Executive Summary: Large enterprises often face escalating AWS bills, but commitment-based discounts like AWS Savings Plans can cut cloud compute costs by up to 66–72%. However, maximizing these savings requires a strategic approach. This Gartner-style advisory presents 15 key strategies for CIOs, IT procurement leads, and FinOps teams to optimize AWS spending through Savings Plans. Each recommendation is explained with practical insights, examples illustrating impact or risk, and guidance to avoid common pitfalls. The goal is to help organizations significantly reduce costs while maintaining flexibility and performance.
AWS Savings Plans: Maximizing Commitment-Based Savings
AWS Savings Plans offer discounted rates in exchange for a one- or three-year usage commitment. While they are a powerful tool for cost optimization, common pitfalls can undermine their benefits if not managed properly. Below are some frequent mistakes enterprises make with Savings Plans, along with how to mitigate them:
- Overcommitting Capacity: Pitfall: Locking into more commitment than actual usage leads to wasted spend (you pay for unused capacity). Example: A team committed to $100/hour usage, but demand dropped to $80/hour, leaving $20/hour paid with no benefit. Mitigation: Commit conservatively to baseline needs and monitor utilization. Start with a lower commitment and add more Savings Plans if usage stays consistently high.
- Undercommitting Resources: Pitfall: Failing to cover steady workloads means missing out on huge discounts – effectively paying on-demand rates when you could pay much less. Example: An enterprise that kept half its instances on-demand spent ~50% more than necessary. Mitigation: Identify all predictable, 24/7 workloads and cover them with Savings Plans or Reserved Instances. Independent experts note that sticking to on-demand for stable workloads means forfeiting discounts of up to ~75%. Regularly review usage so you can increase commitments where safe.
- Choosing the Wrong Plan Type: Pitfall: Opting for a rigid plan (e.g., an EC2 Instance Plan tied to one region/instance family) for a workload that later changes can erode savings. Example: Committing all capacity to a specific instance type, then migrating to a new instance family, leaves your Savings Plan underutilized. Mitigation: Align plan type to workload stability. Use flexible Compute Plans for evolving workloads and Instance Plans only for truly static ones. When in doubt, favor flexibility or split commitments between plan types.
- Siloed Account Purchasing: Pitfall: Purchasing Savings Plans in an account that has its lower-cost usage can cause suboptimal allocation – AWS applies the discount to that account first, even if other accounts have higher-cost usage. Mitigation: Centralize Savings Plan purchases at the AWS Organization level. For example, buying Savings Plans in a dedicated billing account (with no direct resource usage) ensures the discounts automatically apply to the highest-cost workloads across all accounts, maximizing savings.
- “Set and Forget” Management: Pitfall: Treating a 3-year Savings Plan as a one-time task can backfire as your business changes. Mitigation: Institute a FinOps governance process – e.g., quarterly Savings Plan utilization and coverage reviews. If usage patterns shift (new projects, migrations, etc.), adjust by purchasing additional plans or planning for renewal changes. Ingrain cost awareness in teams so they continuously optimize (train engineers and finance staff on reading cost reports and Savings Plan metrics).
Organizations can confidently unlock maximum savings by understanding and addressing these pitfalls early. The next section outlines the top 15 practices to ensure your AWS Savings Plans strategy delivers optimal results.
15 Best Practices to Maximize AWS Savings Plan Benefits
1. Analyze and Forecast Your AWS Usage Patterns
Know your baseline: Thoroughly analyze your historical AWS usage before committing to anything. Use tools like AWS Cost Explorer and CloudWatch metrics to identify which workloads run consistently. Independent advisors recommend reviewing at least 6–12 months of usage data to spot trends. For example, you might find that your web application cluster consistently uses 100 EC2 instances 24/7, while dev/test environments scale down on weekends. Such patterns help pinpoint a safe commitment level. Example: Using Cost Explorer to examine the last six months of EC2 usage, one enterprise identified that 75% of its compute hours were steadily used in one region – a strong candidate for Savings Plans. Armed with this data, forecast future needs (consider upcoming projects, seasonal peaks, etc.). Accurate forecasting ensures you commit to an amount you can use, which is the cornerstone of maximizing Savings Plan value.
