Welcome!

Microservices Expo Authors: Elizabeth White, Liz McMillan, Flint Brenton, Jason Bloomberg, Yeshim Deniz

Related Topics: Containers Expo Blog, Microservices Expo, @CloudExpo

Containers Expo Blog: Article

Building a Cloud Factory

A process empowering companies to more efficiently migrate workloads to the cloud

Few areas of human endeavor can match the pace of change in IT. Even by IT standards, the change being driven by cloud computing sometimes seems surprising. To refer to a virtual environment that has only recently been deployed as "legacy," as some organizations are now doing, underscores the fact that the only thing constant in the data center is change. To deal with change of this magnitude, which can involve transforming the workload hosting model of an entire organization, some industrial-strength thinking is required.

In order to tackle this challenge, it's important to properly frame the cloud transformation problem. Many associate cloud with agility, flexibility, cost transparency and other end-user-oriented benefits. But many of these attributes are primarily associated with new infrastructure requests, and specifically, the use of self-service portals to "spin up" infrastructure to host new applications or host transient processing demands. When it comes to migrating hundreds or thousands of existing workloads into cloud infrastructure, agility is not a benefit that is typically experienced. In fact the opposite is often the case: because clouds require a higher degree of standardization (i.e., a finite catalog of sizes and software options), migrating existing physical and virtual servers into cloud models can actually be quite difficult. In other words, the very features that make clouds agile for new workload deployments can actually make them less agile from a transformation perspective.

This is where the notion of a factory comes in. In industrial processes, factories are the epitome of scalability, repeatability and productivity. Although they may take some effort to "tool up," once they are up and running they can handle a higher flow of activity, efficiently processing inputs to provide consistent output. This notion is also key to large-scale transformation. By applying a common approach that has been properly engineered to give repeatable results, organizations can greatly reduce the time and effort required to migrate to cloud infrastructure.

Within this concept, it is important to expand on what is meant by "properly engineered." Many organizations tackle these kinds of problems from a grassroots perspective, using spreadsheets and smart people to determine action. The problem with this approach is it rarely evolves to the point where it can generate truly accurate answers, mainly because the problem is too complex. Migrating workloads into clouds requires processing volumes of historical data, analyzing configuration information on the servers and applications being migrated, modeling target instance sizes and software stacks, enforcing corporate and regulatory requirements, honoring SLA and data protection rules, etc. Spreadsheets are not well suited to this, in much the same way that they are ill suited for use as corporate accounting platforms. Even if they can be coaxed into giving a decent answer for simple environments, they will not generate the reports needed to satisfy stakeholders, management, engineering, operations, etc., all of whom need significant detail surrounding the decisions being made in order to ensure benefits are achieved and risk is minimized.

Buried in the list of migration analysis requirements is a key concept linking them all together. This is the notion of policy, which represents the ground rules on how workloads should be hosted, where they should and should not go, how much resources they should be allocated, etc. Without properly modeled policies, hosting decisions are left to the practitioner performing the migration, and it can be hit-or-miss whether they do the right thing (or even follow the same policy twice in a row). Planning and managing cloud infrastructure without proper policies is like trying to fill out a tax return without instructions - there are just too many variables to get it right.

With all of these concepts in mind, the exact nature of the cloud factory becomes clearer. It divides the problem into a series of logical steps that combine data, target models and cloud planning and management policies in order to automate the process of deciding exactly where things go and how big to make them. These steps that make up the factory are:

