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Tag: cloud platforms

  • Despite Democratization, IT Department More Central Than Ever

    Despite Democratization, IT Department More Central Than Ever

    There’s been talk of the decentralization of IT within organizations for years, and events of recent years have certainly accelerated this trend. Yet, IT has never been more important to the success of the organization.

    According to ManageEngine’s newly released IT at Work: 2022 and Beyond study, an increasing number of IT-related decisions are being made outside of the formal IT department. Yet, the survey also found that just as non-IT employees and the lines of business take a larger role in choosing their technology stack, collaboration between IT and other areas of the business has actually increased, not decreased as many feared would occur.

    The survey found that 76% of North American decision-makers reported their organization encourages non-IT employees to develop their own applications using low-code/no-code platforms and most departments, most notably notable quality control (24%) and finance (21%), are independently turning to AI/ML solutions to perform their jobs.

    These findings echoed an earlier survey conducted by IDG for Snow Software. This survey found that 67% of respondents believed that at least half of their IT budget is controlled by their various business units and not the IT department. Interestingly, 78% agreed that this is a positive development for their organization and that it would ultimately enable their business to become more innovative and agile.

    That may be so, but many North American IT decision-makers responding to the ManageEngine survey (48%) also believed that a lack of training and basic technical knowledge (47%) are holding back their staff from taking full advantage of the technology available to them. Still, 76% of survey respondents reported that their staff is more technology-savvy today than they were before the pandemic.

    Those benefits aside, a full 99% of respondents said that their organization also faced challenges due to IT decentralization, most notably maintaining IT security (56%), overall quality maintenance (41%) and the reliability of ongoing support (37%).

    Paradoxically, despite the increased technology autonomy within organizations, the ManageEngine survey found that 82% of North American business and technology leaders agreed that collaboration between IT and other lines of business increased in the past two years. Further, 89% believed that the IT department’s success is directly linked with the general success of their organization.

    “Those enterprises that succeed here will be those that are able to not only have the right policies in place that encourage IT and line-of-business collaboration but the technology also in place that will identify applications and cloud services independently deployed by those line-of-business managers,” said Scott Crawford, an analyst with 451 Research, S&P Global Market Intelligence.

    It’s clear that the ease with which low-code/no-code platforms, cloud services and other cloud platforms made business technology accessible to non-IT decision-makers has decentralized and democratized IT decision-making. What’s interesting is that IT departments have found their relevance and importance within organizations increasing, and not decreasing as many feared. Those IT departments that have succeeded, and that will continue to succeed, are those that find themselves capable of supporting the technology decisions their various departments have made rather than centrally trying to control those decisions.

    The ManageEngine survey is based on the responses from 3,300 global IT and business decision-makers with 500 of those respondents residing in North America.

  • Survey Surfaces Multi-Cloud Computing and Cost Challenges

    Survey Surfaces Multi-Cloud Computing and Cost Challenges

    A survey of 360 CIOs and IT leaders in the U.S. and the United Kingdom found that, as the number of cloud platforms an organization employs expands, the number of tools they are required to deploy and master does, too.

    The survey, published this week by Virtana, a provider of a platform for managing cloud migrations, found nearly two-thirds of respondents (63%) reported their organization relied on at least five separate tools for migration, cloud cost optimization, integrated performance monitoring, application performance management and cloud infrastructure monitoring. A full 83% are expending some level of manual effort to consolidate data from all of these tools, or are simply using them in isolation from one another. Only 17% said data integration is fully automated.

    Nearly three-quarters (73%) also noted that siloed efforts limit their ability to realize the full potential of the cloud.

    It appears that multi-cloud computing only makes managing IT more challenging. Not to mention the increased pressure a multi-cloud approach puts on DevOps and developers that already juggle an overwhelming number of tools for development, DevSecOps and more. And, of course, the risk of cloud misconfiguration grows alongside the number of cloud platforms an organization uses.

