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Uptime
Why Businesses Need a Cloud-Agnostic Approach to SQL Server Uptime With Kubernetes
Kubernetes enables businesses to achieve uptime across multiple clouds while avoiding vendor lock-in — a truly cloud-agnostic SQL server environment ...
Don Boxley
|
January 6, 2025
|
Cloud-Agnostic
,
kubernetes
,
SQLServer
,
Uptime
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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)
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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)
*
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)
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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)
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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)
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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)
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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)
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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)
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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)
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Yes
No
If yes, please share your contact information (name, email, and company) so we can reach out.
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