Here’s twtech deep-dive,
cost-optimization of AWS Savings Plans as an alternative to Reserved Instances (RIs).
Focus:
- Cost Explorer and real-world FinOps decision-making.
Breakdown:
- Intro,
- What Are Savings Plans (High-Level),
- Savings Plans Compare to Reserved Instances,
- Cost Explorer’s Role in Deep Cost Analysis,
- FinOps Considerations,
- Practical Use-Cases in Cost Explorer,
- Key Takeaways,
- Insights.
Intro
- Cost Explorer offers tools help
twtech to analyze its usage and spending patterns.
- Cost Explorer is very useful when deciding between AWS Savings Plans and Reserved Instances (RIs).
Key features of Cost Explorer for this analysis include:
Savings Plans
Recommendation:
- The Cost Explorer Savings Plans recommendation engine analyzes twtech historical usage (typically the last 7, 30, or 60 days) to recommend an optimal commitment amount (hourly spend) that would maximize its savings without requiring a full coverage commitment.
RI Utilization and
Coverage Reports:
- twtech can use Cost
Explorer to view specific reports on the performance of its existing Reserved
Instances.
- This report helps twtech to understand how
effectively they are being used (utilization).
- This report
also indicates what percentage of twtech total usage is covered by RIs.
- This data highlights potential coverage gaps.
"What If"
Analysis:
- The tool allows twtech to perform "what if" analyses, letting it visualize potential savings by applying different commitment levels or types of discounts (RI vs. Savings Plan) to past past usage data.
Forecasting:
- Cost Explorer
provides forecasts of twtech future costs based on current and historical usage
trends,.
- This forecast helps twtech to project the long-term financial impact of purchasing either RIs or Savings Plans.
Ultimately (in-a-nut-shell)
- Cost Explorer serves as the primary visualization and analysis tool within AWS for comparing potential cost savings and determining which pricing model (Savings Plans or RIs) best fits twtech organization's specific/ flexible needs
What Are Savings Plans (High-Level)
- AWS Savings Plans are commitment-based discounts that reduce compute costs similarly to Reserved Instances, but instead of locking in specific instance configurations, twtech commits to a dollar-per-hour usage level over a 1- or 3-year term.
There are two
main types relevant to EC2:
- Compute
Savings Plans — most flexible; applies across instance
families, sizes, Regions, OS/tenancy, and covers Fargate and Lambda. Up to ~66% off On-Demand.
- EC2
Instance Savings Plans — deeper discount (up to ~72%); tied
to an instance family in a specific Region, but still flexible on
size/OS/tenancy.
Key distinction from RIs:
- Savings Plans commit to spend ($/hr), not specific instance attributes.
- RIs commit to resources (e.g., m5.large in us-east-2).
- Savings Plans apply broadly across compute usage, even if
twtech infrastructure changes.
Savings Plans Compare to Reserved Instances
Below is
a comparison between
Savings Plans and RIs:
|
Aspect |
Savings Plans |
Reserved Instances (RIs) |
|
Commitment type |
Hourly spend ($/hr)
on eligible compute |
Specific instance config (type, region, OS, tenancy) |
|
Flexibility |
Very high (cross-family/region
for Compute SP) |
Lower; Convertible RIs are moderate |
|
Coverage |
EC2 + Fargate +
Lambda (Compute SP) |
EC2 (and separate RIs for RDS, ElastiCache, etc.) |
|
Discount depth |
Up to ~72% (EC2 SP) |
Up to ~75% (Standard RI) |
|
Capacity guarantee |
❌ No |
✔ Zonal RIs can
reserve capacity |
|
Resell/exchange |
❌ Cannot after short refund window |
✔ Standard can be resold; Convertible can
be exchanged |
|
Management friction |
Lower |
Higher (tracking,
modifications, exchange) |
NB:
The exact
percentages vary by region/payment option
When should twtech prefer Savings Plans:
- Workloads that evolve frequently (instance types/regions change)
- twtech uses other compute services (Fargate, Lambda)
- twtech wants simpler ongoing management
When does RIs still make sense:
- Mission-critical
workloads needing capacity guarantees
- Very
predictable long-lived fleets where max discount matters
Cost Explorer’s Role in Deep Cost Analysis (AWS Cost Explorer is essential for)
1. Historical analysis of
usage & cost (up to ~13 months) to identify steady vs dynamic
consumption.
2. Savings Plans recommendations based on past spend — Cost Explorer suggests optimal commitments
for Savings Plans that fit twtech actual usage pattern.
3. Reserved Instance recommendations similarly, based on how much On-Demand twtech has
used.
4.
Reports on coverage & utilization, e.g.,
Savings Plan Coverage or Reservation Utilization views, so twtech can see how much it spending is covered and how
well it is using what it bought.
How Cost Explorer Helps twtech Evaluate
A. Coverage & Utilization Dashboards
- Coverage shows % of eligible usage covered by Savings Plans or RIs.
- Utilization shows how much of your purchased commitment is actually applied.
- Cost Explorer lets FinOps teams monitor these over time and tune purchases.
B. Recommendation Customization
- twtech can tailor look-back periods (e.g., 7, 30, 60 days) to align with seasonal/usage patterns.
- It simulates potential Saving Plan (SP) or Reserved Instance (RI) purchases and estimated savings based on historical data.
