GCP cost guides
Practical models to estimate common GCP line items and avoid the biggest cost traps.
A simple GCP estimate
- Start with requests/month and GB/month (egress + inter-zone).
- Add storage (GB-month) and lifecycle/retention rules.
- Add logs/metrics ingestion + retention + scan/query.
- Validate boundaries (internet vs internal) and unit conversions.
Common traps
- Under-modeling inter-zone and cross-region transfer.
- High-cardinality metrics labels creating “quietly growing” bills.
- Confusing CDN bandwidth with origin egress (cache fill).
Use a baseline + peak scenario and validate against a real week before making commitments.
20 GCP guides
Artifact Registry pricing (GCP): storage + downloads + egress (practical estimate)
A practical Artifact Registry cost model: stored GB-month baseline, download volume from CI/CD and cluster churn, and outbound transfer. Includes a workflow to estimate GB-month from retention and validate layer sharing and peak pull storms.
BigQuery cost estimation: storage, bytes scanned, and the dashboard trap
Estimate BigQuery-style analytics costs with measurable drivers: stored data (GB-month), bytes scanned (per query), and streaming/exports. Includes a workflow to model baseline vs peak and validate partition pruning and dashboard refresh behavior.
Bigtable cost estimation: nodes, storage growth, and transfer (practical model)
A driver-based Bigtable estimate: provisioned capacity (node-hours), stored GB-month + growth, and network transfer. Includes validation steps for hotspots, compactions, and peak throughput that force over-provisioning.
Cloud Armor pricing (GCP): model baseline traffic, attack spikes, and logging
A practical Cloud Armor estimate: baseline request volume plus an attack scenario (peak RPS × duration). Includes validation steps for spikes, rule footprint, and the secondary cost driver most teams miss: logs and analytics during incidents.
Cloud CDN pricing (GCP): bandwidth, requests, and origin egress (cache fill)
A practical Cloud CDN cost model: edge bandwidth, request volume, and origin egress (cache fill). Includes validation steps for hit rate by path, heavy-tail endpoints, and purge/deploy events that reduce hit rate.
Cloud Functions pricing (GCP): invocations, duration, egress, and log volume
A practical Cloud Functions cost model: invocations, execution time, outbound transfer, and logs. Includes a workflow to estimate baseline + peak and validate retries, cold starts, and log bytes per invocation.
Cloud Logging pricing (GCP): ingestion, retention, and query scans
A practical model for Cloud Logging costs: GB ingested, retention storage (GB-month), and query/scan behavior. Includes a fast method to estimate GB/day from events/sec × bytes/event and a checklist to find dominant sources.
Cloud Monitoring metrics pricing (GCP): time series, sample rate, and retention
A practical metrics cost model: time series count (cardinality), sample rate, retention, and dashboard/alert query behavior. Includes validation steps to prevent high-cardinality explosions and excessive refresh patterns.
Cloud NAT cost (GCP): why it spikes and how to model outbound traffic
A practical Cloud NAT estimate: baseline configuration + outbound GB processed through NAT, with a peak scenario for retries, node churn, and dependency storms. Includes a validation checklist and cost-reduction levers.
Cloud Spanner cost estimation: capacity, storage, backups, and multi-region traffic
Estimate Spanner cost using measurable drivers: provisioned capacity (baseline + peak), stored GB-month (data + indexes), backups/retention, and multi-region/network patterns. Includes a worked template, common pitfalls, and validation steps.
Cloud SQL pricing: instance-hours, storage, backups, and network (practical estimate)
A driver-based Cloud SQL estimate: instance-hours (HA + replicas), storage GB-month, backups/retention, and data transfer. Includes a worked template, common pitfalls, and validation steps for peak sizing and growth.
Dataflow pricing: worker hours, backlog catch-up, and observability (practical model)
Estimate Dataflow cost using measurable drivers: worker compute-hours, backlog catch-up scenarios (replays/backfills), data processed, and logs/metrics. Includes a worked template, pitfalls, and validation steps for autoscaling and replay patterns.
GCP Cloud Run Pricing & Cost (requests, CPU/memory, egress)
Model Cloud Run cost from requests, duration, CPU/memory time, and egress. Includes validation tips for real workloads.
GCP Cloud Storage Pricing & Cost Guide
Understand Cloud Storage cost drivers: storage class, operations, retrieval, and egress with estimation steps.
GCP load balancing pricing: hours, requests, traffic processed, and egress
A driver-based approach to load balancer cost: hours, request volume, traffic processed, and (separately) outbound egress. Includes a worked estimate template, pitfalls, and a workflow to estimate GB from RPS and response size.
GCP VPC egress costs: estimate outbound transfer by destination (practical workflow)
A practical method to estimate GCP outbound transfer: split by destination (internet, cross-region, inter-zone, CDN origin), convert usage to GB/month, and validate boundaries. Includes a worked template, pitfalls, and optimization levers.
Google Kubernetes Engine (GKE) pricing: nodes, networking, storage, and observability
GKE cost is not just nodes: include node pools, autoscaling, requests/limits (bin packing), load balancing/egress, storage, and logs/metrics. Includes a worked estimate template, pitfalls, and validation steps to keep clusters right-sized.
Inter-zone transfer costs on GCP: identify flows, estimate GB/month, and reduce churn
A practical checklist to estimate cross-zone data transfer: load balancers, multi-zone clusters, east-west chatter, and storage/database access patterns. Includes a worked template, validation steps, and control levers.
Private Service Connect costs: endpoint-hours and data processed (practical model)
A practical private connectivity estimate: endpoint-hours plus data processed (GB). Includes a worked template, pitfalls, and validation steps to compare PSC vs NAT/internet egress and avoid paying for both paths.
Pub/Sub pricing: deliveries, retries, fan-out, and payload transfer (practical estimate)
A practical Pub/Sub estimate: publish volume, fan-out (subscriptions), delivery attempts (retries), retention/replay scenarios, and payload transfer. Includes a worked template, pitfalls, and validation steps.
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