My Q1 2022 research agenda
This is the time of year when AR professionals ask analysts what they’re planning for next year. I don’t plan a year in advance. I tend not to even plan a quarter in advance. I write when the mood seizes me, which is probably unfortunate, but given that I write a lot it’s… okay-ish?
But I have a bunch of things drafted (either fully or partially) and that should get released in Q1 of next year. I have a general goal of trying to ensure that I back the advice I write for cloud architects with something for the CIO and other executive leaders that provides a bottom-line strategic summary, and/or material for the other teams the architects work with, so that I publish stuff as part of a set, either alone or in collaboration with analysts in other areas.
Cloud resilience (January): It’s increasingly common for clients to ask about architectural standards for HA/DR in the cloud. This note dissects why cloud services break, how to set architectural standards for HA and DR/failover (i.e. when to be multi-AZ, when to do cross-region failover, etc.), and some basic guidance on stability patterns (use of partitioning, bulkheads, backpressure, etc.)
Cloud self-service (January): Thankfully, most organizations are moving away from a service catalog-driven approach to cloud self-service in favor of cloud-native self-service. This note is about how to empower technical teams with self-service, while still providing appropriate governance.
The cloud operating model (February): Many clients are asking about how to organize for the cloud. This will be a triple-note set — one on designing a cloud operating model, one on implementing the operating model, and a colorful infographic summarizing the concept for the CIO and other executive leaders. It combines my previous guidance on Cloud Center of Excellence (CCOE), structuring FinOps and cloud sourcing, etc. with some new work on program management, and takes a deeper look at all the ways you can put this stuff together.
Cloud concentration risk (March): Concentration risk is a hot topic right now, especially in regulated industries. This concern spans IaaS, PaaS, and SaaS, and the dependencies are not always clear, so many organizations have concentration risk they’re not aware of. I intend to write a baseline note that other analysts have committed to contextualizing for audiences in different industries, as well as for cloud managed and professional services providers. While the sourcing risk of concentration remains minimal, the availability risks of concentration can be meaningful. An organization’s risk appetite and the business benefits of concentration should determine what, if any, steps they take to address concentration risk.
IaaS+PaaS provider evaluation update (April): Getting updated vendor evaluation research out in April basically means spending a good chunk of the first quarter doing that evaluation. (My January notes have already been written. And the February ones are mostly complete, so the schedule above isn’t implausible.) We are not currently discussing the form that this evaluation will take. Gartner management will communicate appropriately when the time comes (i.e. please don’t ask me, as I’m not at liberty to discuss it).
Cloud cost overruns may be a business leadership failure
A couple of months back, some smart folks at VC firm Andreesen Horowitz wrote a blog post called “The Cost of Cloud, a Trillion Dollar Paradox“. Among other things, the blog made a big splash because it claimed, quote: “[W]hile cloud clearly delivers on its promise early on in a company’s journey, the pressure it puts on margins can start to outweigh the benefits, as a company scales and growth slows.” It claimed that cloud overspending was resulting in huge loss of market value, and that developers needed incentives to reduce spending.
The blog post is pretty sane, but plenty of people misinterpreted it, or took away only its most sensationalistic aspects. I think it’s critical to keep in mind the following:
Decisions about cloud expenditures are ultimately business decisions. Unnecessarily high cloud costs are the result of business decisions about priorities — specifically, about the time that developers and engineers devote to cost optimization versus other priorities.
For example, when developer time is at a premium, and pushing out features as fast as possible is the highest priority, business leadership can choose to allow the following things that are terrible for cloud cost:
- Developers can ignore all annoying administrative tasks, like rightsizing the infrastructure or turning off stuff that isn’t in active use.
- Architects can choose suboptimal designs that are easier and faster to implement, but which will cost more to run.
- Developers can implement crude algorithms and inefficient code in order to more rapidly deliver a feature, without thinking about performance optimizations that would result in less resource consumption.
- Developers can skip implementing support for more efficient consumption patterns, such as autoscaling.
- Developers can skip implementing deployment automation that would make it easier to automatically rightsize — potentially compounded by implementing the application in ways that are fragile and make it too risky and effortful to manually rightsize.
All of the above is effectively a form of technical debt. In the pursuit of speed, developers can consume infrastructure more aggressively themselves — not bothering to shut down unused infrastructure, running more CI jobs (or other QA tests), running multiple CI jobs in parallel, allocating bigger faster dev/test servers, etc. — but that’s short-term, not an ongoing cost burden the way that the technical debt is. (Note that the same prioritization issues also impact the extent to which developers cooperate in implementing security directives. That’s a tale for another day.)
