The Rise and Fall of Cloud Management Platforms: Should You Be Concerned?

Executive Highlights:

1. CMPs Had Their Moment: CMPs provided centralized control and cost management for multi-cloud strategies but have struggled to keep pace with modern cloud workloads.
2. Challenges with Evolving Cloud Environments: AI-driven workloads, containers, and cloud-native technologies exposed limitations in CMPs, leading to their decline in favor of more agile alternatives.
3. IPE Solutions Rising:?Infrastructure Platform Engineering (IPE)?is emerging as the flexible, scalable, and automated solution needed to support today's cloud infrastructure.
4. Vendor Lock-In Concerns: HPE’s acquisition of?Morpheus Data?highlights the risk of vendor lock-in, as CMPs are increasingly integrated into proprietary ecosystems like HPE’s?GreenLake
5. A Call for Reassessment: Organizations using CMPs must evaluate whether these platforms meet their future needs or whether?IPE?offers a more flexible and forward-looking approach

• CMP Adoption: Gradual rise until around 2020, followed by a decline as modern cloud-native architectures and IaC solutions gain prominence.
• IaC Adoption: Steady growth, particularly from 2019 onwards, as it becomes a foundational tool for managing cloud infrastructure.
• IPE/Platform Engineering Adoption: Starts later but accelerates rapidly from 2022, reflecting the shift towards more automated, scalable, and flexible cloud management solutions

Warning: This will take about 10 minutes to read.? It attempts to do justice to the contribution CMP’s have made (the Rise), where they started to struggle (the Stumble) and why they have become less relevant as the market and technology changed (the Fall).? So, a decades contribution plus a view on the future of Cloud Infrastructure Automation with a way to assess what this means to you in 10 minutes isn’t that bad! ?

Introduction

For more than a decade,?Cloud Management Platforms (CMPs)?were the cornerstone of enterprise cloud management. In an era dominated by?multi-cloud strategies?and?hybrid infrastructures, CMPs offered a solution that centralized control over cloud resources, enabled governance, and optimized costs. They provided a much-needed simplification in what was becoming an increasingly complex digital environment.

?However, as cloud technology evolved, new challenges emerged. The rapid rise of?AI-driven workloads,?ephemeral environments?like containers, and cloud-native technologies such as?Kubernetes?began to shift how organizations managed their infrastructure. CMPs, which once seemed indispensable, found themselves struggling to adapt to the fast pace of?agile development,?DevOps, and?continuous delivery?practices.

?This report traces the?rise,?stumble, and?decline?of CMPs, offering insights into why these platforms were so widely adopted, the challenges they faced, and how modern cloud management is evolving. Specifically, it explores how?Infrastructure Platform Engineering (IPE)?solutions are stepping in as the next generation of cloud management—offering more automation, flexibility, and scalability to support today's?dynamic workloads.

Additionally, the report looks at the impact of recent market shifts, namely?HPE’s acquisition of Morpheus Data, and what this means for organizations that continue to rely on traditional CMPs. While CMPs may still be relevant in certain legacy contexts, the transition toward IPE solutions highlights a broader shift in how cloud infrastructure will be managed going forward.

The Rise: The Success of CMPs in the Early Days

In the early 2010s, as cloud computing adoption surged, Cloud Management Platforms (CMPs) emerged as essential tools for enterprises transitioning into the cloud. Organizations sought a way to manage multiple cloud providers like AWS, Azure, and GCP, and CMPs delivered a centralized solution to orchestrate multi-cloud environments. By providing visibility, control, and optimization of cloud resources, CMPs became the go-to tool for large IT operations.

Market Adoption and Early Successes CMPs gained traction quickly, with adoption rates reaching as high as 20% during their peak. Early adopters experienced significant benefits, such as a reported 30% reduction in cloud spend, thanks to CMPs’ ability to optimize resource usage and enforce cost controls. At a time when cloud environments were becoming increasingly complex, CMPs provided much-needed visibility and management capabilities, particularly for hybrid cloud architectures.

