As network engineers, you play a crucial role in managing cloud infrastructure that supports your organization’s applications and services. Cloud platforms offer immense flexibility and scalability, but without careful cost management, expenses can quickly spiral out of control. This article provides a comprehensive guide to cloud cost optimization tailored for network engineers, focusing on practical strategies and best practices to reduce cloud spending without sacrificing performance or reliability.
Key takeaways of the article:
- Visibility and governance are foundational: Before you can optimize cloud costs, you must first gain full visibility into your usage and establish strong governance policies. This includes setting clear tagging standards, enforcing usage limits, and using monitoring tools to track where money is being spent and why.
- Strategic deployment reduces long-term costs: Your choice between single-cloud, multi-cloud, or hybrid deployment impacts both performance and expenses. Plan deployments with cost-efficiency in mind—avoid vendor lock-in, optimize data transfers, and align infrastructure with your workload needs to prevent unnecessary spend.
- Automation and rightsizing are essential tactics: Avoid manual misconfigurations by automating scaling, shutdowns, and cost policies. Rightsize compute and storage resources regularly to match actual demand. Leverage autoscaling, scheduled scripts, and pricing models such as reserved instances (RIs) or savings plans for predictable workloads.
- Finance and operations teams (FinOps) alignment drives cost accountability: Cloud cost optimization isn’t just an engineering concern. FinOps teams play a critical role in aligning cloud spending with business value. Foster collaboration between finance, operations, and IT to track key performance indicators (KPIs), allocate costs, and continuously improve cloud return on investment (ROI).
What Is Cloud Cost Optimization?
Cloud cost optimization is the practice of continuously monitoring, managing, and refining your cloud resources to minimize expenses while maintaining service quality. For network engineers, this means designing and operating cloud networks that are cost-effective, scalable, and efficient. The pay-as-you-go model of cloud services can lead to unexpected charges if resources are overprovisioned or left idle, making proactive cost control essential.
Understanding Your Cloud Costs
Before optimizing costs, you must understand how cloud providers bill for their services. Cloud costs typically include compute, storage, data transfer, and network services charges, each with its distinct pricing model.
- Compute: Charged by instance type, size, and usage time
- Storage: Charged based on storage class and amount of data stored
- Data transfer: Costs for moving data in and out of cloud regions
- Networking: Charges for services such as network address translation gateways, virtual private cloud endpoints, and load balancers
Cloud providers offer billing dashboards and cost explorers that help you analyze spending patterns and identify high-cost areas.
Why Do You Need to Optimize Your Cloud Costs?
Cloud cost optimization is essential because it directly impacts an organization’s financial efficiency and operational agility. Studies estimate that up to 30% of cloud spending is wasted on idle, underused, or unnecessary resources, which quietly inflate costs without delivering value. By optimizing cloud costs, organizations can uncover and eliminate these inefficiencies, freeing up budget that can be reinvested into innovation and growth initiatives.
Beyond cost savings, optimization improves operational agility by ensuring resources scale dynamically with demand, avoiding both overspending and performance bottlenecks. It also brings transparency and predictability to budgeting and forecasting, enabling finance teams to align spending with actual needs and avoid surprises. Additionally, reducing redundant or idle resources minimizes the attack surface, strengthening security and compliance.
For network engineers, embracing cloud cost optimization means designing and managing cloud environments that are not only efficient and scalable but also financially sustainable and secure.
Why Cloud Costs Spiral Out of Control
Experienced teams also often find it challenging to manage cloud costs. Here are the most common reasons they escalate:
- Overprovisioned resources: Provisioning for peak loads, then forgetting to scale down
- Idle and orphaned resources: Running instances or volumes with no active use
- Lack of visibility: Teams operating without a centralized view of usage across services or providers
- Inefficient autoscaling: Poorly configured auto-scaling rules leading to excess resource utilization
- Data transfer costs: Egress fees and inefficient architecture raising network costs
The Pillars of Cloud Cost Optimization
1. Visibility and Monitoring
Visibility is essential for identifying cost-saving opportunities in the cloud. Teams need clear, real-time insight into usage patterns, resource consumption, and cost breakdowns across accounts, services, and environments. Effective monitoring enables anomaly detection, trend analysis, and cost forecasting. Dashboards, tagging practices, and usage reports help attribute spend accurately and identify idle or oversized resources. With strong visibility, organizations can make data-driven decisions to optimize their environments and align cloud investments with business priorities.
