diff --git a/content/blog/beyond-yaml-kubernetes-2026-automation-era/index.md b/content/blog/beyond-yaml-kubernetes-2026-automation-era/index.md index 5569a084709c..712c81f10394 100644 --- a/content/blog/beyond-yaml-kubernetes-2026-automation-era/index.md +++ b/content/blog/beyond-yaml-kubernetes-2026-automation-era/index.md @@ -138,14 +138,19 @@ Kubernetes and Pulumi Neo together represent a future of **autonomous infrastruc ## Operator-First: Kubernetes Deploys Your Cloud -The [Pulumi Kubernetes Operator 2.0 GA](https://www.pulumi.com/blog/pulumi-kubernetes-operator-2-0-ga/) introduced a Kubernetes-native approach to infrastructure management. Each Pulumi stack becomes a **Kubernetes Custom Resource**, allowing Kubernetes itself to execute Pulumi programs written in any supported language. - -This enables: +The [Pulumi Kubernetes Operator 2.0 GA](https://www.pulumi.com/blog/pulumi-kubernetes-operator-2-0-ga/) introduced a Kubernetes-native approach to infrastructure management. Each Pulumi stack becomes a **Kubernetes Custom Resource**, allowing Kubernetes itself to execute Pulumi programs written in any supported language. This enables: - Management of AWS, Azure, and GCP infrastructure from within the cluster - Integration with GitOps systems such as Argo CD and Flux - Continuous reconciliation and drift detection through Pulumi’s state and policy engine +With the new [Pulumi Kubernetes Operator 2.3](https://www.pulumi.com/blog/pulumi-kubernetes-operator-2-3/), the operator gets even more production-ready features: + +- Faster and more resilient stack updates through improved workspace lifecycle management +- Support for multi-namespace and multi-tenant deployments +- Better visibility with enhanced events, status reporting, and error surfacing +- Performance improvements for large-scale environments and parallel stack operations + Documentation: [Using the Pulumi Kubernetes Operator](https://www.pulumi.com/docs/iac/guides/continuous-delivery/pulumi-kubernetes-operator/) ## Intelligent Infrastructure Across Every Cloud @@ -174,16 +179,18 @@ For teams preparing for the next phase of Kubernetes management in 2026: 4. [Apply policy guardrails](https://www.pulumi.com/docs/insights/policy/) to enforce security and compliance automatically. 5. Refactor infrastructure into [reusable components](https://www.pulumi.com/docs/iac/concepts/components/) for consistent, scalable operations. -## Workshop: From Zero to Production in Kubernetes +## Agentic Workflows for Production-ready Kubernetes + +Experience Kubernetes automation in practice. See how agentic workflows power production-ready Kubernetes by automating GitOps operations, managing environments, and reducing manual effort in this on-demand workshop. -Experience Kubernetes automation in practice. -Join the hands-on workshop [*From Zero to Production in Kubernetes*](https://www.pulumi.com/events/from-zero-to-production-in-kubernetes/) to learn how to: +Watch [*Agentic Workflows for Production-ready Kubernetes*](https://www.pulumi.com/events/from-zero-to-production-in-kubernetes/) to learn how to: -- Provision and manage clusters across clouds using real programming languages -- Automate workloads with agentic workflows and modern GitOps practices +- Provision and manage clusters across clouds using general-purpose programming languages +- Multi-cloud Kubernetes infrastructure management +- Fleet management with GitOps (Argo CD) - Reduce YAML complexity while maintaining reliability and speed -[Register now](https://www.pulumi.com/events/from-zero-to-production-in-kubernetes/). +[Watch On Demand](https://www.pulumi.com/events/from-zero-to-production-in-kubernetes/). ## Final Thoughts diff --git a/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/2026-cloud-trends -ai-idp-security.png b/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/2026-cloud-trends -ai-idp-security.png new file mode 100644 index 000000000000..515cb070f894 Binary files /dev/null and b/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/2026-cloud-trends -ai-idp-security.png differ diff --git a/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/index.md b/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/index.md index 8c02363bc10a..f098e5e0a898 100644 --- a/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/index.md +++ b/content/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/index.md @@ -1,5 +1,5 @@ --- -title: "Future of the Cloud: 10 Trends Shaping 2025 and Beyond" +title: "Future of the Cloud: 10 Trends Shaping 2026 and Beyond" # The date represents the post's publish date, and by default corresponds with # the date and time this file was generated. Dates are used for display and @@ -7,7 +7,7 @@ title: "Future