5 Reasons CMPs Were Adopted.

1. Multi-Cloud Management: As enterprises adopted multi-cloud strategies to avoid vendor lock-in and leverage the strengths of various cloud providers, CMPs simplified the management of resources across platforms like AWS, Azure, and GCP. By offering a single interface to monitor and control cloud operations, CMPs reduced the complexity of managing multiple environments.
2. Resource Optimization and Cost Control: As cloud usage expanded, cost management became a major concern for enterprises. CMPs offered tools to track cloud resource consumption, allocate resources efficiently, and prevent waste, making them an attractive option for organizations looking to control ballooning cloud costs.
3. Governance and Compliance: From 2012-2015, as critical workloads moved to the cloud, security and compliance became top priorities. CMPs addressed these concerns by providing centralized governance tools, including role-based access control and compliance monitoring, ensuring that cloud operations adhered to internal and industry regulations.
4. Automation of Cloud Operations: CMPs enabled organizations to automate repetitive cloud management tasks such as provisioning, scaling, and de-provisioning resources. By automating these processes, CMPs reduced manual errors and saved time, particularly for IT operations teams, while providing pre-configured workflows to standardize cloud operations.
5. Orchestration of Cloud Services: The complexity of cloud services, such as compute, storage, and networking, surged in the early 2010s. CMPs acted as “managers of managers,” integrating with cloud service provider (CSP) APIs to orchestrate and manage diverse services across platforms. This orchestration simplified cloud integration, reducing the need for bespoke solutions.

?CMPs provided a much-needed centralized solution for managing complex, multi-cloud environments during the early days of cloud adoption. Their ability to optimize resources, automate operations, and enforce governance led to widespread adoption, but as cloud technologies and workloads evolved, CMPs became less agile, paving the way for newer, more flexible tools.

The Stumble: CMPs Struggle to Remain Relevant

After their moment of prominence in the early 2010s, Cloud Management Platforms (CMPs) began facing significant challenges by the mid-2010s that slowed their momentum and eventually led to their decline. The “stumble” period—when CMPs struggled to adapt to emerging trends—likely began around?2015-2017?and persisted for several years before CMPs were widely considered legacy solutions by?2020-2022.

Five critical reasons CMPs lost their edge.

1. Limited Scope & Lack of Agility: CMPs were originally built to manage static cloud infrastructure, but as?ephemeral workloads?(such as containers and serverless computing),?multi-cloud strategies, and?AI-driven applications?became more prevalent, CMPs could not keep up. Their rigid, monolithic architecture made them cumbersome and unable to handle the evolving needs of cloud infrastructure. Organizations now required tools that were faster, more flexible, and capable of supporting?continuous delivery?and?short-lived cloud resources. When it started: Around?2015-2017, as cloud-native technologies like Kubernetes gained traction. Why it mattered: CMPs’ inability to adapt to the dynamic, developer-centric environments of modern cloud infrastructure made them ill-suited for the new landscape.
2. Inability to Manage Modern Workloads: As cloud infrastructure evolved, CMPs struggled to manage?ephemeral environments?that could be spun up and down rapidly—like the containers and virtual machines used for?AI/ML workloads. With the rise of?Kubernetes and?microservices architectures, infrastructure needed to be provisioned and managed in real-time. CMPs, which were designed for more static, long-lived infrastructure, were simply not equipped to handle this level of fluidity.When it started: Around?2016-2018, as Kubernetes adoption exploded, and AI/ML workloads became central to many businesses.Why it mattered: CMPs were seen as too slow and heavyweight, pushing organizations toward more agile, developer-friendly platforms that could manage modern, dynamic workloads.
3. Cloud Cost Management Failures: By the late 2010s, CMPs were failing to deliver on one of their core promises—cost optimization. As cloud adoption grew, businesses struggled with inefficient cloud spending, but CMPs could not provide?real-time, granular cost controls?or?AI-driven optimizations?to prevent resource wastage. Enterprises reported wastage rates as high as 30%, and CMPs lacked the analytics needed to align cloud usage with business value. When it started: Around?2017-2019, when businesses began demanding better tools for managing and optimizing cloud costs. Why it mattered: Cost management became a top priority for cloud users, and CMPs couldn’t meet these demands, making them less valuable compared to platforms that integrated cost control and AI optimization.
4. Complexity and Vendor Lock-In: Although CMPs offered many integrations with cloud platforms and services, this often resulted in increased complexity. The “manager-of-managers” architecture, once a selling point, became a liability, adding multiple layers of management and creating friction with other cloud-native tools. CMPs also led to?vendor lock-in, limiting businesses' flexibility as they sought to move towards more streamlined and adaptable management solutions. When it started: Around?2016-2018, as organizations moved toward?multi-cloud?and?hybrid cloud strategies that required more flexible and adaptive tools. Why it mattered: The complexity of managing CMPs and the lack of flexibility pushed companies to seek simpler, more adaptive solutions that could better integrate with modern DevOps practices.
5. Inability to Embrace DevOps and Automation Trends: CMPs were initially built for?IT operations teams, but the rise of?DevOps?and?Infrastructure as Code (IaC)transformed cloud management by the mid-2010s. The need for?infrastructure automation?and?continuous integration/continuous delivery (CI/CD)?practices became central to cloud operations, but CMPs were too slow to adopt these trends. Their architecture was too complex and lacked the necessary integration with developer workflows, making them increasingly irrelevant as?DevOps-friendly?tools became the new standard. When it started: Between?2015-2018, as IaC tools like Terraform and Ansible gained popularity and DevOps became the preferred methodology. Why it mattered: CMPs failed to bridge the gap between IT operations and DevOps, accelerating their decline as DevOps tools became the norm for managing cloud infrastructure.

