing models and how these similarities and differences might impact the organizational, operational and technological approaches to Cloud adoption as it relates to traditional network and information security practices.  There are those who say Cloud is a novel sea-change and technical revolution while others suggest it is a natural evolution and coalescence of technology, economy, and culture.  The truth is somewhere in between.

There are many models available today which attempt to address Cloud from the perspective of academicians, architects, engineers, developers, managers and even consumers. We will focus on a model and methodology that is specifically tailored to the unique perspectives of IT network and security professionals.

The keys to understanding how Cloud architecture impacts security architecture are a common and concise lexicon coupled with a consistent taxonomy of offerings by which Cloud services and architecture can be deconstructed, mapped to a model of compensating security and operational controls, risk assessment and management frameworks and in turn, compliance standards.

Setting the Context: Cloud Computing Defined

Understanding how Cloud Computing architecture impacts security architecture requires an understanding of Cloud’s principal characteristics, the manner in which cloud providers deliver and deploy services, how they are consumed, and ultimately how they need to be safeguarded.

The scope of this area of focus is not to define the specific security benefits or challenges presented by Cloud Computing as these are covered in depth in the other 14 domains of concern:

• Information lifecycle management
• Governance and Enterprise Risk Management
• Compliance & Audit
• General Legal
• eDiscovery
• Encryption and Key Management
• Identity and Access Management
• Storage
• Virtualization
• Application Security
• Portability & Interoperability
• Data Center Operations Management
• Incident Response, Notification, Remediation
• “Traditional” Security impact (business continuity, disaster recovery, physical security)

We will discuss the various approaches and derivative offerings of Cloud and how they impact security from an architectural perspective using an in-process model developed as a community effort associated with the Cloud Security Alliance.

Principal Characteristics of Cloud Computing

Cloud services are based upon five principal characteristics that demonstrate their relation to, and differences from, traditional computing approaches:

1. Abstraction of Infrastructure
   The compute, network and storage infrastructure resources are abstracted from the application and information resources as a function of service delivery. Where and by what physical resource that data is processed, transmitted and stored on becomes largely opaque from the perspective of an application or services’ ability to deliver it.  Infrastructure resources are generally pooled in order to deliver service regardless of the tenancy model employed – shared or dedicated.  This abstraction is generally provided by means of high levels of virtualization at the chipset and operating system levels or enabled at the higher levels by heavily customized filesystems, operating systems or communication protocols.
2. Resource Democratization
   The abstraction of infrastructure yields the notion of resource democratization – whether infrastructure, applications, or information – and provides the capability for pooled resources to be made available and accessible to anyone or anything authorized to utilize them using standardized methods for doing so.
3. Services Oriented Architecture
   As the abstraction of infrastructure from application and information yields well-defined and loosely-coupled resource democratization, the notion of utilizing these components in whole or part, alone or with integration, provides a services oriented architecture where resources may be accessed and utilized in a standard way.  In this model, the focus is on the delivery of service and not the management of infrastructure.
4. Elasticity/Dynamism
   The on-demand model of Cloud provisioning coupled with high levels of automation, virtualization, and ubiquitous, reliable and high-speed connectivity provides for the capability to rapidly expand or contract resource allocation to service definition and requirements using a self-service model that scales to as-needed capacity.  Since resources are pooled, better utilization and service levels can be achieved.
5. Utility Model Of Consumption & Allocation
   The abstracted, democratized, service-oriented and elastic nature of Cloud combined with tight automation, orchestration, provisioning and self-service then allows for dynamic allocation of resources based on any number of governing input parameters.  Given the visibility at an atomic level, the consumption of resources can then be used to provide an “all-you-can-eat” but “pay-by-the-bite” metered utility-cost and usage model. This facilitates greater cost efficiencies and scale as well as manageable and predictive costs.

Cloud Service Delivery Models

Three archetypal models and the derivative combinations thereof generally describe cloud service delivery.  The three individual models are often referred to as the “SPI Model,” where “SPI” refers to Software, Platform and Infrastructure (as a service) respectively and are defined thusly[1]:

1. Software as a Service (SaaS)
   The capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure and accessible from various client devices through a thin client interface such as a Web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.
2. Platform as a Service (PaaS)
   The capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created applications using programming languages and tools supported by the provider (e.g., java, python, .Net). The consumer does not manage or control the underlying cloud infrastructure, network, servers, operating systems, or storage, but the consumer has control over the deployed applications and possibly application hosting environment configurations.
   
3. Infrastructure as a Service (IaaS)
   The capability provided to the consumer is to rent processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly select networking components (e.g., firewalls, load balancers).

Understanding the relationship and dependencies between these models is critical.  IaaS is the foundation of all Cloud services with PaaS building upon IaaS, and SaaS – in turn – building upon PaaS.  We will cover this in more detail later in the document.