    According to the Virtana survey, a total of 82% of respondents have a multi-cloud strategy, with more than three-quarters (78%) deploying workloads in more than three public clouds. A full 59% now run more than half of their workloads on public clouds. More than half (51%) also plan to increase the number of public cloud instances they support this year, with more than a third (34%) planning on using five or more cloud platforms.

    More challenging still, more than three quarters (76%) are in the early stages of implementing serverless computing frameworks. Overall, more than half (52%) will continue to maintain a hybrid environment as part of their core IT strategy. A full 96% of respondents see value in workload portability, but only 71% are in the early stages of achieving that goal. Top benefits anticipated include maximized cost savings (58%), reduced cloud service provider risk (46%) and increased business agility (43%). However, nearly three-quarters (75%) have either no or few cloud governance capabilities (34%) or have stitched together disparate tools to achieve that goal (41%).

    Jonathan Cyr, vice president of product management for Virtana, said that as the global economy becomes more challenging, it’s only a matter of time before sensitivity to cloud costs start to rise. Each time the overall IT environment expands, increases in complexity drive the total cost of IT higher.

    It’s not clear to what degree that sensitivity to cloud cost might drive more IT organizations to centralize the management of IT environments. In theory, a single control plane could be employed to manage multiple cloud computing environments, but today most clouds are still managed in isolation from one another.

    IT teams also find themselves inadvertently locked into a cloud platform. The more developers invoke proprietary application programming interfaces (API), the more difficult it becomes to migrate a workload from one cloud platform to another.

    It’s all but certain there will be a cloud management reckoning in the months ahead. Development teams may prefer one cloud platform over another for many reasons but, as the cost of IT continues to increase, there will soon be tougher cloud cost questions emanating from the finance office.

  • Encore Platform for Running Distributed Apps in the Cloud Arrives

    Encore Platform for Running Distributed Apps in the Cloud Arrives

    Encore has made generally available a namesake backend development engine for rapidly building scalable distributed IT environments across multiple cloud platforms.

    Fresh off raising $3 million in seed funding, Encore CEO André Eriksson said the Encore platform analyzes source code to eliminate the need to manually configure, connect and set up portable cloud computing environments.

    In addition to being able to automatically setup and manage cloud infrastructure based on the metadata surfaced by static analysis tools, Encore provides access to a built-in continuous integration/continuous delivery (CI/CD) platform, previews of environments, live reloads of cloud environments, authentication, secrets management and automatic distributed tracing capabilities.

    Eriksson said the development of the Encore environment was, in part, inspired by how developers of games today routinely use an engine to build application environments rather than presenting developers with a set of text-based editing tools to build those environments using low-level boilerplate code that has to be written by developers for each application instance.

    Written in the Go programming language, Eriksson said Encore platform is based on an open source Encore Go Framework that prevents IT organizations from becoming locked into an Encore platform that today can be deployed on Amazon Web Services, Google Cloud Platform and Microsoft Azure cloud services.

    The building and deploying of distributed applications has always been a major challenge. Encore is designed to automate most of the routine tasks that DevOps teams today need to manually perform for each distributed application they support. As the number of applications being deployed across various cloud computing platforms increases, the challenges associated with managing those environments increase. Encore is designed to enable developers to easily build and deploy application code in a way that can be centrally managed by a DevOps team, noted Eriksson.

    It also takes advantage of the concurrency capabilities that the Go language enables to make it simpler to build and deploy distributed applications in a cloud-agnostic manner, said Eriksson. DevOps teams can also employ Go to extend the Encore environment within the boundary of certain limitations, he added.

    Essentially, Encore is making a case for an opinionated distributed computing environment that, in return for less flexibility, promises to make it simpler to deploy complex applications. Eriksson said Encore doesn’t see many DevOps teams looking to deploy distributed applications that span multiple cloud services, but they are being required to deploy more applications on different cloud platforms. Each cloud platform a DevOps team needs to support only serves to make the overall IT environment that much more complex to manage, he noted.

