Compute Optimizer Rightsizing
Instance-level recommendations from AWS Compute Optimizer, checked against CloudWatch memory and p99 CPU before anything is resized, so a cheaper instance does not become a latency incident.
EC2 Cost Optimization
Most EC2 bills carry three kinds of waste: oversized instances, On-Demand rates on steady workloads, and commitments bought before rightsizing. We fix them in that order, so you never lock in a discount on capacity you do not need.
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EC2 is usually the largest line on an AWS bill, and the waste in it has a predictable shape. Instances are sized for a launch-day guess and never revisited. Steady workloads stay on On-Demand rates for years. Commitments get bought against the oversized fleet, which turns a temporary problem into a three-year contract. And EBS volumes created before gp3 existed are still paying gp2 rates.
We work the problem in a fixed order because each step changes the baseline for the next one.
Rightsizing starts with AWS Compute Optimizer recommendations, but we do not apply them blind. Compute Optimizer needs the CloudWatch agent to see memory, and an instance that looks idle on CPU can be memory-bound. For each candidate we check:
The rightsizing playbook covers the method in detail, and the rightsizing savings calculator gives a first estimate from your instance list.
Graviton. Arm64 instances list below their x86 equivalents: in our pricing data an m7g.large is $0.0816/hr against $0.1008/hr for an m7i.large. We rebuild container images as multi-arch, benchmark each service on Graviton, and move the ones that hold their throughput. See the Graviton cost optimization guide.
Spot. For stateless and fault-tolerant capacity, Spot runs at up to 90% off On-Demand. Safe Spot use needs diversified instance types, the price-capacity-optimized allocation strategy, Capacity Rebalancing, and a shutdown handler for the two-minute notice. On EKS, Karpenter handles most of this. The Spot selection guide and the Spot instance advisor help pick pools.
EBS gp2 to gp3. gp3 is 20% cheaper per GiB-month than gp2 and decouples IOPS from size. We convert in place and set IOPS and throughput explicitly for any volume whose gp2 baseline was above 3,000 IOPS.
Only after the fleet is rightsized and the architecture changes are in flight do we buy commitments:
| Commitment | Discount vs On-Demand | Flexibility | Best fit |
|---|---|---|---|
| Compute Savings Plans | Up to 66% | Any family, size, Region, OS; also Fargate and Lambda | Spend that will move, including Graviton migrations in progress |
| EC2 Instance Savings Plans | Up to 72% | Any size and OS within one family in one Region | Stable families you will not migrate |
| Standard Reserved Instances | Up to 72% | Fixed family; Regional RIs allow size flexibility | Existing RI processes, or capacity reservations in a zone |
Discount figures are AWS’s published maximums. The RI vs Savings Plans decision guide walks through the trade-offs, and the Savings Plans calculator models coverage at your spend level.
Savings decay without guardrails. We set up AWS Budgets, Cost Anomaly Detection, and alerts on Savings Plans coverage and utilization, and hand over a monthly review checklist. For a full FinOps operating model beyond EC2, see FinOps consulting and AWS cost optimization services.
Before an engagement, run your fleet through the EC2 pricing calculator to compare On-Demand, Spot, and Reserved rates by instance type, and read the EC2 On-Demand pricing breakdown for family-level rates and regional multipliers. For a published example of the full process, see our SaaS cost optimization case study, which took a monthly bill from $85k to $58k.
Instance-level recommendations from AWS Compute Optimizer, checked against CloudWatch memory and p99 CPU before anything is resized, so a cheaper instance does not become a latency incident.
A commitment mix sized to your post-rightsizing baseline: Compute Savings Plans where workloads move between families or to Fargate and Lambda, EC2 Instance Savings Plans or Standard RIs where a family is stable.
Spot for stateless, fault-tolerant capacity with diversified instance pools, price-capacity-optimized allocation, Capacity Rebalancing, and two-minute interruption handling built into the deploy path.
Arm64 builds, multi-arch container images, and a per-service benchmark so the Graviton move is measured on your workload, not on a vendor slide.
In-place gp2 to gp3 volume modification with explicit IOPS and throughput settings, so volumes that relied on gp2 burst behavior keep their performance.
Budgets, Cost Anomaly Detection, and Savings Plans coverage and utilization alerts, so the bill does not drift back after the engagement ends.
Commitments are bought against the fleet after rightsizing, not before. Reserving an oversized instance locks in waste for one to three years.
Our cost-optimization engagements average 35% AWS cost reduction. One SaaS client went from $85k to $58k per month (32%), and that case study is published in full.
AWS Select Tier Services Partner with 50+ AWS certifications on staff.
Our EC2 pricing, Savings Plans, rightsizing, and Spot calculators are public. Run the numbers yourself before you talk to us.
Implementation guides for this service from our team of AWS experts.
Compute Optimizer added 32-day lookback for cyclic workloads in 2025 — critical for monthly batch jobs that looked oversized on 14-day windows. In a June 2026 audit of a $48k/mo account, rightsizing recommendations alone modeled $11k/mo savings at low performance risk.
AWS Graviton processors deliver 20-40% cost savings and better performance-per-watt. Complete guide: migration path, performance benchmarks, and production deployment patterns.
Cheapest Spot pool is often the unstable one. July 2026: price-capacity-optimized + attribute-based selection, stability scoring, interruption hygiene — before you chase $/hr.
Most "RI vs Savings Plan" content treats them as peers. In mid-2026 they are not. A 3-year All-Upfront Compute Savings Plan saves a composite ~$60k/mo SaaS roughly $864k over 3 years vs a 1-year No-Upfront plan—but breaks even at ~22 months and locks instance-family flexibility. Buy the wrong commitment and a Graviton migration strands the discount. Here is the decision tree we use.
EC2 On-Demand is a matrix of family, size, OS, tenancy, and region. In us-east-1 (June 2026) a m7g.large Linux runs $0.0816/hr vs a g5.xlarge GPU at $1.006/hr. Graviton5 M9g/C9g now GA for new fleets.
In-depth guides and best practices from our certified AWS architects.
Eight AWS launches from October 14–20, 2026, ranked by what they change on the bill. ECS Gateway puts 25 services on one ALB (~$394/mo less in us-east-1 hourly charges); two others are not cost launches at all.
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Read articleIn-depth comparisons to help you choose the right approach before engaging.
First-principles comparison of AWS EC2 vs Lambda. Cost crossover points, execution time limits, and architecture decisions.
FinOps platforms show where AWS spend goes. Real savings come from architecture changes, tagging discipline, and commitment strategy — implementation, not dashboards.
Compare nOps and AWS Cost Optimization Hub — when native FinOps tools suffice and when you need architecture implementation on AWS.
Share a Cost Explorer export or read-only access and we will map rightsizing, Graviton, Spot, and commitment opportunities with dollar estimates.
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