Category: AI Stack
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Python for Data Work, Past Automation Scripting (Infra to Data Science Series, Part 5)
Your automation scripts already move data. This part turns that habit into data code: load a month of cluster metrics with pandas, catch the dtype trap that silently breaks a metric column, and see why iterrows is slower than the plain loop you already write.
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Data Science Transition Roadmap and Timeline for Infra Engineers (Infra to Data Science Series, Part 4)
How long the move from infrastructure to data science really takes, broken into four phases you can hold against a calendar, with the sideways move that beats quitting for a bootcamp.
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Operations Mindset vs Data Science Mindset for Infra Engineers (Infra to Data Science Series, Part 3)
An operations mindset chases zero failure; a data science mindset budgets error and ships something useful before it is perfect. Here is how an infrastructure engineer switches between the two without losing the discipline that makes them worth hiring.
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Transferable Skills for Infra Engineers Moving to Data Science (Infra to Data Science Series, Part 2)
An operator moving into data science already holds more of the job than the posting admits. How to audit your skills against a real data science job description, which transfer, which reshape, and the two gaps to close first.
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What a Data Scientist Actually Does, Compared to Infra, SRE and VMware Work (Infra to Data Science Series, Part 1)
If you run infrastructure, keep an SRE rotation or administer VMware, you are not starting data science from zero. What a data scientist actually does, where your skills already transfer, and where to start.
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Red Hat AI vs the Managed Clouds, the Verdict and What to Learn Next (Red Hat Gen AI Series, Part 30)
Capstone of the series: where Red Hat AI beats AWS, Google, Azure and IBM watsonx, where it loses on cost, and an honest verdict on self hosting Granite versus renting a frontier API.
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Air Gapped and Disconnected Red Hat AI Deployments (Red Hat Gen AI Series, Part 29)
Stand up a self hosted Granite assistant in a disconnected data center: mirror images with oc-mirror v2, carry model weights across the gap, trust your registry, and lock down egress.
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Cost and FinOps for Self Hosted GenAI on OpenShift AI (Red Hat Gen AI Series, Part 28)
Self hosting Granite rarely wins on unit cost until you reach billions of tokens a month. Here is how to price a self hosted token, measure real GPU utilisation on OpenShift AI, and find where a managed API stops being cheaper.
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RAG on OpenShift AI With a Self Hosted Vector Store (Red Hat Gen AI Series, Part 27)
Build self hosted RAG on OpenShift AI: Llama Stack, a Milvus vector store and your served Granite model, with the vector-only gotcha that quietly costs recall.
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OpenShift AI Guardrails for a Self Hosted Granite Assistant (Red Hat Gen AI Series, Part 26)
Input and output guardrails for a self hosted Granite assistant on OpenShift AI: deploy the FMS Guardrails Orchestrator, block PII and prompt injection, and keep the added latency inside the tail budget.
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Benchmarking a Self Hosted Inference Deployment With GuideLLM (Red Hat Gen AI Series, Part 25)
A single hand run is not a benchmark. Here is how to measure a self hosted Granite deployment with GuideLLM and gate every model or config change on tail latency, not throughput, so no regression ships unmeasured.
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Token Economics and Latency Tuning for Self Hosted Granite (Red Hat Gen AI Series, Part 24)
What one answer from a self hosted Granite model actually costs, and the three vLLM flags that decide it. A latency aware guide to throughput, TTFT and cost per token on the Red Hat AI Inference Server.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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