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A healthcare startup was spending $50,000 a month on cloud storage it didn’t even use: old backups accumulating from a compliance audit three years prior. They dropped 80% of the dormant data to delete, and moved the rest to cold storage, so they saved a chunky 70% in costs in just one afternoon. You can also schedule a call with us for the same thing.
Why Is Your Cloud Bill More Expensive Than Your Rent?
Begin by shutting off what you don’t need right now — and most companies are leaving 30% of spend begging for "Braaaainss" as zombie resources that no one can recall creating continue to consume.
Do you promise to shut that down? Manually. Developers won’t remember to turn things off, so figure out ways to automatically turn them off in dev environments.
- Rightsize your instances by looking at what you really use versus what you are paying for—that “just in case” incremental capacity costs real money month after month.
- Move old data to cheaper storage tiers, since you likely haven’t used 80% of it in a year.
- Set up spending alerts that go straight to someone with budget authority, not just into some inbox where they will get lost.
- Keep an eye on teams burning the most cash and force them to justify resource requests against the business need.
You’ll want to keep a weekly track because monthly bills come in too late to matter—the damage has already compounded into budget-busting territory.
AWS Cost Reduction
The team's deep understanding of our needs allowed us to achieve a more secure, robust, and faster infrastructure that can handle growth without incurring exorbitant costs.
We thought it would be helpful to lay out a roadmap for optimizing the cloud infrastructure your team uses on AWS. Engineers are spinning up resources faster than they shut them down, so your AWS bill is going up month by month. If you feel that is the case for you, then schedule a call.
Compute Resources
- Shut down EC2 instances not in use and underutilized Lambda functions.
- Size your instances based on 100% real CPU utilization and memory usage data.
- Purchase Reserved Instances only for predictable workloads that are running 24/7.
- Use Spot instances for batch jobs that can tolerate an instant interruption.
Storage Optimization
- Remove old S3 versions, incomplete uploads, and unattached EBS volumes at once.
- Transfer data to lower-cost storage tiers after 90 days.
- Use automated lifecycle rules instead of manual cleanup.
- Remove snapshots older than the business needs.
Database Costs
- Size RDS instances correctly based on real performance numbers, not estimates.
- Switch DynamoDB to on-demand pricing if your incoming traffic is unpredictable.
- Remove old backups past regulatory need.
- Keep track of how many connections you have and the performance of your queries.
Network and Data Transfer
- Keep traffic within the same AWS region, if possible.
- Replace Internet Gateway routes with VPC endpoints.
- Monitor cross-region transfer costs weekly.
- Cache static content with CloudFront.
Monitoring and Alerts
- Configure alerts that ping assigned budget owners in real time.
- Tag everything for cost tracking by team and project.
- Review billing reports at a summary level on a weekly, not monthly basis.
- Use AWS Trusted Advisor recommendations.
Quick Wins
- Remove zombie resources that no one remembers having created.
- Delete storage no one has opened for 6+ months.
- Schedule auto shutdown for your dev environments.
- Examine patterns of data transfer for unnecessary fees.
- Turn on detailed monitoring for expensive services.
Be sure to keep an eye out for NAT Gateway charges, idle load balancers, and over-provisioned databases with low utilization.
10 Rules of the Road for Managing Cloud Infrastructure Costs
Cloud bills are the equivalent of a very high-spending-limit credit card, which they treat as if it has no limit. Engineers spin up resources for a crunch and then forget they exist after launch. These ten methods will stop the bleeding, but only if teams do them.
1. Keep Track of Where Your Money Goes Every Week
Cloud bills obscure the truth behind hundreds of line items. Teams spin up resources when it’s crunch time and then forget about them. Cost allocation tags let you see who spent what on which projects. Pull down detailed billing reports at least weekly and sort them by team or service to see where the real money drains are.
2. Size Your Match Servers Based on Actual Usage
Teams are buying massive servers because they fear slowdowns. The vast majority of workloads are parked at 20% CPU utilization all day long. Look at the actual performance data over two weeks. Halve the server size if usage remains under 50%. Downsize your testing in steps so nothing breaks.
3. Delete Dead Resources Monthly
Dev environments proliferate during busy times. QA servers are not cleaned up after testing. Database snapshots accrue from deleted projects. Create scans to capture orphaned resources. Remove anything that isn’t tied to a pursuit or hasn’t been used for 30 days.
4. Build Alerts That Force Action
Monthly bills come too late to stop the damage. Daily reminders get lost among email clutter. Set weekly budget limits that ping team leads directly. Incorporate up-to-date spending versus planned costs in all alerts. Hold a person accountable for each budget breach.
5. Automate What People Forget
Manual shutdowns break when we forget they’re there. Developers say they’ll clean up after deployments, but they forget. Set up auto-scaling based on realistic traffic patterns. Schedule shutdowns for non-prod environments so servers do not run forever.
