Nearly 95% of companies are now using the cloud in some form.1 And according to Flexera’s 2025 State of the Cloud report, 84% of technical professionals and executives say managing cloud spend is their top challenge.
With spending expected to increase by 28% this year, reducing unnecessary cloud costs has become a critical priority.
But when companies talk about reducing cloud spend, two terms are often used interchangeably: cloud cost monitoring and cloud cost optimization.
While closely related, these are two distinct processes with different goals, tools, and outcomes. Failing to understand the difference can lead to missed savings, inefficiencies, and frustration across DevOps, Finance, and Engineering teams.
In this article, we’ll break down the key differences between monitoring and optimization, why both are necessary, and how you can use them together to build a smarter, more cost-effective cloud strategy.
What Is Cloud Cost Monitoring and Why Does It Matter
Cloud cost monitoring is the process of tracking and visualizing your cloud usage and spending over time. It helps you understand what services you’re paying for, how much you’re using them, and where potential overspend or anomalies might be happening.
At its core, monitoring is about visibility and awareness. You’re not necessarily acting on the data; you’re collecting and analyzing it to identify patterns.
Common Features of Cloud Cost Monitoring Tools:
- Usage breakdown by service, region, or project
- Budget alerts and anomaly detection
- Forecasting based on historical usage
- Reports for finance or business teams
Examples of Monitoring Tools:
- Amazon CloudWatch (AWS Cost Explorer)
- Azure Cost Management + Billing
- Google Cloud Billing Reports (Google Cloud Observability)
- Kubecost
- CloudZero
- Datadog
Monitoring is foundational to understanding cloud usage, but it’s not enough on its own to drive cost reduction. That’s where optimization comes in.
What is Cloud Cost Optimization?
Cloud cost optimization goes a step further – it’s about actively reducing cloud spend without compromising on performance or scalability. Optimization is where the real savings can happen.
Instead of just observing usage, optimization involves analyzing and adjusting workloads, configurations, and pricing models to achieve efficiency.
Cloud cost optimization often overlaps with terms like FinOps, cloud financial management, or cost reduction, but the goal is the same: spend smarter without sacrificing performance.
Optimization also includes proactive governance policies, developer guidelines, and automation scripts to continuously improve cost efficiency.
Common Optimization Strategies:
- Rightsizing overprovisioned resources
- Autoscaling based on real demand
- Scheduling non-production environments to shut down during off-hours
- Switching to reserved or spot pricing where appropriate
- Removing orphaned or unused resources
- Tiering storage based on access needs
- Using serverless computing to reduce infrastructure costs
- Optimizing content delivery (e.g., using a CDN)
- Aligning pricing models with predictable usage
- Leveraging automation to clean up unused environments and reduce waste
- Considering region-based deployments for performance and efficiency
Tools for Optimization:
- Apptio Cloudability
- Spot.io
- Yotascale
- Custom scripts or AI-based tools integrated into CI/CD pipelines
Key Differences Between Monitoring and Optimization
| Feature/Goal | Cloud Cost Monitoring | Cloud Cost Optimization |
| Primary Purpose | Visibility and awareness | Efficiency and cost reduction |
| When It's Used | Ongoing, passive tracking | After identifying opportunities |
| Tools Used | Native cloud billing tools | Optimization platforms or scripts |
| Who Uses It | Finance, DevOps, Operations | DevOps, Engineers, FinOps |
| Example Activity | Viewing monthly billing reports | Rightsizing EC2 instances |
Why Monitoring and Optimization Work Better Together
One without the other leaves a major gap. Monitoring gives you insight, but no savings. Optimization gives you savings, but without monitoring, you won’t know where to start or how effective your efforts are.
A modern FinOps strategy relies on both:
- Monitoring identifies overspend or inefficiencies
- Optimization fixes them
Together, they help align engineering, finance, and product teams around a common goal: maximizing business value from every cloud dollar spent.
