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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BigQuery Cost Optimization: Slots, Pricing and Tips
A BigQuery bill has two parts, compute and storage, and nearly all the surprises are in compute. This guide explains both pricing models, prices three query shapes on a real table, gives the break-even between on-demand and slots, and lists the limits that stop one bad query becoming an expensive one.
Cost Optimization for LLM Applications in Production
LLM bills grow with every token, and most applications waste many of them. This guide breaks a request's cost into its parts, measures prompt caching and output length on a local model, then prices five options for a month of traffic using published list rates, from no changes to a cached small model.
AWS Cost Optimization for Data Workloads
A practical guide to AWS cost optimisation for data platforms: what each service bills for, the levers that move the bill for S3, Athena, Glue, EMR, Redshift and streaming, a measured example where storage layout cuts the data a query reads from 306.5 MB to 92 KB, and the budgets, tags and limits that stop surprises.
S3 Lifecycle Policies and Storage Cost Savings
S3 Lifecycle rules move objects to cheaper storage classes and delete them on a schedule. This guide explains transition and expiration actions, builds a three-rule configuration for a data lake bucket with boto3, and sets out the charges that catch people out: small objects, minimum durations, versions and archives.
Cost Controls and Budgets on Google Cloud
A budget on Google Cloud sends alerts; it does not stop spending. This guide sorts the cost tools into three jobs, seeing where money goes, being told when it changes and being stopped at a limit, and models a runaway query to show what each layer does to the month's bill.
Cost Optimization for ML Workloads in the Cloud
Most of an ML cloud bill comes from three decisions: how capacity is bought, how fully it is used and how efficiently each prediction is made. With live Azure prices and two real models, this guide shows reservations and spot cutting prices by 38 to 82%, and an always-on VM costing seven times its compute.