Future of the Cloud: 10 Trends Shaping 2025 and Beyond

In 2025, several trends will dominate cloud computing, driving innovation, efficiency, and scalability. From Infrastructure as Code (IaC) to AI/ML, platform engineering to multi-cloud and hybrid strategies, and security practices, let’s explore the 10 biggest emerging trends.

1. Cloud Will Become a Business Necessity by 2028

According to Gartner, by 2025 the cloud will be the key driver for business innovation, and estimates that over 95% of new digital workloads will be deployed on cloud-native platforms.

According to McKinsey & Company’s “In search of cloud value” report:

• Cloud enables businesses to innovate, which is worth more than x5 what is possible by simply reducing costs.
• The anticipated increase in EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) attributable to cloud adoption is projected to range between 20% and 30% by the year 2030 - but it’s expected to vary across different sectors.
• Asian companies have the most to gain from the cloud, with $1.2 trillion in EBITDA. American institutions stand to capture about $1.1 trillion in cloud value, while European institutions are at $773 billion due to regulatory constraints.
• Companies that have captured the most ROI consistently do 3 things well: 1/ work closely with business leaders to focus on high-value business cases, 2/ build a robust cloud foundation, and 3/ adopt a product-oriented operating model.

2. Large Organizations with Multi-Cloud and Hybrid Environments

Multi-cloud and Hybrid (mixing cloud and on-premise infrastructure) environments are a trend that is here to stay. According to Forbes and Gartner, by 2025, 85% of large-sized companies will have a multi-cloud strategy. Organizations recognize the importance of leveraging multiple cloud providers and on-premises infrastructure to optimize performance, enhance redundancy, and mitigate risks.

The following trends also relate to this multi-cloud and hybrid approach as companies seek ways to balance flexibility and cost while increasing overall productivity with security and compliance in mind.

3. Infrastructure as Code (IaC) Crucial for Scalability

IaC in general-purpose languages is gaining prominence as organizations seek to automate and streamline their infrastructure management processes and reduce the divide between application development and cloud infrastructure development.

Infrastructure as Code is maturing beyond taming the complexity of the cloud:

• Facilitating the adoption and configuration standardization of multi-cloud and hybrid strategies
• Better integration with multiple cloud providers, like AWS, Azure, and Google Cloud, data stores, and third-party services like Cockroach Labs db, Confluent cloud, Kafka, and more
• Deeper validation on parameters that people are passing in, checking all critical components, ensuring they are configured correctly before deployment
• More efficient resource management
• Robust security and Policy as Code to enforce security practices, guardrails, compliance, cost policies, and more
• Intelligent automation, including automated tests and remediation policies
• AI-driven automation and insights

4. Increased Focus and Budgets for Security (DevSecOps)

Security is no longer a separate consideration but a top priority in the cloud landscape. By 2025, security practices are expected to be seamlessly embedded into every stage of the DevOps lifecyle. Below are the 3 key predictions for the future of DevSecOps:

1. AI-Driven Security: AI and machine learning (ML) will be instrumental in automating security and in providing real-time insights, enabling proactive and predictive security measures.
2. More Focus on Secrets Management: Organizations will prioritize robust secrets management within their DevSecOps processes as data privacy concerns escalate. It will be essential to secure sensitive data such as API keys, credentials, and other secrets to ensure compliance and avoid unauthorized access.
3. Collaboration as a Key Factor: Collaboration between development, security, and operations teams will be crucial for the success of DevSecOps efforts.

Policy as Code will also be an indispensable pillar in many security aspects:

1. Use off-the-shelf rules or define your best practices for security, cost, compliance, and reliability
2. Maintain security across all cloud infrastructure assets
3. Catch policy violations before they escape using CI/CD
4. Automate governance using programmable libraries and REST APIs, easily integrating with external services such as web services, asset tracking databases, pricing lists, and more

5. Platform Engineering – Internal Developer Portals (IDP) for Better Developer Experience

By 2026, 80% of large software engineering organizations will establish platform engineering teams as internal providers of reusable services, components, and tools for application delivery. Platform engineering will ultimately solve the central problem of cooperation between software developers and operators (source: Gartner).

Mid-size to large companies will begin or continue to invest in implementing platform engineering practices, with large tech companies as first adopters. They will provide Internal Developer Portals (IDP) to elevate the Developer Experience (DX, sometimes referred to as DE or DevEx), helping them work faster, like abstracting the complexities of configuring, testing, and validation, deploying infrastructure, and scanning their code for security.

