AWS Domain 4 – Cost Optimization Vocabulary
Key Definitions
Storage Terminology
- Object Storage (Amazon S3)
- Manages data as discrete “objects” in a flat address space.
- Highly durable, virtually unlimited scale.
- Example use-case: log archives, media files, backups.
- Block Storage (Amazon EBS)
- Presents raw, unformatted block devices to EC2. behaves like disks.
- Low-latency, random I/O; ideal for OS & database volumes.
- File Storage (Amazon EFS / Amazon FSx)
- POSIX-compatible hierarchical file system exposed over NFS/SMB.
- Multiple EC2 instances can share the same filesystem.
- Ephemeral Storage (EC2 Instance Store)
- Local NVMe/SATA disks physically attached to host.
- Highest performance, but data lost when instance stops, terminates, or fails.
- Cost Allocation Tags
- Key-value pairs applied to resources.
- Surface in Cost Explorer & Cost and Usage Report (CUR) for granular chargeback/showback.
- AWS Cost Explorer
- Interactive UI for visualising spend & usage trends; 12-month history + 12-month forecast.
- AWS Cost and Usage Report (CUR)
- Hourly/line-item CSV or Parquet delivered to S3; ingest with Athena/QuickSight for deep analytics.
- S3 Lifecycle Configuration
- Rule set that transitions or expires objects automatically (e.g. 30-day → IA, 90-day → Glacier).
- S3 Intelligent-Tiering
- Monitors each object and moves it between frequent & infrequent tiers when access patterns change.
- 99.9\% availability, no retrieval latency, small per-object monitoring fee.
- AWS Snowball (Snow Family)
- Rugged petabyte-scale appliance for bulk data transfer; eliminates long WAN uploads.
- Consolidated Billing (AWS Organizations)
- Parent (“management”) account receives one invoice; savings plans/RIs share across members.
Compute & Pricing Models
- On-Demand – pay per second/hour, 0 commitment, highest rate.
- Reserved Instances (RI) – commit to specific attributes for 1/3 yrs, up to 72\% discount.
- Savings Plans – commit to \$ /\text{hr} spend; flexible across instance family, size, AZ, OS, even Fargate & Lambda.
- Spot Instances – spare capacity, up to 90\% off, reclaimable with 2-minute warning.
- Right-Sizing – selecting the smallest instance/volume that still meets performance SLAs.
- Elasticity – scale out/in automatically; pay only for what you use.
Database Terms
- Relational DB (Amazon RDS / Aurora) – structured tables, ACID transactions, SQL.
- NoSQL DB (Amazon DynamoDB) – key-value / document, serverless, single-digit-ms latency.
- Read Replica – asynchronous read-only copy; off-loads reads, increases aggregate throughput.
- Point-in-Time Recovery (PITR) – restore any second within retention window via logs.
- Aurora Serverless – auto-pauses & scales capacity in 1 sec increments; pay per ACU-second.
- Amazon ElastiCache – managed Redis/Memcached; micro-second latency caching layer.
Networking Glossary
- Site-to-Site VPN – IPSec tunnel over internet; cheapest hybrid choice.
- AWS Direct Connect (DX) – dedicated fiber circuit; predictable bandwidth, lower per-GB egress.
- VPC Peering – 1-to-1 private routing between two VPCs; no transitive routing.
- AWS Transit Gateway (TGW) – hub-and-spoke router for 1000s of VPCs/on-prem; per-GB processing fee.
- Gateway VPC Endpoint – FREE S3/DynamoDB private access; removes NAT/Data-Transfer-Out charges.
- NAT Gateway – managed NAT for private subnets; hourly + per-GB processing cost.
- Amazon CloudFront – global CDN; free origin → edge transfer, lower egress to users.
Storage Fundamentals & Sizing
- Match storage type to workload requirement (file vs block vs object).
• Example – app needs shared POSIX FS ⇒ choose EFS, not S3. - Cheapest compute-adjacent storage = Instance Store (free with EC2 price) but non-persistent.
- Continuous right-sizing: monitor \text{CPU},\text{RAM},\text{IOPS}, throughput, GB-used.
Amazon EBS Cost Optimisation
- Use AWS Trusted Advisor to flag unattached volumes; delete to stop accruing /GiB\text{/month}.
- Volume type migration – io1/io2 → gp3 if high IOPS no longer required.
- Snapshots – automate via Data Lifecycle Manager (DLM); set creation & retention policies.
Amazon S3 Cost Optimisation
- Know storage-class trade-offs: \text{Standard} > \text{Standard-IA} > \text{One Zone-IA} > \text{Glacier} > \text{Deep Archive} (ascending retrieval time, descending cost).
- Lifecycle Policies for predictable age-based transitions & expiration.
- Intelligent-Tiering for unknown / changing access; object-level automation.
- Requester Pays buckets shift egress charges to downloader.
- Centralise backups with AWS Backup; define retention to delete aged copies.
Data Migration & Transfer
- Bulk seeding (TB→PB) → AWS Snowball fastest & cheapest.
- Ongoing hybrid sync → AWS DataSync, Transfer Family, Storage Gateway.
- High-volume dedicated link → Direct Connect; lower long-term /GB than internet.
Monitoring, Management & Governance
- Amazon CloudWatch: collect metrics, set alarms, create dashboards.
- Tagging Strategy essential; tags surface in Cost Explorer & CUR for chargeback.
- Tool selection:
• Cost Explorer → interactive, high-level.
• CUR → raw, line-item; query with Athena/QuickSight. - AWS Budgets: set thresholds, e-mail/SNS alerts, or auto actions (e.g. shut down dev at night).
- AWS Organizations + Consolidated Billing: aggregate usage for volume discounts; single invoice.
