Microsoft Azure and Google Cloud have steadily gained ground, with Azure now accounting for about 20% of global cloud infrastructure spend. Organizations have been moving toward multi‑cloud strategies to avoid vendor lock-in, meet compliance, support hybrid IT models, or take advantage of specific service capabilities unique to each provider.
With adoption on Azure accelerating, cost concerns are rising too. Azure offers a broad and growing range of services, pricing models, and enterprise features. This depth and breadth of capability gives teams more flexibility, but also introduces serious financial risk if costs are not managed properly. Without strong governance, costs often spiral out of control.
Cloud cost management is no longer a good-to-have, but a requirement. Industry research shows that nearly one-third of cloud spend is waste. For a company spending $10 million on cloud every year, that translates to more than $3 million lost to inefficiencies each year.
Much of this waste stems from underutilized or overprovisioned resources, misaligned commitments, and monolithic, outdated architectures (rather than microservices). In most cases, the waste is not deliberate, it exists because finance and engineering operate in silos, with limited visibility into each other’s decisions and priorities.
What is needed is shared accountability. A consistent way to track usage, measure value, and act on cost insights across teams. That’s the core purpose of FinOps.
In this guide, we focus on Azure FinOps, covering the key cost drivers, cultural shifts, native tools, and optimization practices needed to make FinOps work in this environment. This is Part 3 of our Getting Started With FinOps series. Explore Part 1 for AWS and Part 2 for Google Cloud.
Key Cost Drivers in Azure
Understanding where costs originate is the starting point for FinOps. In Azure, the variety of service SKUs, layered pricing models, and flexible deployment options introduce unique cost challenges, many of which aren’t obvious at first glance. Below are the most common sources of cloud waste in Azure environments.
Overprovisioned Virtual Machines
Azure offers hundreds of VM SKUs across general-purpose, compute-optimized, memory-optimized, and storage-optimized families. But in most organizations, VM sizing decisions are either inherited from past configurations or based on worst-case scenarios. The result is persistent over-allocation of CPU, memory, and IOPS — especially in non-production environments.
Static workloads without auto-scaling
Auto-scaling in Azure is available across services, such as Virtual Machine Scale Sets, App Services, AKS, Azure Functions, etc. Yet many workloads are still deployed with fixed capacity. Applications with variable traffic are often deployed on infrastructure designed for peak load, resulting in idle resources during off-peak periods.
Premium storage by default
Azure offers several storage tiers from Premium SSD and Ultra Disks to Standard HDD and Archive tiers, each optimized for different performance and access patterns. In practice, many teams stick with high-performance defaults even for dev, backup, or archival data where it is not required. Without active lifecycle rules or data tiering strategies, costs increase quietly. Storage waste is rarely visible in daily operations, but adds up quickly when multiplied across environments.
Unused or forgotten resources
Unattached managed disks, orphaned NICs, abandoned snapshots, and stale App Service Plans are common in long-running Azure environments. These resources may not show up in high-level billing reports, but continue to generate costs in the background until explicitly deleted.
Misaligned Reservations and Savings Plans
Azure Reservations and Savings Plans offer meaningful discounts, but only when they align with actual usage. Teams that commit too early or too aggressively face overcommitment risk. Others undercommit and rely heavily on Pay-As-You-Go pricing, missing out on available discounts. A mature FinOps practice tracks usage trends and adjusts commitments frequently. Sophisticated teams also leverage a portfolio of commitments and advanced rate optimization strategies to balance flexibility and savings over time.
Underutilized databases and analytics services
PaaS offerings, such as Azure SQL Database, Cosmos DB, Synapse Analytics, Databricks, etc. are often provisioned with more capacity than needed. DTUs, vCores, or throughput settings are rarely revisited, and inactive replicas or unused partitions continue billing even if the workload has changed.
Inefficient network design
Outbound data transfer across Availability Zones or Regions, reliance on NAT gateways and firewalls, or poorly architected hub-and-spoke topologies all contribute to hidden but significant networking costs. These design choices often emerge over time and are rarely revisited once deployed.