of the Cloud: 10 Trends Shaping 2025 and Beyond" # published. To influence the ordering of posts published on the same date, use # the time portion of the date value; posts are sorted in descending order by # date/time. -date: 2024-11-04T07:56:40Z +date: 2025-12-04T07:56:40Z # The draft setting determines whether a post is published. Set it to true if # you want to be able to merge the post without publishing it. @@ -17,12 +17,12 @@ draft: false # of the content of the post, which is useful for targeting search results or # social-media previews. This field is required or the build will fail the # linter test. Max length is 160 characters. -meta_desc: "The year of Cloud Optimization is here! Explore the top 10 trends, including IaC, AI/ML, Kubernetes, platform engineering, security, FinOps, data, and more." +meta_desc: Explore 2026’s top cloud trends, including AI infrastructure, Kubernetes evolution, IaC, DevSecOps, platform engineering, and modern cloud governance. # The meta_image appears in social-media previews and on the blog home page. A # placeholder image representing the recommended format, dimensions and aspect # ratio has been provided for you. -meta_image: "cloud-computing-forecast.png.png" +meta_image: "2026-cloud-trends -ai-idp-security.png" # At least one author is required. The values in this list correspond with the # `id` properties of the team member files at /data/team/team. Create a file for @@ -36,125 +36,203 @@ tags: - infrastructure-as-code - cloud-computing - multi-cloud - - finops - platform-engineering - devops - devsecops - security -# See the blogging docs at https://github.com/pulumi/docs/blob/master/BLOGGING.md -# for details, and please remove these comments before submitting for review. --- -{{< notes type="info" >}} -Note: This post discusses Pulumi Copilot, which Pulumi Neo has replaced. [Learn about Neo →](/docs/ai/) -{{< /notes >}} - -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. +In 2026, 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. +## On This Article + +- [1. Cloud Will Become a Business Necessity by 2028](#1-cloud-will-become-a-business-necessity-by-2028) +- [2. Hyperscalers Accelerate AI-Driven Cloud Expansion](#2-hyperscalers-accelerate-ai-driven-cloud-expansion) +- [3. Hybrid and Multi-Cloud to Drive Innovation](#3-hybrid-and-multi-cloud-to-drive-innovation) +- [4. Enterprises Rebuild Their Cloud Foundations to Operationalize AI](#4-enterprises-rebuild-their-cloud-foundations-to-operationalize-ai) +- [5. IaC Drives Scalable Cloud, Multi-Cloud, and AI Operations](#5-iac-drives-scalable-cloud-multi-cloud-and-ai-operations) +- [6. DevSecOps Evolves Into AI-Integrated Security](#6-devsecops-evolves-into-ai-integrated-security) +- [7. Platform Engineering and Internal Developer Platforms](#7-platform-engineering--internal-developer-platforms-idps) +- [8. AIOps Matures Into a Cloud Operations Standard](#8-aiops-matures-into-a-cloud-operations-standard) +- [9. Kubernetes Dominance and Increased Complexity](#9-kubernetes-dominance-and-increased-complexity) +- [10. AI Code Assistants in the Enterprise](#10-ai-code-assistants-in-the-enterprise) +- [The Future of Cloud: Reinvented for an AI-First Decade](#the-future-of-cloud-reinvented-for-an-ai-first-decade) + ## 1. Cloud Will Become a Business Necessity by 2028 -According to [Gartner](https://www.gartner.com/en/webinar/445864/1051166), 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 [Gartner](https://www.gartner.com/en/infrastructure-and-it-operations-leaders/topics/cloud-computing), by 2028 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. {{< figure alt="The future of cloud computing. Credit: Gartner" src="/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/gartner-cloud-2028.png" caption="The future of cloud computing. Credit: Gartner" width=100% >}} According to McKinsey & Company's "[In search of cloud value](https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/in-search-of-cloud-value-can-generative-ai-transform-cloud-roi)" 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. +- **Cloud value is driven by innovation**, worth 5x more than cost savings. +- **EBITDA uplift of 20–30% by 2030** for high-performing organizations. +- **Asia leads in projected cloud value**, followed by the US and Europe. +- High-ROI organizations excel by aligning cloud strategy with business priorities, building strong cloud foundations, and using modern operating models. + +Teams succeeding in this transition increasingly use Infrastructure as Code, automation, and unified governance frameworks like [Pulumi Insights + Policies](https://www.pulumi.com/product/insights-governance/) to operationalize this value. + +## 2. Hyperscalers Accelerate AI-Driven