2. Rightsize and Optimize Before Committing
Buying a Savings Plan for inefficient infrastructure locks in that inefficiency. Rightsize your resources first. Ensure instances are correctly sized and unused resources are eliminated before you commit. This avoids paying to “reserve” capacity you don’t truly need. As independent experts note, overprovisioned resources lead to “wasted savings” – you might get a discount, but still be overspending on an oversized instance. Example: A company had 3 EC2 instances running at 10% CPU. By downsizing t2 large to t2 medium, before purchasing a plan, their monthly cost dropped from $193 to $96 – a ~$97/month saving, even before Savings Plans discounts. This lower usage baseline meant they could commit to a smaller hourly rate and still cover their needs. Tip: Leverage AWS’s Rightsizing Recommendations and tools like AWS Trusted Advisor to find optimization opportunities. By trimming the fat first, every dollar committed via Savings Plans goes toward productive use.
3. Choose the Right Savings Plan Type (Compute vs. Instance vs. SageMaker)
Not all Savings Plans are identical – selecting the proper type is crucial. AWS offers Compute Savings Plans (maximum flexibility across instance families, regions, OS, and even AWS services like Lambda and Fargate) and EC2 Instance Savings Plans (deeper discounts of up to 72% but locked to a specific instance family in a single region). SageMaker Savings Plans for ML workloads also offer up to 64% off SageMaker instance usage. Match plan to workload: If your workloads frequently change instance types or regions, a Compute Savings Plan is recommended for its versatility. For highly stable, predictable servers (say, a legacy database cluster that will run in the US-East on m5.xlarge for years), an EC2 Instance Plan can yield slightly higher savings. Example: A global retailer adopted a Compute Savings Plan for its autoscaling web tier (ensuring any instance type in any region got discounted) but used an EC2 Instance Plan for a fixed fleet of analytics servers that never changed region. Meanwhile, their data science team leveraged a SageMaker Savings Plan to slash machine learning platform costs by ~64%. Mixing plan types: Many organizations use a mix – e.g., Compute Plans for flexibility and a few Instance Plans for well-known steady workloads – to balance agility and maximum savings.
4. Determine an Optimal Commitment Amount (Coverage vs. Utilization)
A key decision is how much capacity to commit. The goal is to maximize savings without overcommitting. This means covering as much of your steady-state usage as possible (to get discounts) while leaving a buffer for variability. A good rule of thumb is to aim for about 80–85% coverage of your average usage with commitments. This ensures most of your usage is at discounted rates, but you have ~15–20% headroom for unexpected spikes or growth. Example: If your organization averages 1,000 EC2 hours of usage per day, you might commit to ~800 hours in Savings Plans and leave ~200 hours for burst demand on on-demand or Spot instances. This strategy was echoed by independent FinOps consultants who suggest ~80% coverage as a sweet spot. Monitor “utilization rate”: Once you purchase a Savings Plan, track its utilization. Ideally, a Savings Plan’s utilization (the percentage of the purchased commitment used) should be ~100%. You overcommitted if it’s consistently lower (e.g., you only use 60% of what you paid for). By carefully calculating a slightly conservative commitment upfront, you can achieve high utilization and coverage – the perfect balance for savings.
5. Select the Right Term Length and Payment Option
Savings Plans offer 1-year or 3-year terms, and you can pay No Upfront, Partial Upfront, or All Upfront. These choices significantly affect your savings and should align with your financial planning:
- 1-Year vs 3-Year: A 3-year commitment provides deeper discounts but locks you in longer. For example, compute workloads get roughly 50–55 %+ off with a 3-year term vs ~30% off with a 1-year term. One independent analysis showed a 3-year all-upfront plan yielding ~54% savings, compared to ~27–32% on a 1-year plan. If your usage is stable and long-lived, the extra savings of 3-year plans can be very attractive. However, if you expect significant changes in the next year or want more flexibility, the 1-year plan might be safer despite the slightly lower discounts.
- Upfront Payment Options: Paying All Upfront maximizes the discount rate (and may help use up the budget or meet AWS enterprise spend commitments). In contrast, No Upfront means nothing to pay today, but a higher rate (smaller discount). For instance, an m5.16xlarge 1-year plan might be ~27% off with no upfront versus ~32% off if paid fully upfront. All Upfront 3-year deals can exceed 50% savings. Consider your budget and cash flow: Large enterprises often have capital expenditure budgets or need to utilize funds by year-end – an all-upfront purchase can make sense in those cases (and ensures maximum savings locked in). Otherwise, many organizations prefer partial or no upfront for cash flexibility, accepting a slightly smaller discount.
