Pulumi Blog: Cloud computing

Future of the Cloud: 10 Trends Shaping 2027 and Beyond

Sara Huddleston — Thu, 04 Dec 2025 07:56:40 +0000

Cloud infrastructure in 2027 turns on one shift: AI agents are moving from writing code to operating infrastructure directly, with humans approving changes rather than authoring every one. Hyperscaler capital spending, Kubernetes-for-AI adoption, and platform engineering are all accelerating alongside it. Here are the 10 trends shaping cloud computing through 2027 and beyond.

Last year’s edition of this piece predicted a cloud-first, AI-driven decade. The numbers came in since: Microsoft’s Azure business crossed $100 billion in trailing revenue, Google Cloud’s backlog reached $514 billion, and AWS’s AI and custom-silicon businesses each passed a $25 billion annualized run rate. The 2026 predictions held up. What follows is the update for 2027.

1. Cloud Is Becoming a Business Necessity

Cloud is now on the runway Gartner mapped out for it. According to Gartner, by 2028 cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives, up from less than 50% in 2023. Gartner has also forecast that worldwide public cloud spending will exceed $1 trillion in 2027, en route to cloud becoming, in Gartner’s words, a business necessity.

The future of cloud computing. Credit: Gartner

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

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 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 posted its fastest revenue growth since 2021: $42.2 billion in Q2 2026, up 37% year-over-year, accelerating from 28% growth the prior quarter. AWS’s AI business and its chips business, which includes its custom Trainium and Graviton silicon, each exceeded a $25 billion annualized revenue run rate, growing triple-digit percentages year-over-year.
Microsoft Azure crossed a threshold of its own: Azure’s full fiscal-year 2026 revenue surpassed $100 billion for the first time in Microsoft’s fiscal Q4 2026 (ended June 30, 2026), with Azure revenue growing 43% year-over-year, up from 40% the prior quarter. “This year, Azure revenue surpassed $100 billion for the first time,” said Satya Nadella, Microsoft’s chairman and CEO.
Google Cloud revenue rose 82% year-over-year to $24.8 billion in Q2 2026, and its backlog reached $514 billion, up from $106 billion a year earlier. Alphabet raised its full-year 2026 capital expenditure guidance to $195–205 billion, up from an earlier $180–190 billion estimate that had itself already been raised twice this year.
Oracle reported FY2026 cloud revenue of $34.0 billion, up 39% year-over-year, with remaining performance obligations reaching $638 billion, up 363% year-over-year on the strength of large-scale AI infrastructure contracts, including prepaid and customer-supplied GPU deals now totaling $75 billion.

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 and Pulumi Policies.

3. Hybrid and Multi-Cloud to Drive Innovation

Hybrid and multi-cloud strategies are now mainstream:

Hybrid cloud will grow from $130B to $310–330B by 2030 (ResearchAndMarkets).
87% of enterprises run workloads across multiple clouds (Mordor Intelligence).
Gartner predicts that 40% of enterprises will adopt hybrid compute architectures in mission-critical workflows by 2028 (up from 8%).
In Pulumi’s own 2026 survey of 510 platform, DevOps, and product engineers, multi-cloud is already the norm at the teams surveyed: 64% run on AWS, 55% on Google Cloud, and 45% on Azure, with most running more than one.

Credit: Cloud Worldwide Service, Forbes

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, Pulumi Policies, and internal developer platform capabilities.

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’s September 2026 forecast, total worldwide AI spending, spanning software, hardware, and services, is forecast to reach $2.7 trillion in 2026, a 49.5% increase year-over-year. IDC predicts that by 2027, half of enterprises will be using AI agents to redefine how humans and machines collaborate, 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
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.

To support this shift, Pulumi’s perspective on Superintelligence Infrastructure explains why AI workloads, from pre-training to inference at massive scale, require dynamic infrastructure orchestration rather than static configuration.