The more those things are combined — bad designs, poorly implemented, that you can’t easily rightsize or scale — the more that you have a mess that you can’t untangle without significant expenditure of development time.
Now, some organizations will go put together a “FinOps” team to play whack-a-mole with infrastructure — killing/parking stuff that is idle and rightsizing the waste. And that might help short-term, but until you can automate that basic cost hygiene, this is non-value-added people-intensive work. And woe betide you if your implementations are fragile enough that rightsizing is operationally risky.
Once you’ve got your whack-a-mole down to a nice quick automated cadence, you’ve got to address the application design and implementation technical debt — and invest in the discipline of performance engineering — or you’ll continue paying unnecessarily high bills month after month. (You’d also be oversizing on-prem infrastructure, but people are used to that, and the capital expenditure is money spent, versus the grind of a monthly cloud bill.)
Business leaders have to step up to prioritize cloud cost optimization — or acknowledge that it isn’t a priority, and that it’s okay to waste money on resources as long as the top line is increasing faster. As long that’s a conscious, articulated decision, that’s fine. But we shouldn’t pretend that developers are inherently irresponsible. Developers, like other employees, respond to incentives, and if they’re evaluated on their velocity of feature delivery, they’re going to optimize their work efforts towards that end.
For more details, check out my new research note called “Is FinOps the Answer to Cloud Cost Governance?” which is paywalled and targeted at Gartner’s executive leader clients — a combination of CxOs and business leaders.
Refining the Cloud Center of Excellence
What sort of org structures work well for helping to drive successful cloud adoption? Every day I talk to businesses and public-sector entities about this topic. Some have been successful. Others are struggling. And the late-adopters are just starting out and want to get it right from the start.
Back in 2014, I started giving conference talks about an emerging industry best practice — the “Cloud Center of Excellence” (CCOE) concept. I published a research note at the start of 2019 distilling a whole bunch of advice on how to build a CCOE, and I’ve spent a significant chunk of the last year and a half talking to customers about it. Now I’ve revised that research, turning it into a hefty two-part note on How to Build a Cloud Center of Excellence: part 1 (organizational design) and part 2 (Year 1 tasks).
Gartner’s approach to the CCOE is fundamentally one that is rooted in the discipline of enterprise architecture and the role of EA in driving business success through the adoption of innovative technologies. We advocate a CCOE based on three core pillars — governance (cost management, risk management, etc.), brokerage (solution architecture and vendor management), and community (driving organizational collaboration, knowledge-sharing, and cloud best practices surfaced organically).
Note that it is vital for the CCOE to be focused on governance rather than on control. Organizations who remain focused on control are less likely to deliver effective self-service, or fully unlock key cloud benefits such as agility, flexibility and access to innovation. Indeed, IT organizations that attempt to tighten their grip on cloud control often face rebellion from the business that actually decreases the power of the CIO and the IT organization.
Also importantly, we do not think that the single-vendor CCOE approaches (which are currently heavily advocated by the professional services organizations of the hyperscalers) are the right long-term solution for most customers. A CCOE should ideally be vendor-neutral and span IaaS, PaaS, and SaaS in a multicloud world, with a focus on finding the right solutions to business problems (which may be cloud or noncloud). And a CCOE is not an IaaS/PaaS operations organization — cloud engineering/operations is a separate set of organizational decisions (I’ll have a research note out on that soon, too).
Please dive into the research (Gartner paywall) if you are interested in reading all the details. I have discussed this topic with literally thousands of clients over the last half-dozen years. If you’re a Gartner for Technical Professionals client, I’d be happy to talk to you about your own unique situation.
Gartner’s cloud IaaS assessments, 2019 edition
We’ve just completed our 2019 evaluations of cloud IaaS providers, resulting in a new Magic Quadrant, Critical Capabilities, and six Solution Scorecards — one for each of the providers included in the Magic Quadrant. This process has also resulted in fresh benchmarking data within Gartner’s Cloud Decisions tool, a SaaS offering available to Gartner for Technical Professionals clients, which contains benchmarks and monitoring results for many cloud providers.
As part of this, we are pleased to introduce Gartner’s new Solution Scorecards, an updated document format for what we used to call In-Depth Assessments. Solution Scorecards assess an individual vendor solution against our recently-revised Solution Criteria (formerly branded Evaluation Criteria). They are highly detailed documents — typically 60 pages or so, assessing 265 individual capabilities as well as providing broader recommendations to Gartner clients.