    It’s not clear to what degree IT organizations are ready to embrace a more opinionated approach to managing cloud computing environments. However, the concept of relying on one is hardly new. Platform-as-a-service (PaaS) environments have been employed for years. However, with the rise of microservices-based applications that are inherently distributed, the issue may soon be forced as IT organizations find simply no other way to keep pace with the rate at which applications are being developed and then continuously extended after they are deployed.

  • Going Cloud-Native with IBM Z as a Hybrid Cloud Platform

    Going Cloud-Native with IBM Z as a Hybrid Cloud Platform

    When people use the phrase “they don’t make ‘em like that anymore,” 100-year-old bridges, Jon Snow’s sword and American muscle cars often come to mind. If the topic of discussion happens to be computer technology, however, mainframes are without a doubt the Valyrian steel of the enterprise and lucky for us, are still in production today. While the cloud computing concept as we know it has been around for only about a decade, mainframes have been delivering on-demand access to compute and storage resources that are safe, scalable, highly available and resilient for half a century.

    Big Iron Advantage

    In today’s enterprise scenario, the mission to gain an edge over the competition in terms of pure horsepower can be elusive, to say the least. Although 20% of the easy enterprise workloads have moved to cloud platforms, it is estimated a large amount of data and applications continue to be run on-premise as enterprises determine their hybrid cloud strategy. Far from being irrelevant, mainframe architecture now finds itself at the center of this digital battle, causing disruption and giving its users a much-coveted and undeniable edge over the competition. In addition to running over 8,000 VMs on a single system, mainframes offer some of the most scalable storage in the industry.

    In case that isn’t enough, couple that with pervasive encryption, multi-factor authentication, a co-processor dedicated to cryptography and the most trusted and secure Linux environment in the industry today. What you get in the end is a major breakthrough with regard to cloud limitations that many early adopters of cloud technology found out about the hard way. These limitations are especially true with regard to cybersecurity, and though private clouds help alleviate these risks to an extent, IBM Z removes these risks by enabling all-encompassing encryption.

    Enabling the Hybrid Cloud

    While most people were skeptical of mainframes making a comeback until about a year ago, the majority seem to have changed their tune. There are two reasons for this: One is IBM’s new take on the mainframe, called IBM Z; and the other reason is its applications with regard to the hybrid cloud. Hybrid basically refers to organizations using a broad combination of public, private, IaaS and Paas in the same application solution. Mainframes are proving an important part of hybrid infrastructure thanks to the massive compute, storage and scalability features they can deliver.

    Another advantage mainframes have in a hybrid environment is simplicity. Every engineer knows the more moving parts, the higher the risk of a breakdown, and the same holds true for the hybrid cloud. In a complex, multi-cloud environment that often spans more than one public cloud and a variety of on-prem resources, the more discrete devices involved in a network, the higher the risk of something failing. With a mainframe like the IBM Z, you have one device that delivers broad functionality at high efficiency and low cost. And it does it for a few decades, without complaining.

    IBM Z and the Cloud

    IBM’s Z models are lean, mean, transacting machines. Recent innovations in hardware and software design have made it possible to run not just native mainframe apps, but also most Linux-based operating systems and applications on these systems. IBM Z also features machine learning and AI frameworks, as well as support for Apache SparkML, TensorFlow and languages such as Scala and Python. Capable of running more than 12 billion fully encrypted transactions per day on a single machine and 850 million on IBM’s skinny version, the z14 has a 35% capacity increase for workloads compared to the z13, and it’s being touted as the most powerful transaction machine in existence today.

    Combining mainframes and cloud platforms in today’s hybrid environments may sound like old wine in a new bottle, but it effectively gives you the best of both worlds–the scalability of the cloud, along with the power, security and dependability of the mainframe. Additionally, the mainframe’s ability to house both data and applications on the same device, while dedicating processors to specific operations independently, make it ideal for ensuring speed in such complex and distributed environments. IBM Z also features a multiple processing structure that makes it ideal for dealing with the varying bandwidth needs of modern applications. It can process Java workloads up to 50% faster than x86 servers.