The OpenCrowd Cloud Solutions Taxonomy shown in Figure 1 provides an excellent reference that demonstrates the swelling ranks of solutions available today in each of the models above.

Narrowing the scope or specific capabilities and functionality within each of the *aaS offerings or employing the functional coupling of services and capabilities across them may yield derivative classifications.  For example “Storage as a Service” is a specific sub-offering with the IaaS “family,”  “Database as a Service” may be seen as a derivative of PaaS, etc.

Each of these models yields significant trade-offs in the areas of integrated features, openness (extensibility) and security.  We will address these later in the document.

Figure 1 - The OpenCrowd Cloud Taxonomy

Cloud Service Deployment and Consumption Modalities

Regardless of the delivery model utilized (SaaS, PaaS, IaaS,) there are four primary ways in which Cloud services are deployed and are characterized:

1. Private
   Private Clouds are provided by an organization or their designated service provider and offer a single-tenant (dedicated) operating environment with all the benefits and functionality of elasticity and the accountability/utility model of Cloud.The physical infrastructure may be owned by and/or physically located in the organization’s datacenters (on-premise) or that of a designated service provider (off-premise) with an extension of management and security control planes controlled by the organization or designated service provider respectively.

   The consumers of the service are considered “trusted.”  Trusted consumers of service are those who are considered part of an organization’s legal/contractual
   umbrella including employees, contractors, & business partners.  Untrusted consumers are those that may be authorized to consume some/all services but are not logical extensions of the organization.

2. Public
   Public Clouds are provided by a designated service provider and may offer either a single-tenant (dedicated) or multi-tenant (shared) operating environment with all the benefits and functionality of elasticity and the  accountability/utility model of Cloud.
   The physical infrastructure is generally owned by and managed by the designated service provider and located within the provider’s datacenters (off-premise.)  Consumers of Public Cloud services are considered to be untrusted.
3. Managed
   Managed Clouds are provided by a designated service provider and may offer either a single-tenant (dedicated) or multi-tenant (shared) operating environment with all the benefits and functionality of elasticity and the  accountability/utility model of Cloud.The physical infrastructure is owned by and/or physically located in the organization’s datacenters with an extension of management and security control planes controlled by the designated service provider.  Consumers of Managed Clouds may be trusted or untrusted.

4. Hybrid
   Hybrid Clouds are a combination of public and private cloud offerings that allow for transitive information exchange and possibly application compatibility and portability across disparate Cloud service offerings and providers utilizing standard or proprietary methodologies regardless of ownership or location.  This model provides for an extension of management and security control planes.  Consumers of Hybrid Clouds may be trusted or untrusted.

The difficulty in using a single label to describe an entire service/offering is that it actually attempts to describe the following elements:

• Who manages it
• Who owns it
• Where it’s located
• Who has access to it
• How it’s accessed

The notion of Public, Private, Managed and Hybrid when describing Cloud services really denotes the attribution of management and the availability of service to specific consumers of the service.

It is important to note that often the characterizations that describe how Cloud services are deployed are often used interchangeably with the notion of where they are provided; as such, you may often see public and private clouds referred to as “external” or “internal” clouds.  This can be very confusing.

The manner in which Cloud services are offered and ultimately consumed is then often described relative to the location of the asset/resource/service owner’s management or security “perimeter” which is usually defined by the presence of a “firewall.”

While it is important to understand where within the context of an enforceable security boundary an asset lives, the problem with interchanging or substituting these definitions is that the notion of a well-demarcated perimeter separating the “outside” from the “inside” is an anachronistic concept.

It is clear that the impact of the re-perimeterization and the erosion of trust boundaries we have seen in the enterprise is amplified and accelerated due to Cloud.  This is thanks to ubiquitous connectivity provided to devices, the amorphous nature of information interchange, the ineffectiveness of traditional static security controls which cannot deal with the dynamic nature of Cloud services and the mobility and velocity at which Cloud services operate.

Thus the deployment and consumption modalities of Cloud should be thought of not only within the construct of “internal” or “external” as it relates to asset/resource/service physical location, but also by whom they are being consumed and who is responsible for their governance, security and compliance to policies and standards.

This is not to suggest that the on- or off-premise location of an asset/resource/information does not affect the security and risk posture of an organization, because it does, but it also depends upon the following:

• The types of application/information/services being managed
• Who manages them and how
• How controls are integrated
• Regulatory issues

Table 1 illustrates the summarization of these points:

Table 1 - Cloud Computing Service Deployment

As an example, one could classify a service as IaaS/Public/External (Amazon’s AWS/EC2 offering is a good example) as well as SaaS/Managed/Internal (an internally-hosted, but third party-managed custom SaaS stack using Eucalyptus, as an example.)

