Archive

Archive for the ‘Virtualization Security’ Category

Don’t Hassle the Hoff: Recent Press & Podcast Coverage & Upcoming Speaking Engagements

October 26th, 2009 1 comment

Microphone

Here is some of the recent coverage from the last month or so on topics relevant to content on my blog, presentations and speaking engagements.  No particular order or priority and I haven’t kept a good record, unfortunately.

Press/Technology & Security eZines/Website/Blog Coverage/Meaningful Links:

Podcasts/Webcasts/Video:

Recent Speaking Engagements/Confirmed to  speak at the following upcoming events:

  • Enterprise Architecture Conference, D.C.
  • Intel Security Summit 2009, Hillsboro OR
  • SecTor 2009, Toronto CA
  • EMC Innovation Forum, Franklin MA
  • NY Technology Forum, NY, NY
  • Microsoft Bluehat v9, Redmond WA
  • Office of the Comptroller & Currency, San Antonio TX
  • Intercloud Working Group, GooglePlex CA 😉
  • CSC Leading Edge Forum, VA
  • DojoCon, VA

I also forgot to thank Eric Siebert for putting together the VMware Top 20 blog list and putting me on it as well as the fact that Rational Survivability made the Datamation 2009 Top 200 Tech Blogs list.

/Hoff

Incomplete Thought: The Cloud Software vs. Hardware Value Battle & Why AWS Is Really A Grid…

October 18th, 2009 2 comments

Some suggest in discussing the role and long-term sustainable value of infrastructure versus software in cloud that software will marginalize bespoke infrastructure and the latter will simply commoditize.

I find that an interesting assertion, given that it tends to ignore the realities that both hardware and software ultimately suffer from a case of Moore’s Law — from speeds and feeds to the multi-core crisis, this will continue ad infinitum.  It’s important to keep that perspective.

In discussing this, proponents of software domination almost exclusively highlight Amazon Web Services as their lighthouse illustration.  For the purpose of simplicity, let’s focus on compute infrastructure.

Here’s why pointing to Amazon Web Services (AWS) as representative of all cloud offerings in general to anchor the hardware versus software value debate is not a reasonable assertion:

  1. AWS delivers a well-defined set of services designed to be deployed without modification across a massive number of customers; leveraging a common set of standardized capabilities across these customers differentiates the service and enables low cost
  2. AWS enjoys general non-variability in workload from *their* perspective since they offer fixed increments of compute and memory allocation per unit measure of exposed abstracted and virtualized infrastructure resources, so there’s a ceiling on what workloads per unit measure can do. It’s predictable.
  3. From AWS’ perspective (the lens of the provider) regardless of the “custom stuff” running within these fixed-sized containers, the main focus of their core “cloud” infrastructure actually functions like a grid — performing what amounts to a few tasks on a finely-tuned platform to deliver such
  4. This yields the ability for homogeneity in infrastructure and a focus on standardized and globalized power efficient, low cost, and easy-to-replicate components since the problem of expansion beyond a single unit measure of maximal workload capacity is simply a function of scaling out to more of them (or stepping up to one of the next few rungs on the scale-up ladder)

Yup, I just said that AWS is actually a grid whose derivative output is a set of cloud services.

Why does this matter?  Because not all IaaS cloud providers are architected to achieve this — by design — and this has dramatic impact on where hardware and software, leveraged independently or as a total solution, play in the debate.

This is because AWS built and own the entire “CloudOS” stack from customized hardware through to the VMM, management and security planes (much as Google does the same) versus other providers who use what amounts to more generic software offerings from the likes of VMware and lean on API’s and an ecosystem to extend it’s capabilities as well as big iron to power it.  This will yield more customizable offerings that likely won’t scale as highly as AWS.

That’s because they’re not “grids” and were never designed to be.

Many other IaaS providers that have evolved from hosting are building their next-generation offerings from unified fabric and unified computing platforms (so-called “big iron”) which are the furtherest thing from “commodity” hardware you can get.  Further, SaaS and PaaS providers generally tend to do the same based on design goals and business models.  Remember, IaaS is not representative of all things cloud — it’s only one of the service models.

Comparing AWS to most other IaaS cloud providers is a false argument upon which to anchor the hardware versus software debate.

/Hoff

Cloud Providers and Security “Edge” Services – Where’s The Beef?

