Category: Tech Notes
-
TKGI to VKS Migration Business Case and Phased Timeline (TKGI to VKS Series, Part 4)
TKGI is on a lifecycle clock and VCF 9 is the destination. Here is the business case, the drivers that set your real deadline, and a phased timeline you can hand a budget owner.
-
TKGI to VKS Is a Migration, Not an Upgrade (TKGI to VKS Series, Part 3)
TKGI and VKS differ at the control plane, machine lifecycle, network and identity, so there is no in place upgrade path. Here is why this move is a migration, and what that word changes about budget, risk and rollback.
-
TKGI vs VKS Architecture Compared, Component by Component (TKGI to VKS Series, Part 2)
TKGI and VKS set side by side, control plane, cluster lifecycle, networking, storage and identity, so the architecture gap behind the migration is concrete before you design the VCF 9 target.
-
What VKS Is and Why TKGI Is Winding Down (TKGI to VKS Series, Part 1)
There is no upgrade path from TKGI to VKS. Part 1 explains what the vSphere Kubernetes Service is, why the old platform is winding down, and why the move is a migration you plan rather than a patch you apply.
-
Data Science Interviews and Specialisation for Infra Engineers (Infra to Data Science Series, Part 26)
A data science loop runs four to six rounds, and the one that screens out switchers is the case and statistics round, not coding. Prepare for the interview that exists and specialise toward MLOps, where your operations background is an edge.
-
Data Science Portfolio and Resume for Infra Engineers (Infra to Data Science Series, Part 25)
Your infrastructure projects are already a data science portfolio. This part translates an operations resume into outcomes a data team reads and turns your telemetry work into two or three projects that get the interview.
-
Incident Prediction and AIOps, Honestly Assessed (Infra to Data Science Series, Part 24)
Incident prediction on your own telemetry usually fails on arithmetic, not modelling. A base rate check, an honest look at AIOps, and the narrow cases where prediction actually pays.
-
Log Analysis and Clustering at Scale for Infra Telemetry (Infra to Data Science Series, Part 23)
Clustering raw log lines fails because ids and timestamps make every message unique. Mine templates with Drain3 first, then cluster the structure, and a day of logs collapses to a triage table you can read in a minute.
-
Capacity Forecasting From Infrastructure Telemetry (Infra to Data Science Series, Part 22)
A straight line on a seasonal metric tells you when the average crosses your limit, not when the weekly peak does. Forecast with Holt-Winters, read the date off the upper prediction band, and plan against the risk you can afford.
-
Anomaly Detection on Metrics and Time Series for Infra Telemetry (Infra to Data Science Series, Part 21)
Static thresholds on seasonal infrastructure metrics measure the time of day, not trouble. Deseasonalise with STL, score the residual with a median and MAD based z, and reach for an isolation forest when several metrics move together.
-
Experiment Tracking and Model Registry for Infra Data (Infra to Data Science Series, Part 20)
Log every training run, register the good ones as immutable versions, and let a single champion alias decide what serves, so promotion and rollback each become one line. Built on the incident classifier, with the real failures that bite.
-
Pipelines and CI/CD for Machine Learning on Infra Data (Infra to Data Science Series, Part 19)
A pipeline and a CI gate that refuse to promote a model unless it clears a metric on a time aware split, built on the incident classifier from earlier parts, with the real failures that break each stage.
Architect’s Toolkit
PJ’s Tools
- Infra 360 Hub – All Series
- VCF Exam Practice Labs
- VCF 9 Interactive Walkthroughs
- VCF Design Cheatsheet
- VCF Upgrade Planner
- VCF 9 Series Hub
- VCF Deployment Hub
- AI Stack Hub
- AI Infra Sizing & Cost Calculator
- LLM & RAG Cost Calculator
- DrJhaGPT – Ask Pranay
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
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.
You May Have Missed
DrJha