Cloud Expansion + +Hyperscalers are making the largest infrastructure investments in cloud history — nearly all centered on AI workloads, inference, and high-performance compute. + +- **AWS** has integrated [Anthropic’s Claude 3 and Claude 4 models into Amazon Bedrock](https://www.aboutamazon.com/news/aws/anthropic-claude-4-opus-sonnet-amazon-bedrock) for enterprise LLM workflows. “Claude Opus 4 and Claude Sonnet 4 are available today in Amazon Bedrock, enabling customers to build agents with stronger reasoning, memory, and tool use.” — AWS, May 2025 +- **Microsoft Azure** revenue rose 33% year-over-year in Q3 (ended March 31), outperforming estimates of ~29.7%. [AI contributed 16 percentage points to this growth](https://www.reuters.com/business/microsoft-beats-quarterly-revenue-estimates-ai-shift-bolsters-cloud-demand-2025-04-30/), up from 13 points in the prior quarter. "Microsoft is on track to invest approximately $80 billion to build out AI-enabled datacenters to train AI models and deploy AI and cloud-based applications around the world," said Brad Smith, the Microsoft Vice Chair and President. +- **Google Cloud** is committing [$25 billion over two years for data center and AI infrastructure expansion](https://www.utilitydive.com/news/google-cloud-blackstone-aws-us-ai-data-center-buildouts/753202) across the PJM grid, with total capital expenditure for 2025 ranging from $75–85 billion. "As our CEO has said, in these early days of a very transformative technology, the risks of under-investing are dramatically higher than the risks of over-investing," said Eunice Huang, Head of AI and Emerging Tech Policy. +- **Oracle** anticipates 15–20% cloud revenue growth in FY 2026–2027 attributable to AI infrastructure demand, tied to its partnership in the [Stargate initiative](https://www.pcgamer.com/software/ai/openais-skyrocketing-spending-could-see-billions-of-dollars-in-silicon-headed-down-the-ai-mines-in-the-next-few-years-including-2-million-nvidia-chips-headed-to-texas-stargate-facility/). + +As hyperscalers integrate AI deeper into their service layers, engineering teams must adapt with IaC-driven automation, reusable patterns, and policy controls to deploy cloud and AI infrastructure consistently. +See how organizations [deploy AWS infrastructure at the speed of AI with Pulumi](https://www.pulumi.com/aws/#video) and [Pulumi Policies](https://www.pulumi.com/docs/insights/policy/). + +## 3. Hybrid and Multi-Cloud to Drive Innovation -## 2. Large Organizations with Multi-Cloud and Hybrid Environments +Hybrid and multi-cloud strategies are now mainstream: -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. +- Hybrid cloud will grow from **$130B to $310–330B** by 2030 ([ResearchAndMarkets](https://www.businesswire.com/news/home/20250513124988/en/Hybrid-Cloud-Market-Analysis-Growth-Trends-and-Forecasts-Report-2024-2025-2030-Surging-Demand-for-Seamless-Interoperability-Between-Cloud-Services-and-Existing-Systems---ResearchAndMarkets.com)). +- **87% of enterprises** run workloads across multiple clouds ([Mordor Intelligence](https://www.mordorintelligence.com/industry-reports/hybrid-cloud-market)). +- Gartner predicts that **40% of enterprises** will adopt hybrid compute architectures in mission-critical workflows by 2028 (up from 8%). {{< figure alt="Most popular cloud computing infrastructure by industry. Credit: Cloud Worldwide Service, Forbes" src="/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/most-popular-cloud-computing-infrastructure-by-industry.png" caption="Credit: Cloud Worldwide Service, Forbes" width=100% >}} -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. +As AI and regulatory requirements grow, organizations must deploy workloads across AWS, Azure, Google Cloud, on-prem, and edge — while maintaining consistent security, compliance, and configuration. + +Modern cloud teams use: + +- **Infrastructure as Code** for consistent multi-cloud provisioning and environment standardization, forming the backbone of AI infrastructure orchestration +- **Reusable components and internal platforms** to define scalable architecture patterns and accelerate delivery across Kubernetes, AI/ML pipelines, and hybrid environments +- **Policy-driven guardrails** to maintain cost, security, and compliance across environments, supporting cloud governance automation and modern cloud cost governance + +Pulumi enables all three through its [multi-cloud IaC model](https://www.pulumi.com/docs/iac/), [Pulumi Policies](https://www.pulumi.com/product/insights-governance#video), and [internal developer platform capabilities](https://www.pulumi.com/product/internal-developer-platforms/#video). + +## 4. Enterprises Rebuild Their Cloud Foundations to Operationalize