Pulumi users increasingly rely on:

Pulumi IaC for standardized AI infrastructure
Pulumi ESC to manage all secrets and configuration at scale
Pulumi Insights for visibility and misconfiguration analysis
Pulumi Policies for AI-specific guardrails in code, cost detection, and to provide automated compliance protections

5. IaC Drives Scalable Cloud, Multi-Cloud, and AI Operations

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.

Modern Infrastructure as Code is advancing far beyond simple provisioning:

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.
Embedding security and compliance through Policy as Code, 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 through Pulumi Policies.

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.

6. DevSecOps Evolves Into AI-Integrated Security

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 secure third-party AI service usage and protect custom-built AI applications, and separately forecasts that total spending on securing AI will reach almost $4.8 billion in 2027, a 68.7% increase over 2026. Below are the 3 key predictions for the future of DevSecOps:

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.
More focus on secrets management: With AI systems accessing more sensitive data, secure secret storage will be essential. Pulumi ESC helps teams centralize and govern credentials, keys, and tokens safely.
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.

Build for an AI-first cloud

Pulumi gives teams infrastructure as code, reusable components, and policy guardrails to deliver consistently across every cloud and AI workload.

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7. Platform Engineering & Internal Developer Platforms (IDPs)

Gartner predicted that by 2026, 80% of large software engineering organizations would establish platform engineering teams as internal providers of reusable services, components, and tools for application delivery. That target year has now arrived, and CNCF’s own research shows the shift underway: its Q1 2026 Technology Radar report with SlashData found 28% of surveyed organizations already have a dedicated platform engineering team, and 35% are running a hybrid platform that combines existing developer platforms with specialized AI tooling.

“Cloud native platforms have reached a point where developers are not just experimenting but standardizing on CNCF projects that make software delivery reliable at scale,” said Chris Aniszczyk, CTO of CNCF. “What’s especially notable about this research is how organizations are extending those same platforms to support AI workloads, showing how cloud native is the base layer of powering the next era of applications.”

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

Internal developer platform-in-a-box. Credit: Pulumi

IDPs are reshaping how developers interact with cloud infrastructure, bringing together platform engineering, automation, and emerging AI platform engineering practices.

8. AIOps becomes agentic: from suggestions to supervised execution

AIOps in 2027 turns on one question: how much of a change does an agent execute, and how closely does a human still review it? Gartner predicts that agentic AI deployment in IT operations grows from under 5% in 2025 to 70% by 2029, while human-in-the-loop requirements in IT operations workflows fall from 95% in 2025 to 40% by 2028.

Pulumi’s own 2026 survey of 510 platform, DevOps, and product engineers shows the same shift starting inside real teams, and a gap between sentiment and practice that’s worth naming honestly:

82% agree that AI and agents will meaningfully change how they write infrastructure within 12 months.
63% say they trust agents to make production changes, yet 62% of teams still gate those changes behind manual approval, against 19% who let agents run autonomously. Pulumi’s report describes this as stated trust outrunning real guardrails.
Teams expecting agents to generate half or more of their infrastructure code rise from 45% today to 52% within six months.

That gap between trust and guardrails is exactly what a supervised, agentic operating model has to close: an agent that proposes a change, runs a preview, and waits for approval, rather than one that only writes YAML for someone else to apply by hand. Pulumi Neo is built around that loop, proposing infrastructure changes, running previews, and executing approved updates with policy guardrails in place, so the human stays the one accountable for what ships. Pulumi’s The Agentic Infrastructure Era makes the fuller case for why AIOps is headed toward this operating model rather than toward faster dashboards and alerting alone.

AIOps still includes observability, automation, and real-time analytics bridging DevOps, SRE, and IT operations. What’s changed for 2027 is that those signals increasingly feed an agent empowered to act on them, with a person still reviewing the result.

9. Kubernetes Dominance and Increased Complexity

Kubernetes will continue its ascent in 2027. According to Mordor Intelligence, the global Kubernetes market is valued at USD 3.13 billion in 2026 and is projected to reach USD 8.41 billion by 2031, a 21.85% CAGR.

