IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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Google Cloud Storage: Buckets, Classes and Best Practices
Google Cloud Storage holds the raw files of almost every data platform on Google Cloud. This guide covers buckets and naming, choosing a location, the storage classes with their minimum durations and retrieval fees, lifecycle rules and how conflicts between them are resolved, soft delete, and access control.
Vertex AI Tutorial: ML on Google Cloud
Vertex AI is now called Gemini Enterprise Agent Platform, and its machine learning tools work as before. This tutorial follows one model from data to predictions, explains the contract your training code must follow, and trains a real model locally to show what testing on a later day reveals.
Amazon Redshift Explained: The Cloud Data Warehouse
An introduction to Amazon Redshift, AWS's data warehouse: how a leader node, compute nodes and slices run a query in parallel, why data is stored in columns, how managed storage separates compute from storage, Serverless versus a provisioned cluster, how it differs from PostgreSQL, and what to learn first.
GCP Logging and Monitoring with Cloud Operations
Google Cloud collects logs and metrics for you. The work is deciding what to keep, what to measure and when to alert. This guide explains log buckets, sinks, audit logs, log-based metrics and alerting policies, and uses a day of pipeline runs to show why an alert on errors misses silent failures.
Cloud Storage to BigQuery: Building an Ingestion Layer
An ingestion layer is the agreement between whoever delivers files and whoever queries tables. This guide designs one from Cloud Storage to BigQuery: a bucket layout BigQuery can read, one partition per day, loads that can be repeated without duplicates, a guard against misplaced rows, and a per-file audit.
How to Start a Career in Google Cloud in 2026
Google Cloud is the third of the big clouds by use, and most of its users work with another cloud too. But in some areas it is unusually strong: data, AI, mobile apps, and India. This guide uses survey data to show where those openings are, then sets out a 2026 start that spends nothing until you are ready.