It’d be nice if you could simply look at your monthly cloud bill and think “Hmm, that looks about right”. But that seems like a bit of a risk these days. 

As your Azure environment grows alongside your business, the risk of costs spiralling out of control also rises. 

But there are plenty of ways to bring your spending down and stop things getting out of control. You can make use of Azure’s toolkit of cost optimisation features to save money without losing performance. 

In this guide, we’ll look into Azure’s suite of cost optimisation tools. You’ll learn not just how they work, but more importantly, when and how to use them effectively. 

Many organisations find themselves paying more than necessary for their Azure services, not because they lack cost management tools, but because they’re not using the right combinations of tools for their specific scenarios. 

Different scenarios demand different approaches: 

• Steady, predictable workloads benefit most from commitment-based discounts 

• Variable workloads require a mix of flexible pricing options and careful capacity planning 

• Dev/test environments need different optimisation strategies than production 

• Specialised services like Azure Virtual Desktop have their own unique cost considerations 

Modern Azure environments typically involve more than one of these scenarios. So, it makes sense to combine different tools and approaches. 

We’ll tell you how, but first, let’s get the basics sorted. Here’s what each of Azure’s core cost optimisation tools actually does:

Now let’s take a closer look at how each option works.

At its core, Azure Cost Management serves as your central hub for understanding and controlling cloud spending.

While other tools focus on specific types of savings, Cost Management provides the visibility and insights you need to make informed decisions about your entire Azure estate. But it’s not without its complexities.

While the basic features are straightforward, getting the most out of Cost Management takes a bit of know-how.

What the tool does

Cost Management truly shines in several areas that make it indispensable for Azure governance:

Real-time cost visibility: The platform provides near real-time cost tracking across your entire Azure estate. This immediate visibility helps you catch unexpected spending spikes before they become significant issues. You can track spending patterns and identify anomalies. It can help you understand cost drivers across different subscriptions and resource groups.

Budget management and alerts: The budgeting features go beyond simple threshold tracking. You can set up sophisticated alert conditions based on various metrics and trends. So, for instance, you might want alerts when spending exceeds historical patterns, not just when it hits a fixed threshold.

Cost allocation info: For enterprises managing multiple departments or clients, the cost allocation features are invaluable. You can create detailed reports showing resource consumption and costs by department, project, or any other custom tags you’ve implemented.

Limitations to consider

Data latency: While basic costs update quickly, some metrics have longer refresh cycles. Understanding these latency periods is crucial for accurate reporting and decision-making. Some cost data might take 24-72 hours to fully reflect in your reports.

Complex pricing integration: Cost Management doesn’t always immediately reflect new pricing benefits from tools like Reserved Instances or Savings Plans. You’ll need to account for this when analysing cost data during transitions between pricing models.

Resource-specific blind spots: Some Azure services have limited cost visibility in Cost Management. For example, detailed cost breakdowns for certain PaaS services might require additional tools or manual analysis.

Getting the most from Cost Management

To maximise the value of Cost Management, we recommend customising it to your use cases:

Tagging strategy: Implement a comprehensive tagging strategy from the start — this will enable sophisticated cost analysis and allocation. Your tags should reflect your business structure and reporting needs.

Custom views and dashboards: Don’t rely solely on default views. Create custom dashboards that highlight the metrics most relevant to your organisation. This might include trending data for specific resource types or cost comparisons across environments.

Automation integration: Why not connect Cost Management with your automation workflows? You can trigger Azure Automation runbooks based on cost alerts, automatically scaling down resources when spending exceeds thresholds.

Integration with other tools

Cost Management works best when integrated with other Azure cost optimisation tools. For example:

• Use insights from Cost Management to inform Reserved Instance purchases
• Combine cost data with Azure Advisor recommendations for targeted optimisation
• Feed cost metrics into your DevOps pipelines for cost-aware deployment decisions

You should think of Cost Management as your central source of truth and use it alongside other tools for specific optimisation tasks. This approach gives you both the big picture and the detailed control you need for effective cost governance.

While Cost Management helps you understand your spending patterns, Azure Advisor takes a more proactive approach by giving specific recommendations to optimise your Azure environment. It’s essentially Microsoft’s built-in consultant that analyses your Azure usage and provides actionable insights across multiple dimensions. 

