|By Andrew Hillier||
|August 14, 2011 05:45 AM EDT||
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:
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
Today’s IT environments are increasingly heterogeneous, with Linux, Java, Oracle and MySQL considered nearly as common as traditional Windows environments. In many cases, these platforms have been integrated into an organization’s Windows-based IT department by way of an acquisition of a company that leverages one of those platforms. In other cases, the applications may have been part of the IT department for years, but managed by a separate department or singular administrator. Still, whether...
Dec. 9, 2016 04:00 PM EST Reads: 619
"Dice has been around for the last 20 years. We have been helping tech professionals find new jobs and career opportunities," explained Manish Dixit, VP of Product and Engineering at Dice, in this SYS-CON.tv interview at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 9, 2016 03:30 PM EST Reads: 1,222
@DevOpsSummit taking place June 6-8, 2017 at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @DevOpsSummit at Cloud Expo New York Call for Papers is now open.
Dec. 9, 2016 03:00 PM EST Reads: 2,003
Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. In the eyes of many, containers are at the brink of becoming a pervasive technology in enterprise IT to accelerate application delivery. In this presentation, attendees learned about the: The transformation of IT to a DevOps, microservices, and container-based architecture What are containers and how DevOps practices can operate in a container-based environment A demonstration of how ...
Dec. 9, 2016 02:30 PM EST Reads: 1,257
Cloud Expo, Inc. has announced today that Andi Mann returns to 'DevOps at Cloud Expo 2017' as Conference Chair The @DevOpsSummit at Cloud Expo will take place on June 6-8, 2017, at the Javits Center in New York City, NY. "DevOps is set to be one of the most profound disruptions to hit IT in decades," said Andi Mann. "It is a natural extension of cloud computing, and I have seen both firsthand and in independent research the fantastic results DevOps delivers. So I am excited to help the great t...
Dec. 9, 2016 02:30 PM EST Reads: 786
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, Phil Hombledal, Solution Architect at CollabNet, discussed how customers are able to achieve a level of transparency that e...
Dec. 9, 2016 02:15 PM EST Reads: 1,288
Get deep visibility into the performance of your databases and expert advice for performance optimization and tuning. You can't get application performance without database performance. Give everyone on the team a comprehensive view of how every aspect of the system affects performance across SQL database operations, host server and OS, virtualization resources and storage I/O. Quickly find bottlenecks and troubleshoot complex problems.
Dec. 9, 2016 11:45 AM EST Reads: 2,238
Application transformation and DevOps practices are two sides of the same coin. Enterprises that want to capture value faster, need to deliver value faster – time value of money principle. To do that enterprises need to build cloud-native apps as microservices by empowering teams to build, ship, and run in production. In his session at @DevOpsSummit at 19th Cloud Expo, Neil Gehani, senior product manager at HPE, discussed what every business should plan for how to structure their teams to delive...
Dec. 9, 2016 11:45 AM EST Reads: 1,547
DevOps is being widely accepted (if not fully adopted) as essential in enterprise IT. But as Enterprise DevOps gains maturity, expands scope, and increases velocity, the need for data-driven decisions across teams becomes more acute. DevOps teams in any modern business must wrangle the ‘digital exhaust’ from the delivery toolchain, "pervasive" and "cognitive" computing, APIs and services, mobile devices and applications, the Internet of Things, and now even blockchain. In this power panel at @...
Dec. 9, 2016 11:30 AM EST Reads: 1,015
SYS-CON Events announced today that Dataloop.IO, an innovator in cloud IT-monitoring whose products help organizations save time and money, has been named “Bronze Sponsor” of 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. Dataloop.IO is an emerging software company on the cutting edge of major IT-infrastructure trends including cloud computing and microservices. The company, founded in the UK but now based in San Fran...
Dec. 9, 2016 11:00 AM EST Reads: 721
@DevOpsSummit at Cloud taking place June 6-8, 2017, at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long developm...
Dec. 9, 2016 10:15 AM EST Reads: 1,932
As we enter the final week before the 19th International Cloud Expo | @ThingsExpo in Santa Clara, CA, it's time for me to reflect on six big topics that will be important during the show. Hybrid Cloud: This general-purpose term seems to provide a comfort zone for many enterprise IT managers. It sounds reassuring to be able to work with one of the major public-cloud providers like AWS or Microsoft Azure while still maintaining an on-site presence.
Dec. 9, 2016 04:45 AM EST Reads: 2,992
I’m a huge fan of open source DevOps tools. I’m also a huge fan of scaling open source tools for the enterprise. But having talked with my fair share of companies over the years, one important thing I’ve learned is that you can’t scale your release process using open source tools alone. They simply require too much scripting and maintenance when used that way. Scripting may be fine for smaller organizations, but it’s not ok in an enterprise environment that includes many independent teams and to...
Dec. 9, 2016 02:45 AM EST Reads: 805
Between 2005 and 2020, data volumes will grow by a factor of 300 – enough data to stack CDs from the earth to the moon 162 times. This has come to be known as the ‘big data’ phenomenon. Unfortunately, traditional approaches to handling, storing and analyzing data aren’t adequate at this scale: they’re too costly, slow and physically cumbersome to keep up. Fortunately, in response a new breed of technology has emerged that is cheaper, faster and more scalable. Yet, in meeting these new needs they...
Dec. 9, 2016 01:45 AM EST Reads: 1,972
More and more companies are looking to microservices as an architectural pattern for breaking apart applications into more manageable pieces so that agile teams can deliver new features quicker and more effectively. What this pattern has done more than anything to date is spark organizational transformations, setting the foundation for future application development. In practice, however, there are a number of considerations to make that go beyond simply “build, ship, and run,” which changes how...
Dec. 9, 2016 12:45 AM EST Reads: 5,153
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dec. 9, 2016 12:45 AM EST Reads: 1,243
SYS-CON Events has announced today that Roger Strukhoff has been named conference chair of Cloud Expo and @ThingsExpo 2017 New York. The 20th Cloud Expo and 7th @ThingsExpo will take place on June 6-8, 2017, at the Javits Center in New York City, NY. "The Internet of Things brings trillions of dollars of opportunity to developers and enterprise IT, no matter how you measure it," stated Roger Strukhoff. "More importantly, it leverages the power of devices and the Internet to enable us all to im...
Dec. 9, 2016 12:30 AM EST Reads: 931
In IT, we sometimes coin terms for things before we know exactly what they are and how they’ll be used. The resulting terms may capture a common set of aspirations and goals – as “cloud” did broadly for on-demand, self-service, and flexible computing. But such a term can also lump together diverse and even competing practices, technologies, and priorities to the point where important distinctions are glossed over and lost.
Dec. 8, 2016 09:15 PM EST Reads: 1,691
Monitoring of Docker environments is challenging. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and applications they run. These servers and applications running on them are typically very static, with very long uptimes. Docker deployments are different: a set of containers may run many applications, all sharing the resource...
Dec. 8, 2016 07:45 PM EST Reads: 5,774
Logs are continuous digital records of events generated by all components of your software stack – and they’re everywhere – your networks, servers, applications, containers and cloud infrastructure just to name a few. The data logs provide are like an X-ray for your IT infrastructure. Without logs, this lack of visibility creates operational challenges for managing modern applications that drive today’s digital businesses.
Dec. 8, 2016 05:00 PM EST Reads: 1,830