CMPs initially thrived due to their ability to centralize multi-cloud management, optimize costs, and ensure governance. However, starting around?2015-2017, the cloud landscape shifted dramatically.?Ephemeral workloads,?Kubernetes, and?AI-driven apps introduced complexities that CMPs could not handle. Their inability to evolve alongside DevOps and automation practices led to their stumble. CMPs found themselves too large and deeply embedded in enterprise systems to adapt quickly, yet too slow to keep pace with the fast-changing demands of modern cloud infrastructure. By?2020-2022, CMPs were widely viewed as?legacy solutions, overtaken by more agile, developer-centric platforms that embraced?AI,?IaC, and?cloud-native?methodologies.

The Fall: CMPs Couldn’t Keep Up with Modern Infrastructure

As cloud management evolved, CMPs began to show their limitations. Initially, CMPs excelled at integrating with surrounding platforms, like service management tools such as ServiceNow. They provided centralized control over complex environments, but this hierarchical approach, where all infrastructure integrations were subordinate, quickly became a weakness. In the era of?Infrastructure as Code (IaC)?and?GitOps, CMPs’ rigid architecture became increasingly disconnected from the flexible, developer-centric automation that modern cloud environments demanded.

While CMPs attempted to adapt to?DevOps workflows, their closed platforms and reliance on rigid hierarchies created points of friction. Developers, who favored IaC’s agility and its seamless integration with the?software delivery process, found CMPs cumbersome and poorly suited for?continuous delivery pipelines. Although CMPs could technically integrate with IaC tools, they often failed to interpret the full impact of infrastructure changes, resulting in blind automation without proper ownership—ultimately increasing risks and reducing operational efficiency.

By the late 2010s, CMPs were largely relegated to?legacy technology. They remained useful for some?IT operations, but they could no longer support the dynamic infrastructure requirements of modern workloads. The rise of?AI-driven and?ephemeral environments?further exacerbated this divide, as CMPs were outpaced by newer, more agile solutions designed specifically for the speed and complexity of contemporary cloud infrastructure.

