Microservices Expo Authors: Jason Bloomberg, Elizabeth White, Gopala Krishna Behara, Sridhar Chalasani, Tirumala Khandrika

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
By now, every company in the world is on the lookout for the digital disruption that will threaten their existence. In study after study, executives believe that technology has either already disrupted their industry, is in the process of disrupting it or will disrupt it in the near future. As a result, every organization is taking steps to prepare for or mitigate unforeseen disruptions. Yet in almost every industry, the disruption trend continues unabated.
DevOps is often described as a combination of technology and culture. Without both, DevOps isn't complete. However, applying the culture to outdated technology is a recipe for disaster; as response times grow and connections between teams are delayed by technology, the culture will die. A Nutanix Enterprise Cloud has many benefits that provide the needed base for a true DevOps paradigm. In his Day 3 Keynote at 20th Cloud Expo, Chris Brown, a Solutions Marketing Manager at Nutanix, will explore t...
Lots of cloud technology predictions and analysis are still dealing with future spending and planning, but there are plenty of real-world cloud use cases and implementations happening now. One approach, taken by stalwart GE, is to use SaaS applications for non-differentiated uses. For them, that means moving functions like HR, finance, taxes and scheduling to SaaS, while spending their software development time and resources on the core apps that make GE better, such as inventory, planning and s...
As Enterprise business moves from Monoliths to Microservices, adoption and successful implementations of Microservices become more evident. The goal of Microservices is to improve software delivery speed and increase system safety as scale increases. Documenting hurdles and problems for the use of Microservices will help consultants, architects and specialists to avoid repeating the same mistakes and learn how and when to use (or not use) Microservices at the enterprise level. The circumstance w...
Everyone wants to use containers, but monitoring containers is hard. New ephemeral architecture introduces new challenges in how monitoring tools need to monitor and visualize containers, so your team can make sense of everything. In his session at @DevOpsSummit, David Gildeh, co-founder and CEO of Outlyer, will go through the challenges and show there is light at the end of the tunnel if you use the right tools and understand what you need to be monitoring to successfully use containers in your...
What if you could build a web application that could support true web-scale traffic without having to ever provision or manage a single server? Sounds magical, and it is! In his session at 20th Cloud Expo, Chris Munns, Senior Developer Advocate for Serverless Applications at Amazon Web Services, will show how to build a serverless website that scales automatically using services like AWS Lambda, Amazon API Gateway, and Amazon S3. We will review several frameworks that can help you build serverle...
The Software Defined Data Center (SDDC), which enables organizations to seamlessly run in a hybrid cloud model (public + private cloud), is here to stay. IDC estimates that the software-defined networking market will be valued at $3.7 billion by 2016. Security is a key component and benefit of the SDDC, and offers an opportunity to build security 'from the ground up' and weave it into the environment from day one. In his session at 16th Cloud Expo, Reuven Harrison, CTO and Co-Founder of Tufin, ...
SYS-CON Events announced today that HTBase will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. HTBase (Gartner 2016 Cool Vendor) delivers a Composable IT infrastructure solution architected for agility and increased efficiency. It turns compute, storage, and fabric into fluid pools of resources that are easily composed and re-composed to meet each application’s needs. With HTBase, companies can quickly prov...
Building custom add-ons does not need to be limited to the ideas you see on a marketplace. In his session at 20th Cloud Expo, Sukhbir Dhillon, CEO and founder of Addteq, will go over some adventures they faced in developing integrations using Atlassian SDK and other technologies/platforms and how it has enabled development teams to experiment with newer paradigms like Serverless and newer features of Atlassian SDKs. In this presentation, you will be taken on a journey of Add-On and Integration ...
Culture is the most important ingredient of DevOps. The challenge for most organizations is defining and communicating a vision of beneficial DevOps culture for their organizations, and then facilitating the changes needed to achieve that. Often this comes down to an ability to provide true leadership. As a CIO, are your direct reports IT managers or are they IT leaders? The hard truth is that many IT managers have risen through the ranks based on their technical skills, not their leadership abi...
The essence of cloud computing is that all consumable IT resources are delivered as services. In his session at 15th Cloud Expo, Yung Chou, Technology Evangelist at Microsoft, demonstrated the concepts and implementations of two important cloud computing deliveries: Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). He discussed from business and technical viewpoints what exactly they are, why we care, how they are different and in what ways, and the strategies for IT to transi...
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.
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...
DevOps is often described as a combination of technology and culture. Without both, DevOps isn't complete. However, applying the culture to outdated technology is a recipe for disaster; as response times grow and connections between teams are delayed by technology, the culture will die. A Nutanix Enterprise Cloud has many benefits that provide the needed base for a true DevOps paradigm.
As software becomes more and more complex, we, as software developers, have been splitting up our code into smaller and smaller components. This is also true for the environment in which we run our code: going from bare metal, to VMs to the modern-day Cloud Native world of containers, schedulers and micro services. While we have figured out how to run containerized applications in the cloud using schedulers, we've yet to come up with a good solution to bridge the gap between getting your contain...
As organizations realize the scope of the Internet of Things, gaining key insights from Big Data, through the use of advanced analytics, becomes crucial. However, IoT also creates the need for petabyte scale storage of data from millions of devices. A new type of Storage is required which seamlessly integrates robust data analytics with massive scale. These storage systems will act as “smart systems” provide in-place analytics that speed discovery and enable businesses to quickly derive meaningf...
DevOps has often been described in terms of CAMS: Culture, Automation, Measuring, Sharing. While we’ve seen a lot of focus on the “A” and even on the “M”, there are very few examples of why the “C" is equally important in the DevOps equation. In her session at @DevOps Summit, Lori MacVittie, of F5 Networks, explored HTTP/1 and HTTP/2 along with Microservices to illustrate why a collaborative culture between Dev, Ops, and the Network is critical to ensuring success.
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo | @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA. Learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.
The IT industry is undergoing a significant evolution to keep up with cloud application demand. We see this happening as a mindset shift, from traditional IT teams to more well-rounded, cloud-focused job roles. The IT industry has become so cloud-minded that Gartner predicts that by 2020, this cloud shift will impact more than $1 trillion of global IT spending. This shift, however, has left some IT professionals feeling a little anxious about what lies ahead. The good news is that cloud computin...
An overall theme of Cloud computing and the specific practices within it is fundamentally one of automation. The core value of technology is to continually automate low level procedures to free up people to work on more value add activities, ultimately leading to the utopian goal of full Autonomic Computing. For example a great way to define your plan for DevOps tool chain adoption is through this lens. In this TechTarget article they outline a simple maturity model for planning this.