6 cloud cost optimization strategies and tools for AWS, Azure, and GCP

One of the largest challenges of cloud is optimizing the cost. If you don’t keep costs under control, they can skyrocket. (And no one wants to get called into a meeting with the finance team or CFO to discuss out-of-control cloud spending.) 

That’s why it’s best to get in front of cloud costs and optimize them from the start. In this article, we look at ways to manage cloud costs for the three major cloud service providers: Azure, AWS, and GCP.

If you don’t optimize your cloud costs upfront, it can lead to numerous problems with real impact:

• Runaway costs. Without guardrails or budgeting, costs can spiral out of control fast.
• Blown budgets and missed KPIs. Projects may go over budget and put your "cloud-first" strategy under fire.
• Increased risk of service suspension. In many cases (especially with startups or teams with usage limits), unpaid bills or overages can lead to services being paused or throttled.
• Resource sprawl and wasted resources. You may end up paying for unused compute, storage, and networking resources that provide no business value.
• Reduced agility. Cloud overspend can lead to overly strict policies to course correct.
• Slower time-to-market. Teams may be overly cautious about spinning up resources because of unpredictable costs. 
• Competitive disadvantage. Cloud inefficiencies can cause you to pay 2–3x more than competitors for the same capabilities. 
• Eroded executive confidence. When costs consistently exceed projections without corresponding business value, executives may lose trust in a cloud strategy. They start viewing cloud initiatives as money pits rather than strategic investments.

As you can see, not optimizing and controlling the cost of your cloud can lead to many consequences. The most dangerous aspect of unoptimized cloud costs is that they tend to stack up over time like compound interest. 

What starts as a small inefficiency becomes a massive drag on your organization's ability to compete and innovate. The longer you wait to fix these issues, the more costly and complicated the cleanup gets. This leads to technical debt. 

The key to successful cloud cost optimization is treating it like maintaining a garden. It requires regular attention, pruning, and adjustment rather than a set-it-and-forget-it approach. Start with the biggest cost drivers and lowest-hanging fruit, then gradually work your way through more complex optimizations.

Every major cloud services platform has unique tools and ways to help you optimize costs and performance. Let's explore some general strategies for optimizing your cloud costs. Then we'll look at specific strategies for each major cloud provider: AWS, Azure, and GCP.

Here are cloud-agnostic cost optimizations you can do:

Take inventory of your cloud resources to understand how you use them. If you’re underutilizing them, reduce the sizes. 

Use Azure Advisor to identify and resize underutilized VMs. If you use AWS, you can turn to Compute Optimizer or Trusted Advisor for right-sizing EC2, RDS, and Lambda functions. Using Google Cloud? Check out Recommender to adjust machine types or autoscaler settings for Compute Engine. 

Start optimizing your AWS services with Pluralsight’s Managing Compute Costs in AWS course.

Have you ever seen the TV show Hoarders? The same thing can happen in the cloud. 

Teams spin up resources, but over time, people move on to other roles or companies. Unused virtual machines multiply like rabbits, abandoned databases stack up like old magazines, and storage grows like weeds in an untended garden. 

What’s left behind is a pile of abandoned infrastructure no one wants to touch in case they accidentally break something important. This kind of cloud sprawl is more common than you’d think. 

The solution? Keep thorough records. Regularly audit your environment, clean up what’s no longer needed, and spin down unused resources. Even better, automate the cleanup with scripts or policy as code tools like Terraform and scheduled cron jobs.

Storage is one of the most common culprits behind rising cloud costs. Many teams skip the planning phase and fail to choose the right storage tier for the task at hand. Over time, this leads to deserted resources with files sitting in expensive storage classes with no clear owner or purpose. 

A good first step is to educate your teams on the different storage tiers available and when to use each one. Establishing a clear policy for how to allocate storage is also important. For example, consider using an archive tier for data you must retain but don’t need to access frequently. These tiers cost significantly less than hot storage and are ideal for backups, compliance data, or old logs.