One Softjourn client in the expense management space used continuous cloud cost monitoring to pinpoint inefficiencies in their AWS usage.
After identifying idle resources and performance bottlenecks, our DevOps team implemented automation, right-sizing, and strategic reserved instance commitments – ultimately reducing AWS spend by nearly 40% and saving over $25,000 annually without compromising system performance or security.
In another case, Cinewav, a growing ticketing startup, partnered with Softjourn to improve global performance while keeping cloud costs under control.
By combining continuous monitoring with targeted optimization, such as multi-regional deployments, CDN tuning, and smart auto-scaling, our team helped Cinewav improve performance for users worldwide and reduce their AWS runtime costs by 30%.
This balanced approach ensured Cinewav could scale efficiently during high-demand events without overpaying during quieter periods.
Common Pitfalls of Using One Without the Other
As a FinOps consultant, we often see companies that focus only on monitoring fall into what we call “dashboard paralysis” — spending valuable time reviewing charts, alerts, and cost breakdowns, but failing to take meaningful action.
Visibility is important, but without a clear optimization strategy, teams end up observing problems instead of solving them. It’s like watching your car’s fuel gauge dip lower every day but never adjusting how or when you drive.
On the other hand, jumping straight into optimization without proper monitoring can lead to costly missteps. Without accurate data, teams risk rightsizing the wrong workloads, under-provisioning critical systems, or blindly applying cost-saving tactics that jeopardize performance.
Even worse, they lose visibility into long-term usage trends, making it difficult to assess whether changes are truly effective or just reactive.
Both monitoring and optimization are needed to prevent waste, maintain performance, and make confident decisions.
Essential Metrics and Tools to Track Both
Here are a few important metrics we like to track for monitoring and optimizing effectively:
- Cost per workload or service
- Reserved instance and spot instance coverage
- Uptime vs. idle time
- CDN hit/miss ratio and cache effectiveness
- Network and data transfer costs
- Orphaned resources count
- Storage costs by tier
- Autoscaling activity and scaling lag
To measure and manage these, consider combining native tools (AWS, Azure, GCP) with FinOps-friendly dashboards or automated optimization engines.
That level of tracking can be essential for companies struggling with cloud waste, and – unfortunately – cloud waste is a growing concern for nearly every organization.
According to Stacklet’s 2024 State of Cloud Usage Optimization survey, 78% of enterprises estimate that at least a quarter of their cloud spend is wasted, revealing major opportunities for cost savings. Manual processes and growing AI complexity are driving preventable errors, with 15% of companies losing over $75,000 per month.
Additionally, AI isn’t necessarily going to save us: 82% of the same surveyors say AI is increasing cloud complexity and costs, with nearly half admitting they aren’t optimizing their AI-related cloud usage effectively.
And while many companies invest heavily in cloud infrastructure, nearly half struggle to control costs due to overprovisioning, poor scalability, and a lack of visibility across multi-cloud environments.
Metrics like spot instance utilization, API throttling, CDN cache efficiency, and Lambda error rates are often overlooked, but they’re exactly where the hidden inefficiencies live.
Final Thoughts: Building a Cost-Conscious Cloud Culture
As organizations mature in their cloud journeys, cost control becomes a shared responsibility, not just a task for finance or DevOps teams. Encouraging engineers to think about cost, setting usage alerts, running regular audits, and aligning on budgets all contribute to building a truly cost-aware culture.
If you take one thing away from this article, remember: cloud cost monitoring and optimization aren’t competing approaches; they’re two sides of the same coin.
Doing one without the other means you’re likely leaving money on the table. That’s where Softjourn’s cloud experts come in.
We work alongside your teams to turn cloud insights into meaningful savings – without sacrificing performance, security, or scalability.
Let’s talk about how we can help you get more from your cloud while cutting costs along the way.
TL;DR: Monitoring tells you what’s happening. Optimization tells you what to do about it. Softjourn can help you with both.
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