What it does 

Azure Advisor is a wide-ranging analysis tool that provides recommendations in five key areas: 

Cost recommendations: This is where Advisor really shines for cost optimisation. It identifies idle and underutilised resources, suggests right-sizing for VMs and other services, and recommends commitment options like Reserved Instances when they make sense for your usage patterns. 

Performance recommendations: As it identifies bottlenecks and suggests configuration improvements, Advisor helps you get the most out of what you’re already paying for. Better performance from existing resources means less need to scale up and incur additional costs. 

High availability recommendations: Advisor helps make sure your services stay available without unnecessary redundancy costs, finding that sweet spot between reliability and budget. 

Security recommendations: While primarily focused on protecting your environment, security recommendations can also prevent costly incidents and compliance issues down the line. 

Operational excellence recommendations: These are tips on ‘best practice’ that you should consider implementing ASAP. They help streamline your operations and reduce the management overhead associated with your Azure resources. 

Limitations to consider 

Recommendation lag: Advisor analyses usage patterns over time, so it can take several days or weeks of consistent usage before it generates certain recommendations. 

Implementation complexities: While Advisor spots great opportunities for optimisation, implementing some of its recommendations can sometimes require significant changes to your architecture or operations. 

Contextual awareness: Advisor doesn’t always understand the business context of your resources. A seemingly “idle” resource might actually be critical for disaster recovery or periodic processing, for example. It’s smart, but not all-knowing; there are some areas you still need human oversight in. 

Getting the most from Azure Advisor 

If you want to reap the benefits of Azure Advisor, you’ll want to consider following these best practices: 

Regular review schedule: Set up a routine (weekly or bi-weekly) to review and act on Advisor recommendations. It’s easy to check for new recommendations but fail to implement them consistently. Data is just the beginning—you have to take action! 

Prioritisation framework: Figure out a method for evaluating and prioritising recommendations. Think about factors like potential savings, the effort it’s going to take to implement them, and the potential business impacts. 

Delegation system: Assign specific recommendation categories to the appropriate teams in your organisation. Cost recommendations might go to finance or procurement, while performance recommendations go to technical teams.

Automation where possible: Get the machines to help you when it’s appropriate. You can use Azure PowerShell or Azure CLI to get certain recommendations done automatically, especially for repetitive tasks like shutting down idle VMs. 

While both Cost Management and Advisor help you understand and optimise your spending, Azure Monitor provides the performance context needed to make informed decisions about resource allocation. 

Proper monitoring is essential for cost optimisation because it helps you understand exactly which resources you need—no more, no less. 

What it does 

Azure Monitor collects, analyses, and acts on telemetry data from your Azure and on-premises environments: 

Resource utilisation tracking: Monitor gives you detailed metrics on CPU, memory, disk, and network usage across your Azure resources. These insights help identify overprovisioned resources that can be downsized without impacting performance. 

Application performance insights: Through Application Insights, Monitor helps you understand how your apps are performing and being used. This information is crucial for right-sizing application resources based on actual usage patterns. 

Log analytics: The ability to query and analyse logs helps identify patterns, troubleshoot issues, and understand resource usage over time, contributing to more accurate capacity planning. 

Alerting capabilities: With proactive alerts about unusual resource usage patterns or capacity limits you’re about to hit, Monitor helps you address potential issues before they lead to unnecessary spending or performance problems.

Drawbacks of Azure Monitor 

Data retention costs: Storing monitoring data, especially at scale, can become expensive. You’ll need to balance detailed monitoring with cost-effective retention policies. 

Configuration complexity: Setting up a really comprehensive monitoring system across a complex environment will definitely take some careful planning and expertise. It’s possible to either under-monitor or collect too much data without a clear strategy. 

Analysis overhead: The wealth of data that Monitor gives you needs proper analysis to be truly useful. Without dedicated time and expertise to interpret this data, its value for cost optimisation diminishes. 

Getting the most out of Azure Monitor 

If you want Azure Monitor to really impact your cost optimisation positively, you’ll want to: 

Focus on cost-relevant metrics: Identify and track the metrics most relevant to your spending, like resource utilisation rates, idle times, and usage patterns. 

Establish utilisation baselines: Define what “normal” looks like for your workloads so you can identify both underutilised resources (candidates for downsizing) and overutilised resources (which are potential performance risks). 

Configure meaningful alerts: Set up alerts for conditions that actually have cost implications, like sustained low CPU utilisation on expensive VMs or unexpected increases in data storage or transfer. 