Thus when assessing the impact a particular Cloud service may have on one’s security posture and overall security architecture, it is necessary to classify the asset/resource/service within the context of not only its location but also its criticality and business impact as it relates to management and security.  This means that an appropriate level of risk assessment is performed prior to entrusting it to the vagaries of “The Cloud.”

Which Cloud service deployment and consumption model is used depends upon the nature of the service and the requirements that govern it.  As we demonstrate later in this document, there are significant trade-offs in each of the models in terms of integrated features, extensibility, cost, administrative involvement and security.

Figure 2 - Cloud Reference Model

It is therefore important to be able to classify a Cloud service quickly and accurately and compare it to a reference model that is familiar to an IT networking or security professional.

Reference models such as that shown in Figure 2 allows one to visualize the boundaries of *aaS definitions, how and where a particular Cloud service fits, and also how the discrete *aaS models align and interact with one another.  This is presented in an OSI-like layered structure with which security and network professionals should be familiar.

Considering each of the *aaS models as a self-contained “solution stack” of integrated functionality with IaaS providing the foundation, it becomes clear that the other two models – PaaS and SaaS – in turn build upon it.

Each of the abstract layers in the reference model represents elements which when combined, comprise the services offerings in each class.

IaaS includes the entire infrastructure resource stack from the facilities to the hardware platforms that reside in them. Further, IaaS incorporates the capability to abstract resources (or not) as well as deliver physical and logical connectivity to those resources.  Ultimately, IaaS provides a set of API’s which allows for management and other forms of interaction with the infrastructure by the consumer of the service.

Amazon’s AWS Elastic Compute Cloud (EC2) is a good example of an IaaS offering.

PaaS sits atop IaaS and adds an additional layer of integration with application development frameworks, middleware capabilities and functions such as database, messaging, and queuing that allows developers to build applications which are coupled to the platform and whose programming languages and tools are supported by the stack.  Google’s AppEngine is a good example of PaaS.

SaaS in turn is built upon the underlying IaaS and PaaS stacks and provides a self-contained operating environment used to deliver the entire user experience including the content, how it is presented, the application(s) and management capabilities.

SalesForce.com is a good example of SaaS.

It should therefore be clear that there are significant trade-offs in each of the models in terms of features, openness (extensibility) and security.

Figure 3 - Trade-off’s Across *aaS Offerings

Figure 3 demonstrates the interplay and trade-offs between the three *aaS models:

• Generally, SaaS provides a large amount of integrated features built directly into the offering with the least amount of extensibility and a relatively high level of security.

• PaaS generally offers less integrated features since it is designed to enable developers to build their own applications on top of the platform and is therefore more extensible than SaaS by nature, but due to this balance trades off on security features and capabilities.

• IaaS provides few, if any, application-like features, provides for enormous extensibility but generally less security capabilities and functionality beyond protecting the infrastructure itself since it expects operating systems, applications and content to be managed and secured by the consumer.

The key takeaway from a security architecture perspective in comparing these models is that the lower down the stack the Cloud service provider stops, the more security capabilities and management the consumer is responsible for implementing and managing themselves.

This is critical because once a Cloud service can be classified and referenced against the model, mapping the security architecture, business and regulatory or other compliance requirements against it becomes a gap-analysis exercise to determine the general “security” posture of a service and how it relates to the assurance and protection requirements of an asset.

Figure 4 below shows an example of how mapping a Cloud service can be compared to a catalog of compensating controls to determine what existing controls exist and which do not as provided by either the consumer, the Cloud service provider or another third party.

Once this gap analysis is complete as governed by the requirements of any regulatory or other compliance mandates, it becomes much easier to determine what needs to be done in order to feed back into a risk assessment framework to determine how the gaps and ultimately how the risk should be addressed: accept, transfer, mitigate or ignore.

Conclusion

Understanding how architecture, technology, process and human capital requirements change or remain the same when deploying Cloud Computing services is critical.   Without a clear understanding of the higher-level architectural implications of Cloud services, it is impossible to address more detailed issues in a rational way.

The keys to understanding how Cloud architecture impacts security architecture are a common and concise lexicon coupled with a consistent taxonomy of offerings by which Cloud services and architecture can be deconstructed, mapped to a model of compensating security and operational controls, risk assessment and management frameworks and in turn, compliance standards.

It’s that time again.  I am compelled after witnessing certain behaviors to play anthropologist and softly whisper my observations in your ear.

You may be familiar with Beckett’s “Waiting For Godot”*:

Waiting for Godot follows two days in the lives of a pair of men who divert themselves while they wait expectantly and unsuccessfully for someone named Godot to arrive. They claim him as an acquaintance but in fact hardly know him, admitting that they would not recognise him were they to see him. To occupy themselves, they eat, sleep, converse, argue, sing, play games, exercise, swap hats, and contemplate suicide — anything “to hold the terrible silence at bay”

Referencing my prior post about the state of Cloud security, I’m reminded of the fact that as a community of providers and consumers, we continue to wait for the security equivalent of Godot to arrive and solve all of our attendant Cloud security challenges with the offer of some mythical silver bullet.  We wait and wait for our security Godot as I mix metaphors and butcher Beckett’s opus to pass the time.

