A deep dive into AWS Cost Explorer – Forecast Usage.
Focus:
- Practical, Operator-level
lens that fits DevOps / Cloud / FinOps teams.
Breakdown:
- Intro,
- Key
Features of Usage Forecasting,
- How
to Access Usage Forecasts,
- The
concept: “Forecast Usage” Really Means,
- How
AWS Generates the Forecast,
- Supported Services (Most Relevant),
- Forecast
Views twtech Can Build,
- Forecast Confidence Bands (Very Important),
- Common
DevOps & FinOps Use Cases,
- Limitations (Where People Get Burned),
- Professional Tips (Advanced),
- When
NOT to Trust Forecast Usage,
- Final thoughts.
Intro:
- AWS Cost
Explorer offers usage forecasting via machine learning to
predict future usage patterns based on historical data.
- This machine learning functionality helps
twtech to
understand expected trends, monitor key usage, enabling better budget planning
and cost management.
Key Features of Usage Forecasting
Granularity:
- twtech can generate forecasts at a daily or monthly level.
Forecast
Horizon:
- twtech can view forecasts up to 18 months into the future through the console or API, providing long-term visibility for planning.
Prediction
Intervals:
- Forecasts include an 80% prediction interval, indicating that the actual usage is likely to fall within the estimated range 80% of the time.
Data
Requirements:
- For optimal accuracy, AWS recommends enabling
38-month data retention to provide the machine learning model with sufficient
historical context to identify seasonal patterns and long-term trends.
- Without enough data (typically less than a full billing cycle), Cost Explorer will not provide a forecast.
API
Access:
-
Usage forecasts are available programmatically
via the
GetUsageForecastAPI operation, allowing for integration with other tools like AWS Budgets for custom alerts.
Filtering:
- Forecasts can be customized by filtering the data by specific services, usage types (e.g., EC2 running hours), linked accounts, or tags, offering detailed insights into different aspects of twtech AWS environment.
How to Access Usage Forecasts
1. Open the AWS Billing and Cost Management console.
2.
Navigate to Cost Explorer in the left navigation pane.
3.
Select a
report (e.g., Monthly costs by Service)
or create a new custom report.
4.
Adjust the Forecast
Horizon in
the report parameters to the desired future timeframe (e.g., +3M, +12M, up to +18M).
NB:
- By leveraging Cost Explorer's usage forecasting, twtech can proactively manage its AWS resources and plan future cloud investments more effectively.
Useful AWS Documentation link:
https://docs.aws.amazon.com/cost-management/latest/userguide/ce-forecast.html
Cloud FinOps & Forcasting.
AWS
budget Vs Cost Explorer:
Monthly forecasting:
1. The concept: “Forecast Usage” Really Means
- Forecast Usage in AWS Cost
Explorer predicts future service consumption, not just
future spend.
- AWS uses historical usage patterns
+ machine learning time-series
models to forecast:
- Usage quantity (e.g., hours, GB-months, requests)
- Resulting
estimated cost, including discounts (Savings
Plans, RIs) already applied
Key distinction:
|
Feature |
Forecast Usage |
Forecast Cost |
|
Predicts |
Resource
consumption |
Dollar spend |
|
Unit |
Service-specific
units |
USD |
|
Best
for |
Capacity
planning, scaling |
Budgeting, finance |
|
Tied
to pricing changes |
Indirect |
Direct |
2. How AWS Generates the Forecast
AWS Cost Explorer forecasts are based on:
1.
Historical usage trends
2.
Seasonality detection
3.
Recent growth/decline weighting
4.