Example scenario: A fintech company identified a core workload that would run for 3+ years. They chose a 3-year term, All Upfront on that portion, achieving ~50% cost reduction on those instances. For newer workloads where 3-year certainty was lower, they used 1-year No Upfront plans ( ~30% savings ). This blended approach improved savings while managing risk. Bottom line: Align terms and payment with confidence in the workload’s longevity and your organization’s financial strategy. When in doubt, a shorter term or less upfront reduces commitment risk, whereas longer terms and upfront payments maximize savings if you’re confident in steady usage.
6. Leverage AWS Cost Management Tools and Reports
Take advantage of AWS’s tooling to manage and optimize your Savings Plans: AWS Cost Explorer, AWS Budgets, and Cost & Usage Reports are your friends.
- Savings Plan Recommendations: AWS Cost Explorer can recommend Savings Plans based on your past usage. This is a good starting point to identify potential savings. Always review these recommendations critically (they assume the past is prologue), but they help size your commitments.
- Utilization and Coverage Reports: AWS provides dedicated reports for Savings Plan utilization (%) and coverage (% of total usage covered by Savings Plans). Set these up to track how well you’re doing. For example, a utilization report might reveal you only used 90% of your committed hours last month, indicating some waste. A coverage report might show that only 60% of your EC2 hours are covered by Savings Plans, flagging an opportunity to buy more plans for better savings.
- AWS Budgets & Alerts: Establish budgets and alerts to keep costs in check. For instance, set a monthly cloud spending budget and get alerted at 80% of the budget. This can indirectly help Savings Plan management – if on-demand costs spike (maybe a sign that coverage dropped or a Savings Plan expired), an alert will prompt you to investigate. Example: A media company set up an AWS Budget alert when monthly EC2 spending exceeds a threshold; one quarter, the alert triggered, and they discovered a lapsed Savings Plan that wasn’t renewed, causing costs to jump. They promptly purchased a new plan, bringing costs back down.
- Third-Party FinOps Tools: Consider using third-party cloud cost management platforms or FinOps dashboards for more advanced analytics. Tools can automatically detect anomalies, simulate Savings Plan purchases, or allocate costs to business units. For large organizations, these tools complement AWS’s native tooling by providing custom reports, forecasts, and even automation (some services automatically buy and sell RIs/Savings Plans within set policies).
Make these reports and tools part of your team’s routine. For example, schedule a monthly cost review meeting where the FinOps team presents Savings Plan utilization and coverage stats to IT leadership. Consistent use of cost management tools ensures you spot issues early and continuously optimize your savings strategy.
7. Share and Allocate Savings Plans Across Accounts (Organization-Wide)
Large enterprises typically use multiple AWS accounts (per project, team, or region). The good news is that Savings Plans apply across your AWS Organization by default – meaning one account’s Savings Plan can cover usage in another, as long as they are linked under the same payer account. To maximize this benefit, centralize your Savings Plan purchases rather than buying separate plans in each account.
Best practice: Consider using a dedicated billing account with no resources to purchase all Savings Plans. This trick forces AWS to apply the Savings Plan discounts to whichever account’s usage yields the greatest savings first (since the purchase account has none of its usage). According to independent experts, if you tie a Savings Plan to an account with existing usage, it will prioritize that account’s resources even if other accounts have costlier usage that could benefit more. By purchasing in a top-level empty account, you ensure the Savings Plan floats to cover the highest on-demand costs anywhere in the org.
Example: A global SaaS company had one account running only Linux EC2 instances (cheap per hour) and another running Windows SQL Server instances (high hourly cost). When each account bought its own savings plan, the Linux account’s plan didn’t help the Windows account, which kept paying on-demand for very expensive instances. They switched to buying all Savings Plans via the master billing account. This way, the discounts could fully apply to the Windows instances first (maximizing dollar savings), with any leftover discount covering Linux instances. The result was higher overall savings with the same commitment.
Allocate costs fairly: Internally, use tagging or cost allocation reports to apportion the Savings Plan benefits to the appropriate teams. This prevents the “tragedy of commons” where one team’s unused commitment could benefit others, but budgeting silos discourage it. By treating savings plans as an organizational asset, enterprises ensure that no capacity is unused and that every department benefits proportionally from cost savings.
8. Integrate FinOps Governance and Accountability
Make cost optimization a continuous, cross-functional process. Savings Plan management shouldn’t be a one-off task; it needs ongoing attention from both finance and engineering. Establish a FinOps governance model with clear roles, regular meetings, and KPIs around cloud cost.