Here’s a classic illustration of hoping our way to Cloud security from a ComputerWeekly post titled “Cryptography breakthrough paves way to secure cloud services:”

A research student who had a summer job at IBM, has cracked a cryptography problem that has baffled experts for over 30 years. The breakthrough may pave the way to secure cloud computing services.

This sounds fantastic and much has been written about this “homomorphic encryption,” with many people espousing how encryption will “solve our Cloud security problems.”

It’s a very interesting concept, but as to paving the “…path to secure cloud computing,” the reality is that it won’t.  At least not in isolation and not without some serious scale in ancillary support mechanisms including non-trivial issues like federated identity.

Bruce Schneier wades in with his assessment:

Unfortunately — you knew that was coming, right? — Gentry’s scheme is completely impractical…Despite this, IBM’s PR machine has been in overdrive about the discovery. Its press release makes it sound like this new homomorphic scheme is going to rewrite the business of computing: not just cloud computing, but “enabling filters to identify spam, even in encrypted email, or protection information contained in electronic medical records.” Maybe someday, but not in my lifetime.

The reality is that in addition to utilizing encryption — both existing and new approaches — we still continue to need all the usual suspects as they deal with the fact that fundamentally we’re still in a cycle of constructing insecure code in infostructure sitting atop infrastructure and metastructure that has its own fair share of growing up to do.

As a security architect, engineer, or manager, you need to continue to invest in understanding how what you have does or does not work within the context of Cloud.

You will likely find that you will need to continue to invest in threat and trust models analysis, risk management, vulnerability assessment, (id)entity management, compensating controls implemented as hardware and software technology solutions such as firewalls, IDP, DLP, and policy instantiation, etc. as well as host of modified and new approaches to dealing with Cloud-specific implementation challenges, especially those based on virtualization and massive scale with multitenancy.

These problems don’t solve themselves and we are simply not changing our behavior.  We wait and wait for our Godot.

So here’s the obligatory grumpy statement of the obvious as providers of solutions and services churn to deliver more capable solutions to put in your hands:

There is no silver bullet, just a lot of silver buckshot.  Use it all.  You’re going to have to deal with the cards we are dealt for the foreseeable future whilst we retool our approach in the longer term and technology equalizes some of our shortfalls.

Godot is not coming and you likely wouldn’t recognize him if he showed up anyway because he’d be dressed in homomorphic invisible hotpants…

Get on with it.  Treat security as the enterprise architecture element it is and use Cloud as the excuse to make things better by working on the things that matter.

If Godot does happen to show up, tell him I want my weed whacker back that he borrowed last summer.

/Hoff

* Wikipedia

There are voices raging in my head thanks to the battling angel and devil sitting on my shoulders.

These voices echo the security-focused protagonist and antagonist perspectives of Cloud Computing adoption.

The devil urges immediate adoption and suggests the Cloud is as (in)secure as it needs to be while still providing value.

The angel maintains that the Cloud, whilst a delightful place to vacation, is ready only for those who are pure of heart and traffic in non-sensitive, non-mission-critical data.

To whom do I (or we) listen?

The answer is a measured and practical one that we know already because we’ve given it many times before.

Is the Cloud Secure?  That’s  a silly question.  Is the Cloud “secure enough” is really the question that should be asked, and of course,  the answer is entirely contextual.

My co-worker, James Urquhart, wrote a great post today in which he summarized quite a few healthy debates that are good for Cloud Computing as they encourage discourse and debate.  One of them relates to the difference between the consumer and small/midsize business versus enterprise as it relates to Cloud adoption.  This is quite relevant to my point about “context” above, so for the purpose of this discussion, I’m referring to the enterprise.

To wit, enterprises aren’t as dumb as (we) vendors want them to be; they seize opportunity as it befits them and most times apply a reasonable amount of due care, diligence and evaluation before they leap headlong into course corrections offered by magical disruptive innovation.  There are market dynamics at play that are predictable and yet so many times we collectively gasp at the patterns of behaviors of technology adoption as though we’ve never witnessed them before.

Cloud is no different in that regard.  See my post regarding this behavior titled “Most CIO’s Not Sold On Cloud?  Good, They Shouldn’t Be.”

When I see commentary from CEO’s of leading security companies (such as RSA’s Art Coviello and even my own, John Chambers) that highlight security as an enormous concern in Cloud, I urge people to reflect back on any of the major shifts they’ve seen in IT the last 15 years and consider which shoulder-chirper they listened to and why.

