Harsha Penubadi on Cloud Infrastructure 2.0

In 2024, global spending on public cloud services reached a staggering $595.7 billion, marking another explosive year of growth for cloud technology adoption. As industries embrace AI-driven solutions and automation, the cloud has become the backbone of modern IT and business innovation. We're joined by Harsha Penubadi, leading DevOps engineer and cloud expert, to explore where cloud infrastructure and automation are headed next. Penubadi sheds light on the evolution of the cloud and the tech shaping its future.

Mr. Penubadi, cloud infrastructure has come a long way from its early days as a storage solution. Can you walk us through the technical evolution and how we see that reflected today?

Right, cloud infrastructure was introduced as a way to offload data storage, but we recognize it today as the backbone of modern IT. As cloud providers expanded their services, Infrastructure as a Service enabled larger organizations struggling with the overhead from physical infrastructure to virtualize their servers.

This paved the way for Platform as a Service and eventually full-stack migrations, where companies could deploy entire tech stacks within the cloud, integrating databases and containerization tools. And today, cloud infrastructure has evolved to include entire orchestration and management layers, enabling many of the much-needed scalability and automation capabilities. Infrastructure as Code and CI/CD (continuous integration/continuous delivery) have proven very effective in spaces where stability and business continuity are the top priorities.

That brings us to hybrid and multi-cloud solutions. What’s driving this trend?
In a few words: flexibility and avoiding single-vendor lock-in. IT leaders recognize the risks of relying too heavily on one provider, and multi-cloud setups allow companies to take advantage of the unique strengths of different platforms. Workload portability is also a factor, where there are more tools today to enable consistent environments across providers. In a sense, both providers and enterprises have moved in tandem to make hybrid and multi-cloud approaches not only feasible but highly attractive.

But for established industries relying heavily on legacy systems, migrating to the cloud is still challenging. What technical barriers do you commonly encounter?

Right. Migration to IaC has clear benefits, but it’s not a one-size-fits-all solution, and it doesn’t happen overnight. The risks of staying on legacy systems is that they're almost always monolithic and designed for on-premise environments. While they were once best practice, they're now riskier and harder to adapt. Moving these systems often requires decoupling applications or, in many cases, re-architecting them entirely. A 'lift-and-shift' approach, where you move applications as-is, often isn’t sustainable because of performance bottlenecks or compatibility issues. Instead, re-platforming or refactoring becomes necessary, where applications are modified or broken into microservices that can be managed in a cloud environment.

Data migration is also very challenging, especially in industries like healthcare where large, sensitive datasets are involved. Moving data securely without disrupting operations often requires temporary hybrid setups to sync data between on-prem and cloud systems, which is all the more complicated by compliance requirements.

You mentioned security as a top concern. What are the main security challenges you see in cloud adoption, and how can organizations address them?

Cloud environments require a different approach due to the expanded attack surface. We prioritize securing data both at rest and in transit, with strict identity and access management and network security. With the increase in remote work, there are typically far more endpoints to manage. Manual review doesn’t scale effectively, so embedding security checks throughout the CI/CD pipeline—like using automated vulnerability assessments before deployment—is the most scalable solution. Security in these environments is all about consistency rather than reactivity.

What other modernizations are impacting infrastructure deployment? Does AI factor in?

Edge computing is starting to prove itself, especially in latency-sensitive IoT applications like autonomous driving and industrial automation. Instead of backhauling data to a central cloud, edge devices perform most of the processing, sending only relevant data back to the cloud for storage or further analysis.

Complementary technologies like serverless and microservices have also become very common, branching from IaC principles. Abstracting away the server layer and quickly replicating environments is very powerful for both agility-focused companies like start-ups, and larger organizations that are highly distributed, geographically and infrastructural.

Regarding AI: It's a fair question. It’s become another layer of automation across the stack, especially for anomaly detection and resource allocation. A fascinating application is self-healing infrastructure, where systems "learn" to recognize issues like failing nodes or network latency, and adjust configurations or restart services without manual intervention. Many of these changes are focused on quality of life and reducing manual overhead, with the added benefit of increasing your architecture's resilience.

Finally, for organizations wanting to keep pace with advancements in cloud infrastructure, what technical advice would you give?

Adopting Infrastructure as Code is a great first step for companies without strict latency or security requirements—it offers consistency and scalability that can be difficult to achieve with traditional infrastructure. Second, focus on developing an integrated CI/CD pipeline that incorporates DevSecOps best practices relative to your organization's needs. The cost and time savings from automation can be redirected to secure and optimize your architecture. And of course, organizations should focus on upskilling their teams. Having the right expertise makes adoption and implementation much smoother.