- Cross-Team Collaboration: Bring Finance, Cloud Ops, and application teams together on cloud spending decisions. For example, a FinOps committee (chaired by the CIO or CFO office) can meet quarterly to review cost reports and upcoming needs. Regular reviews are essential – a scheduled cadence (monthly for operational reviews, quarterly for strategic adjustments) ensures cost commitments stay aligned with business needs. In these meetings, identify new trends (e.g., a project ramping up usage) and decide if adjustments (like buying another Savings Plan or retiring unused resources) are needed.
- Define Ownership: Assign clear ownership for the Savings Plan strategy. Often, a FinOps lead or Cloud Cost Manager will own tracking Savings Plan performance (utilization, coverage, renewal dates) and drive decisions on new purchases. This person/team should interface with procurement for approvals and with technical teams for implementation. By having accountability, you avoid Savings Plans being “someone else’s problem” that falls through the cracks.
- Educate and Empower Teams: Invest in training engineers and architects on cost awareness. Independent licensing experts such as Redress Compliance emphasize that teams must understand how to monitor and adjust commitments to maintain cost-effective practices. Conduct workshops on using AWS Cost Explorer, interpreting Savings Plans reports, and designing cost-efficient architectures. When developers plan a new service, they should automatically consider if it will run continuously (and thus merit a Savings Plan) or if it can use Spot instances, etc. Example: A fintech company included cloud cost training in their engineer onboarding. Developers learned to tag resources by project and saw reports of their projects’ Savings Plan utilization. This transparency created positive peer pressure to keep utilization high and waste low.
- KPIs and Incentives: Track metrics like “Savings Plan Utilization (%)”, “Coverage (%) of total compute spend under commitments”, and savings achieved vs. potential. Share these metrics with executives. Some enterprises even set cost optimization targets (e.g., increase RI/SP coverage from 70% to 85% by year-end) and include them in performance objectives for relevant teams. Savings Plan optimization becomes ingrained in the company culture when everyone is accountable for cloud efficiency.
9. Continuously Monitor Savings Plan Utilization and Coverage
Purchasing a Savings Plan is not a one-and-done event – you must continually monitor performance to ensure you’re getting the expected savings. Two key metrics deserve constant attention:
- Savings Plan Utilization: This measures how much of your purchased commitment you are consuming. A 100% utilization means every committed dollar is used by equivalent resource usage (ideal), whereas 80% utilization means 20% of your commitment is going unused (wasted spend). Use the AWS Cost Explorer Utilization report to check this. If utilization is consistently below 100%, investigate why. Perhaps you overestimated usage or decommissioned some instances. Mitigation: Look to redirect workloads to use the spare capacity (e.g., is some workload running on-demand that could be shifted under the Savings Plan?). In extreme cases of overcommitment, you may have to accept some sunk costs and ensure you do not renew at that level.
- Coverage of On-Demand Spend: Coverage is the flip side – what percentage of your total compute hours (or dollars) are covered by Savings Plans (or RIs) versus on-demand. If coverage is low (meaning a lot is still in demand), you’re leaving savings opportunities on the table. Many FinOps teams set a target coverage (e.g., “at least 80% of our steady-state compute spend should be at discounted rates”). The AWS Coverage report can show this. If you see only, say, Savings Plans cover 50% of your EC2 spend, that flags a potential to buy more commitments (assuming those on-demand workloads are indeed long-running). Example: One SaaS company monitored coverage and found it dipped to 60% after rapid growth in a new region. They realized they hadn’t bought Savings Plans for the new instances in Southeast. By purchasing additional Savings Plans for that region’s usage, they raised coverage to 85% and saved 20% on that new workload’s costs.
Automate monitoring where possible: Consider setting up alarms or scripts to watch these metrics. You could use AWS CloudWatch Events with a Lambda function to alert if Savings Plan utilization drops below 95% for a certain period. This kind of proactive monitoring (sometimes called Cost Ops) ensures that no savings plan goes underutilized for long without someone knowing. By keeping a close eye on utilization and coverage, you can tune your commitments over time – buying additional plans when needed or curbing usage if you’re overcommitted – to continuously maximize savings.
10. Beware of Overcommitment and Plan for Uncertainty
Overcommitment is one of the biggest risks with Savings Plans. It occurs when you commit to more usage than you need, resulting in paid but unused capacity. As noted earlier, this can happen if you overestimate growth or fail to account for workload variability. To avoid costly overcommitment:
- Commit in Stages: Instead of making one giant 3-year commitment upfront, consider phasing your purchases. For example, you might start by committing to 50% of your estimated need, then ramp up to 70% after a few months of observing actual usage, and so on. AWS allows you to purchase new Savings Plans at any time, so you have the flexibility to increase commitments later. Still, you cannot reduce an existing commitment until it expires. It’s safer to under-commit initially and gradually top-up than to over-commit and have unused discounts.