    Cost Efficiency

    Forty-four of the top 50 banks in the world run on IBM Z servers right now. They understand that running their applications on a mainframe provides security and scalability for a compelling return on investment. Large enterprise systems have had a perception of being expensive, but when you factor in such things as space, power and cooling efficiency, as well as the number of personnel required to administer the system, the total cost of ownership is a value-add when leveraging Z in your hybrid cloud strategy.

    — Twain Taylor

  • How Not to Sabotage Your Multi-Cloud Strategy

    How Not to Sabotage Your Multi-Cloud Strategy

    The immense pressure for enterprises to deliver new applications and insights that exploit new business opportunities has been a driving force for digital transformation. This, in turn, has led IT leaders to embrace a multi-cloud strategy—whether that’s deploying a combination of cloud platforms such as AWS, Azure and Google, or extending private data centers to the public cloud—to achieve greater agility, optimized performance and cost savings resulting from deploying workloads across multiple cloud platforms.

    However, maintaining multiple cloud platforms and services adds complexity and even confusion to enterprise IT environments already crowded with a range of technologies, applications and processes. While a recent Forrester study shows that enterprises are increasing investments in using multi-cloud strategies for business-critical applications and workloads, the majority of these enterprises also report that they experienced issues with deploying and using multi-cloud environments.

    The difficulty in managing IT environments made more complex by multiple cloud services involves three major issues: ignoring the importance of cultural transformation, not addressing the widening skill set gap and implementing a DIY approach to cloud management.

    Here are three ways to deal with these challenges, so you don’t end up sabotaging your multi-cloud strategy.

    Make Culture Change a Priority

    The cultural transformation required to support digital transformation and to fully take advantage of multi-cloud’s power is more than shifting the organizational mindset from capex to opex. It’s also more than picking one or a combination of the big three cloud providers and simply saying, “Let’s do this.” It requires building trust and breaking down the silos of technology knowledge—whether vendor, legacy or emerging technologies—across disparate IT teams to achieve the business goal of speedier application development and faster time to market.

    Specifically, this culture change requires better collaboration between teams and arming central IT with up-to-date processes and management platforms that are focused less on managing infrastructures and more on achieving a balance between visibility and resource control, the linchpin for IT, and creativity, the true north for developers. It will have parameters in place for provisioning resources while helping developers get the resources they need—compute, storage, network services and more—as quickly as possible.

    Culture change also enables the maturing of DevOps processes toward streamlining and bringing order to the clutter and smooth partnerships with other IT teams, especially security and operations. These include processes to eliminate bottlenecks in workflow, to advance automation and self-service, to consolidate resources and to make security integral to—rather than an afterthought in—the development process.

    Invest in Building Expertise in Multi-Cloud and Emerging Technologies

    The more cloud environments an organization has, the more skills and tools are needed to be able to deploy and optimize these environments efficiently. Despite increasing commoditization in the industry, there are still differentiators between cloud vendors and their services, and ways to leverage these to align with an organization’s specific needs. To do this, it is crucial to train the internal DevOps team or hire experts in multi-cloud environments and in key technologies for advancing multi-cloud such as containerization, microservices and serverless computing.

    Additionally, a cloud management platform that provides self-service IT and enables any user to provision, manage and orchestrate IT resources, will allow both end users and admins more time to focus on getting high-quality work done.

    Select a Cloud Management Platform that’s Right for You

    Cloud management platforms address the complexity of hybrid and multi-cloud environments by providing a central platform that allows a selection of the clouds and services that best fit an organization’s needs. They also enable IT to connect to any third-party resource, whether that’s VMware on-prem, AWS in the public cloud or container orchestrators such as Kubernetes, to gather the inventory of cloud computing resources and to provision new resources to be used by anyone in the organization from one place. Self-service IT can also be enabled when appropriate.