September 30th, 2009 16 comments

usbhamburgerPreviously I wrote a post titled “Oh Great Security Spirit In the Cloud: Have You Seen My WAF, IPS, IDS, Firewall…” in which I described the challenges for enterprises moving applications and services to the Cloud while trying to ensure parity in compensating controls, some of which are either not available or suffer from the “virtual appliance” conundrum (see the Four Horsemen presentation on issues surrounding virtual appliances.)

Yesterday I had a lively discussion with Lori MacVittie about the notion of what she described as “edge” service placement of network-based WebApp firewalls in Cloud deployments.  I was curious about the notion of where the “edge” is in Cloud, but assuming it’s at the provider’s connection to the Internet as was suggested by Lori, this brought up the arguments in the post
above: how does one roll out compensating controls in Cloud?

The level of difficulty and need to integrate controls (or any “infrastructure” enhancement) definitely depends upon the Cloud delivery model (SaaS, PaaS, and IaaS) chosen and the business problem trying to be solved; SaaS offers the least amount of extensibility from the perspective of deploying controls (you don’t generally have any access to do so) whilst IaaS allows a lot of freedom at the guest level.  PaaS is somewhere in the middle.  None of the models are especially friendly to integrating network-based controls not otherwise supplied by the provider due to what should be pretty obvious reasons — the network is abstracted.

So here’s the rub, if MSSP’s/ISP’s/ASP’s-cum-Cloud operators want to woo mature enterprise customers to use their services, they are leaving money on the table and not fulfilling customer needs by failing to roll out complimentary security capabilities which lessen the compliance and security burdens of their prospective customers.

While many provide commoditized solutions such as anti-spam and anti-virus capabilities, more complex (but profoundly important) security services such as DLP (data loss/leakage prevention,) WAF, Intrusion Detection and Prevention (IDP,) XML Security, Application Delivery Controllers, VPN’s, etc. should also be considered for roadmaps by these suppliers.

Think about it, if the chief concern in Cloud environments is security around multi-tenancy and isolation, giving customers more comfort besides “trust us” has to be a good thing.  If I knew where and by whom my data is being accessed or used, I would feel more comfortable.

Yes, it’s difficult to do properly and in many cases means the Cloud provider has to make a substantial investment in delivery platforms and management/support integration to get there.  This is why niche players who target specific verticals (especially those heavily regulated) will ultimately have the upper hand in some of these scenarios – it’s not socialist security where “good enough” is spread around evenly.  Services like these need to be configurable (SELF-SERVICE!) by the consumer.

An example? How about Google: where’s DLP integrated into the messaging/apps platforms?  Amazon AWS: where’s IDP integrated into the VMM for introspection?

I wrote a couple of interesting posts about this (that may show up in the automated related posts lists below):

My customers in the Fortune 500 complain constantly that the biggest providers they are being pressured to consider for Cloud services aren’t listening to these requests — or aren’t in a position to respond.

That’s bad for everyone.

So how about it? Are services like DLP, IDP, WAF integrated into your Cloud providers’ offerings something you’d like to see rather than having to add additional providers as brokers and add complexity and cost back into Cloud?

/Hoff

The Emotion of VMotion…

September 29th, 2009 8 comments
VMotion - Here's Where We Are Today

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

Redux: Patching the Cloud

September 23rd, 2009 3 comments

Back in 2008 I wrote a piece titled “Patching the Cloud” in which I highlighted the issues associated with the black box ubiquity of Cloud and what that means to patching/upgrading processes:

Your application is sitting atop an operating system and underlying infrastructure that is managed by the cloud operator.  This “datacenter OS” may not be virtualized or could actually be sitting atop a hypervisor which is integrated into the operating system (Xen, Hyper-V, KVM) or perhaps reliant upon a third party solution such as VMware.  The notion of cloud implies shared infrastructure and hosting platforms, although it does not imply virtualization.

A patch affecting any one of the infrastructure elements could cause a ripple effect on your hosted applications.  Without understanding the underlying infrastructure dependencies in this model, how does one assess risk and determine what any patch might do up or down the stack?  How does an enterprise that has no insight into the “black box” model of the cloud operator, setup a dev/test/staging environment that acceptably mimics the operating environment?

What happens when the underlying CloudOS gets patched (or needs to be) and blows your applications/VMs sky-high (in the PaaS/IaaS models?)

How does one negotiate the process for determining when and how a patch is deployed?  Where does the cloud operator draw the line?   If the cloud fabric is democratized across constituent enterprise customers, however isolated, how does a cloud provider ensure consistent distributed service?  If an application can be dynamically provisioned anywhere in the fabric, consistency of the platform is critical.

