756 articles on cost optimization — what drives the cost, how it is priced, and where the savings actually are.
Bigtable lets you pick SSD or HDD storage per cluster, and the choice changes both storage cost and performance significantly, with HDD storage far cheaper but much slower. Here is how the two compare and when each fits.
BigQuery lets you stream rows in for immediate querying, but streaming ingestion is billed per gigabyte on top of storage and query costs, unlike free batch loads. Here is what streaming costs and how the Storage Write API changes the math.
BigQuery editions let you buy query capacity as slots with autoscaling, so you pay for compute that follows demand instead of a flat commitment or unpredictable on-demand scans. Here is how slot autoscaling is priced and when it beats on-demand.
Persistent Disk snapshots are incremental and billed per gigabyte of stored data, so their cost depends on how much changes between snapshots, not the disk size. Here is how snapshot billing works and how to stop snapshots creeping up your bill.
Filestore comes in tiers from Basic HDD to Enterprise, with per-gigabyte prices that vary several-fold and minimum capacities that set a cost floor. Here is how the tiers compare on cost and which fits your file workload.
Dataproc Serverless runs Spark jobs without a standing cluster, billing per compute unit for the duration of each job, which eliminates idle cluster cost. Here is how it is priced and when it beats a managed Dataproc cluster.
Pub/Sub bills per gigabyte of message throughput with no capacity planning, while Pub/Sub Lite bills for provisioned capacity at a much lower unit rate. Here is how the two compare on cost and when Lite's savings justify its extra management.
Moving data between Google Cloud regions is billed per gigabyte, with rates that depend on whether the regions are on the same continent or across the world. Here is how inter-region egress is priced and how to design around it.
Google Cloud offers two kinds of committed use discount, resource-based and spend-based flexible commitments, and the flexible kind trades some discount depth for the freedom to change machine types and regions. Here is how they compare on cost.
Dividing your infrastructure cost by request volume gives a single number that exposes inefficient endpoints, bad caching, and creeping bloat. Here is how to compute cost per request and use it to drive optimization.
When the cloud bill jumps, the question is always the same: what changed? A disciplined root-cause method, slice by dimension, isolate the delta, tie it to a change, turns a scary spike into a fixable line. Here is the playbook.
A rightsizing sprint saves money once; a rightsizing program saves it continuously. The difference is process: recommendations, ownership, safe rollout, and measurement. Here is how to stand up a program that sticks.
Unattached disks, unassociated IPs, empty load balancers, and stale snapshots bill continuously while delivering nothing. A systematic cleanup finds and removes them safely. Here is the guide, resource by resource.
The most expensive cost decisions are made in architecture, not operations, and they are hard to undo later. Adding a cost lens to design reviews catches the costly pattern before a line of code is written. Here is how.
A managed Kafka service removes the operational burden but charges a premium; self-hosting on your own instances is cheaper per unit but demands real operational effort. Which wins depends on scale and how much of a platform team you have. Here is the comparison with numbers.
Running Elasticsearch or OpenSearch yourself on plain instances is cheaper per unit than a managed search service, but the service handles the hard parts. Which is cheaper depends on cluster size and your operational appetite. Here is the breakdown with numbers.
Running Postgres or MySQL yourself on EC2 is cheaper per hour than RDS, but RDS handles backups, failover, and patching. The premium is real, and so is the operational burden it removes. Here is when self-hosting a database pays off, with numbers.
Running Redis yourself on an EC2 instance is roughly half the price of ElastiCache, but ElastiCache handles failover, patching, and backups. For a cache, the trade-off is different than for a database. Here is when self-hosting Redis makes sense, with numbers.
Managed Airflow (MWAA or Cloud Composer) removes the operational burden of running schedulers and workers, but charges a flat environment fee on top of compute. Self-hosting on your own cluster is cheaper per unit but adds real ops. Here is when each wins, with numbers.
On-demand, reserved instances, savings plans, and spot are four ways to pay for the same EC2 capacity, with discounts from zero to around 90 percent and very different commitments. Which mix is cheapest depends on how predictable and interruptible your workload is. Here is the side-by-side.
Colocation means you own the servers and rent space, power, and cooling in a data center; cloud means you rent capacity by the hour with no hardware. The cost curves cross at a predictable point tied to utilization and scale. Here is when each wins, with numbers.
Bare-metal servers give you a whole physical machine with no hypervisor overhead; cloud VMs slice physical hosts into virtual instances. For steady, resource-hungry workloads bare metal can be cheaper per unit, but VMs win on flexibility. Here is the comparison with numbers.
A cloud GPU costs a few dollars an hour with no commitment; buying the same card costs thousands upfront but nothing per hour after. The crossover is utilization, and for heavy steady GPU work owning can pay back in months. Here is the math.
EKS and GKE both charge a control-plane fee and node compute, but their pricing details, autopilot options, and free-tier treatment differ enough to matter. Which cloud is cheaper for Kubernetes depends on cluster count and how you run nodes. Here is the comparison.