Use autoscaling smartly: Combine Monitor insights with Azure’s autoscaling capabilities to automatically adjust resources based on actual demand, paying only for what you need when you need it. 

Integrate with Cost Management: Correlate performance data from Monitor with spending data from Cost Management to get a complete picture of your cost-performance balance. 

Real-world examples 

Here are a few examples of how Azure Monitor could drive tangible cost savings: 

• Identifying VMs with consistently low CPU utilisation (under 10% for weeks) that are candidates for downsizing or consolidation 

• Detecting test environments that are active outside business hours when they could be automatically shut down 

• Spotting unnecessary premium storage usage for workloads that don’t require high IOPS 

• Recognising network traffic patterns that could be optimised to reduce egress charges 

As it provides the performance context behind your spending, Azure Monitor helps make sure you’re not cutting costs at the expense of user experience or business outcomes. 

While the above tools mostly help you understand current spending, the Azure Pricing Calculator is your tool for looking ahead. It’s a free web-based calculator that helps you estimate the costs of cloud resources before using them. 

As we detail in our guide to the Azure Pricing Calculator, you can get pretty accurate estimates, but again it’s something that requires a bit of patience and understanding. 

What’s so good about the Pricing Calculator? 

• Comprehensive service coverage: The calculator covers virtually every Azure service, including recent additions and preview features. This makes it invaluable for planning new deployments or estimating the cost of architectural changes. 

• Commitment integration: It can factor in Reserved Instances and Savings Plans, helping you understand the potential impact of different commitment options before making purchasing decisions. 

• Scenario modelling: The ability to save and share estimates makes it excellent for comparing different architectural approaches or creating budgets for new projects. 

It’s a no-commitment service that you can play with as much as you want. You can build your dream setup with all the bells and whistles you could ever need, or try to make a budget-friendly implementation that doesn’t break the bank. 

Where the calculator falls short 

Despite its utility, the Pricing Calculator has several limitations you need to account for: 

Static pricing only: The calculator provides point-in-time estimates. It doesn’t account for dynamic pricing changes or spot instance variations. 

Limited real-world factors: It’s not great at estimating many real-world considerations like the below (without manual intervention): 

• Network egress patterns 

• Storage transaction volumes 

• Backup and disaster recovery overhead 

• Management and monitoring costs 

No performance metrics: While it can tell you the cost of different VM sizes, it can’t help you determine which size your workload actually needs. That’s up to you to figure out. 

Making the most of the calculator 

To get the most accurate estimates from the Pricing Calculator, you’ve got to feed it good data. 

1) Start with real data: Use your existing Cost Management data to understand typical usage patterns before making estimates. 

2) Add buffer capacity: Include a margin for unexpected growth and overhead costs. You might consider adding 15-20% to calculator estimates. 

3) Consider the full stack: Remember to include all components you might want to have: 

• Supporting services like backup and monitoring 

• Network costs, especially egress traffic 

• Storage operations and capacity 

• Management tools and extensions 

4) Document assumptions: Keep clear records of the assumptions behind your estimates. This helps with future planning and explains any variances. 

Combining tools for better planning 

The Pricing Calculator works best when used alongside other tools. 

You can always use Cost Management data to validate calculator estimates—compare calculator predictions with your actual costs to refine the estimation process. 

Don’t forget — the calculator is a planning tool, not a budgeting system. Its estimates should be the starting point for discussion, not the final word on projected costs. 

You can also factor in recommendations from Azure Advisor when building estimates, too. 

So, we’ve looked at the tools. You’ve got help with future planning, real-time analysis, and historical data. You’ve also got powerful monitoring and advisory tools that can bring down costs dramatically. 

What else can you do to lower your Azure costs? 

Well, there’s a whole world of tinkering you can get into, depending on what you’re doing. Different workload types demand different cost optimisation approaches. 

Rather than go through every scenario, we’ll give you examples of two common workloads (virtual desktop and data analytics) to show you where costs can be lowered. 

Also see our full guide to Azure cost optimisation which goes into much more detail on how to save money in Azure.

Azure Virtual Desktop: balancing performance and cost 

AVD presents unique cost optimisation challenges due to its usage patterns and resource requirements. As detailed in our guide to Azure Virtual Desktop costs, there are five major factors driving up costs that you should pay attention to. 

