💰 Platform Economics & Cloud Cost Language
6 exercise sets. Master the vocabulary for cloud cost optimisation, FinOps, showback/chargeback, and communicating infrastructure economics.
Cloud Cost Optimisation Vocabulary
Reserved instances, savings plans, spot instances, rightsizing, over-provisioned resources, and idle resource detection vocabulary.
FinOps Vocabulary
FinOps lifecycle (Inform → Optimize → Operate), unit economics, cost per transaction, cloud bill anatomy, and cloud waste vocabulary.
Showback & Chargeback Vocabulary
Showback vs. chargeback models, cost allocation tags, shared service cost splitting, budget alerts, and cost anomaly detection.
Cloud Pricing Vocabulary
On-demand vs. reserved vs. savings plans vs. spot pricing, committed use discounts, pricing calculators, and TCO analysis vocabulary.
Cost Communication Vocabulary
Communicating cloud costs to business: unit cost, cost-per-feature, infrastructure ROI framing, and budget variance vocabulary.
Platform ROI Vocabulary
Platform team ROI, developer productivity ROI, time to first deployment, cost avoided framing, and cost per deployed feature vocabulary.
Frequently Asked Questions
What's the difference between 'Reserved Instances' and 'Savings Plans' in AWS, and when should I use one over the other?
Both Reserved Instances and Savings Plans offer discounted compute pricing compared to on-demand rates, but they differ significantly. Reserved Instances commit to a specific instance type and region for 1 or 3 years, offering the deepest discounts upfront. Savings Plans provide flexibility by committing to a certain amount of compute usage (regardless of instance type) across multiple resources, making them ideal for variable workloads.
I'm seeing 'Idle Time' charges on my EC2 bill – what exactly is causing this and how can I reduce it?
'Idle Time' refers to the period an EC2 instance remains running but isn't actively processing requests. This often happens with instances left running after deployments or scheduled tasks, even if they aren't performing any work. Reducing idle time involves implementing proper shutdown scripts, utilizing auto-scaling groups, and scheduling tasks efficiently.
Can I use 'Cost Explorer' in Azure to analyze my container service (AKS) costs beyond just virtual machine charges?
Yes, Azure Cost Explorer allows you to break down AKS costs into several components. You can filter by Kubernetes services like deployments, namespaces, and pods to identify the most expensive resources driving your overall spend, as well as view storage, networking, and managed service charges.
What is 'Spot Instances' and how does its fluctuating pricing impact my application's stability?
Spot Instances offer significant discounts (up to 90%) on unused EC2 capacity, but these instances can be terminated with short notice if the spot price exceeds your bid. This volatility requires applications using Spot Instances to be fault-tolerant and designed for interruptions – often through checkpointing or automated recovery mechanisms.
Explain 'Right Sizing' in relation to cloud compute resources - what metrics should I focus on?
'Right Sizing' involves choosing the appropriate instance type and size for your workload based on actual resource utilization. Key metrics include CPU, memory, network I/O, and disk I/O – monitoring these helps you identify over-provisioned instances consuming unnecessary costs.
What is the purpose of a 'Cloud Cost Management' tool like CloudHealth or native cloud cost analysis tools?
These tools provide centralized visibility into your cloud spending across multiple providers, enabling you to identify trends, anomalies, and areas for optimization. They typically offer features such as budget alerts, resource tagging, reporting, and recommendations based on usage patterns.
How does 'Auto Scaling' affect my cloud costs, particularly when combined with reserved capacity?
Auto Scaling dynamically adjusts the number of running instances based on demand, preventing over-provisioning during low periods. When coupled with Reserved Instances, this creates a highly cost-effective solution for applications experiencing fluctuating workloads, automatically scaling up to meet peak demands and back down.
What is 'Shadow Computing' and how does it contribute to unexpected cloud costs?
'Shadow Computing' refers to running duplicate versions of your application in a separate environment (like a test or staging) without directly impacting production. This can lead to increased resource consumption – compute, storage, network – if not carefully managed, resulting in inflated cloud bills.
I'm using serverless functions (e.g., Lambda). How do I track and optimize the cost of their execution time?
Serverless function costs are primarily based on invocation duration and memory allocated per execution. Monitoring these metrics in your cloud provider's console or with tools like CloudWatch allows you to identify inefficient code, long-running functions, and opportunities to reduce memory usage.
What is the 'Cost Allocation Tags' feature and why is it important for tracking cloud spend?
Cost allocation tags allow you to categorize your cloud resources (e.g., by department, project, or application) enabling precise cost tracking at a granular level. This facilitates better budget management, resource prioritization, and chargeback processes, providing visibility beyond just aggregated usage.