دانلود کتاب FinOps Handbook for Microsoft Azure: Empowering teams to optimize their Azure cloud spend with FinOps best practices

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Cover\nTitle Page\nCopyright and Credit\nDedicated\nContributors\nTable of Contents\nPreface\nPart 1: Inform\nChapter 1: Bringing Visibility and Allocating Cost\n Technical requirements\n Tools used in this book for implementing FinOps for Microsoft Azure\n Azure CLI\n Power BI Desktop\n Azure Cost Management + Billing\n Azure Advisor\n Azure Monitor\n Azure Pricing Calculator\n What is the Microsoft Azure Well-Architected Framework?\n Creating a baseline using the WAF Cost Optimization assessment\n Cost allocation from an accounting point of view\n What is ABC allocation?\n Cost allocation in Azure for FinOps\n Cost allocation using the account, management group, and subscriptions hierarchy\n Cost allocation using resources tags\n Exploring cost analysis in the Azure portal\n Identifying the offer type for your subscription(s)\n Accumulated and forecasted cost\n Cost grouped by service\n Cost grouped by management group\n Cost grouped by tag\n Creating, saving, and sharing custom cost analysis views\n Summary\nChapter 2: Benchmarking Current Spend and Establishing Budgets\n Technical requirements\n The on-demand and elastic nature of Azure\n Developing KPIs for consistent reporting\n Strategic and operational KPIs\n Leading and lagging KPIs\n Why do you need KPIs?\n Defining, measuring, and reporting KPIs\n Benchmarking between teams\n Creating and managing budgets in Azure cost analysis\n Production marketing website budget\n Marketing development budget\n Marketing production budget\n Overall Marketing department budget\n Tracking the budget spend\n Creating and managing alerts in Azure cost analysis\n Budget alerts\n Spending anomaly alerts\n Summary\nChapter 3: Forecasting the Future Spend\n Technical requirements\n Introduction to forecasting\n Getting your Azure usage data\n Setting up the Cost Management connector for Power BI\n Forecasting based on manual estimates\n Forecasting based on past usage\n Advanced forecasting by application\n Identifying usage charges by application\n Fully loaded costs in forecasting\n Summary\nChapter 4: Case Study – Beginning the Azure FinOps Journey\n Case study – Peopledrift Healthcare\n Challenges\n Objectives\n Solution\n Benefits\n Summary\nPart 2: Optimize\nChapter 5: Hitting the Goals for Usage Optimization\n Technical requirements\n The project management triangle method for goal setting\n Setting OKRs or KPIs\n OKR examples\n KPI – tagging by business unit\n KPI – cost avoidance for unattached disks by business unit\n KPI – Azure Hybrid Benefit utilization by business unit\n KPI – storage accounts with hot, cool, and archive tiers\n Understanding Azure Advisor recommendations for usage optimization\n Accessing Azure Advisor using the portal\n Accessing Azure Advisor using the CLI\n Top 10 usage optimization targets using custom Azure workbooks\n Target 1 – 98% of all your resources must be tagged\n Target 2 – right-sizing underutilized virtual machines\n Target 3 – enabling Azure Hybrid Benefit for Windows and Linux VMs\n Target 4 – right-sizing underutilized SQL databases\n Target 5 – enabling Azure Hybrid Benefit for SQL databases, managed instances, and SQL VMs\n Target 6 – upgrading storage accounts to General-purpose v2\n Target 7 – deleting unattached discs\n Target 8 – deleting unattached public IPs\n Target 9 – Azure App Service – using the v3 plan with reservations and autoscaling\n Target 10 – Azure Kubernetes Service – using the cluster autoscaler, Spot VMs, and start/stop features in AKS\n Trade-offs of cost versus security, performance, and reliability\n Cost versus security\n Cost versus performance\n Cost versus reliability\n Summary\nChapter 6: Rate Optimization with Discounts and Reservations\n Technical requirements\n Commitment-based discounts in Azure\n The Microsoft Enterprise Agreement\n The Microsoft Azure Consumption Commitment (MACC)\n Identifying reservation opportunities for your workload\n Using the Azure Cost Management (ACM) Power BI app\n Scenario 1 – you are purchasing VM reservations for the first time\n Scenario 2 – you have existing reservations but want to purchase a new one for another Region and VM SKU\n Understanding Azure Advisor recommendations for reservations\n Reservation purchase and cadence\n Purchase cadence\n Reservation details, renewal, savings, and chargeback report\n Reservation details\n Auto-renewal\n Reservation savings and chargeback report\n Reservation exchange and cancellation\n Exchange reservations\n Cancel (return) a reservation\n Summary\nChapter 7: Leveraging Optimization Strategies\n Technical requirements\n Introducing Azure Spot market\n Estimating Spot VM discounts\n Spot VM and VM Scale Sets\n Spot VM caveats\n Eviction type and policy\n Limitations\n Pricing history and eviction rate details\n Architecting the workload to handle eviction\n Spot Priority Mix\n Discounting strategies with savings plans\n Savings plan versus reserved instances\n Purchasing a savings plan\n Writing a business case for cost optimization\n Business case: Orion business analytics platform cost optimization\n Summary\nChapter 8: Case Study - Realize Savings and Apply Optimizations\n Case study – Peopledrift Inc., a healthcare company\n Challenges\n The solution\n Benefits\n Summary\nPart 3: Operate\nChapter 9: Building a FinOps Culture\n Technical requirements\n Establishing a CoE for cloud cost management\n Motivating engineering teams to take action\n Incentivizing the team\n Penalizing the team\n Automated tag inheritance, governance, and compliance\n Automated VM shutdown and startup\n Automated budget actions\n Third-party FinOps tools\n Apptio Cloudability\n CloudHealth by VMware\n Cast.ai\n Summary\nChapter 10: Allocating Costs for Containers\n Technical requirements\n FinOps challenges for containerized workloads\n ACI cost allocation\n Introducing Kubecost\n AKS cost allocation\n Showback and chargeback shared AKS clusters\n Cost optimization recommendations for AKS clusters\n Manage underutilized nodes\n Resizing local disks\n Reserved instances\n Right-sizing your container requests\n Remedying abandoned workloads\n Right-size persistent volumes\n Summary\nChapter 11: Metric-Driven Cost Optimization\n Technical requirements\n Core principles of MDCO\n MDCO and reservation reporting using Power BI\n Setting thresholds for purchasing reservations\n Automated reservation purchases based on MDCO triggers\n Summary\nChapter 12: Developing Metrics for Unit Economics\n Technical requirements\n What is cloud unit economics?\n Benefits of cloud unit economics\n Indirect versus direct cost metrics\n Tracking costs back to business benefits\n Developing metrics for unit economics\n Cost per patient encounter\n Revenue per patient encounter\n Gross margin per patient encounter\n Cost per claim\n Revenue per claim\n Activity-based cost model\n Summary\nChapter 13: Case Study – Implementing Metric-Driven Cost Optimization and Unit Economics\n Case study – Peopledrift Inc., a healthcare company\n Challenges\n Objectives\n Solution\n Benefits\n Summary\nIndex\nOther Books You May Enjoy