Poor cost attribution across subscriptions
Azure’s billing hierarchy spans subscriptions, management groups, and resource groups, but many organizations lack consistent tagging or alignment between cloud architecture and business units. Without clear cost allocation, teams/ business units cannot take ownership of what they spend, making it difficult to enforce accountability or optimize at the team level.
Lack of proactive automation
Azure provides native tooling for anomaly detection, budget alerts, auto-shutdown schedules, and recommendation engines. However in many environments, these features are left unconfigured or inconsistently applied.
Without automation, teams operate in reactive mode, discovering cost issues after the fact rather than preventing them early. As usage grows, identifying patterns and taking action before it becomes an issue is essential to scaling cost governance effectively. This can only be enabled by automation.
Cultural Alignment: The First Step Toward Azure FinOps Maturity
Before tools, before savings targets, before automation, FinOps begins with structure. Organizations often jump straight to dashboards or cost alerts without first aligning people around a shared responsibility model. Cultural alignment is the foundation that enables long-term, sustainable cost control in Azure.
Here are the steps required to set the foundation for FinOps implementation.
Secure executive buy-in
FinOps requires changes across teams, processes, and priorities. This does not happen without support from the top. Leaders must treat cloud cost optimization as a strategic goal, not a reactive cleanup exercise. When executive sponsors make FinOps visible, it gets the attention and resources it needs to succeed.
Bring real examples to leadership. Show how small configuration changes in Azure have reduced costs. Share the potential business impact if FinOps were adopted consistently. Emphasize its impact on margins, forecasting accuracy, and financial agility. Without this framing, most efforts get stuck at the team level with no long-term traction.
Standardize tags and cost reporting early
Tagging is the foundation for visibility. If teams cannot tag resources consistently, cost allocation fails. Define a tagging schema that includes business units, environments, owners, and workloads. Enforce it through Azure Policy or infrastructure as code.
Then, build standardized cost views. Use Azure Cost Management or external tools to create dashboards that map costs to teams and services. Make reporting a routine, not a reaction to budget overages.
Make engineers cost-aware from day one
Engineering teams have the most control over cloud usage, but in many cases they operate without cost visibility. This gap creates inefficiencies that go unnoticed for months. The solution is to bring cost education into engineering workflows.
This starts with training. Engineers need to understand how Azure services are priced, what triggers additional charges, and how to make cost-informed architectural decisions. Use specific examples, such as VM families, storage tiers, and Azure SQL configurations to make the impact real.
Then integrate spend insights into their tools. If they work in Azure DevOps, make tracking development costs part of the review process for releases. If they manage infrastructure through code, ensure that there is governance, and IaC templates (e.g., Terraform) reflect cost-optimized defaults.
Promote certification across teams
FinOps certifications help establish a shared baseline of knowledge. Encourage certification not only for platform engineers, but also for finance stakeholders, product owners, and procurement leads. Certifications also signal that cloud cost ownership is a professional responsibility, not a nice-to-have skill.
Address language gaps between teams
Finance speaks in budgets and forecasts. Engineering speaks in throughput, latency, and availability. FinOps helps bridge this communication gap, but only if teams work from a shared vocabulary.
Terms such as utilization, coverage, unit cost, and Effective Savings Rate, must be understood by everyone involved. Without this shared language, finance teams cannot interpret usage reports, and engineering teams cannot prioritize cost-related work.
Standardize terminology in documentation, reporting, and reviews to reduce confusion and make conversations more productive.
Connect cost to business outcomes
Cost conversations gain traction when they are framed around impact. Help teams understand how reducing Azure waste contributes to product margin, customer profitability, or improved forecasting accuracy.
Avoid talking only in dollars. Use outcome-based metrics (e.g., cost per transaction, cost per API call, or cost per region) to make spend relatable and actionable.
