Resource Allocation | Hokstad Consulting

Resource Allocation

Blog posts in the Resource Allocation category

Cost Analysis for Multi-Cloud Workloads

Tactical guidance to reduce multi‑cloud spend: rightsizing, standardised tagging, centralised billing and egress optimisation.

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Shared Cloud Costs: Dev vs Testing Allocation

Allocate shared cloud costs between dev and test with automated shutdowns, ephemeral environments, autoscaling and better tagging.

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Azure Free Tier: Hidden Costs Explained

Azure Free Tier can quickly incur charges from deallocated disks, data egress and logging — see the hidden costs and how to prevent them.

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Dynamic Resource Allocation with Kubernetes

How Kubernetes dynamic resource allocation cuts cloud waste, optimises GPU/CPU use and automates autoscaling with real-time metrics.

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Defining Business Units for Cloud Cost Allocation

Align business units, enforce tagging and allocate shared services to map cloud spend, boost accountability and cut waste.

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Reserved Instance Reporting: Best Practices

Monitor RI utilisation and coverage with Cost Explorer, Budgets and CUR; centralise purchases and set alerts to reduce wasted cloud spend.

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Kubernetes Cost Management: Resource Quotas Explained

How namespace-level resource quotas limit CPU, memory, storage and object counts, with monitoring, LimitRanges and cost-control tips.

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Chargeback vs Showback: Choosing the Right Model

Showback vs chargeback explained: when to use each cloud cost model, their pros and cons, and how to move from transparency to billed accountability.

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Best Practices for CDN Capacity Planning

Practical guidance on forecasting, regional allocation, load balancing, multi‑CDN and real‑time monitoring to optimise CDN capacity, performance and cost.

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5 Steps for Accurate Cloud Cost Forecasting

Use 12–18 months of normalised billing data, identify cost drivers, build driver-based forecasts, monitor continuously and review to cut variance to 5–12%.

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Benchmarking Containers and VMs for Applications

Compare containers and virtual machines by startup speed, memory/CPU overhead, application performance, density and isolation to inform deployment choices.

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HPA vs. Cluster Autoscaler: Cost Efficiency

Compare HPA and Cluster Autoscaler to reduce Kubernetes costs: when to use each, how they interact, and best practices to maximise savings.

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