AI + +While hyperscalers are transforming the global cloud platform, enterprises face a different challenge: adapting their own cloud foundations to support AI at scale. Organizations are moving beyond prototypes and integrating AI into core products, internal workflows, and customer-facing systems, requiring new levels of automation, governance, and AI infrastructure orchestration. + +According to [Gartner](https://www.networkworld.com/article/4058786/gartner-ai-spending-to-reach-1-5-trillion-dollars-this-year.html), global AI infrastructure spending is expected to surpass **$2 trillion in 2026**. [IDC predicts that by 2027](https://blogs.idc.com/2025/10/22/futurescape-2026-moving-into-the-agentic-future/), more than 50% of enterprises will use AI agents to drive core workflows, which requires scalable, secure, and automated cloud architectures to support model execution and orchestration. + +To enable this transition, enterprises are investing in: + +- **GPU provisioning and orchestration**, data pipelines, vector databases, feature stores, and LLM infrastructure needed for real-time AI workloads. +- **Data pipelines, vector databases, and feature stores** needed for real-time AI workloads +- **Model-serving infrastructure**, including gateways, inference routers, and autoscaling layers +- **Strong identity, secrets, and access controls** as AI systems increase security exposure +- **Automation through Infrastructure as Code** to ensure reproducibility and reduce drift +- **Policy-driven governance** to secure cost, compliance, and architectural consistency + +As AI becomes deeply embedded across engineering organizations, teams are increasingly using software engineering approaches such as Infrastructure as Code, reusable components, platform engineering, and policy automation to standardize how AI infrastructure is deployed, scaled, and secured across clouds. -## 3. Infrastructure as Code (IaC) Crucial for Scalability +To support this shift, Pulumi's perspective on [Superintelligence Infrastructure](https://www.pulumi.com/product/superintelligence-infrastructure/) explains why AI workloads, from pre-training to inference at massive scale, require dynamic infrastructure orchestration rather than static configuration. -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. +### Pulumi users increasingly rely on: -[Infrastructure as Code](https://www.pulumi.com/what-is/what-is-infrastructure-as-code/) is maturing beyond taming the complexity of the cloud: +- [Pulumi IaC](https://www.pulumi.com/docs/iac/) for standardized AI infrastructure +- [Pulumi ESC](https://www.pulumi.com/product/secrets-management/) to manage all secrets and configuration at scale +- [Pulumi Insights](https://www.pulumi.com/product/insights-governance/) for visibility and misconfiguration analysis +- [Pulumi Policies](https://www.pulumi.com/docs/insights/policy/) for AI-specific guardrails in code, cost detection, and to provide automated compliance protections -- Facilitating the adoption and configuration standardization of multi-cloud and hybrid strategies -- Better integration with multiple cloud providers, like [AWS](https://www.pulumi.com/docs/iac/clouds/aws/), [Azure](https://www.pulumi.com/docs/iac/clouds/azure/), and [Google Cloud](https://www.pulumi.com/docs/iac/clouds/gcp/), data stores, and third-party services like [Cockroach Labs db](https://www.pulumi.com/registry/packages/cockroach/), [Confluent cloud](https://www.pulumi.com/registry/packages/confluentcloud/), [Kafka](https://www.pulumi.com/registry/packages/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](https://www.pulumi.com/docs/pulumi-cloud/insights/) -- Robust security and [Policy as Code](https://www.pulumi.com/docs/iac/packages-and-automation/crossguard/core-concepts/) to enforce security practices, guardrails, compliance, cost policies, and more -- Intelligent automation, including [automated tests](https://www.pulumi.com/docs/iac/concepts/testing/) and [remediation policies](https://www.pulumi.com/blog/remediation-policies/) -- [AI-driven automation and insights](https://www.pulumi.com/product/pulumi-insights/) +## 5. IaC Drives Scalable Cloud, Multi-Cloud, and AI Operations -## 4. Increased Focus and Budgets for Security (DevSecOps) +As cloud environments expand and AI workloads demand highly dynamic infrastructure, Infrastructure as Code (IaC) is becoming the foundation for scaling reliably across all environments. Organizations are increasingly adopting IaC in general-purpose languages to unify development and infrastructure workflows, reduce configuration drift, and deliver cloud resources at speed. -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: +Modern [Infrastructure as