Introduce FinOps reviews into regular cadence
Embed cloud cost accountability into existing processes. Whether it is a platform sync, a sprint retrospective, or a quarterly business review, make cost a standing agenda item. Use it to review top cost drivers, missed commitments, or untagged resources.
This approach normalizes cost as an engineering and business responsibility rather than a separate finance concern.
Practical Execution: Putting Azure FinOps into Action
Once the foundational elements are in place, the next step is execution. This means turning shared goals into concrete workflows that help your teams identify waste, optimize resources, and scale cost control across Azure environments.
Here’s how to get started:
Analyze your azure spend baseline
Use Azure Cost Management and similar visibility tools to build a clear picture of your current spend. Break it down by service, region, environment, and team. Pay attention to areas with rapid growth, inconsistent tagging, or unallocated costs.
Do not rely only on monthly billing summaries. Go deeper. Look at historical usage trends and identify which services are contributing most to volatility or unexpected spend spikes.
Prioritize cost drivers and high-impact fixes
Focus first on services with the most financial impact. These often include virtual machines, databases, and storage. Look for consistently underutilized compute instances, overprovisioned PaaS configurations, or high-performance storage where standard tiers would suffice.
Use Azure Advisor and Azure Monitor Metrics Explorer to validate underuse of provisioned resources. Flag workloads that are using peak configurations without corresponding demand, and coordinate with engineering to reduce size or scale dynamically.
Layer in usage optimization
Once immediate waste is cleaned up, the next priority is improving how resources are used over time. Usage optimization is about making sure what is running is aligned to actual demand.
Start with continuous rightsizing. Review compute instances, container resources, and PaaS configurations to identify services that are consistently underutilized. Use real usage data over time and not just peak snapshots, to decide where to downsize.
Then implement autoscaling wherever possible. Workloads with variable demand should not be running on fixed capacity. Scale sets, containers, and even serverless functions can respond to traffic patterns more efficiently than static infrastructure.
Finally, make usage optimization a recurring part of engineering workflows. Bring it into sprint reviews, deployment planning, or platform syncs.
Introduce Reservation and Savings Plan coverage gradually
Do not rush into large commitments. Start by identifying steady-state workloads that run 24/7 with predictable usage. Use this data to purchase conservative one-year Reservations or Savings Plans. Set these commitments to “float” to maximize savings and broaden coverage across subscriptions and resource groups.
Monitor coverage, utilization and Effective Savings Rate (ESR) monthly. Increase commitments only when usage patterns are proven and stable. If you see underutilization, exchange or cancel the commitments where applicable instead of letting them go to waste.
Track FinOps metrics consistently
Visibility is only useful if it leads to action. Define core FinOps KPIs that reflect the effectiveness of your FinOps efforts. These may include cost per business unit, utilization rates, and total identified waste.
Review these metrics on a fixed cadence. Share them across both technical and business teams so progress is visible and shared.
Automate for scale and speed
Manual workflows do not scale with large or dynamic Azure environments. Use automation to shut down idle non-production workloads after hours. Enable anomaly detection alerts for spend spikes. Automation keeps cost management from being delayed, forgotten, or dependent on a single team’s availability. It moves FinOps from intention to habit and accelerates its maturity.
Implement governance policies and guardrails
As cloud usage grows, so does the risk of misconfigured resources, overprovisioning, and inconsistent practices. Governance policies help prevent these issues before they happen. They create boundaries that guide teams toward cost-efficient choices without slowing down delivery.
Start by defining cost-conscious defaults. This could include limiting the use of premium SKUs in development environments, enforcing naming and tagging policies, or restricting resource creation to approved regions.
Then implement guardrails to detect and block non-compliant configurations. Use policy engines/tools to require cost-related tags, enquire deployments that exceed size thresholds, or flag resources without expiration dates.
These controls do not replace trust in engineering teams. They provide structure that allows teams to move quickly while staying within responsible financial limits. Well-defined guardrails reduce the need for reactive cleanup and make cost accountability part of the development process.