6. Choose Storage According to the Frequency of Access
Hot storage costs 10 times as much as cold storage. Most data is read once and never accessed again. After 90 days without activity, move files to lower-tier storage. Archive logs and backups to the coldest storage available.
7. Scale Resources with Traffic Patterns
Fixed infrastructure leaks money during lulls — traffic varies by time of day and day of week. Configure auto-scaling groups using load metrics. Enable aggressive scale-down to save costs.
8. Set Up a Discount for Stable Loads
For long-term workloads, reserved capacity offers substantial discounts. Spot pricing saves money for fault-tolerant jobs. Savings Plans offer flexibility across services. Purchase reserved capacity for predictable workloads only. Begin with 6-month terms to determine commitment.
9. Shop Around for Better Pricing
Cloud providers compete for business on certain services. Different platforms price workloads differently. Quarterly, compare options for costly services. Before moving, calculate the time and cost of migration.
10. Downgrade Storage Nobody Touches
The default storage setting is optimized for speed, not cost. Backup policies are often more generous than business needs. Review storage classes monthly and downgrade cold data. Dispose of old backups not required by law.
Why Is Cloud Infrastructure Cost Optimization Important for Your Business?
Forbes notes that when it comes to cloud cost control, it’s all about strong leadership from the top down. While most businesses now consider it a priority, cloud spending typically comes in about 17% over budget. The problem is wasted resources, overprovisioned services, and systems that run when they’re not needed.
Cost optimization remedies this by adjusting usage to real demand so you’re not paying for waste.
DATAFOREST can address this with machine learning and real-time monitoring, collecting information and observing compute, storage, and network utilization to pinpoint inefficiencies. Practices like rightsizing, auto-scaling, or committing to the right pricing models can reduce spending without sacrificing performance.
The benefits extend beyond savings: smoother operations, fewer errors, and more money to invest in growth or innovation.
Cost discipline also depends on a strong culture. With finance, engineering, and operations sharing responsibility in a FinOps model, the business becomes more resource-efficient. With AI-powered forecasting, it’s possible to anticipate changes, control fluctuations, and stay ahead instead of reacting too late.
How DATAFOREST's Success Stories Can Influence Your Strategy?
Real-life victories from DATAFOREST demonstrate that intelligent cloud optimization can deliver drastically reduced costs, major performance improvements, and a stable infrastructure.
How to Scale Your AWS Bill Without Compromising on Speed
With rising AWS expenses, up 265% over nine months for one US IT services company, DATAFOREST uncovered every charge and inefficiency. They scrubbed idle instances and storage, set up off-hours scheduling, optimized CI/CD pipelines, and leveraged Reserved Instances and Savings Plans.
- The result: over $23K monthly savings, a 67.5% decrease in instance costs, and an 8% performance improvement.
Opening Up Bottlenecks, Delivering Performance to the Max
A slow, unstable FinTech company underwent a deep AWS audit. DATAFOREST implemented monitoring, optimized SQL queries, migrated data pipelines, and re-architected the system using Docker, Kubernetes, and horizontal scaling.
- Results: 1000% performance improvement, 20% cost reduction, and improved stability.
Unified Architecture, Instant Insights
An e-commerce company struggled with fragmented multi-cloud infrastructure. DATAFOREST standardized the environment and centralized monitoring through Zabbix and PagerDuty.
- Results: 200% improvement in reliability and performance with 24/7 monitoring.
How Does DATAFOREST's Method Create Real Savings?
DATAFOREST combines infrastructure audits, rightsizing, automation, cost-aligned pricing models, and architectural improvements to reduce waste while boosting performance. Clients typically realize more than 30% in monthly savings during the first optimization cycle, with ongoing improvements as infrastructure evolves.
FAQ
What is cloud infrastructure cost optimization?
It is the practice of improving utilization and efficiency to reduce waste while maintaining performance and reliability.
What is the difference between cloud cost optimization and cloud cost management?
Cloud cost management focuses on staying within budget. Cloud cost optimization focuses on improving usage efficiency to reduce unnecessary spending.
What are the main challenges of cloud optimization?
Accurate forecasting, avoiding over- or under-provisioning, managing multi-cloud environments, and balancing cost with performance and reliability.
What are some reasons cloud costs turn out higher than expected?
Wasted resources, overprovisioned services, unused backups, idle environments, lack of monitoring, and misaligned pricing models.
What are the typical issues companies face when optimizing cloud infrastructure costs?
Lack of visibility into spending, difficulty implementing rightsizing or reserved instance strategies safely, and keeping up with changing pricing models.
What are some ways DevOps techniques can be used to optimize cloud spending?
Automation, infrastructure as code, continuous monitoring, and real-time usage visibility help manage provisioning and control costs proactively.
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