The CNCF’s Q3 2025 State of Cloud Native Development report puts cloud-native adoption among professional ML/AI developers at 41%, with 30% of backend developers now using Kubernetes directly, down from a peak of 36% in Q3 2023 — a slow decrease the report says will likely stabilize at a new, lower proportion “due to the maturity of the technology.” Even so, teams still need flexible GPU scheduling, distributed pipelines, and portable execution environments as AI workloads scale.

Kubernetes is also evolving in response to AI demands, a shift Pulumi covers in more depth in its comparison of Kubernetes IaC tools. Inference workloads, powered by LLMs and GPUs, now require low-latency execution closer to the user, 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.

As we move into 2027, three patterns are becoming clear:

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.

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.

10. AI Code Assistants in the Enterprise

AI-powered coding assistants like GitHub Copilot, Claude Code, Cursor, and others have moved from novelty to everyday tooling for a large share of enterprise software teams, and the same shift is now reaching infrastructure code.

The value of AI code assistants. Credit: Gartner

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.

As enterprise adoption of AI assistants increases, expectations are rising: they must not only generate code but also understand the state of infrastructure, configurations, and security posture. That means being able to answer questions about environments, surface misconfigurations, or act directly on infrastructure. The July 2026 revision of the Model Context Protocol, described by its maintainers as the largest revision of the protocol to date, is part of what makes that direct action practical: AWS shipped a general-availability MCP server for its Agent Toolkit, and Kubernetes tooling vendors like Mirantis’s Lens have followed with built-in MCP servers of their own.

One of the newest developments is the release of Pulumi Agent Skills, a collection of infrastructure expertise packaged for use in AI coding assistants. These skills teach tools such as Claude Code, Cursor, or Gemini CLI to reason about Pulumi projects, reducing hallucination and improving outputs based on real infrastructure conventions and practices.

Combined with infrastructure access via tools like Pulumi’s Remote MCP Server, teams can build secure, AI-driven workflows where assistants provide insights and Pulumi Neo safely executes actions with previews, policies, and orchestration.

AI code assistants are no longer experimental; they’re fast becoming a competitive advantage in cloud software development.

The Future of Cloud: Built Around Agentic Operations

Cloud infrastructure is entering its most transformative era since the rise of Kubernetes. The trends shaping 2027 point to one clear pattern: AI now sets the organizing principle for cloud strategy, ahead of any single workload running on top of it.

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.

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 2027 and beyond.

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Who moved my menus?

Craig Symonds — Mon, 15 Sep 2025 10:00:00 -0700

We’re excited to share a new update to Pulumi Cloud: a redesigned left-hand navigation that makes it faster and easier to find what you need. With this update, the most common workflows are now front and center, while related features are grouped in a way that better reflects how teams actually use Pulumi Cloud every day.

This change is all about helping you spend less time clicking around and more time building, deploying, and managing your cloud infrastructure.

Faster Access to What You Use Most

We’ve moved the most commonly used sections of Pulumi Cloud like Stacks, Environments, and Resources into the top-level navigation. That means the things you use most are always just one click away.

The redesigned navigation groups related features into four clear categories, each designed around the way infrastructure teams work:

Platform includes all the IDP services that help you set up your infrastructure: defining services, configuring components and managing templates.
Management groups together all the tools you use to configure the tools you use daily like: accounts, policies and deployments. It also includes the tools used to monitor the interactions with the Pulumi platform like: approvals and audit logs.
Settings lists the tools you use to configure how the Pulumi platform needs to work for your organization including: billing and usage, access management and integrations.

These categories help to reduce clutter and give each section a clear purpose, so you always know where to go.

