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SRE, autoscaling, Tailscale, Kubernetes, argo cd, Kubernetes v1.33, AI, Nelm, Kubernetes, architecture, , architecture, Rackspace, GPUs, Kubernetes, Solo.io Kubernetes cloud foundry keptn cloud-native automation

Kubernetes Release Cycles and Vendor Support Harbor Freedoms–and Sacrifices

Analysis of the "lag gap" between upstream Kubernetes releases and vendor GA availability, comparing release cadence, support windows, and lifecycle cost tradeoffs across hyperscalers, VMware VCF, and Red Hat OpenShift to guide ...

Jack Wallen | March 25, 2026 | AWS EKS, Azure AKS, cluster costs, cncf, compliance, DISA STIG, enterprise devops, enterprise Kubernetes, EOL, extended support fees, FedRAMP, FIPS, GA delay, GKE, hyperscalers, innovation velocity, kubernetes, lag gap, lifecycle support, platform choice, Red Hat OpenShift, release cadence, rollback, stability, support window, TCO, upgrade strategy, vendor support, virtualization, VMware VCF

Microsoft Draft Helps Developers Adopt Kubernetes

Microsoft Draft Helps Developers Adopt Kubernetes

Microsoft’s Deis has released Draft to makes it easy for developers to build applications that run on Kubernetes. Draft does this by providing tools and simplifying steps required to build for Kubernetes ...

Prakash Sarma | June 16, 2017 | automation, container management, containers, continuous delivery, Deis, devops, docker, docker coreos, enterprise devops, kubernetes, linux container

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Migrating Apache Solr Workloads to Amazon OpenSearch Service

29 September 2026

Migrating Apache Solr Workloads to Amazon OpenSearch Service

Modernize for the AI Era

16 September 2026

Modernize for the AI Era

The Strategic Imperative: Embracing Agentic B2B Selling

8 September 2026

The Strategic Imperative: Embracing Agentic B2B Selling

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Migrate and Modernize your applications with at Zscaler Zero Trust Security Platform on AWS

17 September 2026

Migrate and Modernize your applications with at Zscaler Zero Trust Security Platform on AWS

From Reactive to Autonomous: The New IT and Security Playbook

3 September 2026

From Reactive to Autonomous: The New IT and Security Playbook

Automate, Secure and Govern Agentic Workflows with JFrog

1 September 2026

Automate, Secure and Govern Agentic Workflows with JFrog

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ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

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Supermicro Debuts Kubernetes Edge AI Appliance with Red Hat and Everpure

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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)*
- 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)*
- 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)*
- 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)*
- 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)*
- 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)*
- 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)*
- 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)*
- Yes
- No
If yes, please share your contact information (name, email, and company) so we can reach out.

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