6. The Rise of AIOps Through the Combination of AI and Automation

In 2025, AIOps will gain further relevancy in the IT operations landscape, becoming integral to DevOps practices. As AI and automation continue to evolve, the fusion of these technologies will enable organizations to achieve unprecedented levels of efficiency and scalability.

• Proactive Operations: AI-powered tools will assist teams in foreseeing issues with greater accuracy, minimizing downtime, and reducing the firefighting nature of incident management. These tools will automatically detect anomalies, optimize performance, and trigger remediation actions.
• Intelligent Automation: Routine operational tasks like patching, monitoring, and resource scaling will be fully automated. AI-driven decision-making will allow for smarter resource allocation and optimization, dynamically adjusting infrastructure and workloads in response to real-time demands and predictions.
• Data-Driven Insights: AIOps will analyze vast amounts of operational data and provide actionable insights, enabling teams to focus on high-impact tasks such as improving system architecture and user experience. The AI-powered insights will also inform better strategic decisions, helping teams to continuously evolve their DevOps practices.
• Collaboration Across Teams: AIOps will bridge the gap between DevOps, SecOps, and IT operations by bridging monitoring and automation. Cross-team collaboration will improve as AI systems consolidate and interpret data from various departments, allowing for a more cohesive approach to system management.

7. Investment in Data and Data Streaming

Data streaming is a buzzword set to go up in the maturity curve:

• Data Sharing for faster innovation. Collaboration within and beyond organizational boundaries is facilitated through data sharing, utilizing streaming protocols like Kafka, APIs like REST/HTTP, and adhering to open standards like AsyncAPI.
• Data Contracts for better data governance include enforcing policies for structure, integrity constraints, metadata, rules, and other specifications.
• Serverless Stream Processing will make building scalable and elastic streaming apps easier. The focus shifts towards deriving business value by leveraging a fully managed, integrated, and secure infrastructure.
• Multi-Cloud Deployments for cost-efficient delivery value, addressing the need for seamless data movement across cloud providers, organizations invest in data bridge creation, migrations, and disaster recovery solutions.
• Reliable Generative AI. This encompasses activities such as model training, real-time model scoring, and integration with third-party services, such as GenAI LLMs or Software as a Service (SaaS) offerings, to enhance the capabilities of artificial intelligence.

Event streaming technology can be transformative but often difficult to adopt. Watch Collin James, Engineering Leader and Software Architect at Dutchie, describe how a small team has enabled Kafka adoption by creating a monorepo of Pulumi projects that manage resources on Confluent Cloud.

8. Kubernetes Dominance and Increased Complexity

Kubernetes, the open-source container orchestration platform, will continue its ascent in 2025. According to Markets N Research, the global Kubernetes market size was valued at USD 1.8 billion in 2022 and is projected to be USD 7.8 billion by 2030, exhibiting a CAGR of 23.40% during the forecast period.

The “growing pains” will also increase with rising concerns in security, networking, deployment, scalability, cost, and impact on developer productivity. Read the previous LinkedIn Newsletter article From Complexity to Simplicity: Streamlining Kubernetes with Infrastructure as Code.

9. Cost Transparency and Governance

As cloud environments become more complex, ensuring cost transparency and governance will be a priority. In 2025, businesses will continue to invest in cloud optimization and/or cost management tools and processes to monitor and control cloud spending effectively. This includes implementing policies, managing resource allocation, and utilizing cost analytics to make informed decisions about resource utilization.

As a result, IDC predicts that complexities and IT budget pressures will drive 70% of Global 1000 companies to increase FinOps maturity with granular chargebacks, benchmarking, and multiple-cloud optimization.

10. Enterprises Will Allow the Use of AI Code Assistants

Developers worldwide have explored or are currently using AI-powered coding assistants. However, many enterprises have shown resistance to allowing them to be part of their AI tools in software development. Still, software engineering leaders are beginning to recognize that these coding assistants can enhance team productivity, improve code quality, and maintain a competitive advantage.

By 2027, the use of AI assistants will dramatically increase developer velocity to meet functional business requirements for 70% of new digital solutions in production (source: IDC).

According to Gartner, by 2028, 75% of enterprise software engineers will use dedicated AI code assistants, and 63% of organizations are currently piloting, deploying or beginning to use AI code assistants, just like Pulumi AI.

Keeping up with the Future Cloud Trends

From advanced technologies like AI/ML and Kubernetes to practices like FinOps and Security, the cloud of 2025 is set to redefine best practices for enhanced efficiency, security, and scalability. You may have noticed that many trends overlap, and a holistic view will be crucial for organizations aiming to stay ahead.