How to Optimize Costs with Azure Savings Plan

Managing cloud expenses resembles managing your electricity bill; you might keep the lights on, but if the air conditioning runs all day, expect an inflated bill. Azure operates similarly. While you can scale, deploy, and innovate rapidly, failing to implement effective cost controls may lead to overspending.

If you currently utilise Azure or are considering expanding your cloud presence, Azure Savings Plans could be a game-changer for cutting your compute costs—but only if used effectively.

In this article, we’ll delve into what Azure Savings Plans entail, how to use them optimally, pitfalls to avoid, and how a tool like Turbo360 can help maximise every pound spent.

What is the Azure Savings Plan?

The Azure Savings Plan for Compute is a pricing strategy that allows you to commit to a fixed hourly expenditure on computing services in exchange for substantial discounts—up to 65% off standard pay-as-you-go prices.

This plan is particularly beneficial for workloads with predictable usage patterns. In contrast to Azure Reserved Instances (RIs), which are restricted to specific VM sizes and regions, Savings Plans provide flexibility. Your commitment automatically applies across eligible services, sizes, and regions.

Here’s a simplified explanation of how it works:

• You commit to an hourly spend (e.g., $20/hour).
• Azure monitors your use of qualifying services, such as VMs, App Services, and Containers.
• The discounted rate applies to your usage based on your commitment.
• Any usage exceeding the commitment will be charged at standard pay-as-you-go rates.

Eligible Resources Include:

• Virtual Machines (VMs)
• Azure App Services (Premium plans)
• Azure Container Instances
• Azure Functions (Premium plan)
• Dedicated Hosts

Important Note: Azure Savings Plans do not include storage, networking, databases, or other non-compute services.

Why Should You Consider Savings Plans?

Here’s what makes them appealing:

• Substantial savings of up to 65% based on commitment and duration
• Flexibility surpassing Reserved Instances (applicable across VMs, sizes, and regions)
• Streamlined management—no need to allocate specific workloads to reservations
• Enhanced coverage for dynamic environments that may shift or scale VM SKUs

However, keep in mind that you are making a financial commitment—doing due diligence before diving in is essential.

A Step-by-Step Guide to Optimising Azure Costs with Savings Plans

Let’s translate theory into practice with actionable steps to maximise your return on investment with this model.

1. Analyse Your Historical Usage

Prior to committing, ascertain:

• Your consistently used resources
• Your current hourly expenditure on compute
• Identifying 24/7 workloads versus burst workloads
• Usage trends over the past 30, 60, and 90 days

Utilise Azure Cost Management reports or third-party tools like Turbo360 for visual insights.

Tip: Focus on identifying patterns rather than solely peaks. Savings Plans reward consistent usage.

2. Establish Your Baseline Hourly Commitment

Once you comprehend usage trends, determine a safe minimum spend that consistently aligns with your environment. This will be your committed spend (e.g., $15/hour).

If your average cost is $25/hour, consider committing to $15–$20/hour to keep a buffer for burst or variable workloads.

Remember:

• Underutilisation = Waste. You’ll pay for your commitment even if unutilised.
• Overutilisation = Missed savings. Exceeding your plan will incur standard pay-as-you-go charges.

3. Decide Between 1-Year and 3-Year Terms

Azure provides two term options:

If your workloads are new or if your application architecture changes frequently, the 1-year plan is more accommodating. Conversely, if you’re managing production systems with little change, the 3-year plan offers maximum savings potential.

4. Understand Scope: Shared vs. Single Subscription

Azure allows your savings plan to be scoped in two ways:

• Single Subscription (savings apply solely within that subscription)
• Shared (savings apply across all eligible subscriptions under your billing account)

Tip: Opt for shared scope if you manage multiple subscriptions. It provides broader coverage and mitigates underutilisation.

5. Tag and Monitor Your Commitments

After activating your savings plan, ensure to:

• Track usage against commitment
• Identify which teams or applications are benefitting
• Monitor your plan’s return on investment

Implement Azure tags or cost management tools to keep this information visible, useful for internal chargebacks or showback models.

6. Use Spot VMs and Autoscaling for Fluctuating Workloads

While Savings Plans fit well with steady workloads, how do you handle unexpected traffic surges?

Employ this strategy:

• Utilise the Savings Plan for your stable workloads.
• Deploy Spot VMs or autoscale policies to accommodate spikes without unnecessary commitments.

This approach enables cost efficiency and flexibility simultaneously.

7. Regularly Review and Adjust

Even with an excellent plan, cloud workloads evolve.

Set up a quarterly or bi-annual review to:

• Evaluate changes in your usage patterns
• Adjust commitment levels as necessary (only applicable for new plans)
• Consider implementing multiple plans if your expenses rise over time

Note: Azure does not permit reductions or cancellations of savings plans once purchased. Therefore, regular reviews are imperative to prevent overspending.

Common Pitfalls to Avoid

Here are some practical mistakes to steer clear of:

• Overcommitting based on peak usage
• Committing to workloads that are set to be deprecated
• Disregarding multi-subscription scenarios and opting for single-scope plans
• Neglecting to monitor actual utilisation post-plan purchase
• Forgetting to factor in autoscaling behaviour in your forecasting

By avoiding these missteps, you’ll gain a significant advantage.

So… How Do You Know What to Commit To?

This is the million-pound question—or perhaps a few thousand pounds each month. Relying on manual checks of Azure usage, Excel modelling, and growth predictions can be tedious and prone to errors. This is where Turbo360 comes into play.

How Turbo360 Assists in Optimising Your Azure Savings Plan

Turbo360’s Cost Analyzer removes the guesswork from savings plan optimisation by providing in-depth insights into your cloud spending patterns, helping you plan your commitments more accurately.

Here’s how it aids you:

Identify Suitable Candidates for Savings Plan

Turbo360 analyses your historical usage trends to help determine which workloads are stable enough to commit to. You can filter by:

• Subscription
• Application
• Environment (production, development, etc.)
• Resource group or tag

Recommend Optimal Commitment Amount

Instead of estimating, Turbo360 suggests a commitment amount based on actual usage data. You’ll be informed if $30/hour or $20/hour better suits your baseline.

Monitor Utilisation & ROI in Real-Time

Utilisation tracking continues after your purchase. Turbo360 consistently monitors:

• Your commitment usage
• Where your savings are being applied
• Whether you’re approaching underutilisation or overuse

Receive Proactive Notifications

Get alerts if:

• Your plan is under-utilised
• You’re frequently approaching your limit
• New workloads qualify for savings plan coverage

Generate Reports for Financial Teams

The Cost Analyzer creates detailed, clear reports you can share with financial or leadership teams to justify your commitment decisions or plan for the future.

Final Thoughts

Azure Savings Plans stand out as one of the most effective tools for long-term cloud cost management, especially for teams managing predictable compute workloads. However, this strategy is only effective if you:

• Understand your usage
• Choose the correct commitment
• Continuously monitor and adjust

Turbo360 simplifies this entire process, making it smarter, quicker, and significantly less stressful. Its Cost Analyzer module allows for informed decision-making, minimises guesswork, and ensures your cloud budget is spent efficiently—without causing you sleepless nights.