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data engineering

Infra is power: How Platform Engineering Became Corporate America’s New Kingmaker
August 13, 2025

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What Is Your Platform Engineering 2.0 Platform Made Of?

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Which description best matches your role? (Select one)(Required)

Platform engineering

DevOps, DevSecOps or SRE

Software engineering

Cloud or infrastructure engineering

Enterprise architecture

Data science, ML engineering or MLOps

Security, risk or compliance

FinOps

Engineering or IT leadership

Consultant or technology vendor

Other

What is your organization's current platform engineering status? (Select one)(Required)

Operating a mature internal platform

Operating a platform that is still expanding

Building our first internal platform

Evaluating or planning a platform initiative

Operating multiple purpose-built platforms

No current platform engineering initiative

Unsure

What are the primary outcomes expected from your platform? (Select up to three)(Required)

Improve developer productivity

Accelerate and standardize software delivery

Improve security, compliance or reliability

Control infrastructure, cloud or AI costs

Support AI/ML development and operations

Govern AI models and agents

Modernize traditional applications

Enable hybrid or multicloud operations

Meet data sovereignty or residency requirements

Other

What is your platform primarily made of? (Select all that apply)(Required)

Backstage

Another internal developer portal or service catalog

APIs, command-line tools or agent interfaces

CI/CD, GitOps or infrastructure as code

Self-managed Kubernetes

Managed public-cloud Kubernetes

VMware Cloud Foundation or VMware vSphere

Another private-cloud or virtualization platform

Public-cloud infrastructure and managed services

Virtual machines managed outside Kubernetes

Serverless or application platform services

Bare-metal infrastructure

Multiple platforms without a common control layer

Unsure

Other

How is your organization supporting AI workloads? (Select one)(Required)

Extending our existing platform to support AI

Building a separate AI/ML platform

Connecting our platform to external model APIs

Using a managed public-cloud AI platform

Operating a private AI platform

Combining external services with internally hosted models

Supporting AI experimentation without a formal platform

Not currently supporting AI workloads

Unsure

Which AI-specific platform capabilities are available today? (Select all that apply)(Required)

AI gateway or unified model access

Model registry, evaluation or serving

AI-specific observability

Token or inference cost accounting

GPU provisioning, scheduling or optimization

Agent identity and permissions

Agent behavioral guardrails and auditability

MCP server discovery or governance

Data access, lineage or residency controls

None of these

Unsure

How mature are your AI governance and cost controls? (Select one)(Required)

Embedded across the platform, with clear ownership and cost attribution

Partially centralized, but important gaps remain

Managed separately by individual teams

Primarily applied after deployment or after costs are incurred

No consistent governance or cost-control model

Not applicable

Unsure

What is the greatest constraint preventing your platform from delivering what the business now expects? (Select one)(Required)

Platform adoption or developer experience

Orchestration and integration

Kubernetes or workload management

Infrastructure or GPU availability

Data access and governance

AI model or agent management

Security or compliance

Observability

Cost visibility and FinOps

Platform skills or staffing

Funding or executive support

Difficulty demonstrating platform value

Other

Optional: What is the one capability you most need to add or improve?

Would you be willing to participate in a short follow-up interview? (Select one)(Required)

Yes

No

If yes, please share your contact information (name, email, and company) so we can reach out.

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