Suggesting that enterprises aren’t already conscious of what the Cloud means to their operational and security models is intellectually dishonest, really.

We’ve all seen convenience, agility and economics stomp all over security before and here’s how this movie will play out:

Cloud will reach a critical mass wherein the technology and operational models mature to a good-enough point, enough time passes without a significant number of material breaches or outages that disrupt confidence and then it becomes “accepted.”  Security, based upon how, where, why and when we invest will always play catch-up.  How much depends on how good a job we do to push the agenda.

The reality is that broad warnings about security in the Cloud are fine; they help remind and reinforce the fact that we need to do better, and quite frankly, I think we are.  So we can either chirp about how bad things are, or we can do something about it.

The good news is that even with the froth and churn, there is such a groundswell of activity by many groups (like the Cloud Security Alliance and the Jericho Forum) that we’re seeing an unprecedented attempt by both suppliers and consumers to do a better job of baking security in earlier.  The problem is that many people can’t see the forest for the trees; expectations of how quickly things can change are distorted and so everything appears to be an instant failure.  That’s sad.

Of course Cloud Security is not perfect, but in measure, the dialog, push for standards and recognition of need (as well as many roadmapped solutions I’m privy to) shows me that our overall response is a heck of a lot better that I’ve seen it in the past.

We’re certainly still playing catch up on the technology front and working toward better ways of dealing with instantiating business process on top of it all, but I’m quite optimistic that we’re compressing the timeframe of defining and ultimately delivering improved security capabilities in Cloud computing.

In the meantime, the compelling market forces of Cloud continue to steamroll onward, and so these apocalyptic assessments of Cloud Security readiness are irrelevant as we continue to see companies large and small utilize Cloud Computing to do things faster, better, more efficiently, cost effectively and with a level of security that meets their needs, which in the end is all that matters.

At the same point — and this is where the devil will prove out in the details — execution is what matters.

/Hoff

I’ve covered this before in more complex terms, but I thought I’d reintroduce the topic due to a very relevant discussion I just had recently (*cough cough*)

So here’s an interesting scenario in virtualized and/or Cloud environments that make use of virtual appliances to provide security capabilities*:

Since virtual appliances (VAs) are just virtual machines (VMs) what happens when a SysAdmin spins down or moves one that happens to be your shiny new firewall protecting your production VMs behind it, accidentally or maliciously?  Brings new meaning to the phrase “failing closed.”

Without getting into the vagaries of vendor specific mobility-enabled/enabling technologies, one of the issues with VMs/VAs is that there’s not really a good way of designating one as being “more important” or functionally differentiated such as “security” or “critical application” that would otherwise ensure a higher priority for service availability (read: don’t spin this down unless…) or provide a topological dependency hierarchy in virtualized network constructs.

Unlike physical environments where system administrators (servers) are segregated from access to network and security appliances, this isn’t the case in virtual environments. In Cloud environments (especially public, multi-tenant) where we are often reliant only upon virtual security capabilities since we have no option for physical alternatives, this is an interesting corner case.

We’ve talked a lot about visibility, audit and policy management in virtual environments and this is a poignant example.

/Hoff

*Despite the silly notion that the Google dudes tried to suggest I equated virtualization with Cloud as one-in-the-same, I don’t.

I recently read a story from Kelly Jackson Higgins of Dark Reading outlining what are described as the “Six Worst Cloud Security Mistakes:”

1. Assuming the cloud is less secure than your data
2. Not verifying, testing, or auditing the security of your cloud-based service provider.
3. Failing to vet your cloud provider’s viability as a business.
4. Assuming you’re no longer responsible for securing data once it’s in the cloud.
5. Putting insecure apps in the cloud and expecting that to make them more secure.
6. Having no clue that your business units are already using some cloud-based services.

A very interesting list, for sure, and a reasonable set of potential “mistakes” to ponder, but I’m really having trouble with one in particular.

The one that’s getting my goose honking is #1: Assuming the cloud is less secure than your data.

Really? I maintain that this generalization about Cloud being more or less secure (in regards to one’s own capabilities) is a silly thing to argue; let’s see why.

We start off with what I think is a strange bit of contradiction:

It’s only natural for security pros to be control freaks. Being charged with securing a company’s data and intellectual property requires a healthy dose of paranoia and protectionism. But sometimes that leads to false impressions about cloud security. “One common mistake is that as soon as you talk about the cloud, [organizations] assume it’s less secure than their own IT security operation,” says Chenxi Wang, principal analyst at Forrester Research. “More control does not necessarily lead to more security.”

Assuming that one of the reasons a company might consider outsourcing their IT security operations to a third party [Cloud] provider IS the fact that they have more control or at least equal to what a company can provide themselves, it occurs to me this sort of statement can be interpreted many ways.  Here’s one, for example.