The criteria are always divided into Required, Preferred, and Optional categories — essentially, things that everyone wants (and where they need to compensate/risk-mitigate if something is missing), things that most people want but can live without or work around readily, and things that are use case-specific. The Required, Preferred, and Optional criteria are weighted into a 4:2:1 ratio in order to calculate an overall Solution Score.
If you are a Gartner for Technical Professionals client, the scorecards are available to you today. You can access them from the links below (Gartner paywall):
- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
- IBM Cloud
- Oracle Cloud Infrastructure
- Alibaba Cloud International (English-language offerings available outside of China)
We will be providing a comparison of these vendors and their Solution Scorecards at the annual “Cloud Wars” presentation at the Gartner Catalyst conference — one of numerous great reasons to come to San Diego the week of August 11th (or Catalyst UK in London the week of September 15th)! Catalyst has tons of great content for cloud architects and other technical professionals involved in implementing cloud computing.
Note that we are specifically assessing just the integrated IaaS+PaaS offerings — everything offered through a single integrated self-service experience and on a single contract. Also, only cloud services count; capabilities offered as software, hosting, or a human-managed service do not count. Capabilities also have to be first-party.
Also note that this is not a full evaluation of a cloud provider’s entire portfolio. The scorecards have “IaaS” in the title, and the scope is specified clearly in the Solution Criteria. For the details of which specific provider services or products were or were not evaluated, please refer to each specific Scorecard document.
All the scores are current as of the end of March, and count only generally-available (GA) capabilities. Because it takes weeks to work with vendors for them to review and ensure accuracy, and time to edit and publish, some capabilities will have gone beta or GA since that time; because we only score what we’re able to test, the evaluation period has a cut-off date. After that, we update the document text for accuracy but we don’t change the numerical scores. We expect to update the Solution Scorecards approximately every 6 months, and working to increase our cadence for evaluation updates.
This year’s scores vs. last year’s
When you review the scores, you’ll see that broadly, the scores are lower than they were in 2018, even though all the providers have improved their capabilities. There are several reasons why the 2019 scores are lower than in previous years. (For a full explanation of the revision of the Solution Criteria in 2019, see the related blog post.)
First, for many feature-sets, several Required criteria were consolidated into a single multi-part criterion with “table stakes” functionality; missing any part of that criterion caused the vendor to receive a “No” score for that criterion (“Yes” is 1 point; “No” is zero points; there is no partial credit). The scorecard text explains how the vendor does or does not meet each portion of a criterion. The text also mentions if there is beta functionality, or if a feature was introduced after the evaluation period.
Second, many criteria that were Preferred in 2018 were promoted to Required in 2019, due to increasing customer expectations. Similarly, many criteria that were Optional in 2018 are now Preferred. We introduced some brand-new criteria to all three categories as well, but providers that might have done well primarily on table-stakes Required functionality in previous years may have scored lower this year due to the increased customer expectations reflected by revised and new criteria.
Customizing the scores
The solution criteria, with all of the criteria detail, is available to all Gartner for Technical Professionals clients, and comes with a spreadsheet that allows you to score any provider yourself; we also provide a filled-out spreadsheet with each Solution Scorecard so you can adapt the evaluation for your own needs. The Solution Scorecards are similarly transparent on which parts of a criterion are or aren’t met, and we link to documentation that provides evidence for each point (in some cases Gartner was provided with NDA information, in which case we tell you how to get that info from the provider).
This allows you to customize the scores as you see fit. Thus, if you decide that getting 3 out of 4 elements of a criteria is good enough for you, or you think that the thing they miss isn’t relevant to you, or you want to give the provider credit for newly-released capabilities, or you want to do region-specific scoring, you can modify the spreadsheet accordingly.
If you’re a Gartner client and are interested in discussing the solution criteria, assessment process, and the cloud providers, please schedule an inquiry or a 1-on-1 at Catalyst. We’d be happy to talk to you!
Updating Gartner’s cloud IaaS evaluation criteria
In February of this year, we revised the Evaluation Criteria for Cloud IaaS (Gartner paywall). The evaluation criteria (now rebranded Solution Criteria) are essentially the sort of criteria that prospective customers typically include in RFPs. They are highly detailed technical criteria, along with some objectively-verifiable business capabilities (such as elements in a technical support program, enterprise ISV partnerships, ability to support particular compliance requirements, etc.).