    In addition, by ensuring cloud management platforms are built on a single pane of glass, IT can gain a holistic view of hybrid and multi-cloud environments. It also allows effective monitoring of resource utilization across those environments, thus ensuring that cloud spend is not only reined in but also optimized.

    Finally, a cloud management platform should connect both legacy and new technologies within cloud environments. Although the complexity will not go away, it gets easier to manage. Instead of having multiple teams from different departments managing and accessing resources in separate environments, a central team handles complexity with enterprisewide visibility and control.

    The way to succeed is to embrace the complexity by configuring it and managing it behind the scenes, so developers and end users consume IT resources from one consistent way, regardless of where it comes from. Leave the complexity to the cloud and IT architects and let your end users and developers get to work.

    — Brian J. Kelly

  • The Key to Multi-Cloud Success

    The Key to Multi-Cloud Success

    In the era of cloud-based architectures, companies have implemented multiple cloud platforms but have yet to reap the full benefits. Whether it’s Amazon Web Services (AWS), Google Cloud or Microsoft Azure—or some combination thereof—a recent Forrester study found that nearly 86% of enterprises have incorporated a multi-cloud strategy. Not only does this strategy take companies out of the business of hosting their own applications, it also leads to benefits including avoiding vendor lock-in, reduced costs and optimized performance.

    While it’s clear that a multi-cloud strategy offers many benefits and flexibility for an organization, there are more moving parts to track (with the added challenge of hybrid, multi-generational infrastructure), making it all the more critical that businesses have a solid monitoring strategy in place. Luckily, the collection of monitoring data is essentially a solved problem; instead, businesses today are faced with an endless cycle of day-two operational challenges such as avoiding downtime and maintaining visibility.

    As Andreessen Horowitz so aptly put it, software is eating the world; every company is becoming (or has become) a software company. Software is not only ubiquitous, it’s powerful, enabling us to solve a wide range of problems. This emphasis on software within companies has led to the emergence of multiple cloud providers such as Amazon, Google and Microsoft, which all recognized the trend and seized the opportunity by building cloud computing platforms.

    Because companies no longer have to build their own data centers, they can focus on their core business of delivering value to their customers. With the public cloud, they’re able to achieve far greater time-to-value than they would if left to build their own data centers and cloud platforms.

    Today, companies can build a portable software stack that is DevOps-driven, free from vendor lock-in and capable of delivering a superior set of capabilities than can be gained from a single provider. Although we’re now consuming infrastructure from cloud providers (which has its own inherent risks), we have better tooling to enable multi-cloud strategies, minimizing the risk of being reliant on any one provider for cloud services.

    The Missing Piece: Multi-Cloud Monitoring

    In this software-dependent world, availability is critical, and downtime is not only expensive but also damaging to business reputation. As a result, monitoring systems and applications has become a core competency, crucial to business operations. To fully reap the rewards of a multi-cloud strategy and thrive in this cloud-based world, implementing a unified monitoring solution is critical for success. In addition to the existing benefits multi-cloud offers, a unified solution gives operators constant and complete visibility into their infrastructure, applications and operations.

    Surviving as a Modern Enterprise

    Improved operational visibility through monitoring is often cited as a top priority among chief information officers (CIOs) and senior operations leadership, and good monitoring is a staple of high-performing teams. Yet, too often it’s implemented as an afterthought in reaction to changes in the mission-critical systems that power businesses. When this happens, organizations can struggle to reap the benefits of multi-cloud because they lack sufficient visibility to detect and avoid problems or recover from expensive downtime.

    Further complicating this underlying challenge is the fact that ephemeral infrastructure platforms such as Kubernetes are the new normal, while digital transformation, cloud migration, DevOps, containerization and other initiatives are compelling movements in the modern enterprise. Although they vary in scope and overlap or intersect in practice, they are unified in purpose: To deliver increased organizational velocity, empowering organizations to ship more changes faster.