- Use Shorter Terms for Unpredictable Areas: If parts of your environment are new or likely to change within a year (e.g., a pilot project or a workload that may be re-architected), consider using 1-year Savings Plans for those, or even hold off until the usage stabilizes. Save 3-year commitments for very stable, core services. This way, you aren’t locked in too long if things change. One strategy is to have a mix of 1-year and 3-year plans aligned to confidence levels (we discuss mixing strategies more in item 14).
- Track and Reforecast: Treat your committed spend as its own “budget”. If you committed to $10k/month of computing, and your actual usage starts dipping below that, that’s a red flag. Immediately investigate whether the drop is temporary or structural. If it’s a lasting drop (e.g., you optimized some workloads), you might shift other workloads onto AWS to use up the commitment or avoid buying new plans. If you have an AWS Enterprise Agreement (EDP) with a spending commitment, coordinate those with Savings Plans (more on that later). Forecast regularly – don’t rely only on the initial plan. Business conditions (product demand, M&A, etc.) can change, so revisit your usage forecast at least quarterly and adjust future Savings Plan purchases accordingly.
Example: A large media company committed very heavily to EC2 Savings Plans, expecting a big customer growth that didn’t fully materialize. They ended up with ~15% of their compute commitment unused, effectively overspending hundreds of thousands of dollars. The lesson they learned was to commit more conservatively and use shorter-term plans for uncertain growth areas. They now maintain a policy to never commit above 90% of last quarter’s steady usage and to always leave some buffer for safety.
Overcommitting can “lock up” a budget that could have been used elsewhere. You can mitigate the risk by planning for uncertainty through phased commitments, diversified terms, and constant re-evaluation. As one cloud cost expert put it, Savings Plans require thoughtful planning to maximize benefits and align with organizational goals – in other words, don’t overshoot your needs.
11. Avoid Undercommitment: Don’t Leave Money on the Table
While being cautious is wise, be careful not to swing too far and undercommit relative to your steady usage. Undercommitment means you are running significant workloads on on-demand pricing that could be covered by a Savings Plan – essentially forgoing savings that you could capture with a bit more commitment. The cost of hesitating to commit is real: on-demand rates can be 2x-4x more expensive than committed rates for the same resource. Industry analyses show that organizations that rely only on on-demand for predictable workloads pay dramatically more, missing discounts up to 72% (or even 75% in some cases) that AWS offers.
Identify low-risk commitments: Look for compute usage that has been very consistent over time (e.g., always-on servers, baseline microservices, nightly batch jobs that run like clockwork). If a Savings Plan or RI does not cover these, that’s low-hanging fruit for optimization. For example, if you have a database cluster that has run 8 XL instances for the past year, running it on-demand is burning money – you can confidently commit those 8 XL instances to a Savings Plan and instantly save perhaps 30-50%.
Quantify the opportunity cost: It sometimes helps illustrate the impact on stakeholders. Example: An e-commerce company realized they were only 50% covered by Savings Plans, meaning half their usage was on-demand. Their FinOps lead calculated that covering an additional $50,000/month of on-demand usage with Savings Plans would yield roughly $20,000/month in savings at a 40% discount rate. That’s $240,000/year of potential savings they were leaving on the table by not committing. Seeing that number made executives believe increasing the Savings Plan coverage was worth the commitment risk. They purchased additional Savings Plans to reach ~85% coverage, significantly reducing their cloud bill.
Use AWS recommendations and expert input: AWS’s recommendation tool often flags under-commitment by suggesting you purchase more Savings Plans (with an estimated savings amount). Third-party advisors or consultants (like independent licensing experts from Redress Compliance or ProsperOps-type services) can also help analyze your usage and confidently identify where committing more will pay off. If you’ve done the homework on your usage patterns (as in item #1), trust the data – don’t shy away from the commitment to long-term resources.
In sum, be bold enough to commit to known steady workloads. Undercommitting not only means higher costs but can also signal to finance that you’re not fully optimizing spending. The key is to find the optimal commitment level (as discussed in item #4) and then ensure you commit that amount. Cloud cost efficiency is a competitive advantage, and undercommitting is an opportunity cost you can ill afford in a large-scale environment.