Service-specific behavior models
Important constraints:
- Minimum 3 months of historical data
- Forecast horizon:
- Up to 12 months
- Accuracy improves with:
- Stable workloads
- Consistent usage patterns
AWS does not
assume:
- New services
being added
- Major
architecture changes
- Sudden
traffic spikes
3. Supported Services (Most Relevant)
Forecast
Usage works best for usage-driven services:
Strong
Accuracy
- EC2 (Instance hours)
- EBS (GB-months)
- S3 (GB-months, requests)
- RDS
/ Aurora
- NAT
Gateway
- Data
transfer
Weak
/ Unreliable
- Lambda (event-driven
bursts)
- Step Functions
- Ad-hoc data analytics (Athena,
Glue)
- One-time migrations
NB:
- As a DevOps engineer, always treat event-based
services as directional only, not precise.
4. Forecast Views twtech Can Build
A.
Service-Level Usage Forecast
Example:
EC2 → Running Hours →
Next 6 Months
Use this to:
- Predict capacity growth
- Decide Savings Plan commitment size
- Spot runaway scaling early
B.
Usage Forecast by Dimension
twtech can forecast usage filtered by:
- Linked
account
- Region
- Instance
family
- Purchase option (On-Demand vs SP)
Example:
EC2 → us-east-2 → m6i
family → Usage forecast
This is gold for:
- Platform
teams
- Multi-account
environments
- Workload
owners
C.
Usage vs Historical Overlay
Overlay:
- Actual usage
- Forecasted
usage
Use this to:
- Validate
forecast quality
- Detect
behavior shifts
- Identify
workload drift
5. Forecast Confidence Bands (Very Important)
AWS provides confidence
intervals:
- Lower bound (conservative)
- Expected forecast
- Upper bound (worst case)
Interpretation:
|
Scenario |
Action |
|
Upper
bound rising fast |
Investigate scaling policies |
|
Lower
bound still high |
Baseline cost won’t drop |
|
Wide
band |
Usage volatility |
NB:
FinOps best practice:
- Plan commitments closer to the lower-to-mid band, not the
upper bound.
6. Common DevOps
& FinOps Use Cases
1,
Savings Plan Sizing
Before committing:
- Forecast EC2 + Fargate + Lambda
usage
- Compare against current SP coverage
Rule of thumb:
- Commit to 70–80% of forecasted steady-state usage
2,
Capacity Planning
Forecast usage answers:
- “Is twtech growing linearly (constant) or exponentially (sky-rocketing) ?”
- “Does twtech need architectural changes before cost explodes?”
3,
Early Cost Anomaly Detection
Usage forecast rising ≠ expected?
- Check:
- Auto Scaling configs
- Kubernetes HPA thresholds
- Misconfigured cron jobs
4,
Budget Guardrails
Usage forecast + budgets:
- Create usage-based budgets
- Alert before spend increases, not after
7. Limitations (Where
People Get Burned)
❌ Forecast does NOT account for:
- New workloads
- Traffic spikes (Black
Friday, launches)
- Architecture refactors
- Pricing model changes
❌ Accuracy drops when:
- Usage is
bursty
- Workloads are
ephemeral
- Usage
recently changed direction
Always combine
forecast with:
- Cost Anomaly Detection
- Service-level dashboards
- Engineering context
8. Professional Tips (Advanced)
Compare Forecast vs RI/SP Coverage
- If forecast > covered usage →
increase commitment
- If forecast < covered usage →
risk of underutilization
Export Forecast Data
Use:
- Cost Explorer API (
GetCostForecast) - QuickSight Pull into:
- Grafana
- FinOps dashboards
Forecast Usage ≠ Forecast Cost
twtech Always review both:
- Usage tells twtech what
- Cost tells twtech impact
9. When NOT to Trust Forecast Usage
|
Scenario |
Better Tool |
|
Spiky
workloads |
Cost Anomaly Detection |
|
New
product launch |
Traffic modeling |
|
Short-term
analysis |
Daily usage charts |
|
Lambda-heavy
stacks |
Request-level metrics |
10. Final thoughts
- Forecast Usage predicts resource consumption,and cost.
- Forecast Usage is Best for EC2, storage, steady-state workloads
- Forecast Usage is Essential for Savings Plan sizing
- Forecast Usage is Not reliable for event-driven or bursty services
- Forecast Usage uses the confidence bands + engineering context.
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