Speaking of logs, archive them aggressively. The same applies to any data that users rarely access. Below are some cloud specific tools that can help you automate and manage storage cost optimization:

• Azure: Use Blob Lifecycle Management to automatically tier data to Cool or Archive storage.
• AWS: Use S3 Lifecycle Policies and Intelligent Tiering to transition data to Glacier or Deep Archive.
• GCP: Use Object Lifecycle Management to move data from Standard to Nearline or Coldline.

Network traffic costs are like highway tolls. You might not notice a few dollars here and there, but take the wrong route repeatedly and you'll end up paying for a luxury car with toll fees alone.

Network egress charges are one of those "death by a thousand cuts" expenses that can quietly devour your cloud budget. Data transfer costs between regions, availability zones, and to the internet can add up faster than parking meters in downtown Manhattan.

That’s why it’s important to understand your cloud traffic patterns and architect your cloud infrastructure to minimize unnecessary traffic flow and data movement. Smart routing can conserve both time and resources. Here are some strategies to assist with this:

Data locality planning should be part of your initial architecture decisions. Store data close to where it's processed and consumed. If your application servers are in US-East but your database is in Europe, you're paying a premium for every query.

Compression and optimization can reduce the volume of data being transferred. Enable gzip compression for web content, optimize images and videos, and consider data deduplication for backup and archival workloads.

Performing traffic pattern analysis using tools like AWS Cost Explorer, Azure Cost Management, or GCP Cloud Billing can reveal unexpected data transfer patterns. Sometimes a misconfigured application or service is creating unnecessary network chatter. 

Content caching strategies use CDNs in your application but go beyond typical CDN capabilities. Implement application-level caching, database query caching, and API response caching to reduce the need for repeated data transfers.

You can also use the following tools across each of the clouds to optimize your traffic: 

• Azure: Use ExpressRoute or Traffic Manager for optimized routing.
• AWS: Consolidate data regions or use VPC Endpoints or Global Accelerator.
• GCP: Reduce egress by colocating services and using Private Google Access.

Each cloud provider offers what I like to call “cloud whisperer” tools. These are AI-powered services that analyze your environment and provide optimization recommendations. 

Microsoft Azure has Azure Advisor, AWS offers Compute Optimizer and Cost Anomaly Detection, and GCP provides the Recommender API and Active Assist tools. 

These aren't just nice-to-have features—these are your first line of defense against cloud cost creep. Make sure you regularly review and act on their recommendations. They’re there to help you tune your environment for peak efficiency.

Finally, it’s essential to stay on top of your cloud costs, unused resources, and network traffic patterns. This isn’t a one-time task. It demands continuous focus and regular attention. Regular monitoring helps you catch inefficiencies early and avoid surprises on your cloud bill.

Make sure to set up budgets and alerts to track spending and flag anomalies before they become problems. Each cloud provider offers native tools to support this, and there are also excellent third-party solutions available if you need more advanced insights.

Here are some native options from each cloud platform:

• Azure: Use Cost Management and Azure Monitor for real time insights and budget tracking.
• AWS: Use CloudWatch, Cost Explorer, and Budgets for forecasting and cost alerts.
• GCP: Use Billing Dashboards, Cloud Monitoring, and BigQuery exports for detailed analysis.

Here are some platform-specific cost optimizations that you can do: 

• Azure: Take advantage of Azure Hybrid Benefit if you have existing Windows Server licenses, and consider Azure Cost Management for detailed spending analytics.
• AWS: Leverage AWS Trusted Advisor for optimization recommendations and use AWS Cost Explorer to identify spending patterns and anomalies.
• GCP: Use sustained use discounts that automatically apply to long-running workloads. Also, think about Google’s per-second billing for saving money on shorter workloads.

I hope you found this article helpful and are leaving with practical strategies you can start using today to optimize your cloud costs. 

Now you have a toolkit of strategies to tackle cloud cost optimization across AWS, Azure, and GCP. Pick the approach that addresses your biggest pain point and start utilizing it today. Your budget will thank you!

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