You’d be surprised how often cloud costs go off the rails not because of huge production workloads, but because of everything around them.
“We thought it was just a dev box…”
and then it showed up on the invoice.
They usually come from everything else:
- A test instance left running all weekend
- A staging environment no one touched in months
- That “temporary” resources that became permanent
- A misconfigured auto-scaler creating more than needed
And this isn’t just an anecdote.
Flexera’s 2024 State of the Cloud Report shows that organizations estimate that around 1/3 of their cloud spend is wasted and that’s just the part they know about.
I’ve seen these mistakes across many teams. Different industries. Different clouds. Same problems.
So, what are the mistakes that lead to cloud waste?
1. Non-production environments running 24/7
Dev, test, PoC; none of these need to run full-time. Yet in many environments, they do.
This adds up fast, especially when teams forget to tear them down.
Fix: Automate shutdown schedules using native cloud tools (like AWS Instance Scheduler or Azure Automation). At the very least, stop them outside working hours.
2. Orphaned resources
Unattached storage volumes. Idle load balancers. Snapshots with no owner.
These often slip under the radar, but not off the bill.
Fix: Tag everything at the time of creation. Run regular audits. Use tools like AWS Config or custom scripts to detect unused resources.
3. Relying on on-demand pricing for everything
On-demand is flexible, and expensive.
Teams often run predictable workloads this way simply because it’s the default.
Fix: Classify workloads. Use Reserved Instances or Savings Plans for steady-state. Go spot/preemptible for batch or interruptible tasks.
4. Poor tagging practices
If it’s not tagged, you can’t track it.
No tracking means no accountability, and that’s how budgets get blown.
Fix: Enforce tagging policies at the org level. Use cost allocation tags to assign spend to teams or projects.
5. No budget alerts or anomaly detection
A lot of teams only discover a cost issue when the invoice arrives.
At that point, it’s too late.
Fix: Set up budget thresholds per project or team. Enable anomaly detection tools like AWS Cost Anomaly Detection or Azure Budget alerts.
6. Using the wrong service tiers
Running cold data on premium storage. General-purpose compute for low-traffic workloads.
It’s easy to overlook… until the bill arrives.
Fix: Review service usage regularly. Move infrequent-access data to archival tiers. Swap general compute for managed or serverless options where applicable.
7. Multiple environments with no governance
Different teams. Multiple subscriptions or accounts. No central view.
This leads to duplicated services, inconsistent policies, and rising costs.
Fix: Use landing zones, management groups, or org-level policies. Build dashboards that consolidate spend across environments.
8. Manual provisioning with no lifecycle controls
If it’s created manually, it’s rarely cleaned up properly. Multiply this across a team, and you have a sprawl problem.
Fix: Use Infrastructure as Code (IaC). It makes resource management repeatable and auditable, and cleanup becomes part of the process.
Habits
Cloud cost optimization isn’t about squeezing pennies from production.
It’s about catching the silent, easy-to-miss stuff that builds up over time.
The cloud can be cost-effective. But it requires discipline.
Start with small habits:
- Tag consistently
- Automate shutdowns
- Use the right pricing model
- Monitor, always
Small habits → Big savings.
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