I followed this up with a practical example when Microsoft’s Azure services experienced a hiccup due to this very thing.  We see wholesale changes that can be instantiated on a whim by Cloud providers that could alter service functionality and service availability such as this one from Google (Published Google Documents to appear in Google search) — have you thought this through?

So now as we witness ISP’s starting to build Cloud service offerings from common Cloud OS platforms and espouse the portability of workloads (*ahem* VM’s) from “internal” Clouds to Cloud Providers — and potentially multiple Cloud providers — what happens when the enterprise is at v3.1 of Cloud OS, ISP A is at version 2.1a and ISP B is at v2.9? Portability is a cruel mistress.

Pair that little nugget with the fact that even “global” Cloud providers such as Amazon Web Services have not maintained parity in terms of functionality/services across their regions*. The US has long had features/functions that the european region has not.  Today, in fact, AWS announced bringing infrastructure capabilities to parity for things like elastic load balancing and auto-scale…

It’s important to understand what happens when we squeeze the balloon.

/Hoff

*corrected – I originally said “availability zones” which was in error as pointed out by Shlomo in the comments. Thanks!

Quick Question: Any Public Cloud Providers Using Intel TXT?

September 15th, 2009 3 comments

Does anyone know of any Public Cloud Provider (or Private for that matter) that utilizes Intel’s TXT?

Specifically, does anyone know if Amazon makes use of Intel’s TXT via their Xen-derivative VMM?

Anyone care to share whether they know of any Cloud provider that PLANS to?

Thanks in advance.

Email responses welcome also [hoff @ packetfilter .com]

/Hoff

NESSessary Question: Will Virtualization Undermine Network Equipment Vendors?

August 30th, 2009 1 comment

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?

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, VyattaArista with vEOS and Cisco with the Nexus 1000v*…interesting times for sure.

/Hoff

*Disclosure: I work for Cisco.

Cloud Computing [Security] Architectural Framework

July 19th, 2009 3 comments

CSA-LogoFor 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


Problem Statement

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

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

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

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 - 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.

Figure 4 - Mapping the Cloud Model to the Security Model
Figure 4 – Mapping the Cloud Model to the Security Model

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.


[1] Credit: Peter M. Mell, NIST

Hey, Uh, Someone Just Powered Off Our Firewall Virtual Appliance…

June 11th, 2009 11 comments

onoffswitchI’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.

Virtual Networking Battle Heating Up: Citrix Leads $10 Million Investment In Vyatta

June 9th, 2009 No comments

Those crafty Citrix chaps are at it again.

Last month I reported from Citrix Synergy about discussions I had with Simon Crosby and Ian Pratt about the Citrix/Xen Openswitch which is Citrix’s answer to the Cisco Nexus 1000v married to VMware’s vSphere.

Virtualization.com this morning reported that Vyatta — who describe themselves as the “open source alternative to Cisco” — just raised another round of funding, but check out who’s leading it:

Vyatta today announced it has completed its $10 million Series C round of financing led by Citrix Systems. The new funding round also includes existing investors, Comcast Interactive Capital, Panorama Capital, and ArrowPath Venture Partners. As part of the investment, Gordon Payne, senior vice president and general manager of the Delivery Systems Division at Citrix, has joined the Vyatta Board of Directors where he will assist the company in its next phase of development.

Today, Vyatta also announced that it has joined the Citrix Ready product verification program to create solutions for customers deploying cloud computing infrastructures.

Vyatta will use the funds for operating capital as the company scales its sales efforts and accelerates growth across multiple markets.

Vyatta runs on standard x86 hardware and can be virtualized with modern hypervisors, including the Citrix XenServer™ virtualization platform. Vyatta delivers a full set of networking features that allow customers to connect, protect, virtualize, and optimize their networks, improving performance, reducing costs, and increasing manageability and flexibility over proprietary networking solutions. Vyatta has been deployed by hundreds of customers world-wide in both virtual and non-virtual environments.

This is very, very interesting stuff indeed and it’s clear where Citrix has its sights aimed.  This will be good for customers, regardless of platform because it’s going to drive innovation even further.

The virtual networking stacks — and what they enable — are really going to start to drive significant competitive advantage across virtualization and Cloud vendors.  It’s ought to give customers significant pause when it comes to thinking about their choice of platform and integration.

Nicely executed move, Mr. Crosby.

/Hoff