338 articles on aws — what drives the cost, how it is priced, and where the savings actually are.
Personalize bills data ingestion, training hours to build recommendation models, and real-time inference by provisioned throughput (TPS-hours). Over-provisioned recommendation capacity and frequent retraining drive the bill. Here is the model.
Amazon Connect bills per minute of end-customer contact usage plus telephony (per-minute inbound/outbound and phone number charges), with optional add-ons for features. Call volume and duration drive the bill. Here is the pay-as-you-go model.
Macie bills a per-bucket inventory charge plus per GB of S3 objects analyzed for sensitive data. Scanning entire large buckets on every run drives the bill. Sampling and scoping to sensitive data are the levers. Here is the model.
Shield Advanced costs a flat subscription (about $3,000/month, with a one-year commitment) covering an organization, plus data transfer for protected resources. It suits high-value, attack-prone applications. Here is when the subscription pays off.
Cloud Map bills per registered service-discovery resource per month and per API discovery call, plus any health checks. It is inexpensive, but high-frequency discovery lookups from many clients can add up. Here is the model.
App Mesh adds no charge of its own; you pay for the Envoy proxy sidecars that run alongside your services, consuming CPU and memory on every task or pod. At scale, the sidecar overhead is the real cost. Here is what to watch.
Rekognition bills per image processed for image analysis and per minute for video, with rates by feature (labels, faces, moderation, text). High-volume or per-frame analysis drives the bill. Here is the model and how to control it.
Textract bills per page processed, with higher rates for forms, tables, and query features than plain text detection. Running advanced analysis on documents that only need text extraction over-pays. Here is the per-page model.
Transcribe bills per second of audio (rounded up per request), with higher rates for features like speaker identification, medical, and custom models. Long audio and premium features drive the bill. Here is the per-second model.
Comprehend bills per unit of text (100 characters, with a per-request minimum) for NLP tasks like sentiment, entities, and key phrases, with higher rates for custom models. Analyzing more text or in more ways than needed drives the bill.
Security Hub bills per security check evaluated against your resources and per finding ingested from integrated services, both tiered. Large accounts with many resources and chatty integrations drive the bill. Here is the model.
Amazon Inspector bills per EC2 instance scanned per month and per container image scanned (with re-scans on updates), plus Lambda function scanning. Large fleets and frequent image pushes drive the bill. Here is the model.
t4g (Graviton, ARM) burstable instances cost about 20% less than t3 (Intel) for comparable size, often with better performance per dollar. The catch is ARM compatibility. Here is the comparison and when the switch is free money.
AWS instance families (general purpose, compute, memory, storage, and accelerated) target different workloads, and using the wrong family over-pays for resources you do not need. This is a practical guide to choosing the cost-effective family.
i4i storage-optimized instances offer faster NVMe local storage and better price-performance than the older i3 generation. For high-IOPS, low-latency local-disk workloads, the newer generation is usually the cost-effective choice. Here is the comparison.
MediaConvert bills per minute of output video, priced by resolution, frame rate, and features like HDR or advanced codecs. Encoding more than you need, in higher tiers than required, drives the bill. Here is how the per-minute model works.
IoT Core bills connectivity per million connection-minutes, messaging per million messages, and rules-engine actions, plus device shadow and registry operations. Chatty devices and heavy rule fan-out drive the bill. Here is the model.
Amazon Managed Service for Prometheus bills per metric sample ingested, per query processed, and for storage. High-cardinality metrics and short scrape intervals drive ingestion cost. Here is how the model works and how to control cardinality.
Amazon Managed Grafana bills per active user per month, by role (editor or viewer), plus optional add-ons. Cost scales with your user base, not dashboards or data. Here is how the per-user model works and how to keep it lean.
Keyspaces (managed Cassandra) bills read and write request units, storage per GB-month, and optional features, with on-demand and provisioned capacity modes. It scales to zero with no clusters to manage. Here is how it prices versus self-managed Cassandra.
S3 Express One Zone charges far higher storage (around $0.16/GB-month) but much lower per-request costs than S3 Standard, in a single AZ for low latency. For request-heavy, latency-sensitive workloads it can be cheaper overall. Here is the math.
Global tables replicate a DynamoDB table across regions, so you pay replicated write capacity, storage in every region, and cross-region replication transfer. The multiplier is the number of regions. Here is when multi-region is worth it.
EFS charges storage plus, depending on throughput mode, either nothing extra (Bursting), per throughput used (Elastic), or per provisioned throughput. Picking the wrong mode over-pays or throttles. Here is how the modes price and when to use each.
CloudFront Functions cost about $0.10 per million invocations for lightweight viewer logic; Lambda@Edge bills per request plus duration for heavier compute across more event types. Choosing the lighter tool where it fits cuts edge cost. Here is the comparison.