The Solution Criteria are intended to help cloud architects evaluate cloud IaaS providers (and integrated IaaS+PaaS providers such as the hyperscale cloud providers), whether public or private, or assess their own internal private cloud. We are about to publish Solution Scorecards (formerly branded In-Depth Assessments) for multiple providers; Gartner analysts assess these solutions hands-on and determine whether or not they have capabilities that meet the requirements of a criterion.
The TL;DR version
In summary, we revised the Solution Criteria extensively in 2019, and the results were as follows:
- The criteria have been updated to reflect the current IaaS+PaaS market.
- Expectations are significantly higher than in previous years.
- Expectations have been aligned to other Gartner research, taking into account customer wants and needs in the relevant market, not just in a cloud-specific context.
- Many capabilities have been consolidated and are now required.
- Most vendor scores in the Solution Scorecards have dropped dramatically since last year, and there is a much broader spread of vendor scores.
The Evolution of Customer Demands
The Evaluation Criteria (EC) for Cloud IaaS was first published in 2012. It received a significant update every other year (each even-numbered year) thereafter. When first written, the EC reflected the concerns of our clients at the time, many of whom were infrastructure and operations (I&O) professionals with VMware backgrounds. With each iteration, the EC evolved significantly, yet incrementally.
In the meantime, the market moved extremely quickly. The market evolution towards cloud integrated IaaS and PaaS (IaaS+PaaS) providers, and the market exit (or strategic de-investment) of many of the “commodity” providers, radically changed the structure and nature of the market over time. Cloud IaaS providers weren’t just expected to provide “hardware infrastructure”, but also “software infrastructure”, including all of the necessary management and automation. This essentially forced these providers into introducing services that compete in many IT markets and in an extraordinary number of software niches.
Furthermore, as the market matured, the roles and expectations of our clients also evolved significantly. The focus shifted to enterprise-wide initiatives, rather than project-based adoption. Digital business transformation elevated the importance of cloud-native workloads, while IT transformation emphasized the need for high-quality cloud migration of existing workloads. The notion that a cloud IaaS provider could successfully run all, or almost all, of a customer’s IT became part of the assumptions that needed to underpin the provider evaluation process.
Today’s cloud IaaS customers have high expectations. Experienced customers are becoming more sophisticated, but late adopters also have high expectations of a provider that have to be met to help the customer overcome barriers to adoption.
For 2019, we decided to take a look at the EC“from scratch”, in order to try to construct a list of criteria that are the most relevant to the initiatives of customers today. In many cases, our clients are trying to pick a primary strategic IaaS provider. In other cases, our clients already have a primary provider but are trying to pick a strategic secondary provider as they implement a multicloud strategy. Finally, some of our clients are choosing a provider for a tactical need, but still need to understand that provider’s capabilities in detail.
Constructing the Revision
The revision needed to keep a similar number of criteria (in order to keep the assessment time manageable and the assessment itself at a readable length) — we ended up with 265 for 2019.
In order to keep the total number of criteria down, we needed to consolidate closely-related criteria into a single criterion. Many criteria became multi-part as a result. We tried to consolidate the “table stakes” functionality that could be assumed to be a part of all (or almost all) cloud IaaS offerings, in order to make room for more differentiated capabilities.
We tried to be as vendor-neutral as possible. The evaluation criteria have evolved since the initial 2012 introduction; when we introduced new criteria in the past, we often ended up with criteria requirements that closely mirrored the feature-set of the first provider to offer a capability, since that provider shaped customer expectations. In this 2019 revision, we tried to go back to the core customer requirements, without concern as to whether cloud provider implementations fully aligned with those requirements — the criteria are intended to reflect what customers want and not what vendors offer. There are requirements that no vendors meet, but which we often hear our clients ask for; in such cases we tried to phrase those requirements in ways that are reasonable and implementable at scale, as it’s okay for the criteria to be somewhat aspirational for the market.
We tried to make sure that the criteria were worded using standard Gartner terms or general market terminology, avoiding vendor-specific terms. (Note that because vendors not-infrequently adopt Gartner terms, there were cases where providers had adopted terminology from earlier versions of EC, and we made no attempt to alter such terms.)
We tried to keep to requirements, without dictating implementation, where possible. However, we had to keep in mind that in cloud IaaS, where there are customers who want fine-grained visibility and control over the infrastructure, there still must be implementation specificity when the customer explicitly wants those elements exposed.