What’s Changed and Where to Find It

Several important updates make the new navigation cleaner and more intuitive:

Deployment Runners merged into Deployments: Deployment Runners are now integrated into the Deployments section. This unifies deployment tasks and their configuration in one place.
New Project integrated into Projects/Stacks: Instead of a separate menu entry, creating a new project is now handled by using the New Project button within the main Stacks page, reducing clutter and consolidating related actions.
Import integrated into Projects/Stacks: Importing unmanaged resources into stacks can now be initiated directly from the main Stacks page by selecting the Import button, better aligning aligning it with the overall stack management.
Customer Managed Keys integrated into Organization: As an organization-wide setting, Customer Managed Keys are now located under the Organization tab.

These changes reduce redundant items, consolidate related tasks, and surface the most important workflows where you expect them.

Cleaner Organization, Less Clutter

By consolidating related features, the left navigation UI is easier to scan and navigate. Infrastructure management tools like Stacks, Resources, Deployments and Policy Findings are grouped together, while IDP, platform configuration and organizational settings are streamlined under their own sections. The result is a navigation that mirrors how infrastructure teams actually work.

Built for Teams at Scale

Pulumi Cloud is used by teams managing everything from a handful of resources to thousands across multiple clouds and environments. This navigation update scales with you, helping teams quickly navigate between the services they need without slowing down as usage grows.

At Pulumi, we believe infrastructure as code should accelerate, not slow down, how teams deliver in the cloud. By simplifying navigation and surfacing the most important actions, Pulumi Cloud becomes an even faster, more reliable place to manage your infrastructure.

This update is another step toward our mission: enabling teams everywhere to build, deploy, and manage cloud infrastructure with greater speed, confidence, and joy.

Try It Out

The new navigation is available today for all Pulumi Cloud users. Sign in to Pulumi Cloud and experience the streamlined workflow for yourself. For more details, check out the docs.

We’d love your feedback as we continue to make Pulumi Cloud the best platform for modern infrastructure as code.

PulumiUP 2024: Dive Into the Future of Cloud, Platform Engineering, and AI/ML

Sara Huddleston — Wed, 11 Sep 2024 07:04:40 +0000

PulumiUP 2024 is just around the corner! It will be held on September 18th, starting at 8 AM PT | 15:00 UTC +0, and with over 5,500 engineers from all over the world already registered, this is shaping up to be the must-attend event for cloud professionals, platform engineers, and AI/ML enthusiasts alike. From entry-level engineers to tech executives, this event brings together professionals from companies of all sizes to explore the latest innovations and best practices in Cloud and IaC, Platform Engineering & DevOps, and AI/ML.

If you haven’t registered yet, now’s the time! Start building your schedule today, select the talks you want to watch live and on-demand and add them to your schedule.

PulumiUP at Glance

Main Track: Keynote, Cloud Culture Talks, and More

In the Main Track, you’ll hear directly from the Pulumi leadership team about exciting product innovations. Don’t miss the Cloud Culture talks focused on the human side of technology and collaboration.

Keynote and New Product Announcements - Joe Duffy (Co-founder and CEO), Luke Hoban (CTO), and other key Pulumi leaders will unveil new products and innovations shaping the next wave of cloud development. Expect to see live demos showcasing how these tools can revolutionize your workflows, from cloud infrastructure to security automation.
"Why Care About Building a Cloud Center of Excellence?" - Alex Radu (VP Product & Marketing Manager, Public Cloud, J.P. Morgan) discusses why building a Cloud Center of Excellence is essential for long-term cloud strategy success.
"What Is ‘HugOps’ and Why Is It Important?" - Rees Pozzi (Senior Platform Engineer, Kainos) explores the meaning and importance of “HugOps,” a practice promoting empathy and collaboration in the tech world but also by all those impacted by it.

AI/ML Track Highlights

Panel: AI for Cloud Development

AI is transforming how we approach development and infrastructure, and PulumiUP offers an incredible lineup of talks and panels on the topic.