Review, report, and iterate regularly
FinOps is a continuous iterative cycle that your business should maintain over time. Make it a regular practice to meet with each of your stakeholders to review cloud spending and track the progress of all your strategic goals.
Use these regular meetings to discuss findings from issues (e.g., budget overruns or inefficient resource usage) and provide direct feedback to each department on how they can improve. This continuous loop of “review, report, and iterate” is what ensures your FinOps practice evolves and continues to deliver maximum business value as you grow.
Azure Native Tools That Support FinOps
Azure provides a number of built-in tools that help teams monitor spend, analyze usage, and identify savings opportunities. While third-party platforms can add granular value, these native services offer a strong foundation for FinOps practices, especially when configured intentionally and used consistently.
Azure Cost Management
This is the core tool for monitoring, forecasting, and reporting on Azure spend. Azure Cost Management suite allows teams to break down costs by subscription, resource group, tag, or service. Budgets and alerts can be set at different levels to track usage against targets. This also supports export of cost and usage data for more detailed analysis.
Azure Advisor
Azure Advisor provides cost optimization recommendations across compute, storage, networking, and databases. It flags underutilized resources, overprovisioned VMs, and idle services that can be cleaned up or resized. While not always exhaustive, it serves as a solid starting point for identifying easy wins.
Azure Reservations and Savings Plan Console
This interface allows teams to view, purchase, and manage Reservations and Savings Plans. It provides recommendations based on historical usage and shows current coverage and utilization rates. FinOps teams should review this data regularly to avoid overcommitment or underutilization.
Azure Policy
Azure Policy helps enforce governance at scale. It allows you to define and apply rules, such as required tagging, approved VM sizes, storage tier restrictions, and location controls. Policies can be configured to audit, deny, or modify non-compliant deployments. This is essential for maintaining cost hygiene across large or fast-changing environments.
Azure Budgets
The Budgets feature by Microsoft Azure allows teams to set spend thresholds for subscriptions, resource groups, or services. Alerts can be triggered when spend approaches or exceeds a defined limit. While budgets do not block usage, they provide early signals that help teams take corrective action before overspending occurs.
Cost Anomaly Detection
Azure offers basic anomaly detection that can flag sudden spikes in usage or cost at the subscription or service level. These alerts help FinOps teams investigate and resolve unexpected changes before they turn into budget overruns.
Azure Pricing Calculator
The pricing calculator helps estimate the cost of new workloads before deployment. It is especially useful for planning multi-region or hybrid architectures, modeling storage needs, or understanding the price implications of service tiers and configurations.
Improve Your Azure Cost Optimization Efforts With ProsperOps
Managing Azure costs manually is complex, time-consuming, and prone to inefficiencies. While Azure provides native cost management tools, they often require constant monitoring, manual intervention, and deep expertise to extract maximum savings.
Especially when it comes to commitment management, Azure provides recommendations for Savings Plans and Reservations but not automatic execution on them. Organizations also need to be able to allocate their costs and savings across teams internally. When commitments are set to “Shared” scope, there’s no telling which of the eligible resources will receive the savings benefit from commitments.
ProsperOps solves these challenges and helps businesses automate cloud cost optimization, eliminate waste, and maximize savings, ensuring that every cloud dollar is spent effectively.
ProsperOps delivers cloud savings-as-a-service by automatically creating a portfolio of commitments to maximize your savings and flexibility while lowering Commitment Lock-in Risk. Using our Autonomous Discount Management platform, we optimize the hyperscaler’s native discount instruments to reduce your cloud spend and help you achieve 45% ESR or more, placing you in the top 5% of FinOps teams.
Additionally, ProsperOps’ Intelligent Showback works alongside ADM to automatically reallocate commitment costs and savings monthly, saving you time from back-and-forths with finance/accounting and allowing you to close the books effectively.
Make the most of your cloud spend across AWS, Azure, and Google Cloud with ProsperOps. Schedule your free demo today!