- AWS Control Tower: opinionated multi-account landing zone; guardrails & budget enforcement.
Cost-Optimised Compute Solutions
Five Pillars
- Right-Sizing
- Pick correct instance family (C = compute, R = memory, M/T = general).
- Hybrid hardware (Outposts) still follows right-size principle.
- Increase Elasticity
- EC2 Auto Scaling adds/removes instances per demand; prefer horizontal scale (many small).
- Tag groups for policy targeting.
- Pricing Model Selection
- On-Demand, RI, Savings Plan, Spot; align to workload predictability & fault-tolerance.
- Savings Plans = modern, service-agnostic discount mechanism.
- Match Storage to Usage
- Optimise attached EBS (size, type) to avoid waste.
- Continuous Monitoring & Improvement
- CloudWatch metrics → right-size candidates.
- Cost Explorer → visualize trends.
Load Balancing & Scaling
- Elastic Load Balancing (ELB) distributes traffic & supplies health metrics to Auto Scaling.
- Configure RequestCountPerTarget scaling policy for precise scaling.
- Use ELB health checks for automatic replace of unhealthy instances → no wasted.
Managed Services & Edge
- Replace self-hosted DB on EC2 → Amazon RDS/Aurora; eliminate license & admin overhead.
- CloudFront caches at edge → reduce origin DTO & latency.
Cost-Optimised Database Solutions
Polyglot Persistence Strategy
- Do not stuff everything into one RDS instance.
• Large binaries → S3 (store object key in DB).
• High-traffic, schema-flexible sets → DynamoDB.
• Transactional relational → RDS/Aurora.
Scaling Economically
- Read-heavy pressure → add Read Replicas (horizontal) before vertical scaling.
- Integrate ElastiCache to serve hot queries from memory.
- Enable RDS storage auto-scaling to grow without downtime.
Managed & Serverless
- Prefer managed (RDS, DynamoDB) over self-managed EC2 databases for lower TCO.
- Aurora Serverless shines for intermittent or unpredictable workloads; billed per ACU-second.
Backup & Lifecycle
- Align snapshot schedule to RPO; no need for excessive retention.
- Automate deletion of aged snapshots (DLM or AWS Backup).
- Know which engines offer PITR (RDS, DynamoDB) and configure accordingly.
Cost-Optimised Network Architectures
Data Transfer Cost Rules
- Data IN to AWS → 0.
- Data OUT to internet → paid.
- Inter-AZ traffic within Region → paid.
- Inter-Region traffic → paid.
- Same-AZ traffic → free.
- Optimise by keeping traffic local & private.
Connectivity Choices
- Site-to-Site VPN – default, low-cost hybrid link.
- Direct Connect – choose only for high, steady bandwidth or compliance.
- Cost-effective HA pattern → DX primary + VPN backup (cheaper than dual DX).
Inside the VPC
- Use Gateway VPC Endpoints for S3/DynamoDB; free & avoids NAT.
- VPC Peering for few VPCs (no processing fee).
- Transit Gateway for many VPCs (simplicity outweighs per-GB fee in complex topologies).
NAT Gateway Economics
- Production ⇒ one NAT GW per AZ for HA.
- Dev/Test ⇒ single shared NAT GW to cut hourly & processing charges (accepts lower availability).
CloudFront & Edge Optimisation
- Origin → edge transfer free; user delivery cheaper than origin DTO.
- Caching reduces repeat origin calls, saving per request and per-GB.
API Gateway Cost Controls
- Usage Plans & API Keys enforce throttles/quotas; avoid runaway consumer costs.
Region Selection
- Some Regions (e.g. us-east-1) cheaper; deploy there if latency & compliance permit.
- Cost Explorer – visual trends, forecasts.
- CUR – deepest granularity; join with Athena for SQL queries.
- AWS Budgets – alert/act on threshold breaches (e.g. stop non-prod at >\$100).
- Trusted Advisor – checks idle resources, RI coverage, security gaps.
- CloudWatch – resource utilisation; trigger Lambda to downsize when under-utilised.
Exam “NEED-TO-KNOW” Highlights
- Storage-class selection & S3 Lifecycle vs Intelligent-Tiering decision tree.
- Deleting unattached EBS & old snapshots = immediate savings.
- Read Replica vs vertical scale for read saturation.
- Snowball fastest & cheapest for PB migrations.
- Gateway Endpoints eliminate S3/DynamoDB data-transfer fees.
- Spot = deepest discount; only for interruptible workloads.
- Savings Plan = flexible commitment across services.
- NAT GW dev pattern: single, shared gateway.
- CloudFront: free origin-to-edge; primary DTO-saving tool.
Example Scenario Q&A
- S3 logs: 30-day IA, 90-day archive → use Lifecycle Configuration (predictable schedule).
- Minimise VPC cost → optimise NAT usage, use Gateway Endpoints, keep traffic in one AZ.
- Dev NAT savings → deploy one NAT GW, route all private subnets to it.
- Route design to cut transfer → keep compute & DB in same AZ, cache with CloudFront, use endpoints.
- Snapshot cost savings = (\text{Idle GiB}) \times (\$ /\text{GiB‐month}).
- Spot discount up to 90\% vs On-Demand.
- RI/Savings Plan discount up to 72\%.
- S3 Glacier Deep Archive retrieval ≤ 12\text{ hrs}; lowest /\text{GiB‐month}.
Continuous Improvement Loop
- Design to requirements (functionality first).
- Tag & Measure (enable visibility).
- Analyse Spend (Cost Explorer/CUR).
- Optimise (right-size, automate lifecycle, choose pricing model).
- Repeat monthly – cloud pricing is variable; optimisation is iterative.