"Data Privacy Challenges with Large Language Models" - Aditi Godbole (Data Science, AI & ML Leader, SAP) will address the critical question of managing data privacy, addressing LLM basics, AI data privacy fundamentals, and specific privacy issues in LLMs.
"Pulumi Powered AI/ML on Kubernetes" - Jason Smith (App Modernization Specialist, Google Cloud) will show you how to serve an open-source LLM with a RAG on Kubernetes and set up a Kubernetes environment for AI/ML workloads with Pulumi.
"AI Tools for Developers" - Jim Clark (Principal Software Engineer, Docker) will explore how Tools can enhance the capabilities of AI assistants and show how the combination of AI, Tools, and containerized runtimes, can enhance interactions between developers and their tools.
"The AI Governance Challenge" - Patty O’Callaghan (Technical Director, Charles River) will explore the complexities of AI governance and how to navigate them.
Panel Discussion: “AI for Cloud Development” - Luke Hoban (CTO, Pulumi), Phillip Carter (Principal Product Manager, Honeycomb), Giri Sreenivas (CPO, Docker), Clare Liguori (Senior Principal Software Engineer, AWS) and Meagan Cojocar (Principal Product Manager, Pulumi) will provide diverse perspectives on how AI is shaping cloud infrastructure.

Platform Engineering and DevOps Track Highlights

Panel: Secrets and Policies—Automating Cybersecurity

The Platform Engineering & DevOps track at PulumiUP is perfect for anyone looking to automate infrastructure, secure their systems, and scale their environments with ease. This track features talks and panels on cutting-edge technologies and practices.

"Moving Mountains: How IaC Unlocks Massive Refactoring Possibilities" - Shaun Verch (Infrastructure Engineer, Oso) will show you how infrastructure as code can transform large-scale refactoring projects.
"Using Pulumi to Empower Kubernetes Fleet Management" - Blake Romano (Senior Software Engineer, Imagine Learning) will show you how Imagine Learning leverages Pulumi to manage a fleet of Kubernetes clusters and other platform resources quickly and reliably, and how it revolutionized their workflow.
"Streamline Your Infrastructure Deployment with GitOps and Pulumi Operator" - Sam Cogan (Solutions Architect & Azure MVP, WTW) will highlight how you can define your infrastructure in Git, and have Pulumi automatically reconcile it into deployed infrastructure.
"Is This a Platform? Platform Engineering Before PMF" - Jk Jensen (Team Lead, Staff Software Engineer, MystenLabs) will share how they built their service platform around Pulumi to help engineers and researchers move from prototypes to deployed environments, enabling their teams to iterate more quickly and develop an increasing number of systems without additional complexity.
"Security Automation—Faster. Cheaper. Better." - David Giambruno (VP of Engineering and DevOps, Tivity Health) and Joe Duffy (Founder/CEO, Pulumi) will discuss security automation and how these efforts impacted speed and agility, cost optimization and improved security and compliance.
"Meet Devs Where They Are: Why IaC Must Be Real Code" - Jeremy Adams (Head of Ecosystems, Dagger) will present why real code (that teams already use for applications) is essential for both IaC and CI/CD pipelines, and to meet modern DevOps best practices.
"Security of IaC Pipelines and Infrastructure Governance With Policies-As-Code" - Marina Novikova (Senior Partner Solutions Architect, AWS) and Andy Taylor (Senior Networking Specialist/ Solutions Architect, AWS) will explore security best practices for IaC pipelines and infrastructure governance using policies-as-code, cover best practices for handling sensitive information like access keys, tokens and encryption keys, and scaling and automating your DevSecOps.
Panel Discussion: “Secrets and Policies—Automating Cybersecurity” - Arun Loganathan (Senior Product Manager, Pulumi), Maya Kaczorowski (PM of Security), Jason Meller (VP, Product, 1Password), and Ofir Cohen (CTO, Container Security, Wiz) will explore the intersection of innovation and security, offering insights into how AI is reshaping the threat landscape and how organizations can stay ahead.

Cloud and IaC Track Highlights

Panel: Infrastructure as Code - Can we do better?