5 Key Factors Contributing to the Decline of CMPs

1. Technological Advancements by Cloud Providers: Modern cloud workloads—driven by?AI, machine learning, and containerization—are highly dynamic, requiring on-demand provisioning and real-time management. Cloud-native tools provided directly by?Cloud Service Providers (CSPs), such as AWS and Azure, handle these tasks more efficiently than CMPs. The dynamic nature of these workloads, which can spin up and down within minutes and span multiple cloud regions, demands automation tools deeply integrated with CSP platforms. CMPs were not designed for this level of diversity and speed, making it difficult for them to keep pace with modern workloads.
2. Outdated “Manager-of-Managers” Role: CMPs were originally designed to manage?multi-cloud environments?through centralized control. However, the shift toward?ephemeral environments?and?containerized applications?has rendered this centralized architecture outdated. CMPs, which often act as isolated automation islands, struggle to support modern?infrastructure automation practices, leaving them poorly equipped to manage today’s dynamic cloud infrastructure.
3. High Complexity and Proprietary Skill Requirements: CMPs frequently require specialized skills and involve complex setup and maintenance processes. This complexity not only increases operational overhead but also prolongs the time and effort needed to derive value from CMP deployments. In contrast, newer?platform engineering?tools, like?Quali’s Torque, integrate more seamlessly with IaC and?development pipelines, reducing both complexity and operational costs by streamlining processes.
4. Longer Time to Value and Higher Total Cost of Ownership (TCO): Implementing CMPs is a time-consuming process, often taking months to deliver value. Significant costs are incurred through customizations, integrations, and ongoing maintenance, making CMPs harder to scale efficiently over time. Comparatively, modern infrastructure Platform Engineering (IPE)?tools, offer much faster time to value—typically in minutes or hours—and drastically lower TCO by automating complex processes and minimizing manual intervention.
5. Shift Toward Infrastructure as Code (IaC) and Platform Engineering: The increasingly diverse nature of cloud workloads demands that infrastructure management be programmable and automated. IaC tools enable precise control over how infrastructure is provisioned, allowing businesses to support specific workloads, from data-intensive AI to multi-cloud deployments. CMPs, however, lacked the flexibility and?AI-driven automation?required to optimize modern cloud environments. As workloads became more transient and resource-intensive,?AI and machine learning?became essential for optimizing resource allocation and responding dynamically to infrastructure demands—capabilities that CMPs simply couldn’t match.

CMPs, once the cornerstone of multi-cloud management, began to falter as cloud technologies evolved. Their inability to adapt to?modern workloads, embrace?DevOps, and provide real-time cost management led to their downfall. While CMPs were designed to centralize and control infrastructure, their rigid architecture and high complexity prevented them from keeping pace with?AI-driven?and?ephemeral environments. In contrast , infrastructure Platform Engineering?tools have emerged as more agile and developer-friendly, providing the flexibility and automation required for today’s dynamic cloud needs.

The?HPE acquisition of Morpheus Data

Business Wire: ?At the time of writing, HPE is in the process of acquiring Morpheus Data. This marks a critical moment for the Cloud Management Platform (CMP) space, highlighting a shift in focus that may signal challenges for current CMP users. HPE’s decision to acquire Morpheus is less about enhancing multi-cloud management across a broad set of platforms and more about strengthening its?GreenLake?ecosystem, which focuses on HPE’s own cloud services.

The acquisition is clearly aimed at enhancing HPE’s GreenLake platform by integrating Morpheus’ multi-cloud orchestration and automation capabilities, with a focus on improving?hybrid IT operations?and adding?basic cloud cost reporting. This is a?strategic decision?for HPE to bolster its own cloud offerings, not necessarily to provide a neutral or vendor-agnostic multi-cloud management solution that many enterprises using Morpheus may need.

What It Means for Morpheus Users

For enterprises currently relying on Morpheus to manage multi-cloud environments, this acquisition could mean:

1.????? Vendor Lock-In: HPE’s GreenLake is its flagship platform, and future development of Morpheus is likely to be tightly aligned with GreenLake’s ecosystem. While Morpheus may retain some multi-cloud capabilities, the focus will likely shift toward supporting HPE’s offerings, limiting its utility for those managing non-HPE environments like AWS, Azure, or GCP (Business Wire)(ExecutiveBiz)(ITPro).

2.???? Narrowing Innovation: HPE is expected to direct resources towards enhancing GreenLake-specific features rather than advancing Morpheus' broad multi-cloud functionalities. This could mean that Morpheus’ previous strengths in DevOps and hybrid cloud management might be deprioritized (ITPro)(Constellation Research Inc.).

A Cautionary Lesson: This acquisition serves as a reminder to businesses still relying on CMPs: the market is evolving, and the original value propositions of CMPs—particularly in neutral, multi-cloud management—are becoming less relevant. As vendors like HPE acquire these platforms to bolster their own services, the risk of?vendor lock-in?increases, and the flexibility once offered by CMPs diminishes. It may be time for enterprises to reconsider whether their cloud management needs are better met by?Infrastructure Platform Engineering (IPE)?solutions, which offer greater flexibility, real-time governance, and tighter integration with modern cloud-native practices.

