91 articles on gcp — what drives the cost, how it is priced, and where the savings actually are.
Cloud Armor bills per security policy (about $5/month), per rule (about $1/month), and per million requests processed (about $0.75), with Managed Protection Plus adding a subscription. Here is how the standard model prices and what drives the bill.
Artifact Registry charges about $0.10 per GB-month of storage (first 0.5 GB free) plus network egress for downloads. In-region pulls to Google compute are cheap; cross-region and internet pulls add transfer. Here is the breakdown and how to trim it.
Cloud CDN bills cache egress to users (tiered by region), cache fill from the origin, and a small per-request lookup fee. A high cache-hit ratio lowers both origin load and cost. Here is the breakdown and how to raise hit ratio.
Compute and storage have converged, but data transfer hasn't. Here's the shared structure (ingress free, egress tiered, cross-region charged), where AWS/Azure/GCP diverge, and the universal levers to cut it.
Bigtable bills nodes (~$474/month each, minimum one) + storage. The node floor makes it expensive below scale. Here's how to tune nodes, SSD vs HDD, and when a cheaper datastore wins.
Delete waste, right-size, commit the baseline, use Spot, tier storage, cut egress, then keep it down with a cost gate. A practical, impact-ordered checklist with links to the details for each step.
GCP load balancers bill forwarding rules (~$18/month each for the first five) plus data processed. Here's why sprawl drives the bill and how URL maps and a CDN cut it.
Comparable compute and storage sit in a narrow band across the three clouds. The real differences are egress, the discounts you'll commit to, and managed services. Here's how to compare apples-to-apples.
Autopilot bills pod resource requests (~$0.0445/vCPU-hour), not nodes, so oversized requests are the overspend. Here's how to right-size requests, use Spot Pods, and pick compute classes.
Cloud Functions 2nd gen runs on Cloud Run, so rates converge, but Cloud Run's concurrency lets one instance serve many requests, making it cheaper for request-heavy workloads. Here's how to choose.
Persistent disks bill per provisioned GB-month by type: pd-standard ~$0.04, pd-balanced ~$0.10, pd-ssd ~$0.17. Here's which to use, why you pay for provisioned size, and how to stop over-paying for SSD.
Spot VMs run 60-91% below on-demand for the same machine type, preemptible at any time. Here's what belongs on Spot, how it differs from preemptible, Spot GKE pools, and how to design for preemption.
AlloyDB costs more per vCPU than Cloud SQL but is much faster for analytical workloads, so it can need less compute for the same performance. Here's how each bills and which to pick.
BigQuery on-demand bills ~$6.25/TB scanned; capacity bills for slots. Here's which model is cheaper for your query volume, and why partitioning and never SELECT * is the biggest saving on either.
GCP charges for egress to the internet, between regions, and even between zones, but not ingress or same-zone traffic. Here's the egress map, the three patterns that drive the bill, and how to cut it.
Cloud Run bills per request-second and scales to zero; GKE bills for nodes 24/7. The cheaper option comes down to utilization. Here's the crossover, the min-instances trap, and where Autopilot fits.
SUDs are automatic (30% off steady workloads). CUDs require commitment (25-55% off). They don't stack. Here's the math, the break-even, and the optimal strategy: 3-year flexible CUDs on baseline, SUDs above, Spot for elastic.
Autopilot bills per-pod (vCPU, memory, ephemeral storage). Standard bills per-node. The break-even is around 50-55% node utilization. Here's the actual pricing math with n2-standard-4 nodes, when each mode wins, and how to migrate without surprises.
Estimate Google Cloud costs from Terraform configurations with sustained-use discounts applied automatically, Committed Use Discounts via usage file, and Spot VMs detected from the resource. No GCP credentials required.