Code](https://www.pulumi.com/what-is/what-is-infrastructure-as-code/) is advancing far beyond simple provisioning: -1. **AI-Driven Security**: AI and machine learning (ML) will be instrumental in automating security and in [providing real-time insights](https://www.pulumi.com/blog/pulumi-insights-2/), enabling proactive and predictive security measures. -2. **More Focus on Secrets Management**: Organizations will prioritize [robust secrets management](https://www.pulumi.com/product/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. +- **Standardizing multi-cloud and hybrid patterns** so teams can deploy consistently across AWS, Azure, Google Cloud, on-prem, and edge environments. +- **Integrating seamlessly with cloud providers and third-party services**, including data platforms and messaging systems like CockroachDB, Confluent Cloud, and Kafka. +- **Providing deeper validation and type-safety**, ensuring parameters, dependencies, and security controls are correct before deployment. +- **Improving cloud resource efficiency and visibility** with tools like [Pulumi Insights Discovery](https://www.pulumi.com/docs/insights/discovery/). +- **Embedding security and compliance through [Policy as Code](https://www.pulumi.com/docs/insights/policy/)**, enforcing guardrails, cost controls, and regulatory requirements automatically, enabling truly policy-driven cloud management. +- **Enabling intelligent automation**, from unit and integration tests to auto-remediation policies and policy-driven approvals. +- **Incorporating AI-driven optimization and insights**, helping teams detect misconfigurations, analyze usage patterns, and generate infrastructure updates with tools like [Pulumi Neo](https://www.pulumi.com/product/neo/) and [Pulumi Policies](https://www.pulumi.com/blog/policy-next-gen/). -[Policy as Code](https://www.pulumi.com/docs/iac/packages-and-automation/crossguard/) will also be an indispensable pillar in many security aspects: +As organizations scale both traditional cloud workloads and AI-driven systems, IaC has become critical for achieving secure, repeatable, and high-velocity operations across every environment. -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 +## 6. DevSecOps Evolves Into AI-Integrated Security -## 5. Platform Engineering – Internal Developer Portals (IDP) for Better Developer Experience +As AI becomes embedded across cloud-native systems, DevSecOps is entering a new era. Gartner predicts that by **2028, over 50% of enterprises will use AI security platforms** to protect their AI investments. Below are the 3 key predictions for the future of DevSecOps: -**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](https://www.gartner.com/en/articles/what-is-platform-engineering)). +1. **AI-driven security automation**: Teams will increasingly rely on AI to detect threats, enforce policies, and generate secure infrastructure patches. See Pulumi’s capabilities in [AI-powered remediation](https://www.pulumi.com/product/insights-governance/#video). -Mid-size to large companies will begin or [continue to invest in implementing platform engineering practices](https://www.pulumi.com/product/internal-developer-platforms/), with large tech companies as first adopters. They will provide [Internal Developer Portals (IDP)](https://www.pulumi.com/blog/building-developer-portals/) 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. +2. **More focus on secrets management**: With AI systems accessing more sensitive data, secure secret storage will be essential. [Pulumi ESC](https://www.pulumi.com/product/secrets-management/) helps teams centralize and govern credentials, keys, and tokens safely. + +3. **Greater cross-team collaboration**: Dev, Sec, and Ops workflows will converge under shared frameworks: IaC, policy automation, runtime scanning, and GitOps. + +As organizations increase their use of AI across cloud-native systems, the need for tightly aligned security, governance, and cloud governance automation becomes even more urgent. At the Gartner Data & Analytics Summit in Sydney, Carlie Idoine, VP Analyst at Gartner, emphasized this growing dependency: + +*"[AI]... it doesn’t deliver value on its own – AI needs to be tightly aligned with data, analytics, and governance to enable intelligent, adaptive decisions and actions across the organization."