12. Consider the AWS Enterprise Discount Program (EDP) for Additional Savings
For organizations with very large AWS spend (typically millions of dollars per year), AWS’s Enterprise Discount Program (EDP) can be another avenue to reduce costs. An EDP is a custom enterprise agreement where you commit to spend a certain amount (often over 3-5 years) across AWS in exchange for overall discounts or credits. It’s essentially a volume-based discount program, not tied to specific services like Savings Plans are.
How EDP complements Savings Plans: Think of EDP as a macro-level commitment and Savings Plans as a micro-level (service-specific) commitment. They are not mutually exclusive – in fact, they stack in practice. For example, you might negotiate a 10% overall discount via EDP due to committing $20M/year to AWS and using Savings Plans to get 50% off your EC2 usage. The Savings Plan discount applies first to reduce the EC2 costs, and then your EDP discount might apply on top of the already-reduced spending (or AWS might give it as a credit structure). The specifics depend on your EDP terms. The point is that large enterprises should pursue both: use Savings Plans to minimize spend, and an EDP to get an additional percentage off the total bill.
However, EDPs come with their commitment risks and complexity:
- High Commit Levels: EDPs require a significant minimum spend (often starting at $1M–$ 5 M+ per year). They make sense only if your AWS usage is already at that scale or growing.
- Broad Coverage: The discount typically covers most AWS services broadly, which is great for things Savings Plans don’t cover (like RDS, S3, etc.). This can simplify cost management – basically, all spending contributes to fulfilling your commitment.
- Negotiation and Terms: EDP contracts with AWS sales can span 1 to 5 years. They require forecasting your total AWS spend accurately. You might lose the discount or incur penalties if you underuse an EDP (don’t meet your committed spend). If you overuse, you pay extra (though sometimes you can amend the contract or true-up later).
When to leverage EDP: According to independent experts, AWS EDP is ideal for large-scale, long-term AWS customers with diverse services and consistently high spending. If you’re a Fortune 500 firm running on AWS, an EDP can yield broad savings beyond what service-specific plans can do. Conversely, sticking with Savings Plans and RIs might be more practical if your footprint is smaller or uncertain.
Example: A global manufacturing company spending ~$10 million annually on AWS entered a 3-year EDP, committing to $40 million over 3 years. In return, AWS provided a structured discount (plus some free support and training credits). This gave the company ~12% off their total bill. They still used Savings Plans for EC2/Lambda to get those specific savings, which helped them comfortably meet the committed spend (since Savings Plans still count as AWS spend). The EDP essentially amplified their savings across all services.
Best practice: If you pursue an EDP, align it with your Savings Plan strategy. Use your spending forecasts (from item #1) to negotiate the right commitment level. And ensure you maintain high Savings Plan utilization. Since an EDP typically counts after such discounts, you don’t want to underutilize Savings Plans and then struggle to reach the EDP spend commitment. In essence, EDPs and Savings Plans together form a layered approach: Savings Plans drive maximum savings on computing, and EDPs give bulk savings on everything. Engaging independent licensing consultants (like Redress Compliance) or AWS cost advisors can help structure these deals favorably and verify that the math works out in your case.
13. Extend Commitment-Based Savings to All Eligible Services (Not Just EC2)
AWS Savings Plans primarily cover computing services, such as EC2, Fargate, and Lambda (plus SageMaker for that specific plan). However, large organizations consume many other AWS services, some offering reservation or savings models. To truly optimize AWS spend, don’t stop at EC2 Savings Plans; look at other services with commit discounts and incorporate those into your strategy:
- Databases (Amazon RDS, Amazon Redshift, DynamoDB) offer Reserved Instances/capacity options. RDS and Redshift Reserved Instances can save you around 30–65%, similar to EC2 RIs. DynamoDB has Reserved Capacity pricing. Savings Plans do not cover RDS, Redshift, ElastiCache, DynamoDB, etc., so if you have large, steady usage on these, use their native reservation offerings. Example: A SaaS company had an Oracle database on RDS that was running full-time. By purchasing a 3-year Reserved Instance for that RDS database, they saved 40% compared to on-demand. This RDS RI worked with their EC2 Savings Plans, covering the database layer savings that Savings Plans couldn’t reach.
- Data Warehousing and Analytics: Redshift, EMR, and OpenSearch (ElasticSearch) have reservation models. Use Redshift Reserved Nodes, EMR contracts, etc., if applicable. For OpenSearch (Amazon OpenSearch Service), consider its reserved instance option.