2. Governance and Policies
Governance provides structure and accountability in the cloud. It includes establishing usage policies, setting budgets, enforcing tagging standards, and managing permissions. These controls prevent cost overruns, reduce shadow IT, and improve security. Implementing automation for policy enforcement, such as restricting high-cost instance types or requiring approval for specific services, ensures consistency. Governance empowers teams to innovate safely within set parameters while maintaining operational and financial discipline.
3. Automation and Scaling
Automation ensures cloud resources scale efficiently with demand. Autoscaling, scheduled shutdowns, and serverless architectures help minimize idle resources and reduce costs. Automation scripts or tools can enforce best practices, such as rightsizing instances or cleaning up unused resources. By removing manual intervention, teams avoid human error and respond faster to changes in workload. Well-implemented automation procedures improve both performance and cost efficiency across dynamic cloud environments.
4. Optimization of Storage and Compute Utilization
Optimizing compute and storage utilization involves matching the right resource types and pricing models to your actual workload needs. This includes choosing the appropriate instance families, leveraging spot instances and RIs, and managing storage tiers effectively. You should apply lifecycle rules to archive or delete unused data and regularly review performance metrics to rightsize services. These practices prevent overprovisioning and reduce unnecessary expenses, especially in high-volume or data-intensive operations.
Best Practices for Cloud Cost Optimization
1. Conduct Regular Cloud Cost Audits
A regular cloud cost audit is one of the most effective ways to control and reduce unnecessary spending. Audits help identify underutilized, idle, or orphaned resources that silently accumulate charges over time. During an audit, teams should analyze current consumption across services, instances, and departments. Key focus areas include compute usage (e.g., VM uptime versus CPU utilization), storage (such as old snapshots and unused volumes), and network egress.
Audits should also review the completeness and accuracy of tagging, ensuring resources are properly categorized for accountability. By benchmarking usage against historical trends, organizations can uncover cost anomalies and consumption spikes that indicate misconfigurations or wasteful practices.
To maintain consistency, establish a recurring audit schedule, such as monthly or biweekly, and integrate the findings into internal reports or dashboards. Automating parts of this process using tools such as AWS Cost Explorer or SolarWinds® Observability SaaS can reduce manual effort and deliver real-time visibility.
Cloud cost audits are not just financial exercises—they create feedback loops that inform architecture decisions, rightsizing efforts, and cloud governance policies.
2. Continuously Rightsize Cloud Resources
Rightsizing involves adjusting cloud resources (e.g., VMs, containers, databases) to match actual workload requirements. Overprovisioning is a common mistake: teams often select instance types with more CPU, memory, or input/output operations per second than needed, resulting in persistent cost inefficiencies.
Continuous rightsizing requires collecting granular usage metrics—such as CPU utilization, memory pressure, and storage throughput—and comparing them to the allocated limits of each resource. If your Elastic Compute Cloud (EC2) instance runs at 10% CPU usage for 90% of the day, you’re likely paying more than necessary.
Start by identifying persistent underutilization patterns, then use automation or scripting to downsize those resources. Consider switching to burstable instances, autoscaling groups, or serverless functions where appropriate.
Rightsizing should also take future growth and performance requirements into account. Avoid making decisions based only on short-term data: consider peak usage windows and application-specific needs.
Modern observability platforms, such as SolarWinds Observability SaaS, can assist with continuous monitoring of resource performance, helping teams make smart adjustments while maintaining service level agreements (SLAs) for optimal performance. By implementing rightsizing as a standard part of your DevOps or FinOps workflow, you ensure costs scale sensibly with usage.
3. Eliminate Idle, Unused, or Orphaned Resources
One of the quickest wins in cloud cost optimization is eliminating idle or orphaned resources. These include instances running without traffic, unattached volumes, outdated snapshots, unused load balancers, or expired Domain Name System zones. Left unchecked, these resources quietly inflate bills while delivering zero value.
Idle resources are often remnants of testing environments, continuous integration and continuous delivery (CI/CD) pipelines, or discontinued projects. Without effective resource ownership and lifecycle policies, they persist well beyond their usefulness.