The Cloud and IaC track is ideal for those wanting to deepen their understanding of infrastructure as code and its impact on modern cloud computing. Learn from industry pioneers and see where the future of IaC is headed.

"From CDK to Pulumi: Evolution of SST" - Dax Raad (Founding Engineer, SST) and Jay V (Founder, SST) will share insights into the early development of their product, initially built on AWS Cloud Development Kit (CDK), the challenges they encountered and the groundbreaking decision to transition to Pulumi.
"Unified Software Development at BMW Software Factory with Pulumi" - Jan-Peter Alten (Expert Software Engineer, DevOps, BMW Group) will showcase how BMW uses Pulumi to unify their software development processes, resulting in an increase in developer productivity, streamlined infrastructure management, and enhanced scalability, security, and compliance across their complex software ecosystem.
"Stacking Accounts: Multi-Account Deployments in a Single Stack for Monitoring, Management, and More" - Denis Willett (Software Engineer, North Carolina Institute for Climate Studies) will explain how they use Pulumi for managing 60+PB of environmental data across AWS, GCP, and Azure and leverage multi-account deployments in a single stack via the Pulumi Automation API.
"Industrialize the Configuration of Your GitHub Repositories With IaC" - Alexandre Nédélec (Software Engineer, Avanade) will live code using the GitHub, Azure native, and Azure AD Pulumi providers to create a GitHub repository and configure its pipeline to deploy to Azure using OpenID Connect.
Panel Discussion: “Infrastructure as Code — Can We Do Better?” - Joe Duffy (Co-Founder and CEO, Pulumi), Brian Grant (CTO, Stealth), Elad Ben-Israel (Co-Founder and CEO, Winglang), Adam Jacob (Co-Founder and CEO, System Initiative), and Luke Hoban (CTO, Pulumi) will discuss the past, the present, and the future of Infrastructure as Code and the overall infrastructure technologies.

Workshops and Hands-On Learning

Want to get hands-on experience? Our live workshops are designed to deepen your understanding of trending topics, Pulumi, and its applications.

"Managing Team Secrets with 1Password & Pulumi ESC" on September 25, led by Phil Johnston (1Password) and Diana Esteves (Pulumi).
"Securing IaC Pipelines in Regulated Industries" on September 26, led by Josh Kodroff (Pulumi) and Marina Novikova (AWS).
"Deploy Tailscale infrastructure in AWS with Pulumi" on October 15, led by Diana Esteves (Pulumi) and Lee Briggs (Tailscale).
"Observability as Code for AI Apps with New Relic and Pulumi" on October 30, led by Diana Esteves (Pulumi) and Harry Kimpel (New Relic).

Amazing Partners and Sponsors

Thank you to our amazing customers, sponsors, and partners for supporting PulumiUP!

AWS The world’s most comprehensive and broadly adopted cloud, offering over 200 fully featured services from data centers globally.
Google Cloud Help developers build quickly, securely, and cost effectively with the next generation of modern infrastructure designed to meet specific workload and industry needs.
New Relic Data for engineers to monitor, debug, and improve their entire stack.
Docker Accelerate how you build, share, and run applications.
1Password Streamline how you manage SSH keys, API tokens, and other infrastructure secrets throughout the entire software development life cycle.
Tailscale Make creating software-defined networks easy: securely connecting users, services, and devices.
Pinecone Build remarkable GenAI applications fast, with lower cost, better performance, and greater ease of use at any scale.
Wiz Secure everything you build and run in the cloud.
Honeycomb Observability that helps solve problems you couldn’t before.
Mysten Labs Building critical infrastructure to enable a more decentralized internet.
Imagine Learning Empowering educators to inspire breakthrough moments in every student’s unique learning journey with digital-first, K–12 education solutions.
Dagger Powerful, programmable open source CI/CD engine that runs your pipelines in containers.
Oso Authorization as a service.