    While they are a boon to business initiatives and developer productivity, these practices can increase exponentially the number and duration of day-two operational challenges. Delaying adoption of the solution to these challenges only increases risk exposure and cost.

    Be Prepared for the Cloud Gold Rush

    According to Gartner, the number of cloud-managed service providers is expected to triple by 2020. While this gold rush is good news for analysts, investors and operators alike—everyone (except Amazon?) benefits from a competitive market—it suggests that the multi-cloud trend will only become more diverse moving forward. Given the already complex landscape and this forecast, it’s impractical to expect turnkey monitoring solutions to provide enough coverage—a different approach is needed.

    The good news is that the solution is surprisingly simple: Treat monitoring and observability like we do the rest of our DevOps toolchain—as a pipeline. When containerization gained in popularity and we incorporated Docker and Kubernetes into our multi-cloud strategy, we didn’t have to replace our CI pipelines; we simply shipped containers instead of RPMs, essentially making our CI tools future-proof.

    For monitoring and observability, that future-proof solution is the monitoring event pipeline. At the end of the day, there are only so many mechanisms for observing systems (APM and observability client libraries, Prometheus-style /metrics or /healthz endpoints, logs and good old-fashioned service health checks are a few great examples). Once we start to think about these as workflows that can be automated via monitoring pipelines, we’re empowered to continuously adapt and thrive (maintaining visibility and avoiding downtime) in the ever-evolving and increasingly multitudinous cloud world of IT infrastructure.

    — Caleb Hailey

  • Python Benefiting From Increase in DevOps Use

    Python Benefiting From Increase in DevOps Use

    DevOps and Python have developed a mutually beneficial relationship.

    In a recent survey released by the Python Software Foundation and software development company JetBrains, researchers found that more and more developers are using the program language for an array of versatile projects, including DevOps and machine learning.

    In fact, Python developers told the researchers that DevOps is increasingly part of their professional development work.

    “In 2018 we had significantly more respondents specifying they’re involved in DevOps (an increase of 8 percent compared to 2017). In terms of Python users using Python as their secondary language, DevOps has overtaken web development,” according to the “2018 Python Developers study,” which is based on responses from 18,000 developers in 150 countries.

    Over the last two years, Python has grown more important to developers thanks to its flexibility, especially when it comes to web development. It’s no surprise that as other projects have gained popularity in the enterprise—DevOps and machine learning—developers have started adopting the language to other disciplines, especially as businesses invest more in application development.

    In TIOBE’s February 2019 index, Python now ranks third behind favorites such as Java and C, edging out C++ for its current position.

    Digging into the numbers, the survey finds that 43 percent of developers are using Python for DevOps projects, as well as system administration and writing automation scripts. That’s an increase from the 35 percent who reported the same types of uses for the programming language in 2017.

    The report notes that these numbers reflect a combination of Python used as either the primary or secondary language for various projects. As the report notes: “DevOps/system administration/writing automation scripts has moved into first place among Python users using it as a secondary language.”

    Machine learning is another up-and-coming category, with 38 percent of developers using Python for these projects compared to 31 percent last year.

    Overall, data analysis remains the No. 1 use case for Python developers, with 58 percent reporting that it’s their main focus when it comes to development.

    In second place is web development, according to the report.

    In terms of the top cloud platforms for Python developers, Amazon Web Service is the top choice, with 36 percent of respondents reporting that they use AWS. From there, it’s Google Cloud Platform (29 percent) Heroku (26 percent), DigitalOcean (23 percent) and Microsoft Azure (16 percent).

    About a third of those surveyed responded that they don’t use any cloud platforms.

    When asked about running code in a cloud production environment, 47 percent responded that they use virtual machines, although 40 percent of Python developers reported that they prefer containers. Another 28 percent use platform as a service (PaaS) and 21 percent are taking the leap to serverless computing.

