FIG_001[ overview ]
Lower AWS spend by turning EC2, EBS, and non-production waste into a weekly execution system with measurable savings outcomes.
FIG_002[ where aws spend usually leaks ]
Where AWS spend usually leaks
Idle EC2 Baselines
Fleets are sized for historical peak traffic but run underutilized for most of the week.
EBS Drift
Unattached volumes and stale snapshots accumulate quietly across accounts and teams.
Always-On Non-Prod
Development and staging environments keep running outside working hours by default.
Premature Commitments
Savings Plans and reservations are purchased before foundational waste is removed.
FIG_003[ a sharper aws optimization lens ]
A sharper AWS optimization lens
This is the operating sequence teams use to reduce burn without slowing delivery.
Speed
Prioritize actions by execution velocity, not theoretical model output.
Ownership
Every top spend line needs a named owner and weekly follow-through.
Automation
Turn repeatable cleanup and scheduling actions into default guardrails.
Commitments
Buy commitments only after baseline demand is measured and stable.
FIG_004[ next steps ]
Unconventional but practical truths
- The biggest AWS wins are usually boring, repeatable compute fixes
- One weekly operating loop beats one heroic quarterly optimization sprint
- If engineering does not own cost, finance ends up owning preventable waste
How XOLOS helps
XOLOS turns AWS billing complexity into a prioritized action queue, helping teams execute remediation quickly and track savings impact continuously.
FIG_005[ faq ]
AWS cost optimization FAQ
What are the fastest AWS savings opportunities?
The fastest wins usually come from rightsizing underutilized EC2 resources, deleting unattached EBS volumes, and shutting down non-production workloads outside business hours.
Savings Plans or Reserved Instances?
Savings Plans are typically more flexible for modern workloads, while Reserved Instances can still fit highly predictable usage patterns.
How do we control S3 and EBS growth?
Set lifecycle and retention policies, enforce ownership tags, and continuously remove stale data and old snapshots that no team actively needs.
How should we detect AWS cost anomalies?
Use daily anomaly alerts tied to service owners, then run fast triage with usage, deployment, and architecture context to resolve root causes quickly.