The Future of DevOps

When I was asked to think about my technology predictions for 2025, it occurred to me how much happened from 2023 until now, where the dust is still settling and the reverberations from these seismic shifts in our ecosystem are still taking hold of our industry. 

The Infrastructure as Code (IaC) landscape is entering an era of transformation. The ubiquitous tools we came to know and love are being replaced with newer more open options — if we just recap all of the major milestones from then until now: Terraform is losing ground to other more open solutions after closing its license in August 2023, the fork of OpenTofu and its contribution to the Linux Foundation, and the consequent acquisition of Hashicorp by IBM, as well as the growing momentum around other IaC tooling like Crossplane, Pulumi and even ARM templates. 

All of these have played and will continue playing a major part in redefining this category and the way we manage infrastructure over the coming years.

Until recently, most of the IT and DevOps effort was focused on getting laggards into the cloud — with cloud migrations being in advanced stages of adoption, organizations are now focusing on optimizing their infrastructure practices, addressing increasing complexity, and aligning strategies with business objectives. IaC will be a pivotal force in moving from cloud migration to full codification. 

This evolution is driven by two key forces: 

1. The diversification and wider scope of IaC frameworks as broader cloud management layers 
2. The integration of artificial intelligence (AI) to supercharge and alleviate growing challenges 

Together, these trends are redefining how infrastructure is built, monitored, and optimized — for performance and cost. Alongside these shifts, developer enablement through platform engineering is emerging as a critical focus area in the race toward scalable and efficient infrastructure management.

Prediction #1. AI-Driven Drift Management: Progress Without Perfection 

Drift management remains one of the most persistent challenges in IaC. Drift, the misalignment between declared infrastructure states and their actual implementation, becomes more pronounced as environments scale in complexity. This challenge is exacerbated by the dynamic nature of multi-cloud and hybrid setups.

AI is poised to revolutionize how drift is detected and managed. Emerging tools use AI to identify patterns in drift, recommend automated reconciliation steps, and enforce preventive policies. These tools are beginning to turn drift management from a reactive process into a proactive strategy. However, despite its promise, AI is not able to entirely eliminate drift. 

Manual intervention, the source of drift, will remain essential in modern, demanding, and complex incident-driven environments or nuanced scenarios that require immediate resolutions. The future of drift management will involve a symbiotic relationship between AI tools coming in to detect and resolve issues more rapidly that arise as a result of human intervention, making it a mitigated but persistent challenge — however, with additional guardrails to not undo critical changes, even when created manually.

Prediction #2. The Diversification of IaC Frameworks: A Unified Yet Fragmented Landscape 

The cloud and IaC ecosystem is becoming increasingly fragmented as organizations embrace hybrid setups that combine multi-cloud/cloud-native operations powered by a diversity of tooling per use case like OpenTofu, Terraform, Crossplane, Pulumi, Helm, CloudFormation, and ARM/Bicep, and other Kubernetes-native solutions. This diversification is a direct response to the growing complexity of multi-cloud strategies, workload requirements, and the demand for vendor-agnostic infrastructure management.

Managing these diverse frameworks requires robust solutions to unify operations and enforce policy compliance. Enterprises are moving toward adopting tools and practices that streamline operations across multiple frameworks, such as shared policy enforcement layers or universal state management platforms. This diversification isn't just about technical evolution; it reflects a strategic shift toward greater adaptability, resilience, and less lock-in, providing greater flexibility in infrastructure management.

Prediction #3. Cost Optimization Becomes a Core Pillar of DevOps Practices 

Looking ahead, cost optimization will evolve from being a reactive, siloed activity to a proactive, integrated part of DevOps workflows. Teams will adopt CostOps principles, embedding cost management into the CI/CD pipeline and infrastructure provisioning processes. Automated cost analysis will be tied directly to deployment pipelines, providing real-time feedback on the financial impact of code and infrastructure changes before they are deployed. AI-powered tools will play a significant role, offering predictive insights into cloud expenditures and enabling dynamic scaling and engineering decisions based on both performance and cost efficiency. 

Additionally, DevOps platforms will increasingly integrate cost data with observability tools, giving teams a unified view of application performance, resource utilization, and associated expenses. Cost optimization will also become deeply intertwined with IaC diversification. As frameworks proliferate, they bring opportunities to better align infrastructure provisioning with financial goals. 

Tools that integrate cost visibility and predictive budgeting into IaC practices are gaining traction, offering insights that connect infrastructure choices to real-time expenses. By weaving cost optimization into their multi-framework strategies, organizations can achieve operational efficiency and financial sustainability, and the ability to do this cross-cloud and framework will be essential in multi-cloud and multi-framework realities.

Prediction #4. AI Codifying the Uncodified: From ClickOps to Code 

One of the most transformative developments in IaC is the role of AI in converting manual configurations into automated, reusable code. This is particularly significant in addressing the challenges of “ClickOps” — manual, ad hoc infrastructure changes that leave organizations with unmanaged, fragmented environments.

AI-powered tools are now capable of analyzing existing infrastructure, detecting uncodified configurations, and generating corresponding IaC definitions. This capability accelerates cloud migrations and simplifies infrastructure management, empowering organizations to achieve complete codification of their environments. The rise of natural language interfaces, where users can query metrics, generate configurations, and debug issues through conversational AI, will democratize IaC adoption, making it accessible even to teams with limited technical expertise.

Prediction #5. The Rise of Internal Developer Platforms (IDPs): Empowering Self-Service

We can’t have a predictions post without talking about platform engineering. So, in case you’re wondering, no, DevOps is not dead; it’s just evolving — and platform engineering is just one manifestation of that evolution.  

Internal Developer Platforms (IDPs) are emerging as one way for engineering teams to try to reduce the complexity of provisioning, configuring, and managing the infrastructure that powers applications. IaC practices are at the core of making this possible in a repeatable, consistent way at scale. Platforms like Backstage, Port, and Cortex provide developers and operators with a unified, self-service interface for managing infrastructure. By integrating IaC tools and frameworks, IDPs enable seamless workflows that reduce operational overhead and enforce best practices.

IDPs represent more than convenience; they embody the shift toward infrastructure democratization. By abstracting the complexities of IaC frameworks, these platforms allow teams to focus on delivering business value rather than navigating the intricacies of infrastructure. As organizations continue to diversify their infrastructure and tooling stacks, IDPs will play a critical role in unifying operations and enabling agility in a multi-framework world.

Toward 2025: The New IaC Landscape

The future of IaC is a convergence of complexity, automation, and innovation. AI will transform many domains from drift management through unprecedented insights while leaving room for human intervention to cost management, providing a greater correlation between cost and company goals. IaC frameworks that deliver vendor neutrality will be the backbone of framework diversification, driving greater flexibility and resilience, with cost optimization becoming a core element of this strategy. 

Meanwhile, AI will continue to codify the uncodified, simplifying infrastructure management and will accelerate cloud migrations. Finally, IDPs will rise as the key to managing this complexity, offering self-service platforms that empower teams to work seamlessly across diverse frameworks.

As we look toward 2025, organizations must embrace these shifts to stay competitive. By integrating AI-driven tools, adopting multi-framework strategies, and leveraging the power of IDPs, enterprises can prepare for the next chapter in the IaC journey. The future is not just about managing infrastructure — it’s about redefining how we approach it to unlock new levels of efficiency and innovation.