Defining the Criteria
During the process of determining the criteria, we sought input broadly within Gartner, both in terms of discussing the criteria with other analysts as well as incorporating things from existing Gartner written research. (And the criteria reflect, as much as possible, the discussions we’ve had with clients about what they’re looking for, and what they’re putting into their RFPs.)
In some cases, we needed input from specialists in a topic. In some areas of technology, clients who need to have deep-dive discussions on features may talk almost exclusively to analysts specialized in those areas. Those analysts are familiar with current requirements as well as the future of those technology areas, and are thus the best source for determining those needs. For example, areas such as machine learning and IoT are primarily covered by analysts with those specializations, even when the customers are implementing cloud solutions. There are also areas, such as Security, where we have detailed cloud recommendations from those teams. So we extensively incorporated their input..
We also looked at non-cloud capabilities when there were market gaps relative to customer desires. There are areas where either cloud providers do not currently have capabilities, or where those capabilities are relatively nascent. Thus, we needed to identify where customers are using on-premises solutions, and want cloud solutions. We also needed to determine what the “minimum viable product” should be for the purposes of constructing a criterion around it.
Feedback from non-cloud analysts was also important because it identified areas where clients were not using a cloud solution because of something that was missing. In many cases, these were not technology features, but issues around transparency, or the lack of solutions acceptable on a global basis.
Finally, the way that customers source solutions, build applications, and manage their data is changing. We tried to ensure that the new criteria aligned with these trends.
Because more and more of our clients are deploying cloud solutions globally, every criterion also had some requirements as to its global availability. These are used only for advisory purposes and are not part of scoring.
The vendors were allowed to give feedback on the criteria prior to publication. We wanted to check if the criteria were reasonable, and seemed fair. We incorporated feedback that constituted good, vendor-neutral suggestions that aligned to customer requirements.
The End Results
When you see the Solution Scorecards, you may be surprised by lower scores on the part of many of the providers. We’re being transparent about the Evaluation Criteria (Solution Criteria) revision in order to help you understand why the scores are lower.
The lower scores were an unintentional side-effect of the revision, but reflect, to some degree, the state of the market relative to the very high expectations of customers. Note that this year’s lower scores do not indicate that providers have “gone backwards” or removed capabilities; they just reflect the provider’s status against a raised bar of customer expectations.
We expect that when we update the scorecards in the second half of this year, scores will increase, as many of the vendors have since introduced missing capabilities, or will do so by the next update. We retain confidence that the solution criteria are a good reflection of a broad range of current customer expectations. Because many vendors are doing a good job of listening to what customers and prospects want, and planning accordingly, we think that the solution criteria will also be reflected in future vendor roadmaps and market development.
We discuss the Solution Scorecards and scores in a separate blog post.
Transitioning roles at Gartner
I’m excited to announce that, as of yesterday, I’ve joined the Gartner for Technical Professionals (GTP) team here at Gartner. For years, I’ve enjoyed working closely with Kyle Hilgendorf, Eli Khnaser, Mindy Cancila, Doug Toombs, Marco Meinardi, Alan Waite, and many others in our GTP research division, and I’m looking forward to deepening this collaboration.
Those of you who have known me for a while might remember that I spent more than 15 years in Gartner’s Technology and Service Provider division, and then, for the last two and a half years, I’ve been in the Infrastructure Strategies team in Gartner’s IT Leaders group. Throughout all of these years, I’ve written a lot of deep-dive research for both managerial and technical audiences, and spent a lot of time talking to everyone from the CIO to the sourcing managers and engineers in the trenches, as well as vendors and investors. I’ve always enjoyed being more hands-on, though, and the move into GTP will give me a chance to write more in-depth practical advice.
For the next couple of months, I’ll be in a state of transition. I’ll be doing both types of inquiry for a while, but in the future, clients will need a Gartner GTP “seat” to speak with me. In the next month or two, you’ll see me publish a bunch of research into the ITL agendas, as I finish up that work, and then rethink my previously-planned agenda (much of which will still likely be published, albeit into GTP). I’ll be at the Gartner Catalyst conference in August, with my first GTP presentation, called “Improve Cloud Operations with Site Reliability Engineering”, focused on how to take the principles, practices, and tools used to manage massive cloud-native applications, and apply them at an enterprise level for cloud operations at a more typical scale.