A good practice is to run weekly automated discovery jobs to find:
- Idle VMs (low CPU or network I/O)
- Elastic Block Storage volumes not attached to any instance
- Aged backups or snapshots no longer required for compliance
- Unused Elastic IP addresses or load balancers
- Zombie containers or Kubernetes pods
Many cloud providers now offer automated cleanup options. Amazon Web Services (AWS) has resource lifecycle manager tools, and Google Cloud offers recommender services. You can also set time-to-live tags that trigger resource deprovisioning after a specific period.
Pair this with automated alerts through observability tools such as those by SolarWinds, which can flag underutilized resources and send actionable recommendations to infrastructure teams. By regularly eliminating idle assets, you can significantly reduce waste, often saving 10% – 20% on your monthly bill with minimal effort.
4. Set Up Cost Alerts and Budget Thresholds
Cost optimization begins with visibility, and its first layer comes through cost alerts and budget thresholds. These tools allow cloud administrators and finance teams to monitor real-time spending and take action before overruns occur.
Start by setting monthly or quarterly budgets based on the project, environment (development, testing, or production ), or business unit. Platforms such as AWS, Azure, and Google Cloud Platform (GCP) offer built-in budget management features that notify stakeholders via email, Slack, or dashboards when spending crosses a specific threshold (e.g., 80%, 90%, or 100% of the budget).
Alerts can also be fine-tuned to trigger on anomalies, such as unexpected spikes in data transfer, storage usage, or compute time. For example, if an autoscaling group starts launching too many instances due to a misconfiguration, an alert will catch the trend before it leads to a financial blowout.
Advanced observability platforms such as SolarWinds Observability SaaS extend this by correlating performance metrics with cost, allowing teams to trace why spending is increasing. Is it due to increased load? A bug in the application? Or a misconfigured service?
With the right alerting strategy, cost anomalies can be addressed in real time instead of being discovered weeks later in a billing report, enabling proactive optimization and cross-team accountability.
5. Implement Resource Tagging for Cost Attribution
Tagging is a foundational practice for organizing and allocating cloud costs. By tagging resources with metadata, such as environment (production and development), project (customer relationship management and DataPipeline), owner, or department, teams can gain granular insight into who or what is consuming resources.
Without tagging, cloud bills appear as a flat list of services, making it nearly impossible to track costs by business unit, team, or application. This lack of accountability leads to wastage and hinders budgeting.
Effective tagging strategies include:
- Establishing required tags (e.g., Environment, Project, and Owner)
- Enforcing tagging policies through cloud governance tools
- Automating tag validation and correction using scripts or third-party tools
- Using hierarchical tags for large organizations
Tagging also enables advanced reporting, using showback and chargeback models, critical for FinOps maturity. With platforms such as SolarWinds Observability SaaS, tagged resources can be grouped and filtered in cost dashboards, making it easier to monitor cloud spend in context.
Tagging transforms a generic cloud bill into an actionable data set, giving teams the insight they need to take ownership of their usage and spend.
6. Use Spot and Reserved Instances Strategically
Cloud providers offer various pricing models to help customers reduce costs when predictable or interruptible workloads are involved. Two of the most powerful options are:
- RIs: Prepay for a specific instance type and region for one to three years, receiving a discount of up to 70% compared to on-demand prices.
- Spot instances: Use spare compute capacity at massive discounts (up to 90%), with the caveat that the instance can be terminated with short notice.
Both options can deliver significant savings, but they must be applied strategically.
RIs are ideal for predictable, always-on workloads, such as databases, web servers, and backend APIs. Use historical data to identify consistently running instances, then convert them to RIs.
Spot Instances are perfect for fault-tolerant and batch jobs, such as CI/CD pipelines, testing environments, data processing, and rendering tasks. Use orchestration tools (e.g., AWS Auto Scaling Groups, Kubernetes, or Terraform) to automatically provision spot capacity and handle interruptions.
Combined with observability tools by SolarWinds, you can identify which workloads are stable enough for RIs and which can tolerate volatility for spot usage. This hybrid approach allows you to drastically reduce compute costs while maintaining operational resilience.
Cloud Provider-Specific Tips
Each major cloud provider offers distinct tools and features for managing and optimizing costs. Understanding the nuances of your chosen platform can unlock additional savings and prevent unnecessary spending.
- Amazon Web Services
AWS provides robust cost management features through the AWS Cost Explorer, Budgets, and Savings Plans. You can use Compute Optimizer to get rightsizing recommendations for EC2, Lambda, and Elastic Container Service. Also, the Trusted Advisor tool highlights idle resources and underutilized services. Implement Simple Storage Service Intelligent-Tiering for automatic storage optimization, and leverage Savings Plans over RIs for more flexibility.