- Other Commit Programs: AWS has Savings Plans for AWS Compute (we covered) and things like Reserved Capacity for SageMaker endpoints (distinct from SageMaker Savings Plans, which cover the instance usage). Even Amazon S3 has bulk discount tiers but no explicit reservation – however, if you have a long-term data storage need, you can use S3’s Intelligent Tiering or Glacier for cost savings (not a commitment, but lifecycle management). While not “Savings Plans”, these choices are similar in spirit – committing to a usage pattern for lower cost.
- Marketplace and Enterprise Software Licensing: If running enterprise software on AWS (Oracle, SAP, etc.), optimize those licenses too. While beyond AWS Savings Plans directly, it’s part of the overall cost picture. (Always consult independent licensing experts to ensure you’re compliant and not overpaying for licenses on the cloud; companies like Redress Compliance specialize in this, though that’s tangential to AWS Savings Plans focus.)
The main point is to treat all your major AWS expenses with a savings mindset. AWS environments in large orgs include databases, caching layers, data lakes, etc. For each service, evaluate if there’s a long-term commitment option. Often, Reserved Instances are the counterpart to Savings Plans for these other services. AWS recommends combining Savings Plans and RIs to maximize savings across different workloads.
Extending your cost optimization to every tier (computing, database, storage) ensures no big cost center is left paying the full price. Many companies achieve significant savings by doing this: e.g., covering 80% + of EC2 with Savings Plans and 80% + of RDS/Redshift with RIs. The savings all add up to the bottom line. Use AWS’s Cost Explorer “Purchase option” filter to see how much each service’s cost is On-Demand vs Reserved; any big chunk of On-Demand for a steady service is an opportunity to execute a reservation. A holistic commitment strategy across services will yield a significantly lower total AWS bill for the same usage.
14. Mix and Match Commitment Strategies for Flexibility and Maximum Savings
Sophisticated enterprises treat cloud commitments like a portfolio, mixing different commitments to balance risk and reward. Just as an investment portfolio might blend stocks and bonds, a cloud cost portfolio can blend various commitment terms and options:
- Blend 1-year and 3-year terms: You might use 3-year Savings Plans for the most stable core of your infrastructure (to lock in the highest savings rate) and 1-year plans for areas where you want more flexibility. For instance, commit 60% of your baseline usage on 3-year plans and another 20% on 1-year plans. This way, if your needs change, you’re never more than a few months away from adjusting some of your commitments. Many organizations find 1-year commitments easier to plan for, using them heavily, and only go to 3-year commitments for things they’re very confident will not change. This staggered approach also means not all commitments come up for renewal simultaneously, smoothing out procurement and budget impacts.
- Mix All Upfront vs. No Upfront: You can mix payment options. Perhaps take a few large Savings Plans as All Upfront (to get better pricing and utilize available budget), and others as No Upfront (to spread payments monthly). This can help with internal budgeting – e.g., using a leftover budget at the end of the year to purchase an All Upfront plan, which yields lower monthly bills in the subsequent year.
- Diversify across Plan Types: As discussed in #3, combining Compute Savings Plans for flexibility and EC2 Instance Savings Plans for specific known workloads can yield a good balance. You might also consider Standard vs Convertible RIs (if you still use RIs) in the mix. For example, before Savings Plans existed, a common tactic was to use Standard RIs for the very steady stuff and Convertible RIs for areas that might change (because convertibles could be exchanged for different types). Compute Savings Plans largely replace the need for Convertible RIs by providing built-in flexibility. But you might still juggle a combination if you have some legacy RIs or specific needs (like RDS).
- Spot and On-Demand for the rest: Ensure your strategy acknowledges that some workloads remain on-demand or Spot. For truly stateless or fault-tolerant tasks, using Spot instances (with 70-90% discounts but possible interruptions) is the cheapest option, even cheaper than Savings Plans. Some enterprises run certain dev/test or big data processing on Spot, saving huge amounts. You wouldn’t cover those workloads with Savings Plans because they intentionally use Spot when available. Conversely, any on-demand usage that’s not sporadic or suitable for Spot should be evaluated for Savings Plan coverage. Essentially, each workload should have a cost strategy: either it’s covered by a commitment (Savings Plan/RI), or it’s using Spot, or it truly needs on-demand (rare cases like very spiky, unpredictable, short jobs). Being conscious of this ensures you maximize savings across the board.
Example of a mixed strategy: A global e-commerce company broke down its cloud usage into tiers:
- Tier 1 (Critical steady workloads): e.g., checkout service, databases. These ran 24/7. The company put these on 3-year All-Upfront Savings Plans (and RDS RIs for databases) to get the absolute lowest rate.