* + +This perspective mirrors what we’re seeing across modern DevSecOps practices: AI can amplify security, but only when paired with strong foundations in secrets management, governance, and cross-team collaboration. + +## 7. Platform Engineering & Internal Developer Platforms (IDPs) + +According to [Gartner](https://www.gartner.com/en/articles/what-is-platform-engineering), **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. + +Mid-size to large companies will begin or continue to invest in implementing [platform engineering practices](https://www.pulumi.com/blog/platform-engineering-pillars-3/), with large tech companies as first adopters. They will provide [Internal Developer Platforms (IDP)](https://www.pulumi.com/blog/announcing-pulumi-idp/) to elevate the [Developer Experience](https://www.pulumi.com/blog/developer-experience-business-critical/) (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. {{< figure alt="Internal developer platform-in-a-box. Credit: Pulumi" src="https://www.pulumi.com/blog/developer-portal-platform-teams/platform-teams.png" caption="Internal developer platform-in-a-box. Credit: Pulumi" width=100% >}} -## 6. The Rise of AIOps Through the Combination of AI and Automation +IDPs are reshaping how developers interact with cloud infrastructure, bringing together platform engineering, automation, and emerging AI platform engineering practices. -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. +## 8. AIOps Matures into a Cloud Operations Standard + +AIOps is becoming mainstream, helping teams predict failures, auto-scale infrastructure, and resolve incidents with minimal manual effort. 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](https://www.pulumi.com/docs/iac/packages-and-automation/automation-api/)**: 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](https://www.pulumi.com/docs/pulumi-cloud/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: +AIOps features include observability, automation, and real-time analytics to bridge DevOps, SRE, and IT operations. -- **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. +## 9. Kubernetes Dominance and Increased Complexity -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](https://www.pulumi.com/resources/enabling-kafka-adoption-pulumi-and-confluent-cloud/) that manage resources on Confluent Cloud. +Kubernetes will continue its ascent in 2026. According to [Markets N Research](https://marketsnresearch.com/report/1649/global-kubernetes-market), 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. -## 8. Kubernetes Dominance and Increased Complexity +The CNCF Annual Survey shows AI/ML workloads rapidly moving onto Kubernetes — including batch pipelines, model experimentation, real-time inference, and data preprocessing — even as only 41% of ML/AI developers are cloud-native today. This shift is accelerating as teams need flexible GPU scheduling, distributed pipelines, and portable execution environments. -Kubernetes, the open-source container orchestration platform, will continue its ascent in 2025. According to [Markets N Research](https://marketsnresearch.com/report/1649/global-kubernetes-market), 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. +[Kubernetes is also evolving in response to AI demands](https://www.pulumi.com/blog/beyond-yaml-kubernetes-2026-automation-era/#the-2026-convergence-of-ai-platforms-and-policy-in-kubernetes). Inference workloads, powered by LLMs and GPUs, now require low-latency execution closer to the user. This shift is pushing organizations to build intelligent orchestration layers that schedule AI pipelines across edge and core clusters, often leveraging Kubernetes as the common control plane for AI cluster orchestration. -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](https://www.linkedin.com/pulse/from-complexity-simplicity-streamlining-kubernetes-infrastructure?lipi=urn%3Ali%3Apage%3Ad_flagship3_pulse_read%3BHF6x7jyoRWSmk9POeHy0TA%3D%3D). +As we move into 2026, three patterns are becoming clear: -## 9. Cost Transparency and Governance +- **Kubernetes is evolving to support AI** through GPU-aware scheduling, Kubernetes GPU scheduling optimizations, and more advanced workload orchestration. +- **Governance and consistency matter more than ever**, as teams struggle to secure and manage multi-cluster, multi-cloud environments. +- **Platform engineering is essential**, providing curated patterns and automation rather than raw YAML to reduce cognitive load. -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](https://www.pulumi.com/blog/property-search/), and utilizing cost analytics to make informed decisions about resource utilization. +Kubernetes will remain a strategic foundation — but operating it effectively now depends on robust automation, strong security controls, and standardized delivery models that scale across clouds, clusters, and AI pipelines. -As a result, [IDC](https://www.netapp.com/media/93564-operationalize-fin-ops-for-continuous-cloud-and-cost-efficiency.pdf) predicts that complexities and IT budget pressures will drive **70% of Global 1000 companies to [increase FinOps