- Azure
Microsoft Azure offers Cost Management + Billing, which helps track usage and forecast costs. Use Azure Advisor for personalized cost-saving recommendations and Azure Reservations for discounts on one- or three-year commitments. Azure Hybrid Benefit allows you to bring on-premises licenses to the cloud, reducing compute costs. Implement resource locks and role-based access control to avoid accidental overprovisioning.
- Google Cloud Platform
GCP includes Cost Management Tools, Budgets and Alerts, and Recommender—an artificial intelligence-powered tool that provides insights on cost savings and performance improvements. Use Committed Use Discounts (CUDs) and Sustained Use Discounts (SUDs) for predictable workloads. GCP also offers billing export to BigQuery, allowing deep, customizable cost analysis. Automate cost visibility through Looker dashboards for real-time insights.
Each platform has its own best practices, so tailor your optimization strategy accordingly and stay updated with newly released cost management features.
Cloud Cost Optimization for FinOps Teams
Cloud cost optimization is no longer just an IT function—it’s a strategic priority for FinOps teams. These teams bridge the gap between technical decision-makers and business stakeholders to ensure every dollar spent on the cloud delivers measurable value.
FinOps professionals focus on real-time visibility, accountability, and collaboration. They work closely with engineering to ensure resources are efficiently provisioned and with finance to align spend with forecasts. One of their key responsibilities is cost allocation—ensuring each team, product, or project is accountable for its usage.
Best practices for FinOps teams include:
- Implementing chargeback/showback models to make teams responsible for their cloud usage
- Establishing KPIs around cost per customer, cost per deployment, and usage efficiency
- Driving budget awareness within engineering through dashboards and alerts
- Promoting cross-functional reviews of monthly cloud spend
Automation tools and dashboards help FinOps teams deliver cost transparency and foster a culture of efficiency. By integrating cost considerations into the development lifecycle (e.g., during CI/CD or sprint planning), FinOps teams empower organizations to scale cloud usage responsibly while maximizing ROI.
A strong FinOps function enables businesses to treat cloud like a strategic investment—not just an expense.
Cloud Cost Optimization in Multi-Cloud and Hybrid Environments
While single-cloud deployments offer simplicity and volume discounts, multi-cloud approaches provide greater flexibility, risk mitigation, and bargaining power. However, this flexibility can introduce hidden costs and complexity.
Cost Implications of Multi-Cloud
A multi-cloud infrastructure leverages services from multiple providers, often to avoid vendor lock-in, improve service availability, or meet compliance needs across geographic regions. While this can enhance resilience and performance, it may also increase data migration costs when moving workloads between clouds. Organizations also miss out on volume-based pricing and volume discounts that can be gained by sticking with a single vendor.
Deploying across multiple clouds can also require duplicate investments in tooling, monitoring, managed databases, storage solutions, and security frameworks. Each cloud provider has different billing models, making unified cost visibility a challenge.
Governance and Deployment Considerations
Effective cost control in multi-cloud environments starts with robust governance. A cloud governance board can help standardize policies, control usage, and ensure teams follow cost-effective practices across platforms. Enforcing naming conventions, access controls, and tagging through infrastructure as code (IaC) helps maintain consistency across providers.
Deployment strategies should align with a cloud-native development strategy—choosing services and architectures optimized for each cloud platform. However, this can further entrench software licenses and increase the risk of vendor-specific dependencies, counteracting the benefits of a multi-cloud approach.
Additionally, using managed databases and storage solutions can simplify operations, but they may also lock you into higher long-term costs. Evaluate whether you can adopt open-source or portable alternatives to maintain flexibility.
Hybrid Cloud Considerations
In hybrid cloud deployments, where workloads span on-premises and public cloud infrastructure, challenges include integrating legacy systems, aligning SLAs, and handling data gravity. Careful workload placement is essential to avoid unnecessary data egress and network charges.
Common Mistakes to Avoid
1. Ignoring Idle or Underutilized Resources
One of the most common cloud cost mistakes is paying for resources that are not actively in use. These include idle VMs, unattached storage volumes, and underutilized database instances. Teams often forget to decommission test environments or leave compute resources running at full capacity during off-hours. These costs silently accumulate and impact your bottom line.