- Tier 2 (Important but evolving workloads): e.g., recommendation engine, which might be redesigned within a year. They used 1-year No-Upfront Savings Plans for these – still getting ~30% off but with the ability to not renew or change strategy a year later.
- Tier 3 (Batch and dev workloads): e.g., nightly data processing, QA environments that could handle interruptions. These were run on Spot instances mostly. They purchased only a small 1-year Savings Plan for baseline needs here and left the rest to the Spot market.
- Tier 4 (New experimental workloads): no commitments initially; run on-demand until patterns emerge, then move to the appropriate tier above in the next cycle.
This diversified approach yielded an overall compute cost reduction of about 45% versus on-demand while retaining flexibility to adjust. Crucially, it prevented under- and over-commitment by not using a one-size-fits-all plan.
Action item: Review your workloads and consider categorizing them by how predictable or changeable they are. Apply a suitable commitment strategy to each category. Don’t put all your eggs in one basket – a mix of term lengths, payment options, and plan types can optimize savings while hedging against the unknown. By treating cloud commitments as a portfolio to be managed, you can dynamically optimize as conditions change, much like rebalancing investments.
15. Continuously Reevaluate and Evolve Your Savings Plan Strategy
Cloud environments are dynamic, and so must be your cost optimization strategy. The “set and forget” approach doesn’t work in the long run. Commit to a process of continuous improvement for your AWS Savings Plans usage:
- Regular Renewal Planning: Always know when your existing Savings Plans expire. Plan renewals well in advance. For 1-year plans, start reviewing renewal options a couple of months out: do you extend them, increase, decrease, or shift to a different type? For 3-year plans, begin reassessing at least 6 months before expiry. AWS will typically notify you of expiring Savings Plans, but don’t wait passively – incorporate it into your roadmap. Some organizations keep a calendar of commitment expiry dates and align them with budgeting cycles. Example: An entertainment company had a major 3-year Savings Plan expiring Q4 this year. In Q2, their FinOps team already analyzed current needs and prepared a recommendation to renew with a different mix (they had moved lots of workloads to containers, so they decided to go with Compute Savings Plans this time instead of the older EC2 instance plans). This proactive approach ensured a seamless transition with no period of unnecessarily paying on demand.
- Adapt to Changing Usage: Implement a feedback loop where changes in your AWS usage trigger reevaluation of your Savings Plan coverage. If a new project is ramping up or an old system is being retired, immediately factor that into your commit strategy. For growing workloads, you might purchase additional Savings Plans mid-year to cover the growth rather than waiting. You might decide not to renew some plans or switch types for shrinking or shifting workloads. AWS’s utilization and coverage reports (and your monitoring from item #9) will inform these decisions. A good practice is a quarterly analysis of Savings Plan performance and any upcoming capacity changes so that you can adjust incrementally rather than being caught off guard.
- Stay Updated on AWS Offerings: AWS pricing and services evolve. They may introduce new Savings Plans or pricing models (for example, AWS has added SageMaker Savings Plans, and who knows, maybe plans for other services). Stay informed via AWS announcements regarding Invent conferences or expert blogs. New tools or features (like AWS Compute Optimizer improvements or changes to the AWS Marketplace for RIs) could open up further savings. Being an early adopter of a beneficial change can give you an edge. Engaging with the FinOps community or AWS user groups can also yield tips on optimizing that you hadn’t considered.
- Benchmark and Learn: Compare your organization’s cloud cost efficiency against industry benchmarks. Effective cost per EC2 instance-hour, percent of spend on commitments vs. on-demand, etc., can show if you’re leading or lagging. Get external audits or use SaaS tools to score your FinOps maturity if possible. Large enterprises sometimes bring in consultants (independent of AWS) to review their cloud cost strategy annually. This can highlight blind spots or new savings opportunities.
Finally, cultivate a culture of cost awareness. When engineers and architects know that cost optimization is an ongoing effort, they will design with that in mind (e.g., turning off resources, using serverless to auto-scale to zero, etc., in addition to Savings Plans). Incorporate cloud cost metrics into business reviews so they stay on leadership’s radar.
AWS Savings Plans management should be treated as a living process, like performance tuning or security monitoring. Set goals (e.g., improve Savings Plan utilization to 99%, maintain 85% coverage, reduce waste to <$5k/month, etc.), track progress, and iterate. Organizations that excel in cloud cost optimization regularly revisit and refine their tactics, ensuring they extract maximum value from AWS while supporting business needs. With the 15 practices outlined above, your enterprise can do the same, achieving significant AWS cost savings year after year and avoiding the pitfalls that can erode those savings.
