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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

The Efficiency Era: How Kubernetes v1.35 Finally Solves the “Restart” Headache

Kubernetes v1.35 introduces in-place resource resizing, revolutionizing how stateful workloads are managed. Discover the benefits of dynamic resource allocation, traffic distribution, and the improvements that enhance operational efficiency for platform engineers ...

Pavan Madduri | March 3, 2026 | AI/ML workloads, cloud costs, Dynamic Resource Allocation, efficiency era, FinOps, immutability, Kubernetes architecture, Kubernetes enhancements, Kubernetes v1.35, Openshift, operational efficiency, resource resizing, self-healing infrastructure, Stateful Workloads, system performance, traffic distribution, vertical scaling

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Modernizing Manufacturing: How to Move from Legacy Infrastructure to Cloud-Ready Operations

18 August 2026

Modernizing Manufacturing: How to Move from Legacy Infrastructure to Cloud-Ready Operations

Migrating Apache Solr Workloads to Amazon OpenSearch Service

28 July 2026

Migrating Apache Solr Workloads to Amazon OpenSearch Service

From Pilot to Production: AI that Delivers Business Outcomes

27 July 2026

Disaster Recovery in Uncertain Times

2 September 2026

Disaster Recovery in Uncertain Times

From Reactive Alerts to Predictive Event Intelligence

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From Reactive Alerts to Predictive Event Intelligence

ADR vs. EDR: Why EDR Isn’t Enough in the AI Era

19 August 2026

ADR vs. EDR: Why EDR Isn’t Enough in the AI Era

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

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Software Testing and Test Automation

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Which of the following best describes your involvement in software testing or test automation at your organization? (Select one)*
- I actively perform software testing or test automation
- I manage or lead software testing or QA teams
- I make decisions about testing tools, frameworks, or automation strategy
- I do both hands-on testing and make strategic/tool decisions
- None of the above

How much of your organization's software testing is still performed manually today? (Select one)*
- Almost all
- More than half
- About half
- Less than half
- Almost none

How much effort does your team spend maintaining existing automated tests compared to creating new test coverage? (Select one)*
- Mostly maintaining existing tests
- More maintenance than new coverage
- About equal
- More new coverage than maintenance
- Very little maintenance required

How much has AI-assisted software development increased the pressure on your testing teams over the past 12 months? (Select one)*
- Significantly increased pressure
- Moderately increased pressure
- Slightly increased pressure
- No meaningful impact yet
- Unsure

What is the biggest obstacle preventing your organization from expanding software test automation and adopting agentic testing? (Select one)*
- Automated tests are too difficult or costly to maintain
- Release cycles move too quickly to keep tests current
- Too much coding or scripting expertise is required
- Testing tools and frameworks are too fragmented
- Lack of time, budget, or staffing
- Difficulty proving business value or ROI
- Insufficient AI or intelligent automation capabilities

Which improvement would create the greatest business impact for your organization over the next 12 months? (Select one)*
- Reducing manual testing effort
- Reducing automated test maintenance
- Accelerating release cycles
- Expanding test coverage across more technologies
- Consolidating testing tools and frameworks
- Enabling more non-developers to automate testing
- Improving the resilience and adaptability of automated tests

Which statement best reflects your organization's current perspective on AI-powered or agentic software testing? (Select one)*
- We are actively evaluating or adopting AI-powered testing approaches
- We are interested, but still assessing practical value and trust
- We believe current automated testing approaches are sufficient
- We are primarily focused on improving existing automation before adopting AI-assisted testing
- We have not yet explored AI-powered testing in a meaningful way

How important is the ability to execute continuous, largely autonomous software testing with minimal human intervention ("lights-out" or "dark factory" testing) to your organization's future software delivery strategy? (Select one)*
- Critical strategic priority
- Important, but still early-stage
- Somewhat important
- Low priority today
- Not relevant to our organization
- Unsure

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