The cloud IaaS team at Gartner is exceptionally collaborative across our divisions and teams, and I expect to continue working very closely with all the awesome analysts that I’ve worked with over the years. Gartner is backfilling my previous role, and I highly encourage any cloud IaaS experts out there to reach out to me if you’re interested. Here’s the job req: https://bit.ly/2JBagOb
Critical Capabilities launched, new Magic Quadrant starting
The Critical Capabilities for Public Cloud IaaS, 2016 has now been published. The Critical Capabilities is a technical assessment of public cloud IaaS offerings against a set of use cases — cloud-native applications, general business applications, application development environments, batch computing, and (new for 2016) the Internet of Things. It’s part of our integrated series of cloud IaaS assessments and complements our Magic Quadrant for Cloud IaaS (Gartner clients: see interactive version).
We are now launching right back into the Magic Quadrant cycle for 2017, with the goal of publishing a new Magic Quadrant in April 2017, and a new Critical Capabilities shortly thereafter.
A lot has happened since the early-2016 research process for our 2016 Magic Quadrant and Critical Capabilities cycle for this market. Multiple providers have launched new offerings and are phasing out their previous offerings, and there are some important new market entrants. We want to make sure that our research notes offer current representations of provider capabilities. (Usefully, a shift to April publication also gets us back to a schedule that aligns with our infrastructure & operations conference season.)
In previous years, we’ve issued an open invitation for the pre-qualification survey to all cloud IaaS providers. This year, we are not doing so; instead, we have issued invitations only to providers who we believe are highly likely to qualify.
If you are a cloud IaaS provider that did not receive an invitation, but you believe you are highly likely to qualify for inclusion, please email me at Lydia dot Leong at Gartner dot com to discuss it.
Gartner’s cloud IaaS assessments, 2016 edition
We’re pleased to announce that the 2016 Magic Quadrant for Cloud Infrastructure, Worldwide has been published. (Link requires a Gartner subscription. If you’re not a Gartner client, there are free reprints available through vendors, and various press articles, such as the Tech Republic analysis. Note that press articles do not always accurately reflect our opinions, though.)
Producing the Magic Quadrant is a huge team effort that involves many people across Gartner, including many analysts who aren’t credited as co-authors, administrative support staff, and people in our primary-research and benchmarking groups. The team effort also reflects the way that we produce an entire body of IaaS research as an integrated effort across Gartner’s research divisions. (The approach described below is specific to our IaaS research and may not apply to Gartner’s assessments in other markets.)
Whether you already have a cloud IaaS provider and are just looking for a competitive check-up, you’re thinking of adding one or more additional providers, or you’re just getting started with cloud IaaS, our work can help you find the providers that are right for you.
The TL;DR list of assessments:
- Magic Quadrant (market and technical evaluation)
- Evaluation Criteria (230+ technical and service traits to look for in a provider)
- In-Depth Assessments (detailed assessments of specific providers against the Evaluation Criteria)
- Critical Capabilities (use-case-based technical evaluations; 2016 update coming soon)
- CloudHarmony and Tech Planner Cloud Module (real-world stats and cost-performance comparisons)
- Peer Insights (IT leaders review providers)
(Note that not all of these might be available as part of your current Gartner client subscription.)
Gartner has produced a Magic Quadrant for Cloud IaaS since 2011. The MQ is our overall perspective on the market, looking at the provider solutions from both a technical and business angle. Gartner clients can use the interactive MQ tool to change the weightings of the criteria to suit their own evaluation priorities (if you read the detailed criteria descriptions, there’s an explanation of how each criterion maps to buyer priorities). The interactive MQ can also be used to get a multi-year historical perspective.
The MQ covers public, hosted private, and industrialized outsourced private cloud IaaS; it’s not just a public cloud MQ. We look at multi-tenant and single-tenant, located in either provider or customer premises, cloud IaaS offerings. We also look at the full range of compute options (VMs, bare-metal servers, containers) that are delivered in a cloud model (API-provisionable via automation, and metered by the hour or less), not just VMs. In addition, we consider some integrated PaaS-layer services (we call these cloud software infrastructure services, which include things like database as a service), but we have a separate enterprise application PaaS MQ for pure aPaaS. While we consider the provider’s overall value proposition in the context of cloud IaaS (including their ability to deliver managed services, network services, etc.), this isn’t a general cloud computing or outsourcing MQ.