  1. Candidate Qualification: This process determines whether a given set of workloads are suitable to be hosted in a given cloud environment. This is both qualitative and quantitative in nature and designed to separate true candidates from the workloads that are better suited to go elsewhere (more on this later in step 6). Examples of quantitative criteria include maximum I/O rates, context switching limitations, maximum CPU and memory sizes, etc. Qualitative criteria include data sensitivity, SLA requirements, backup strategy and other considerations. By applying a policy capturing all of these factors, a rapid and accurate assessment can be made.
  2. Sizing: This takes the qualified candidates and determines what cloud instances are best suited to host them given their historical levels and patterns of utilization. This again is subject to policy, which governs how much history is considered, target utilization levels, etc. The result is a detailed specification of the instance sizes needed and the projected utilization levels in the "to be" environment. Note the use of benchmarks is critical in this step, as the translation of CPU utilization from the current environment to the cloud depends on the relative speeds of the CPU employed in each.
  3. Load Balancing: Also a sizing step, this is focused on the load balancers and clusters being migrated. Because cloud environments offer different sizing options, and can even offer more advanced "elasticity" features, it is not always desirable to do a straight one-to-one translation of these servers into cloud capacity. For example, an 8-way IIS cluster might translate onto 12 smalls, 6 mediums and 3 large instances. Of these options, the one that meets the policy criteria (e.g., size for yearly peak activity, allow for N+1 resiliency) at the lowest cost will be the winner. This result is combined with the general sizing results from the previous step to provide a complete sizing plan.
  4. Software Stack Mapping: This step considers the OS and software configurations of the source servers and maps them onto the "closest" configuration available in the cloud. Because cloud catalogs only offer a finite set of software options, this is effectively a standardization analysis. For Infrastructure-as-a-Service (IaaS), this step is typically limited to the OS-level configuration and matches the OS attributes of the existing servers and VMs to the operating systems that are on offer in the cloud (which is typically a much shorter list). For Platform-as-a-Service this step also includes scrutiny of the actual software inventory and applications installed. The result may say "server X looks the most like an IIS v6 server, but differs from the standard image in the following ways..." This not only provides the optimal stack to deploy, but also generates a remediation list that is critical for reducing risk during implementation.
  5. Placement: Once the final specification is arrived at (through sizing, balancing and software mapping), the next step for internal cloud environments is determining exactly where the workloads should be placed in the infrastructure actually hosting the cloud environment. Because most clouds are based on virtual environments, the key is to fit the new VMs into the environment in a way that optimally leverages server resources. This step looks somewhat similar to placement of workloads in virtual environments (which tends to resemble placing Tetris blocks in available server capacity), but the policy regarding overcommit has a large influence on the resulting placements. If the policy is to strictly reserve the capacity for each cloud instance, then the environment will be very safe but relatively inefficient, as the workload density will be quite low (think of playing Tetris with the blocks wrapped in bubbles). If the policy is to fully overcommit resources, then the end customer may have a higher risk of contention if they place unanticipated demands on the environment, but the higher density that results can result in significantly lower costs (think Tetris blocks packed tightly together, requiring far less capacity).
  6. Exception Handling: Going back to step 1, there are typically components of an application or business service that may not be suitable for hosting in the cloud. For these systems, it is necessary to evaluate other hosting options in order to determine what to do with them. Because there is often an order of precedence with respect to the hosting options, this step involves the systematic qualification of the rejected workloads against an ordered set of hosting strategies. These strategies can include using cloud instances with customized allocations, using dedicated cloud servers, hosting in a virtual environment, using dedicated blades, using dedicated rack mount servers or leaving the workloads alone (a last resort). By passing the rejected candidates through this gauntlet of options, each will arrive at a viable outcome.

The result of applying these steps is a methodical, exhaustive and rapid process for planning cloud migrations. By taking a data-centric, policy-driven approach, fewer mistakes are made, less rework is required, and application owners and other stakeholders will have much higher confidence they will arrive on the other end unscathed. This transparency, combined with the detailed specifications and implementation details that emerge, can rapidly accelerate cloud initiatives. This not only reduces time-to-value, but also enables IT organizations to keep up with the pace of technology innovation, which shows no sign of letting up.

More Stories By Andrew Hillier

Andrew Hillier is CTO and co-founder of CiRBA, Inc., a data center intelligence analytics software provider that determines optimal workload placements and resource allocations required to safely maximize the efficiency of Cloud, virtual and physical infrastructure. Reach Andrew at [email protected]