Build Your Schedule Now

With so many compelling topics across AI/ML, Platform Engineering, DevOps, and Cloud and IaC, now is the time to build your PulumiUP schedule. Select the sessions that match your goals and interests to maximize your experience. Plus, you’ll receive a link to watch your chosen panel discussions and tech talks on-demand!

Haven’t registered yet? It’s not too late! Join 5,500 engineers worldwide in this groundbreaking event and gain the insights you need to drive innovation at your company. Register now->

We can’t wait to see you there!

Pulumi and RedMonk on developer-first infrastructure and why it matters

George Huang — Tue, 26 Apr 2022 00:00:00 +0000

What do assembly languages and the cloud have in common? Are abstractions the future of cloud computing? What does “infrastructure” really mean? And why do these questions matter to the platform engineers, infrastructure engineers, and developers who are building modern cloud applications today?

Joe Duffy (Founder & CEO, Pulumi) and James Governor (Co-founder, RedMonk) recently answered these questions and more in a conversation about developer-first infrastructure. Developer-first infrastructure means empowering developers to build and deploy modern cloud applications and infrastructure through the use of software engineering practices that tame modern cloud complexity.

If you’re interested in learning how the worlds of software engineering and cloud infrastructure are intersecting in addition to principles and best practices for building in the cloud, then watch the 28-minute video below.

Highlights of Pulumi and RedMonk’s discussion on developer-first infrastructure

In the first half of the discussion, Joe and James discuss the complexities of building on the modern cloud as application architectures have evolved from simple three-tier apps to the modern, distributed applications of today. Joe traces the evolution of modern computing in which complexity has been tamed over time through abstractions: from low-level assembly languages to higher-level languages and runtimes that make software more accessible, and finally to operating systems. They then discuss how an analogous transformation has yet to occur in the cloud on a mainstream basis.

“The level of abstraction [that most people are doing] with cloud infrastructure reminds me of assembly languages. You look at writing these YAML templates that over-specify every detail of the underlying architecture. I think [the industry] can do better. I think we can be inspired by what we’ve done in programming languages.” — Joe Duffy

In the second half of the discussion, the two discuss what developer-first infrastructure is, and how companies can use this philosophy to tame modern cloud complexity and accelerate development velocity. Companies that execute this well have a “developer-first multiple” — that is, the most valuable companies in the world today are the ones who’ve thought hard about the developer experience for their own employees or the communities that interact with them.

Joe describes five principles of developer-first infrastructure that make developers’ lives easier when building on the cloud.

Cloud Engineering
Harmonized Applications and Infrastructure
Beyond “Lift and Shift”
Secure and Observable By-Construction
An API for Everything

Finally, Joe dives into the best practices of developer-first infrastructure:

Unified Engineering: Software engineering tools and practices for applications and infrastructure.
APIs: Making everything programmable and composable with APIs.
Everything as Code: Use “as code” techniques like infrastructure as code and policy as code.
Polyglot: Embrace the best language ecosystems for the job at hand.
Modularity: Tackle complexity with real sharing and reuse, not copy & paste.
Continuous Delivery: Deliver and scale applications and infrastructure with automated techniques.
Continuous Verification: Verify and enforce guardrails at all times.
Environment Parity: Share as much as possible between dev, test, and prod environments.
Securely Configured: Loosely couple and securely configure environments.
Distributed Architectures: Go beyond “lift and shift” to building truly cloud-native applications and infrastructure.
Observable: Instrument applications and infrastructure to log high cardinality events, early and often.

Next steps

Developer-first infrastructure means empowering developers to build and deploy modern cloud applications and infrastructure through the use of software engineering practices that tame modern cloud complexity. If you feel inspired after viewing the Pulumi/RedMonk discussion video, then consider applying developer-first principles and practices for your next greenfield project or application using an infrastructure as code tool like Pulumi. You can also watch Joe Duffy’s presentation on developer-first infrastructure from the Cloud Engineering Summit to learn more about developer-first.