cost optimization
798 articles on cost optimization — what drives the cost, how it is priced, and where the savings actually are.
Right-size RDS instances guide: databases without the bloat
RDS instances are often provisioned larger than the workload needs, and unlike stateless compute, resizing a database takes care. Here is how to right-size RDS instance class, storage, and IOPS to real usage without risking the database.
Route 53 cost explained: DNS pricing and its hidden lines
Route 53 charges per hosted zone, per million queries, and for health checks, so DNS cost is usually small but can surprise you at high query volume or with many zones and health checks. Here is the full pricing picture.
S3 Intelligent-Tiering explained: automatic storage cost savings
S3 Intelligent-Tiering moves objects between access tiers automatically based on usage, cutting storage cost for data with unknown or changing access patterns, for a small monitoring fee. Here is how it works and when to use it.
S3 lifecycle policies cost savings: aging data to cheaper storage
S3 lifecycle policies automatically transition objects to cheaper storage classes and expire them on a schedule, cutting storage cost for data with a known access pattern. Here is how to design policies that save without losing what you need.
S3 request cost surprise: when API calls beat storage on the bill
S3 charges per request, not just per GB stored, so a workload making millions of small GET, PUT, or LIST calls can pay more for requests than for storage. Here is why it happens and how to cut request cost.
S3 storage classes cost compared: picking the cheapest tier
S3 offers storage classes from Standard to Glacier Deep Archive, trading storage price against retrieval cost and latency. Matching each object to the right class is a major cost lever. Here is how the classes compare.
SageMaker cost optimization guide: taming ML infrastructure spend
SageMaker cost spans notebooks, training jobs, and always-on inference endpoints, and each has its own trap. Idle notebooks and over-provisioned endpoints are the usual culprits. Here is how to optimize each stage.
Savings Plans vs Reserved Instances for EC2: which commitment wins
Both Savings Plans and Reserved Instances discount EC2 in exchange for a commitment, but they differ in flexibility and how they apply. Savings Plans commit to a dollar-per-hour spend; RIs commit to specific capacity. Here is how to choose.
Self-hosted runners cost savings: cheaper CI at scale
Hosted CI runners are billed per minute and get expensive at high build volume; self-hosted runners on your own compute can cost far less per minute but add operational and idle-capacity overhead. Here is the tradeoff.
Showback vs chargeback explained: two ways to make cost accountable
Showback shows teams what they spend; chargeback bills it back to their budgets. Both make cloud cost accountable, but they differ in enforcement and organizational fit. Here is how to choose between them.
Snowflake cost optimization: controlling warehouse credits
Snowflake cost is driven by virtual warehouse compute credits, and the biggest wastes are oversized warehouses and warehouses left running idle. Here is how to right-size, auto-suspend, and tune Snowflake spend.
Spot vs on-demand savings explained: big discounts with a catch
Spot instances offer steep discounts off on-demand prices for spare capacity that AWS can reclaim with short notice. For fault-tolerant workloads the savings are large; the catch is interruption. Here is how to use spot safely.
SQS vs SNS vs EventBridge cost: pricing three messaging services
SQS, SNS, and EventBridge all move messages between services but price differently, per request, per publish and delivery, and per event with routing. Which is cheapest depends on your fan-out and routing needs. Here is the comparison.
Step Functions cost explained: paying per state transition
AWS Step Functions bills the Standard workflow type per state transition, so a workflow with many steps or high execution volume can cost more than expected. The Express type prices differently. Here is how to keep orchestration cheap.
T3 vs T3a cost: a cheaper burstable instance for the same shape
T3a instances use AMD processors to deliver the same burstable profile as T3 Intel instances at a lower price. For most general-purpose workloads the swap is a simple, low-risk saving. Here is how they compare.
Tagging strategy for cost allocation: the foundation of FinOps
Consistent resource tags are what let you attribute cloud cost to teams, projects, and environments. Without them, cost is an unattributable lump. Here is how to design and enforce a tagging strategy that makes cost accountable.
Tracing sampling cost impact: keeping traces useful and affordable
Distributed tracing is billed by span or trace volume, so capturing every request gets expensive at scale. Intelligent sampling keeps the diagnostic value while cutting the volume you pay for. Here is how sampling affects cost.
Training vs inference cost split: where the AI budget really goes
AI cost divides into training (building the model, often GPU-heavy and periodic) and inference (running it, continuous and scaling with usage). They have different profiles and different levers. Here is how to think about the split.
Understanding your Azure bill: reading the charges that matter
An Azure invoice mixes compute, storage, networking, and service charges across subscriptions and resource groups, which makes it hard to read. Knowing the structure, and where the big and surprising lines come from, is the first step to control. Here is how to read it.
Unexpected AWS charges explained: the usual bill surprises
Most surprise AWS charges come from a short list of usual suspects, data transfer, NAT gateways, idle resources, request fees, and forgotten services. Knowing them turns a mystifying bill into a fixable one. Here is the catalog of surprises.
us-east-1 vs us-west-2 cost: comparing two popular regions
us-east-1 and us-west-2 are two of AWS's cheapest and most feature-complete regions, with pricing that is close but not identical. Here is how they compare on cost, and what else to weigh beyond the sticker price.
Vector database cost compared: managed, self-hosted, and add-on
Vector databases for AI and search come as managed services, self-hosted engines, and add-ons to existing databases, each with a different cost model. Which is cheapest depends on scale, query volume, and operational appetite. Here is the comparison.
Vertex AI cost optimization guide: controlling GCP ML spend
Vertex AI cost spans training jobs, online prediction endpoints, notebooks, and pipelines, and the biggest drains are always-on endpoints and idle notebooks. Here is how to optimize each part of GCP's managed ML platform.
VMware to cloud cost: what leaving the hypervisor costs
Migrating VMware workloads to the cloud can mean a like-for-like lift onto managed VMware services or a re-architecture to native cloud. Each has a distinct cost profile, and recent VMware licensing changes have sharpened the math. Here is the breakdown.