What is cloud cost optimization?
Cloud cost optimization is the systematic practice of reducing cloud spend while improving cloud efficiency through enhanced visibility, resource rightsizing, workload automation, and team accountability.
Unlike simple cost cutting, cloud cost optimization balances performance needs with spending controls to maximize business value from cloud investments.
The Cloud Visibility Playbook
Read this playbook to achieve continuous, agent-less visibility across every cloud resource and data flow.
How does cloud cost optimization work?
Cloud cost optimization stands on four core principles:
Eliminate waste: Research shows that anywhere between 28%-50% of cloud spend simply goes down the drain. That’s a lot, regardless of if your enterprise is small, medium, or large. To cut down on the waste, identify and plug inefficiencies like idle resources and poorly optimized software logic.
Rightsize resources: Overprovisioned resources contribute to wasted spend, which takes a big bite out of bottom lines. Don’t want this to happen to you? Rightsize cloud resources based on computing needs tracked over time to cut unnecessary expenditure and boost profit margins.
Optimize pricing models: Enterprises can incur well over $50,000 monthly in wasted spend, and overlooking discounted pricing models like reserved/spot instances is a major reason why. Explore what pricing model works best for various workloads and then make the switch.
Empower teams with visibility and accountability: Transform complex cloud bills into actionable insights to help teams make smarter, cost-conscious decisions about what resources they’re purchasing, who’s provisioning/using said resource, and why. This ensures accountability, prevents cloud sprawl, and abstracts bill shock.
Common causes of cloud cost waste
1. Overprovisioned compute and storage
Overprovisioning occurs when, due to the fear of performance issues, enterprises intentionally purchase more resources than workloads need. The result? Enterprises pay for unused capacity, a common scenario with oversized EC2 instances, idle Kubernetes nodes, and excessive IOPS.
Solutions: Collect and track usage metrics for accurate rightsizing, and autoscale nodes to meet performance needs.
2. Zombie resources: Unused but still running
Unattached volumes, stale snapshots, idle load balancers—these quietly eat up budget and increase attack surface.
Solutions: Uncover and terminate/reassign unused resources. Common places to look are orphaned volumes and snapshots, unassociated IP addresses, unused machine images, and load balancers with no instances attached.
Automating resource lifecycle management and idle resource cleanups also helps save you money.
3. No autoscaling or shutdowns
Static infrastructure = wasted spend. Dynamic workloads demand dynamic scaling.
Solutions: Rather than letting resources go to waste when traffic drops, automate scaling for fluctuating workloads and shutdowns for predictable ones.
4. Inefficient infrastructure architecture choices
When infrastructure is designed without cost in mind, cloud spend balloons quickly. What infrastructure choices could be spiking your cloud costs?:
Wrong storage tier: Using high-performance or general-purpose storage (like AWS S3 Standard or GP2 volumes) for data that’s rarely accessed or archival in nature results in unnecessary spend.
Solution: Use lifecycle policies and cost-aware architecture reviews to shift cold data to cheaper tiers like S3 Glacier or archival blob storage
Overpowered compute instances: Deploying workloads on compute families optimized for CPU or memory when not needed results in major overspending.
Solution: Use rightsizing tools to match instance type and size to actual workload requirements.
Unoptimized load balancer and networking use: Running multiple load balancers when a single shared one would do, or using public IPs and NAT gateways where private networking would suffice, leads to recurring waste.
Solution: Audit networking architecture and consolidate or redesign where possible.
Cross-region data transfers: In addition to creating performance, data governance, and compliance problems, architectures involving cross-region data transfers rack up high data egress costs, which often comes as a rude awakening to enterprises.
Solutions: Use traffic routing strategies and edge caching/CDNs to minimize inter-region communication
5. Limited and siloed cost visibility
When teams can’t see or understand how their cloud budget is spent in real time and make adjustments immediately, inefficient spending, inaccurate forecasts, and bill shock becomes the norm. In many cases, siloed cost data is a barrier to effective optimization:
Single-cloud siloes: Most cloud service providers (CSPs) provide some visibility and tooling to manage cost, but do not give teams a holistic view into their cloud cost in multi-cloud environments and often lack the business context to empower effective decision making. WIthout a unified view, teams must manually piece together disparate data to get the full picture.