    Additionally, when developing for the cloud, about 35 percent of those in the survey report that they use Docker containers.

    This increase use of Python within DevOps, as well as other connected areas such as serverless computing, does not surprise Anshu Agarwal, the CEO and co-founder of Nimbella, a cloud-agnostic, serverless cloud platform for developers. She noted the language’s use within a wide range of projects, specifically machine learning and AI, are driving this change.

    “Python developers are driving serverless requirements in new and unique ways, primarily because of the interest in data analysis, ML and AI,” Agarwal wrote in an email. “These data analysis and ML/AI-centric serverless use cases are different than request/response style serverless functions which run for much shorter durations. Python functions in serverless may have much longer durations (10s of minutes or hours), and consume a lot more memory. For such functions a different kind of serverless framework needs to be adopted that can handle long running workloads.”

    When it comes to continuous integration systems, about a third of respondents don’t use any. However, when they do, Jenkins is the most popular at 25 percent, followed by Gitlab CI and Travis CI, with 18 percent each. For configuration management, 20 percent reported using Ansible, while 9 percent used custom tools. Puppet, Salt and Chef also appeared in the list.

    Finally, about two-thirds of Python developers (69 percent) use Linux as their main operating system of choice for development. Microsoft Windows comes in a distant second at 47 percent and Apple’s macOS in third at 32 percent, according to the study.

    — Scott Ferguson

  • Morpheus Data Advances DevOps Across Hybrid Clouds

    Morpheus Data Advances DevOps Across Hybrid Clouds

    Thanks to the rise of multi-cloud computing, the challenges associated with managing DevOps are becoming exponentially greater. Most IT organizations are not likely to be 100 percent sure at any given time which application workload is running where.

    To address that issue, Morpheus Data has added a Cross-Platform Discovery module to its Unified Ops Orchestration platform that employs machine learning algorithms to determine not only what applications, virtual machines and containers have been deployed on-premises or in a public cloud, but also how much capacity, memory usage and power consumption each is using and their and overall performance.

    At the same time, Morpheus Data is adding integration with Github and Jenkins continuous integration/continuous delivery (CI/CD) environments as well as support for both Docker Swarm and Kubernetes clusters.

    Finally, Morpheus Data has added connectors to IBM Cloud, Upcloud and HPE OneView services and been certified as a ServiceNow partner. The Unified Ops Orchestration platform already supports Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform.

    Brad Parks, vice president of marketing and business development for Morpheus Data, notes that as IT environments become more distributed in the age of the cloud, new approaches to change management will be required. The Unified Ops Platform provides an opportunity to consolidate change management processes within the context of a single control plane.

    While more IT organizations are making use of multiple cloud services, most are managing each IT environment in isolation. Over time, the lack of unification of the control planes for each of those environments conspires to increase the total cost of ownership for IT. Morpheus Data is making a case of for unifying the management of multiple platforms running on-premises or in public cloud instead of requiring IT staff to master multiple management tools.

    That single management plane, Parks says, also makes it much easier for IT organizations to take dynamically employ multiple cloud environments. Price points for cloud services are liable to change at any moment, but it doesn’t necessarily follow that the same type of workload will continue to be deployed on the same cloud. At the same time, the characteristics of a workload may have evolved to the point where it doesn’t make financial sense to deploy it on a public cloud. A common management platform makes it possible to move that workload with the least amount of disruption possible.

    Most IT organizations today are concerned about getting locked into a cloud service provider. Being able to demonstrate an ability to switch between cloud service providers gives IT organizations an opportunity to negotiate cloud service contracts from a position of strength. Most cloud service providers are counting on the fact that the cost of switching from one provider to another is simply too high. Integrated DevOps processes wrapped around a common management plane, however, will make it clear to all concerned that the platform provider serves at the pleasure of the internal IT department, not the other way around.

    — Mike Vizard