2. Lack of Proper Tagging and Cost Attribution
Without a clear tagging strategy, it’s nearly impossible to understand where cloud spend is going. Resources should be tagged by project, team, environment, and cost center. A lack of tagging leads to poor cost attribution, making showback and chargeback models ineffective. This creates confusion, prevents accountability, and complicates optimization efforts. Consistent, enforced tagging—ideally through IaC and cloud policies—enables visibility across departments.
3. Overprovisioning Compute and Storage
Overprovisioning occurs when you allocate more resources than necessary to ensure performance and reliability. While it may seem like a safe strategy, it often leads to inflated cloud bills. Teams commonly choose larger instance types or high-performance storage options “just in case.” This approach may be justified for mission-critical applications, but it is wasteful for non-production or low-usage workloads.
4. Failing to Use Reserved Instances or Savings Plans
Relying solely on on-demand pricing models is convenient but significantly more expensive over time. Many organizations fail to commit to RIs or savings plans, even for predictable workloads. This results in higher per-hour costs and missed savings opportunities—often up to 60%. While RIs and savings plans require upfront planning and commitment, they are ideal for steady-state workloads and core infrastructure. Without these options, organizations overspend on compute, databases, and storage.
5. Underestimating Data Transfer and Egress Fees
Cloud providers often charge for moving data across services, regions, or outside their ecosystem. These data transfer and egress fees can become a major hidden cost, especially in multi-cloud or hybrid cloud environments. Many teams underestimate how their architecture choices, such as frequent API calls between regions or large data migrations, can accumulate fees. Without visibility into these charges, they’re difficult to predict or manage.
Tools and Platforms for Cloud Cost Optimization
Effectively managing cloud costs requires powerful tools that provide visibility, analytics, and actionable insights. While native cloud provider tools, such as AWS Cost Explorer, Azure Cost Management, and Google Cloud Billing, offer foundational capabilities, third-party platforms often deliver enhanced features for deeper cost optimization and infrastructure observability.
Here is a comparison of tools that support cloud cost management and help with optimization:
| Tool | Type | Pros | Cons |
| CloudHealth by VMware | Third-party | Strong multi-cloud support | Costly for small teams |
| Kubecost | Open-source | Great for Kubernetes | Requires configuration |
| Apptio Cloudability | Enterprise | Finance-first FinOps platform | Steeper learning curve |
| AWS Cost Explorer | Native | Deep AWS integration | AWS specific |
| SolarWinds Observability SaaS | Hybrid Monitoring | Full-stack visibility + cost insights | Best paired with other governance tools |
How Network Monitoring Enhances Cloud Cost Optimization
While most cloud cost optimization focuses on compute and storage, network traffic is an often overlooked cost driver. Poorly designed traffic flows and unmonitored bandwidth spikes can lead to inflated egress charges.
This is where network monitoring tools—especially those with full-stack observability—play a key role.
SolarWinds Observability SaaS provides real-time insights across applications, infrastructure, and network layers—including cloud-native services. Here’s how it helps with cost optimization:
- Traffic analysis: Pinpoints bandwidth-heavy services and unnecessary data transfers
- Anomaly detection: Catches usage spikes before they cause billing surprises
- Tag-based tracking: Attributes network usage to teams, applications, or environments
- Cross-cloud visibility: Unifies cost and performance data across AWS, Azure, GCP, and hybrid environments
By integrating observability with cost data, SolarWinds helps teams not only cut waste but also prevent recurring cost incidents.
Conclusion: Cloud Cost Optimization Checklist
Cloud cost optimization is not a one-time effort—it’s a continuous, strategic process. From visibility and governance to automation and cross-team collaboration, the best strategies ensure every dollar spent on cloud services drives real value. Grab the Cloud Cost Optimization Checklist to support your optimization efforts:
- Conduct regular audits of cloud spend.
- Enable cost alerts and budgets.
- Enforce tagging across all resources.
- Use reserved/spot instances strategically.
- Review autoscaling and storage configurations.
- Implement network monitoring tools such as SolarWinds Observability.
- Document policies and share insights cross-functionally.
Monitoring plays a crucial role in that equation. Solutions such as SolarWinds Observability SaaS go beyond basic metrics to provide deep insights into cloud performance and network activity—making it easier to control costs, forecast usage, and eliminate inefficiencies.