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@MicroservicesExpo Stories
Most companies are adopting or evaluating container technology - Docker in particular - to speed up application deployment, drive down cost, ease management and make application delivery more flexible overall. As with most new architectures, this dream takes a lot of work to become a reality. Even when you do get your application componentized enough and packaged properly, there are still challenges for DevOps teams to making the shift to continuous delivery and achieving that reduction in cost ...
All organizations that did not originate this moment have a pre-existing culture as well as legacy technology and processes that can be more or less amenable to DevOps implementation. That organizational culture is influenced by the personalities and management styles of Executive Management, the wider culture in which the organization is situated, and the personalities of key team members at all levels of the organization. This culture and entrenched interests usually throw a wrench in the work...
Don’t go chasing waterfall … development, that is. According to a recent post by Madison Moore on Medium featuring insights from several software delivery industry leaders, waterfall is – while still popular – not the best way to win in the marketplace. With methodologies like Agile, DevOps and Continuous Delivery becoming ever more prominent over the past 15 years or so, waterfall is old news. Or, is it? Moore cites a recent study by Gartner: “According to Gartner’s IT Key Metrics Data report, ...
Many organizations are now looking to DevOps maturity models to gauge their DevOps adoption and compare their maturity to their peers. However, as enterprise organizations rush to adopt DevOps, moving past experimentation to embrace it at scale, they are in danger of falling into the trap that they have fallen into time and time again. Unfortunately, we've seen this movie before, and we know how it ends: badly.
In his session at Cloud Expo, Alan Winters, U.S. Head of Business Development at MobiDev, presented a success story of an entrepreneur who has both suffered through and benefited from offshore development across multiple businesses: The smart choice, or how to select the right offshore development partner Warning signs, or how to minimize chances of making the wrong choice Collaboration, or how to establish the most effective work processes Budget control, or how to maximize project result...
In his keynote at 19th Cloud Expo, Sheng Liang, co-founder and CEO of Rancher Labs, discussed the technological advances and new business opportunities created by the rapid adoption of containers. With the success of Amazon Web Services (AWS) and various open source technologies used to build private clouds, cloud computing has become an essential component of IT strategy. However, users continue to face challenges in implementing clouds, as older technologies evolve and newer ones like Docker c...
For organizations that have amassed large sums of software complexity, taking a microservices approach is the first step toward DevOps and continuous improvement / development. Integrating system-level analysis with microservices makes it easier to change and add functionality to applications at any time without the increase of risk. Before you start big transformation projects or a cloud migration, make sure these changes won’t take down your entire organization.
Without a clear strategy for cost control and an architecture designed with cloud services in mind, costs and operational performance can quickly get out of control. To avoid multiple architectural redesigns requires extensive thought and planning. Boundary (now part of BMC) launched a new public-facing multi-tenant high resolution monitoring service on Amazon AWS two years ago, facing challenges and learning best practices in the early days of the new service.
You often hear the two titles of "DevOps" and "Immutable Infrastructure" used independently. In his session at DevOps Summit, John Willis, Technical Evangelist for Docker, covered the union between the two topics and why this is important. He provided an overview of Immutable Infrastructure then showed how an Immutable Continuous Delivery pipeline can be applied as a best practice for "DevOps." He ended the session with some interesting case study examples.
Both SaaS vendors and SaaS buyers are going “all-in” to hyperscale IaaS platforms such as AWS, which is disrupting the SaaS value proposition. Why should the enterprise SaaS consumer pay for the SaaS service if their data is resident in adjacent AWS S3 buckets? If both SaaS sellers and buyers are using the same cloud tools, automation and pay-per-transaction model offered by IaaS platforms, then why not host the “shrink-wrapped” software in the customers’ cloud? Further, serverless computing, cl...
"We view the cloud not as a specific technology but as a way of doing business and that way of doing business is transforming the way software, infrastructure and services are being delivered to business," explained Matthew Rosen, CEO and Director at Fusion, in this SYS-CON.tv interview at 18th Cloud Expo (http://www.CloudComputingExpo.com), held June 7-9 at the Javits Center in New York City, NY.
Without lifecycle traceability and visibility across the tool chain, stakeholders from Planning-to-Ops have limited insight and answers to who, what, when, why and how across the DevOps lifecycle. This impacts the ability to deliver high quality software at the needed velocity to drive positive business outcomes. In his general session at @DevOpsSummit at 19th Cloud Expo, Eric Robertson, General Manager at CollabNet, will discuss how customers are able to achieve a level of transparency that e...
We all know that end users experience the internet primarily with mobile devices. From an app development perspective, we know that successfully responding to the needs of mobile customers depends on rapid DevOps – failing fast, in short, until the right solution evolves in your customers' relationship to your business. Whether you’re decomposing an SOA monolith, or developing a new application cloud natively, it’s not a question of using microservices - not doing so will be a path to eventual ...
"DivvyCloud as a company set out to help customers automate solutions to the most common cloud problems," noted Jeremy Snyder, VP of Business Development at DivvyCloud, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
We all know that end users experience the Internet primarily with mobile devices. From an app development perspective, we know that successfully responding to the needs of mobile customers depends on rapid DevOps – failing fast, in short, until the right solution evolves in your customers' relationship to your business. Whether you’re decomposing an SOA monolith, or developing a new application cloud natively, it’s not a question of using microservices – not doing so will be a path to eventual b...
"This all sounds great. But it's just not realistic." This is what a group of five senior IT executives told me during a workshop I held not long ago. We were working through an exercise on the organizational characteristics necessary to successfully execute a digital transformation, and the group was doing their ‘readout.' The executives loved everything we discussed and agreed that if such an environment existed, it would make transformation much easier. They just didn't believe it was reali...
"Opsani helps the enterprise adopt containers, help them move their infrastructure into this modern world of DevOps, accelerate the delivery of new features into production, and really get them going on the container path," explained Ross Schibler, CEO of Opsani, and Peter Nickolov, CTO of Opsani, in this SYS-CON.tv interview at DevOps Summit at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Your homes and cars can be automated and self-serviced. Why can't your storage? From simply asking questions to analyze and troubleshoot your infrastructure, to provisioning storage with snapshots, recovery and replication, your wildest sci-fi dream has come true. In his session at @DevOpsSummit at 20th Cloud Expo, Dan Florea, Director of Product Management at Tintri, provided a ChatOps demo where you can talk to your storage and manage it from anywhere, through Slack and similar services with...
"I focus on what we are calling CAST Highlight, which is our SaaS application portfolio analysis tool. It is an extremely lightweight tool that can integrate with pretty much any build process right now," explained Andrew Siegmund, Application Migration Specialist for CAST, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Explosive growth in connected devices. Enormous amounts of data for collection and analysis. Critical use of data for split-second decision making and actionable information. All three are factors in making the Internet of Things a reality. Yet, any one factor would have an IT organization pondering its infrastructure strategy. How should your organization enhance its IT framework to enable an Internet of Things implementation? In his session at @ThingsExpo, James Kirkland, Red Hat's Chief Archi...