To understand the cloud computing landscape today and what true digital transformation looks like, we should first understand how we got here.
During the early part of the last decade, we witnessed what I’ll call the VM Cloud Era. VM, of course, stands for virtual machine, technology that was widely used on-premises and a foundational technology for public cloud providers, like AWS, Google, Azure, etc. Many new organizations, like start-ups, realized they could forgo buying or operating their own hardware and just started with workloads and applications hosted on public clouds. This was a major catalyst for many of the great cloud-native companies that we rely on today, such as Twitter, Spotify and PayPal. By the end of the VM Cloud Era, very few start-ups operated their own data centers.
During the latter part of the last decade, the Infrastructure Cloud Era began, which is when public cloud providers saw a large increase in organizations using a vast array of infrastructure services – not just servers, but storage, databases, containers, etc. This broadened adoption saved time and costs because cloud providers could easily scale up and down quickly as peaks and valleys occurred. Faster product development was made possible because companies did not need long-term infrastructure planning for new compute requirements, some of which may lay idle for long periods. Often, security was better too.
By reducing the on-premises hardware management load on IT staff, organizations could direct people and resources to focus on more strategic initiatives. In the Infrastructure Cloud Era, many companies that ignored the availability of broad cloud services trailed behind with time-to-market and cost savings from their cloud-adopting competitors.
Although the return on investment of these early cloud eras was important, it did not provide a compelling or disruptive result. Nor did this period of migrations fundamentally change how people worked outside of IT. This is because digital transformation is more than simply shifting workloads and infrastructure needs to the cloud for convenience or cost-savings.
This brings us to the post-pandemic period that I call the Transformation Cloud Era, where IT organizations are not just making infrastructure decisions, but teaming with the business or public agency on transforming employee, customer and constituent service delivery. Digitalization is now fundamental. This era is about spreading transformation across an organization’s service delivery chain.
To take advantage of this new era, data centers will be hybrid and multi cloud – culminating in a best-of-breed on-premises, single tenant setup along with multiple public cloud, multi-tenant deployments.
To facilitate constant innovation and progress, today's most innovative organizations are building their Transformation Cloud strategy. A Transformation Cloud is a new approach to digital transformation. The result is an organization that benefits from modern cloud computing to drive innovation, generate new revenue streams, and adapt quickly to market changes and customer needs.
Organizations have to be open to embrace the change brought as new eras evolve. Any journey is best done with an experienced, reliable and like-minded partner.
DX Unified Infrastructure Management (DX UIM) is such a partner that has stood the test of time over the last two decades. DX UIM provides a single pane of glass for monitoring across the infrastructure stack – traditional and hyperconverged on-premises (private cloud) as well as multiple public cloud environments. It provides a complete solution for performance monitoring and alarm management.
DX UIM by Broadcom delivers the digital infrastructure observability needs of global enterprises, government agencies and managed service providers in terms of security, scalability and reliability for the new Transformation Cloud Era.

Ashish Aggarwal
Ashish is a seasoned product management leader with extensive experience in the enterprise software industry, specializing in observability solutions. As a lead product manager, Ashish spearheads the modernization of ingestion processes for DX Operational Observability and oversees Infrastructure Observability,...
Other resources you might be interested in
Rally Office Hours: October 2, 2025
The Rally Model Context Protocol (MCP) Server acts as a standardized interface for AI models and developer tools. Learn about this exciting new feature then follow the weekly Q&A session with Rally...
Why 1% Packet Loss Is the New 100% Outage
In an era of real-time apps and multiple clouds, the old rules about 'acceptable' network errors no longer apply. See why you need end-to-end observability.
Rally Office Hours: September 25, 2025
Rally Office Hours delivers an essential product tip: Learn to transition from Legacy Custom Pages to powerful Custom Views. Plus, Q&A insights.
Defining the Network Engineer of Tomorrow
Read this post and see why the most important investment isn't in new hardware, but in transforming your team from device managers to service delivery experts.
Harnessing AppNeta’s Browser- and HTTP-based Workflows to Track User Experience
AppNeta’s browser- and HTTP-based workflows let you see what users actually experience. Preempt issues before they become headaches for your end users.
“Rego U” Recap: Why SPM Is Still Hot
Rego Consulting’s Annual Conference underscored why strategic portfolio management (SPM) is still essential. Leverage SPM to bridge strategy and execution.
What's New in AutoSys 24.1: Built for the Modern Automation Landscape
See how AutoSys 24.1 is designed to streamline your daily tasks, accelerate troubleshooting, and simplify how you integrate with the latest technologies.
Rally Office Hours: September 18, 2025
In the latest edition of Rally office hours, learn about changes to the Progress Views widget and then follow the weekly Q&A session with Rally product experts.
Automic Automation Cloud Integrations: Google Cloud Batch Agent Integration
See how Broadcom's Google Cloud Batch Automation Agent makes it easy to schedule, queue, and execute batch processing workloads on Google Cloud resources.