I find myself confused by the highlighted sentence regarding control and security within the context of what is written.  In fact, if you read the next paragraph, it seems to imply that the because a Cloud provider has more control they can offer better security:

In fact, with services such as Google’s SaaS, data loss is less likely because the information is accessible from anywhere and anytime without saving it to an easily lost or stolen USB stick or CD, according to Eran Feigenbaum, director of security for Google Apps. And Google’s security-patching process is more streamlined than a typical enterprise because its server architecture is homogeneous, he says. “Many attacks [come from a] lack of patch management and server misconfiguration…For Google, when the time comes to patch, we can do so across the entire platform in a uniform fashion,” he said.

I’ll say it again: SaaS is a convenient way of dumbing down “Cloud Computing” to a singular instance/application/service but it completely obviates Platform and Infrastructure as a Service offerings, which are wildly different animals, especially from a security perspective.  Please see my latest commentary about this in my response to Bruce Schneier’s equation of SaaS with Cloud Computing to the exclusion of PaaS/IaaS.

I’ve made the point before that comparing managing/patching a single application and its supporting infrastructure in a SaaS offering to an enterprise that would otherwise have to support not only that service but potentially hundreds more is a completely unfair comparison.  If you want to compare apples to apples, I’d maintain that any organization with a mature security program whose only charter was to support (securely) a single application could do it just as well as a SaaS provider, all other things being equal.

The differences here become scale and multi-tenancy in the case of the Cloud provider, I think these issues actually make a Cloud environment more difficult to secure.

Also, suggesting with the Google example that “data loss is less likely” because it’s “accessible from anywhere” and doesn’t involve “…lost or stolen USB stick(s) or CD(s)” seems an awfully arbitrary one given the fact that one of the most interesting data loss/leakage incidents in recent Cloud history came from Google’s Docs offering due to an operator (Google) system misconfiguration.  USB sticks and CDs are also a very narrow definition of data loss/leakage.

Then there’s the more global view SaaS and other cloud providers have, Feigenbaum says. “As an enterprise, you only see a small slice of what’s affecting you [threat-wise],” Feigenbaum said during a panel on cloud security at the RSA Conference in April. “A cloud provider can have the economy of scale for a holistic vision…the cloud shifts security and also makes it better,” he said.

I don’t have anything to argue about here; a wider perspective and better visibility is a good thing.  Again, however, this depends upon the type of service, what is being monitored and protected, on behalf of whom and from whom.

But that doesn’t mean you should blindly trust your cloud provider, though the larger ones do tend to have a better handle on threats due to their size, Forrester’s Wang says. “These people deal with security issues at more complex levels than your own IT team sees on a daily basis,” Wang says. “It’s a misconception to say cloud security is definitely less capable or more problematic.”

No, you shouldn’t blindly trust your providers but that last statement suggests we should similary trust that providers do a better job and deal with security issues at more complex levels?  What does that even mean? Please do NOT tell me that a SAS70 Type II is your answer.  Just as “It’s a misconception to say cloud security is definitely less capable or more problematic,” I can just as easily suggest the converse is true without evidence.

I would like to see the empirical data that backs that set of statements up and the common metrics I can use to measure across providers and enterprises alike.  Thought so.

Thus far, security has been one of the main hurdles to adoption of cloud-based services, says Michelle Dennedy, chief governance officer for cloud computing at Sun Microsystems. “Trust in the cloud, more than technical abilities, has been hindering adoption,” Dennedy says. “But the cloud can be more secure than a private environment in many cases.”

Michelle is definitely correct; trust represents a fundamental issue with Cloud adoption, and it rolls both ways.  Asking us to “trust but verify” when what we’re being asked to verify can’t easily be trusted poses a very difficult scenario indeed.

By the way, I think the worst Cloud Security mistake is not knowing what Cloud Security even means.

/Hoff

Update: Please see this post if you’re wondering why I edited this piece.

I read a recent story in the Guardian from Bruce Schneier titled “Be Careful When You Come To Put Your Trust In the Clouds” in which he suggests that Cloud Computing is “…nothing new.”

Fundamentally it’s hard to argue with that title as clearly we’ve got issues with security and trust models as it relates to Cloud Computing, but the byline seems to be at odds with Schneier’s ever-grumpy dismissal of Cloud Computing in the first place.  We need transparency and trust: got it.

Many of the things Schneier says make perfect sense whilst others just make me scratch my head in abstract.  Let’s look at a couple of them:

This year’s overhyped IT concept is cloud computing. Also called software as a service (Saas), cloud computing is when you run software over the internet and access it via a browser. The salesforce.com customer management software is an example of this. So is Google Docs. If you believe the hype, cloud computing is the future.