2016 marks our sixth iteration of a pure cloud IaaS MQ. Previously, in 2009 and 2010, we included cloud IaaS in our hosting MQ, but by 2010, it was already clear that the hosting and cloud IaaS buyer wants and needs were distinctly different. Since 2011, we’ve produced a global cloud IaaS MQ, along with three regional hosting MQs (suitable for customers looking for dedicated servers or managed hosting on a monthly or annual basis), and three regional data center outsourcing MQs (which include customized private cloud services as part of a broader portfolio of infrastructure outsourcing capabiities). Not every infrastructure need can or should be met with cloud IaaS.
The core foundation of our assessment is our Evaluation Criteria for Cloud IaaS. Over the years, we’ve converged the technical-detail questionnaire that we ask providers to fill out during the Magic Quadrant research process, with the Gartner for Technical Professionals (GTP) document that we produce to guide buyers on evaluating providers. This has resulted in nearly 250 service traits that the Evaluation Criteria document categorizes as Required (almost all Gartner clients are likely to want these things and these have the potential to be showstoppers if missing), Preferred (many will want these things), and Optional (use-case-specific needs). This gives us a consistent set of formal definitions for service features — things you can put a clear yes/no to. As a buyer, you can use the Evaluation Criteria to score any cloud IaaS provider — and even score your own IT department’s private cloud.
In the course of doing this particular Magic Quadrant, providers fill out very detailed questionnaires that list these service features and capabilities (broken down even more granularly than in the Evaluation Criteria), indicating whether their service has those traits, and they’re also asked to provide evidence, like documentation. We also ask them to provide other information like the location of their data centers, languages supported across various aspects of service delivery (like portal localization and tech-support languages spoken), a copy of their standard contract and SLAs, and so forth. We score those questionnaires (and check service features against documentation, and with hands-on testing if need be). We also score things like the buyer-friendliness of contracts, based on the presence/absence of particular clauses. Those component scores are used in many different individual scoring categories within the Magic Quadrant.
We also produce a set of In-Depth Assessments for the providers that our clients are most interested in evaluating. The In-Depth Assessments are detailed documents that score an individual provider against the Evaluation Criteria; for every criteria, we explain how the provider does and doesn’t meet it, and we provide links to the corresponding documentation or other evidence. The results of our hands-on testing are noted, as well. For many buyers, this minimizes the need to conduct an RFP that dives into the technical solution; here we’ve done a very detailed fact-based analysis for you, and the provider has verified the accuracy of the information. (Buyer beware, though: Providers sometimes produce something that looks like one of these assessments, even quoting the Gartner definitions, but with their own more generous self-assessment rather than the stringent Gartner-produced assessment!)
Then, we produce Critical Capabilities for Public Cloud IaaS (2016 update still in progress). This technical assessment looks at a single public cloud IaaS offering from each of the providers included in the Magic Quadrant. The same technical traits used in the other assessments are used here, but they are divided into categories of capabilities, and those capabilities are weighted in a set of common use cases. You can also customize your own set of weightings. In addition to providing quantitative scores, we summarize, in a fair amount of detail, the technical capabilities of each evaluated provider. This allows you to get a sense of what providers are likely to be right for your needs, without having to go through the full deep-dive of reading the In-Depth Assessments. (Critical Capabilities are also available to all Gartner clients and reprints may be offered by providers on their websites, whereas the In-Depth Assessments are only available to GTP clients.)
Performance, and price-performance, is important to many buyers. Gartner provides hardware benchmarking via a SaaS offering called Tech Planner. We offer a Cloud Module within Tech Planner that uses technology that we derived from our acquisition of CloudHarmony. We conduct continuous automated testing on many cloud IaaS providers, including all providers in the Magic Quadrant. We benchmark compute performance for the full range of VMs and bare-metal cloud servers offered by the provider, along with storage performance and network performance; we use this to calculate price-performance metrics. We monitor the availability of their services across the globe. We track provisioning times. All this data is used as objective components to the scores within the Magic Quadrant. Much of this data is directly available to Tech Planner customers, who can use these tools to calculate performance-equivalencies as well as determine where workloads will be most cost-effective.
Finally, we collect end-user reviews of cloud IaaS providers, called Peer Insights. IT leaders (who do not need to be Gartner clients) can submit reviews of their providers; we verify that reviews are legitimate, and it’s one of the very few places where you’ll see enter senior IT executives and architects writing detailed reviews of their providers. We use this data, along with vendor-provided customer references, and the many thousands of clients conversations we have each year with cloud IaaS buyers, as part of the fact base for our Magic Quadrant scoring.