A New Era: The Rise of Infrastructure Platform Engineering (IPE)

As Cloud Management Platforms (CMPs) decline in relevance, the industry has shifted toward?Infrastructure Platform Engineering (IPE)?and?Environments as Code (EaC), offering superior agility, automation, and scalability for managing modern cloud infrastructure. These solutions are driving a new era of cloud management, with Infrastructure as Code (IaC) at its core, enabling infrastructure to be seamlessly defined, managed, and embedded into the software delivery lifecycle.

When integrated with IPE,?IaC?is simplified, standardized, and transformed into reusable building blocks that create environments-as-code (EaC). These environments can easily incorporate policies, resource tagging, and integrations, providing real-time control and visibility over cloud resources. Organizations benefit from optimization aligned with workload priorities and real-time insights into cloud costs, ensuring that infrastructure remains flexible, efficient, and purpose-driven.

IPE lays the groundwork for?continuous delivery?and?real-time optimization, making cloud infrastructure as programmable as software. This ensures massive scalability, supporting dynamic workloads like AI and microservices. Additionally, the use of AI and GenAI enhances cloud provisioning through natural language, guided execution, and intelligent workflows, offering users of all skill levels secure, automated access to cloud resources.

?Why IPE Solutions Are the Future

AI-Driven Insights and Real-Time Governance: Modern IPE platforms leverage?AI-driven automation?and?policy-driven governance?to continuously optimize cloud resources in real-time, setting them apart from the reactive processes of CMPs. By incorporating?Policy as Code, IPE platforms ensure governance is seamlessly enforced across environments.

• AI-Driven Automation: IPE platforms use AI to analyze workloads and adjust infrastructure dynamically, ensuring resources are used efficiently. This proactive approach reduces waste and enhances performance, making IPE more responsive to infrastructure demands.
• Real-Time Policy Enforcement: Platforms like?Quali Torque?automatically enforce security, compliance, and operational policies across all environments, helping to prevent security breaches or compliance failures.
• Why this matters: AI-driven governance and optimization ensure that infrastructure is not only scalable but also governed effectively, making cloud management both smarter and safer than ever before.

Agile Infrastructure for Modern Workloads: IPE platforms are purpose-built to handle the highly dynamic workloads found in modern environments—such as?AI-driven applications,?AI modeling, ephemeral containers, and?serverless computing. With?Environments as Code (EaC), these platforms take IaC one step further by managing the entire environment (including software, infrastructure, and dependencies) as code.

• Seamless Multi-Cloud Integration: IPE solutions simplify managing multi-cloud environments by orchestrating resources across AWS, Azure, GCP, and other platforms with ease.
• Environments as Code (EaC): IPE platforms allow businesses to automate the lifecycle of entire environments, ensuring that resources are provisioned, secured, and governed automatically. This helps eliminate the manual configuration challenges that CMPs could never fully resolve.
• Why this matters: The ability to manage entire environments as code significantly improves agility, enabling businesses to spin up environments rapidly, test new workloads, and decommission them as needed—particularly important for?Kubernetes?and?micro-service based architectures.

Future-Proof Flexibility IPE platforms are designed with a?cloud-agnostic architecture, providing businesses with the flexibility to work across multiple cloud providers or hybrid environments without worrying about vendor lock-in. This flexibility is crucial as organizations adopt?AI,?machine learning, and?edge computing?technologies, which require infra. that can adapt easily.

• Cloud-Agnostic Infrastructure Management: IPE platforms are not bound to a specific cloud provider, allowing organizations to scale their infrastructure across different clouds as needed, while maintaining consistent governance and security policies.
• Alignment with Business Outcomes: With IPE, infrastructure is tightly aligned with business objectives, ensuring that resources are managed efficiently and adapt to strategic goals.
• Why this matters: Flexibility and adaptability are key to staying competitive in a rapidly evolving cloud landscape, and IPE platforms ensure that businesses are ready for future innovations without requiring costly infrastructure changes.

Lower Total Cost of Ownership (TCO) and Faster Time to Value Compared to CMPs, IPE platforms offer a significantly?lower Total Cost of Ownership (TCO)?by automating complex infrastructure tasks and reducing manual intervention. IPE platforms integrate deeply with?IaC tools like Terraform and OpenTofu, making infrastructure management faster, more automated, and less resource-intensive.