Clearly there is a lot of hype around Cloud Computing, but I believe it’s important — especially as someone who spends a lot of time educating and evangelizing — that people like myself and Schneier effectively separate the hype from the hope and try and paint a clearer picture of things.

To that point, Schneier does his audience a disservice by dumbing down Cloud Computing to nothing more than outsourcing via SaaS.  Throwing the baby out with the rainwater seems a little odd to me and while it’s important to relate to one’s audience, I keep sensing a strange cognitive dissonance whilst reading Schneier’s opining on Cloud.

Firstly, and as I’ve said many times, Cloud Computing is more than just Software as a Service (SaaS.)  SaaS is clearly the more mature and visible set of offerings in the evolving Cloud Computing taxonomy today, but one could argue that players like Amazon with their Infrastructure as a Service (IaaS) or even the aforementioned Google and Salesforce.com with the Platform as a Service (PaaS) offerings might take umbrage with Schneier’s suggestion that Cloud is simply some “…software over the internet” accessed “…via a browser.”

Overlooking IaaS and PaaS is clearly a huge miss here and it calls into question the point Schneier makes when he says:

But, hype aside, cloud computing is nothing new . It’s the modern version of the timesharing model from the 1960s, which was eventually killed by the rise of the personal computer. It’s what Hotmail and Gmail have been doing all these years, and it’s social networking sites, remote backup companies, and remote email filtering companies such as MessageLabs. Any IT outsourcing – network infrastructure, security monitoring, remote hosting – is a form of cloud computing.

The old timesharing model arose because computers were expensive and hard to maintain. Modern computers and networks are drastically cheaper, but they’re still hard to maintain. As networks have become faster, it is again easier to have someone else do the hard work. Computing has become more of a utility; users are more concerned with results than technical details, so the tech fades into the background.

<sigh> Welcome to the evolution of technology and disruptive innovation.  What’s the point?

Fundamentally, as we look beyond speeds and feeds, Cloud Computing — at all layers and offering types — is driving huge headway and innovation in the evolution of automation, autonomics and the applied theories of dealing with massive scale in compute, network and storage realms.  Sure, the underlying problems — and even some of the approaches — aren’t new in theory, but they are in practice.  The end result may very well be that a consumer of service may not see elements that are new technologically as they are abstracted, but the economic, cultural, business and operational differences are startling.

If we look at what makes up Cloud Computing, the five elements I always point to are:

Certainly the first three are present today — and have been for some while — in many different offerings.  However, combining the last two: on-demand, self-service scale and dynamism with new economic models of consumption and allocation are quite different, especially when doing so at extreme levels of scale with multi-tenancy.

So let’s get to the meat of the matter: security and trust.

But what about security? Isn’t it more dangerous to have your email on Hotmail’s servers, your spreadsheets on Google’s, your personal conversations on Facebook’s, and your company’s sales prospects on salesforce.com’s? Well, yes and no.

IT security is about trust. You have to trust your CPU manufacturer, your hardware, operating system and software vendors – and your ISP. Any one of these can undermine your security: crash your systems, corrupt data, allow an attacker to get access to systems. We’ve spent decades dealing with worms and rootkits that target software vulnerabilities. We’ve worried about infected chips. But in the end, we have no choice but to blindly trust the security of the IT providers we use.

Saas moves the trust boundary out one step further – you now have to also trust your software service vendors – but it doesn’t fundamentally change anything. It’s just another vendor we need to trust.

Fair enough.  So let’s chalk one up here to “Cloud is nothing new — we still have to put our faith and trust in someone else.”  Got it.  However, by again excluding the notion of PaaS and IaaS, Bruce fails to recognize the differences in both responsibility and accountability that these differing models brings; limiting Cloud to SaaS while simple for cute argument does not a complete case make:

To what level you are required to and/or feel comfortable transferring responsibility depends upon the provider and the deployment model; the risks associated with an IaaS-based service can be radically different than that of one from a SaaS vendor. With SaaS, security can be thought of from a monolithic perspective — that of the provider; they are responsible for it.  In the case of PaaS and IaaS, this trade-off’s become more apparent and you’ll find that this “outsourcing” of responsibility is diminished whilst the mantle of accountability is not.  This is pretty important if you want ot be generic in your definition of “Cloud.”

Here’s where I see Bruce going off the rails from his “Cloud is nothing new” rant, much in the same way I’d expect he would suggest that virtualization is nothing new, either:

There is one critical difference. When a computer is within your network, you can protect it with other security systems such as firewalls and IDSs. You can build a resilient system that works even if those vendors you have to trust may not be as trustworthy as you like. With any outsourcing model, whether it be cloud computing or something else, you can’t. You have to trust your outsourcer completely. You not only have to trust the outsourcer’s security, but its reliability, its availability, and its business continuity.