More than a dozen analysts are directly involved in all of these assessments, and many more analysts provide peer-review input into those assessments. It’s an enormous effort, involving a great deal of teamwork, to produce this body of interlinked research. We’re always trying to improve its quality, so we welcome your feedback!
You can DM me on Twitter at @cloudpundit or send email to lydia dot leong at gartner.com.
Open invitation to MSP partners of hyperscale cloud providers
Back in January, I announced the creation of a new Gartner Magic Quadrant for Public Cloud Infrastructure Managed Service Providers. This MQ will evaluate MSPs that deliver managed services on top of Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
We are currently putting together a contact list of providers to survey. We expect to begin this process in late July. We encourage MSPs who are interested in participation to add their names to the contact list.
MSPs should fill out THIS FORM.
My 2016 research agenda
At the beginning of February, as part of a little bit of organizational deck-chair shuffling here at Gartner, some analysts were transferred to teams that better reflect their current research focus. I am one of those people; I’ve been transferred from our Technology and Service Provider (T&SP) division to our IT Leaders division’s Infrastructure Strategies team, reflecting the fact that I’ve mostly been serving the IT Leaders constituency for several years now.
My planned research agenda for 2016 remains the same, and I’ll continue to work with the exact same people and clients, but I now have a new team manager (Rakesh Kumar — and hopefully a better alignment between the things that I’m actually doing and the way Gartner sets goals and incentives for analysts.
I will continue to write research for both our end-user (IT Leaders) clients, as well as for our T&SP (Business Leaders) clients. Vendor clients should note that my transfer does not change access privileges to my documents targeted at vendors, or inquiry access. You will still need to hold a Business Leaders seat to read T&SP content that I author, or to ask inquiry questions related to that content.
My research agenda for 2016 centers on five major themes:
- The managed and professional services ecosystem for cloud providers
- Large-scale migration to the cloud
- Excellence in governance
- The convergence of IaaS and PaaS
- The adoption of containers
I’ll talk briefly about my interests in each of these spaces.
Managed and professional services
The MSP ecosystem, especially around AWS and Azure, is a vital part of driving successful cloud adoption, especially with late-majority adopters. This is my primary research focus this year, as I build out both research for end-users (IT Leaders clients) as well as service providers and technology vendors. This is largely a run-up to a new Magic Quadrant slated for Q4 2016 publication.
Large-scale migration to the cloud
Customers have begun migrate existing workloads to cloud IaaS at scale (i.e., migrating entire data centers or substantial portions of their existing infrastructure estate). This is no longer just early pioneers, but mainstream, non-tech-centric companies, often in the mid-market, usually with the assistance of third parties. These customers typically articulate needs that have been more commonly associated with outsourcing in the past — cost-optimization, better management of infrastructure and apps, staff reduction, keeping pace with technology evolution, and the like.
This is my next greatest priority in terms of writing this year. I’m building research aimed at clients who are evaluating migrations, as well as those who are in the process of migrating. I’m also writing research that is aimed at the vendor/provider side, since this new wave of customers has different requirements, necessitating both a different go-to-market approach as well as different sets of priorities in service features.
Excellence in governance
As organizations grow their use of the cloud, the need for governance is vital. Governance is not control, per se, and IT organizations need assistance in understanding the emerging best practices around governance. The vendor ecosystem also needs to build appropriate products and services that help IT organizations implement good cloud governance — which differs in some vital ways from traditional models of IT governance.
The convergence of IaaS and PaaS
As the IaaS and PaaS markets move ever closer together, customers need guidance as to how to best adopt integrated offerings. Moreover, this has implications for providers on both sides of the spectrum (and their ecosystems), as well as vendors who sell technology to build private clouds.
Last year, I spent just about as much time talking to clients about containers as I did about cloud IaaS — that’s how much of a hot topic it was. This year, as container coverage is dispersed across a lot more analysts, it’s become less of a focus for me, but I remain deeply interested in the evolution of the ecosystem, not just in the cloud, but also within traditional data centers.
While these topics are some key broad themes, I’ll certainly be thinking about and writing about a great deal more. I tend to be a more spontaneous writer, and so I might sit down in an afternoon and rapidly write a note about something that’s been on my mind lately, even if it’s not part of my planned research. Indeed, I tend not to plan research except to the minimum extent that Gartner requires (generally “big rock” items like Magic Quadrants and so forth), so if you have feedback on what you’d like to see me produce, please feel free to let me know.