Solution: Invest in cloud cost optimization tooling that supports unified visibility across a multi-cloud environment
Functional siloes: As the owners of infrastructure and applications, engineers are closest to the decisions that directly impact cloud spend. When cloud cost tools are built primarily for finance teams, they often emphasize budget tracking and spend reports over insights engineers can use. This disconnect means engineers are either excluded from cost conversations altogether or expected to interpret raw financial data without sufficient context—like usage patterns, performance tradeoffs, or architectural implications. The result? Missed opportunities to optimize workloads, delayed responses to inefficiencies, and friction between teams.
Solution: Invest in cloud cost optimization tooling that supports engineering workflows by providing clear ownership, actionable insights, and complete context into the cloud environment and relationships between resources.
6. Shadow IT
Shadow IT refers to resources spun up without stakeholder oversight or approval, outside of policy, or without governance. Shadow IT can cause cloud sprawl, uncontrolled spend, and unmitigated security risks.
Solutions: Create centralized procurement policies, and use cloud-native security solutions to find and resolve shadow assets.
Key strategies for cloud cost optimization
An important first step in achieving cloud cost optimization is having a cloud operating model. A cloud operating model defines how an organization manages, governs, and optimizes its cloud environments across teams, tools, and processes. It's the foundation for sustainable cost optimization at scale.
Once the model is in place, implement these six cloud cost optimization best practices:
1. Tagging and resource ownership
Enforce consistent tagging by team, project, or environment using policy-as-code tools, infrastructure-as-code (IaC) tools, and centralized tagging policies. Tagging boosts visibility into resource ownership and facilitates accountability. This enables development teams to take proactive ownership over cloud costs for the resources and services they own.
Define your tagging policies and create a tagging schema.
Use cloud-native PaC tools (e.g., AWS tag policies) to automate resource tagging immediately after a resource spins up.
Mandate tagging, verify compliance, and ensure consistency across multi-cloud environments using IaC tools like Terraform or CloudFormation.
Generate cost reports based on the tags for easy cost attribution and unit-based forecast accuracy.
2. Rightsizing compute resources
Regularly analyze utilization and resize instances or workloads accordingly. Tools like AWS Compute Optimizer and GCP Recommender API will come in handy.
Test rightsized resources for optimal performance; you don’t want them to underperform at the slightest hint of a traffic spike.
3. Auto-scaling and scheduled shutdowns
Dynamically adjust resource availability to real-time traffic to cut unnecessary spending without impacting performance.
Autoscaling is an important way to keep downsized resources working optimally; it scales compute resources up/down or in/out as traffic rises and ebbs.
Scheduled shutdowns or scaling to zero ensures resources with specific usage periods only run when actively in use.
Use metrics/policy-based autoscalers (like AWS Auto Scaling groups), cloud-native schedulers (such as AWS Instance Scheduler), or serverless event bus services for non-critical workloads (for example, Amazon EventBridge).
4. Leverage spot/reserved instances and savings plans
Match workloads to the best pricing model. Use Spot Instances for non-critical / stateless / fault-tolerant workloads; Reserved Instances for predictable, stateful workloads; and Savings Plans for flexible but consistent workloads.
5. Storage lifecycle policies
Base tiered storage on frequency of access and speed requirements.
Enforce policies that automatically monitor access patterns and move infrequently accessed data to cold storage.
6. Cost dashboards and budget alerts
Visualize cloud spend in real time by team, ownership, or environment tag. Configure dashboards to automatically trigger alerts when thresholds are reached (e.g., when 70% of monthly quota is reached). This allows teams to quickly adjust spending habits and prevent cost overrun.
The role of FinOps in cloud cost optimization
FinOps brings together finance, engineering, and business teams to optimize cloud spending through collaboration, accountability, and data-driven decision-making. It plays a critical role in real-time cloud cost optimization, providing the glue that helps finance, operations, and engineering teams sync up on the mission of cutting unnecessary cloud spend while maximizing business value.
Before we get into the FinOps process itself, let’s talk about the stakeholders involved in FinOps and their roles.
FinOps works in three phases:
Phase 1 — Inform: Get real-time, unified visibility into cloud spend across the entire cloud environment, including multi-cloud. Shared dashboards should provide a source of truth for engineering, finance, and ops teams. In-depth, real-time visibility will facilitate shared accountability, proper cost allocation, and accurate forecasts.
Phase 2 — Optimize: Implement the cost optimization strategies discussed above to cut waste, prevent budget overruns, and improve efficiency.