C. Data-Driven Commitment Decisions
- Instead of guessing: Cost Explorer quantifies tradeoffs — e.g., if twtech baseline is stable, it will show an SP commitment level that maximizes coverage for lowest cost.
- twtech can
compare between Compute SP and EC2 Instance SP options or between SP and RI scenarios.
FinOps Considerations
1) Risk of Over-Commitment
- Savings Plans commit you to paying a set $/hr even if usage dips; unused commitment still costs twtech money. RIs’ coverage risk is similar but with resource specificity.
2) Monitoring & Refresh
- twtech should refresh recommendations periodically (Cost Explorer) to adapt to workload changes.
- twtech avoids committing more than it actual baseline usage unless it is comfortable with the risk.
3) Hybrid Strategies Are Common
Many FinOps
teams use a hybrid approach:
- Standard RIs where twtech must reserve capacity or have unchanging fleets.
- Savings Plans for flexible compute across services/teams.
- Spot for elastic/dynamic workloads.
NB:
- Cost Explorer data underpins all of these decisions — letting twtech to quantify coverage, utilization, and real savings.
Practical Use-Cases in Cost Explorer
A) Baseline Analysis
- Identify long-running workloads and trend usage over months.
- Separate steady vs. variable usage.
B) Coverage Simulation
- Use Cost Explorer’s Savings Plans recommendations to simulate different commitment levels and view estimated savings.
- Compare SP vs RI recommendations and forecast future spend.
C) Utilization Tracking
- Post-purchase, use the SP Coverage & Utilization Reports to see if twtech commitment is fully used.
- Spot gaps where more coverage could lower costs.
D) Continual Re-Evaluation
- As usage shifts (new instance types, serverless growth, etc.), the suit re-runs recommendations to see if twtech commitments still make sense.
Key
Takeaways
- Savings Plans are generally the more flexible alternative to Reserved Instances, particularly for modern, evolving workloads.
- Cost Explorer is twtech primary analysis tool for comparing Savings Plans vs RIs, understanding how commitments map to usage, and how effectively commitments are applied.
- A data-driven FinOps approach (analyzing usage patterns, coverage, utilization) helps twtech to choose the right commitments and avoid over- or under-commitment.
- A blended strategy can unlock savings while managing capacity risk — and Cost Explorer informs all of it.
Link to useful documentation Resource:
https://docs.aws.amazon.com/savingsplans/latest/userguide/sp-ris.html?utm_source=chatgpt.com
twtech Insights:
AWS offers four types of Savings Plans:
1.
Compute Savings Plans,
2.
Database Savings Plans,
3.
EC2 Instance Savings Plans,
4.
SageMaker AI Savings Plans.
Compute Savings Plans:
- Provide the most flexibility and prices that are up to 66% off of On-Demand rates.
- Compute Savings Plans automatically apply to twtech EC2 instance usage, regardless of:
- instance family (for example, m5, c5, etc.),
- instance size (for example, c5.large, c5.xlarge, etc.),
- Region (for example, us-east-1, us-east-2, etc.),
- Operating system (for example, Windows, Linux, etc.),
- Tenancy (for example, Dedicated, default, Dedicated Host).
- Compute Savings Plans also apply to twtech Fargate and Lambda usage.
- With Compute Savings Plans, twtech can:
- Move a workload from c5 to m5,
- Shift its usage from Asia (Japan) to America (Ohio).
- Migrate its application from Amazon EC2 to Amazon
ECS using Fargate at any time.
- twtech can continue to benefit
from the low prices provided by Compute Savings Plans as it execute these changes.
- Provide flexibility to use AWS database
services while reducing costs by up to 35% on:
- Aurora,
- RDS,
- DynamoDB,
- ElastiCache,
- DocumentDB,
- Timestream,
- Neptune,
- Keyspaces,
- DMS.
- Engine,
- instance family,
- size,
- Availability Zone (AZ),
- Region,
- Serverless usage.
- change between Aurora db.r7g and db.r8g instances,
- Shift a workload from us-east-2 (Ohio) to South us-east-1 (North Virginia).
- Modernize from RDS for Oracle to Aurora PostgreSQL-Compatible Edition,
- Move a workload from RDS to DynamoDB while maintaining its discounted rates.
EC2 Instance Savings Plans
- Provide savings up to 72% off On-Demand, in exchange for a commitment to a specific instance family in
a chosen AWS Region (for example, m5 in
Virginia).
- Instance size (for example, m5.xlarge, m5.2xlarge, etc.),
- OS (for example, Windows, Linux, etc.),
- Tenancy (Host, Dedicated, Default) within the specified family in a Region.
- change its instance size
within the instance type (for example, from
c5.xlarge to c5.2xlarge),
- Change its operating system
(for example, from
Windows to Linux),
- Move from Dedicated tenancy to Default and continue to receive the discounted rate provided by its EC2
Instance Savings Plan.
- Provide savings up to 64% off for On-Demand rates.
- Instance family (for example, ml.m5, ml.c5, etc.),
- instance sizes (for example ml.c5.large, ml.c5.xlarge, etc.),
- Region (for example, us-east-1, us-east-2, etc.),
- component (for example, Notebook, Training, etc.).
- move a workload from ml.c5 to ml.m5,.
- Shift its usage from us-east-2 (Ohio) to us-west-1 (California).
- Migrate its usage from Training to
Inference at any time and continue to receive benefits.
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