You don’t want your critical data to be on some cloud computer that abruptly disappears because its owner goes bankrupt . You don’t want the company you’re using to be sold to your direct competitor. You don’t want the company to cut corners, without warning, because times are tight. Or raise its prices and then refuse to let you have your data back. These things can happen with software vendors, but the results aren’t as drastic.

…
Trust is a concept as old as humanity, and the solutions are the same as they have always been. Be careful who you trust, be careful what you trust them with, and be careful how much you trust them. Outsourcing is the future of computing. Eventually we’ll get this right, but you don’t want to be a casualty along the way.

So therefore I see a huge contradiction.  How we secure — or allow others to — our data is very different in Cloud, it *is* something new in its practical application.   There are profound operational, business and technical (let alone regulatory, legal, governance, etc.) differences that do pose new challenges. Yes, we should take our best practices related to “outsourcing” that we’ve built over time and apply them to Cloud.  However, the collision course of virtualization, converged fabrics and Cloud Computing are pushing the boundaries of all we know.

Per the examples above, our challenges are significant.  The tech industry thrives on the ebb and flow of evolutionary punctuated equilibrium; what’s old is always new again, so it’s important to remember a couple of things:

1. Harking back (a whopping 60 years) to the “dawn of time” in the IT/Computing industry making the case that things “aren’t new” is sort of silly and simply proves you’re the tallest and loudest guy in a room full of midgets.  Here’s your sign.
2. I don’t see any suggestions for how to make this better in all these rants about mainframes, only FUD
3. If “outsourcing is the future of computing” and we are to see both evolutionary and revolutionary disruptive innovation, shouldn’t we do more than simply hope that “…eventually we’ll get this right?”

The past certainly repeats itself, which explains why every 20 years bell-bottoms come back in style…but ignoring the differences in application, however incremental, is a bad idea.  In many regards we have not learned from our mistakes or fail to recognize patterns, but you can’t drive forward by only looking in the rear view mirror, either.

Regards,

/Hoff

Simon Crosby and I were interviewed by Mike Mimoso of SearchSecurity.com at the RSA conference.  This was after a panel at the America’s Growth Capital conference and prior to our debate which included Steve Herrod of VMware.

It’s a two-part video that got a bit munged when the cameraman let the tape run out about 1/2 way through 😉

Part 1 can be found here.

Part 2 can be found here.

In my Four Horsemen presentation, I made reference to one of the challenges with how the networking function is being integrated into virtual environments.  I’ve gone on to highlight how this is exacerbated in Cloud networking, also.

Specifically, as it comes to understanding how the network plays in virtual and Cloud architectures, it’s not where the network *is* in the increasingly complex virtualized, converged and unified computing architectures, it’s where networking *isn’t.*

What do I mean by this?  Here’s a graphical representation that I built about a year ago.  It’s well out-of-date and overly-simplified, but you get the picture:

There’s networking at almost every substrate level — in the physical and virtual construct.  In our never-ending quest to balance performance, agility, resiliency and security, we’re ending up with a trade-off I call simplexity: the most complex simplicity in networking we’ve ever seen.   I wrote about this in a blog post last year titled “The Network Is the Computer…(Is the Network, Is the Computer…)”

If you take a look at some of the more recent blips to appear on the virtual and Cloud networking  radar, you’ll see examples such as:

• Cisco’s UCS with converged 10Gb/s Ethernet/FCOE including the Nexus 1000v virtual switch and VN-Link (and upcoming VN-Tag)
• The Forthcoming Citrix/Xen/KVM Virtual Networking Stack 
• Blade Network Technology’s SmartConnect™ and VMready™ 
• Arista Networks Cloud Networking Solutions
• Netronome’s Network Flow Processors for Unified Computing 

This list is far from inclusive.  Yes, I know I’ve left off blade server manufacturers and other players like HP (ProCurve) and Juniper, etc.  as well as ADC vendors like f5.  It’s not that I don’t appreciate their solutions, it’s just that I have a couple of free cycles to write this, and the list above appear on the top of my stack.

I plan on writing in more detail about the impact some of these technologies are having on next generation datacenters and Cloud deployments, as it’s a really interesting subject for me coming from my background at Crossbeam.

The most startling differences are in the approach of either putting the networking (and all its attendant capabilities) back in the hands of the network folks or allowing the server/virtual server admins to continue to leverage their foothold in the space and manage the network as a component of the converged and virtualized solution as a whole.

My friend @aneel (Twitter)  summed it up really well this morning when comparing the Blade Network Technology VMready offering and the Cisco Nexus 100ov:

huh.. where cisco uses nx1kv to put net control more in hands of net ppl, bnt uses vmready to put it further in server/virt admin hands

Looking at just the small sampling of solutions above, we see the diversity in integrated networking, external fabrics, converged fabrics (including storage) and add-on network processors.

It’s going to be a wild ride kids.  Buckle up.

/Hoff