Phase 3 — Operate: Continuously measure and improve on cost optimization outcomes by defining and tracking FinOps KPIs, including:
Cost per workload: Tracks spend on a specific application or service by breaking cost analysis down per unit of work (e.g., cost per transaction or API call)
Benefit: Pinpoints the most cost-sapping workloads for further optimization and rightsizing
Forecast accuracy: Checks how accurately budget forecasts align with actual spend
Benefit: Ensures budgets are realistic, with no overspending or underspending issues
Unallocated spend: Identifies unattributed cost, which may occur due to shadow IT or untagged resources
Benefit: Boosts accountability and security
Optimization coverage: Measures the percentage of optimized resources, like resources with auto-scaling or zero-scaling enabled
Benefit: Determines how well teams are leveraging cost optimization strategies
Cloud cost optimization across AWS, Azure, and GCP
Most cloud service providers (CSPs) support cloud-cost optimization via diverse price offerings and native tools. But remember: For FinOps to work, teams need a unified view and source of truth on cloud cost that provides the context to take action and supports a multi-cloud environment.
AWS
Cost Explorer: Lets you visualize historical cloud spend, create visuals of forecasts, examine cost spikes (and the cause) over time, and create custom tags for transparent team-based resource governance
Trusted Advisor: Gives real-time cost optimization recommendations, flags inefficiencies (think idle resources and old snapshots), and auto-remediates issues
Compute Optimizer: Tracks usage patterns and performance via CloudWatch metrics to recommend options for rightsizing overprovisioned/underprovisioned resources
Savings Plans: Offers an option for committing to consistent resource usage (for predictable workloads) in exchange for discounts
Azure
Microsoft Cost Management: Tracks and predicts spend, provides visuals for team/tag-based resource allocation, and integrates with advanced analytics tools
Azure Advisor recommendations: Prevents cloud sprawl by offering rightsizing suggestions, shutting down idle resources, etc.
Azure Reserved VM Instances: Lets you pre-pay (at heavily discounted rates) for resources under a one-year or three-year contract; ideal for long-term, baseline workloads
GCP
Cloud Billing Reports: Lets you dig into cloud costs by resource, team, label, or project; GCP also enables you to build customized dashboards with filters
Recommender API: Offers recommendations for rightsizing, triggers threshold alerts and actions, and more
Committed use discounts: Offers considerable discounts in exchange for committing to spend a minimum amount on assets or use a minimum level of resources for one or three years
How security and cost optimization work hand-in-hand
Security and cloud cost optimization intersect. Improving security can help cut cloud waste, and proper cloud cost optimization can reduce the attack surface. How? That’s where security solutions like cloud native application protection platforms (CNAPP) come into play. They…
Inventory assets and provide unified visibility across multi-cloud environments which is critical for surfacing cost-relevant risks (e.g., unused but over-permissioned workloads and zombie assets)
Prevent misconfigurations that could lead to costly security incidents (including publicly exposed storage buckets that can be easily exploited by cyberattackers)
Identify shadow IT to prevent cloud sprawl, untracked spending, and unmonitored security risks
Use automation and policy-as-code to enforce tagging, provisioning limits, and least-privilege access
Securely decommission unused/orphaned resources to reduce spend and risk
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How Wiz enhances cloud cost optimization
Wiz not only strengthens cloud security but also empowers organizations to optimize cloud expenditures intelligently—combining security insights with cost visibility to maximize business outcomes.
Look to Wiz Cloud Cost Optimization for:
Granular, resource-level cost reporting: Wiz creates a comprehensive inventory of every resource in your cloud environment. With Wiz Cloud Cost Optimization you can monitor spend for each resource and understand the relationships between resources. You can also group costs by project or service so you can more easily attribute spend to different teams, products, or application features.
Detection of outdated resources: Wiz identifies resources operating on extended support versions, such as Amazon EKS clusters,which incur higher costs. By pinpointing these clusters, organizations can decide to upgrade or decommission them, leading to substantial savings.
Identification of unused and orphaned resources: Wiz detects idle or unattached resources, such as unused volumes or load balancers, that contribute to unnecessary costs.
Rightsizing based on usage metrics: Wiz identifies rightsizing opportunities based on resource allocation vs. actual resource usage, helping you trim costs.
Security-driven cost insights: By correlating security postures with cost and usage data, Wiz helps prioritize cost-saving measures that also enhance security, ensuring security teams don’t spend time fixing resources that could be eliminated.
Ready to control your cloud spend while ensuring optimal security and maximum value? Request a live demo of Wiz today.