Session host optimisation forms the foundation of AVD cost management. The compute costs for your VMs are typically the largest contributor to your overall AVD expenses. The key lies in finding the right balance between performance and cost-efficiency by carefully choosing VM sizes that match your user workloads. We’ve found that many organisations over-provision their session hosts, leading to unnecessary costs that could be avoided with proper sizing. 

Scaling plans are equally important, yet often overlooked. Without proper scaling plans, session hosts can run 24/7 even when nobody’s using them. Using smart start/stop schedules based on actual usage patterns can dramatically reduce costs while maintaining availability during peak hours. 

Storage costs often surprise organisations implementing AVD too, particularly related to FSLogix profile management. Profile containers, user data, and temporary storage all need careful consideration. We recommend implementing a tiered storage strategy, excluding unnecessary files from profiles, and regularly cleaning up profiles of former employees to keep costs in check. 

Two additional factors frequently impact AVD costs: image bloat and management overhead. Each time you update your AVD images, older versions can accumulate in your Azure Compute Gallery, driving up storage costs if not regularly pruned. Meanwhile, the ongoing management of AVD environments requires expertise that, if lacking, can lead to inefficiencies and higher operational costs. 

Data and analytics workloads 

Data and analytics services often represent a big portion of Azure spending, with costs that can grow unpredictably if you don’t properly manage them. Storage volumes increase continuously, while complex analytics workloads can consume substantial compute resources. 

• Storage tier optimisation – Azure offers multiple storage tiers with varying costs and access speeds. Implementing automated lifecycle management policies to move infrequently accessed data to cooler tiers can significantly reduce costs without sacrificing functionality. 

• Query and processing efficiency – Poorly optimised queries in services like Synapse Analytics, Databricks, or Data Factory can consume excessive resources. Regular performance reviews and query optimization can reduce processing time and associated costs. 

• Right-sizing analytics clusters – Many organisations maintain unnecessarily large Spark clusters or Synapse SQL pools. Implementing auto-scaling based on actual workload demands and scheduling cluster shutdowns during inactive periods can deliver substantial savings. 

When working with data lakes and warehouses, think about implementing data retention policies that automatically archive or delete data based on business requirements and compliance needs. This stops the continuous growth of storage costs while still giving teams access to business-critical information. 

General workload optimisation 

Beyond specific scenarios like AVD, effective cost optimisation benefits from a systematic approach to resource management. In short: be organised, and don’t forget to check things regularly. 

As outlined in our strategies for reducing cloud costs, the best results come from a mix of automated management with regular human oversight. 

Three major factors consistently contribute to unnecessary spending: 

• Skills gaps – The technical complexity of Azure means organisations without specialised expertise often overlook hidden costs or configure environments inefficiently. Addressing this might mean investing in training, hiring specialists, or partnering with an expert MSP. 

• Overprovisioning – Many businesses migrate to the cloud by simply copying their on-premises infrastructure without optimisation. Modern cloud resources are often more powerful than legacy hardware, meaning you could achieve the same performance with smaller, more cost-effective resources. 

• Idle resources – VMs, disks, and other services that are no longer actively used but still running silently drain budgets. Implementing proper governance with tagging, naming conventions, and automated policies is essential to prevent this waste. 

When these are addressed, you have the opportunity to lower costs dramatically. 

As your cloud environment evolves, so should your cost strategy. Ask yourself: 

• Are you actively monitoring how your cloud use is changing? 

• When did you last review your Azure Advisor recommendations? 

• Is your team equipped with the right skills and information? 

This process isn’t a one-off; it’s a continuous practice. So, keep reviewing your setup and checking those bills. 

One thing to note is that Microsoft’s own tools for cost-saving recommendations might not be the most impartial source of buying information. 

That’s not to say they’re untrustworthy, but it’s in their best interests to maximise your bills, so you might want to look elsewhere occasionally. You could always seek advice from a trusted partner. One with a deep understanding of keeping costs low and performance high in Azure. 

That sounds awfully familiar… 

Synextra’s team of cloud specialists combine deep technical expertise with practical experience in running cost-effective Azure solutions. We can help you make the most of Azure pricing tools with a sensible, no-nonsense strategy. You’ll end up with real savings alongside supporting your business objectives. 

Get in touch to discuss how we can help you optimise your Azure costs effectively.