maturity](https://www.pulumi.com/blog/finops-with-pulumi/)** with granular chargebacks, benchmarking, and multiple-cloud optimization. - -## 10. Enterprises Will Allow the Use of AI Code Assistants +## 10. AI Code Assistants in the Enterprise 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](https://www.pulumi.com/product/copilot/) will dramatically increase developer velocity** to meet functional business requirements for 70% of new digital solutions in production (source: [IDC](https://www.digitalnewsasia.com/business/idc-reveals-its-top-predictions-cloud-2023-and-beyond)). +**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](https://www.digitalnewsasia.com/business/idc-reveals-its-top-predictions-cloud-2023-and-beyond)). {{< figure alt="The value of AI code assistants. Credit: Gartner" src="/blog/future-cloud-infrastructure-10-trends-shaping-2024-and-beyond/ai_code_assistants_value.png" caption="The value of AI code assistants. Credit: Gartner" width=100% >}} -According to [Gartner](https://www.gartner.com/en/newsroom/press-releases/2024-04-11-gartner-says-75-percent-of-enterprise-software-engineers-will-use-ai-code-assistants-by-2028), **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](https://www.pulumi.com/ai). +According to [Gartner](https://www.gartner.com/en/newsroom/press-releases/2024-04-11-gartner-says-75-percent-of-enterprise-software-engineers-will-use-ai-code-assistants-by-2028), **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. + +As adoption grows, teams want their AI assistants connected to the real state of their cloud environments so they can ask questions, review configurations, and understand drift or misconfigurations. [Pulumi’s Remote MCP Server](https://www.pulumi.com/blog/remote-mcp-server/) makes this possible by allowing teams to integrate their preferred AI assistant, including tools like Claude or Cursor, directly with Pulumi-managed infrastructure. The server provides controlled, secure access so assistants can explore stacks, surface issues, and help teams understand their cloud footprint in real time. + +When a task involves multi-step workflows or code-level modifications, [Pulumi Neo performs the execution safely](https://www.pulumi.com/blog/remote-mcp-server/#autonomous-infrastructure-with-pulumi-neo)using previews, policy enforcement, and automated orchestration. The combination of AI-assisted understanding and Pulumi-driven execution gives teams a modern pattern for cloud operations that is fast, secure, and consistent. + +This trend marks a major shift in how engineering teams work. AI assistants are becoming active participants in cloud development and operations, and Pulumi provides the foundation to use them confidently across enterprise environments. For a deeper look at what AI-driven cloud operations can enable, explore [10 things you can do with Pulumi Neo](https://www.pulumi.com/blog/10-things-you-can-do-with-neo/). + +## The Future of Cloud: Reinvented for an AI-First Decade + +Cloud infrastructure is entering its most transformative era since the rise of Kubernetes. The trends shaping 2026 reveal a clear pattern: AI is no longer a workload — it’s becoming the organizing principle of cloud strategy. + +- **AI-native cloud architectures** that require elastic compute, GPU orchestration, fast data access, and governance built into every layer +- **Infrastructure as Code as the operational backbone**, standardizing deployments across AI, cloud, and hybrid environments +- **Platform engineering and IDPs** to enable self-service, gold-standard patterns, and automated guardrails +- **Security integrated into every pipeline**, with AI-assisted threat detection, strong secrets management, and policy-driven compliance +- **AIOps and intelligent automation** are becoming standard for scaling modern cloud systems +- **Kubernetes evolving for AI**, driving new orchestration patterns across edge, core, and inference clusters +- **Multi-cloud and hybrid ecosystems** accelerating to support interoperability, resilience, and global workload placement + +Taken together, these shifts point to a new model of cloud operations that is intelligent, automated, policy-aware, and built on software engineering principles rather than manual configuration. -## Keeping up with the Future Cloud Trends +Organizations that invest now in **modern IaC**, **unified governance**, **reusable components**, and **policy frameworks** — all core capabilities of the Pulumi Cloud platform — will be positioned to lead in an AI-first world. The gap between teams that modernize and those that do not will widen rapidly in 2026 and beyond. -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. +{{< blog/cta-button "Try Pulumi for Free" "/docs/get-started/" >}}