• Reduced Setup Time: IPE platforms can be deployed in hours or less, enabling businesses to realize value quickly.
• Automated Scaling and Optimization: IPE platforms automatically adjust infrastructure to meet workload demands, reducing the need for manual scaling and driving down operational costs.
• Why this matters: With faster setup times and greater automation, IPE platforms reduce the complexity and costs associated with cloud management, helping businesses improve their cloud ROI.

?Tight Integration with DevOps and Infrastructure as Code (IaC) Modern cloud infrastructure must be integrated into?DevOps pipelines?to support?continuous integration and delivery (CI/CD). IPE platforms are designed to work seamlessly with?Infrastructure as Code (IaC), allowing infrastructure to be provisioned, updated, and scaled through automated scripts and processes.

• Continuous Delivery (CD): IPE platforms allow developers to automatically provision environments and manage infrastructure as part of their CI/CD pipelines, reducing the risk of manual errors and improving deployment speeds.
• IaC Automation: IPE platforms treat infrastructure as software, ensuring that every environment is reproducible and easily modified. By leveraging IaC, businesses can apply the same rigorous standards of automation and version control to their infrastructure as they do to their codebase.
• Why this matters: By embedding infrastructure into the development lifecycle, IPE platforms enable teams to move faster, deliver more reliably, and maintain greater consistency across all cloud environments.

The future of cloud infrastructure is being shaped by?Infrastructure Platform Engineering and Infrastructure as Code (IaC), which enable businesses to automate, scale, and govern their environments more efficiently than ever before.?AI-driven insights,?policy-based governance, and?real-time automation?ensure that IPE platforms provide the flexibility, agility, and cost savings that modern businesses need to thrive.?Gartner’s Hype Cycle?predicts that IPE platforms will continue to gain market share, with faster time to value and lower operational costs compared to CMPs.

So what does all this mean to you?

For Enterprises Using CMPs:

• Re-assess your current cloud management tools.
• Consider the risks of vendor lock-in and stagnation in innovation.
• Explore IPE solutions for enhanced flexibility and real-time governance.

The Morpheus Example:

• Explain how HPE’s acquisition of Morpheus reflects the broader market trend toward proprietary ecosystems.
• Highlight the potential loss of innovation focus in Morpheus for non-HPE users.

The Future of Cloud Management:

• IPE solutions are poised to dominate, offering the speed, flexibility, and AI-driven intelligence required for modern cloud-native environments.

Additional Resources:

1. Gartner’s Reports on Cloud and Platform Engineering

You can explore relevant Gartner reports and research by visiting their?Research?and?Insights?section. They frequently publish insights into cloud trends, DevOps, and platform engineering.

2. Infrastructure as Code (IaC) Best Practices

Carnegie Mellon University’s Software Engineering Institute (SEI) Final Report on IaC: This report explores the feasibility of IaC, focusing on its ability to automate the setup of virtual machines, networks, and cloud environments through code. It discusses prototype tools for generating IaC scripts and provides practical insights into accelerating IaC adoption. You can find this resource?here (SEI)

3. DevOps.com

DevOps.com?provides a wide range of articles, case studies, and resources focused on the latest trends in DevOps, including automation and IaC implementation.

4. The Cloud Native Computing Foundation (CNCF)

CNCF?offers extensive resources on cloud-native technologies, including Kubernetes, CI/CD pipelines, and infrastructure platform engineering.

Discover More About IPE at Quali

To learn more about how?Infrastructure Platform Engineering (IPE)?can streamline your cloud operations, visit the?Quali?website, where you can find valuable resources on:

• Quali's?Torque?Platform: Discover how?Torque?simplifies cloud infrastructure automation with?Environments as Code?and helps manage complex, ephemeral workloads with ease.
• Blogs?and?Case?Studies: Stay updated with the latest industry insights and real-world case studies on the implementation of IPE and IaC in enterprise environments.
• Product?Demos?and?Webinars: Explore webinars and demos that highlight how Quali's solutions empower organizations to achieve faster time-to-value with automated cloud provisioning and infrastructure management.