Everyone knows internet egress costs money. Almost nobody prices the traffic that never leaves the region. us-central1-a to us-central1-b, over internal IPs, inside your own VPC: roughly $0.01/GB. It looks like LAN traffic. It is billed like WAN traffic. That number sounds trivial until you do the arithmetic on a real cluster. A three-zone GKE setup with no topology awareness, where a service mesh, a Prometheus remote-write, and a chatty API-to-cache path all round-robin across zones, will do 30-60 TB a month of cross-zone chatter without anyone noticing. At ~$0.01/GB that is $300-$600/month for bytes that were never supposed to leave the rack, generated by a HA topology nobody re-examined after the initial deploy. Three more places GCP charges you for traffic that feels free: 1. Cloud NAT is a second meter. ~$0.045/GB processed, on top of egress, billed on data processed in both directions. Your private GKE nodes pulling images from Artifact Registry and shipping logs to Cloud Logging through NAT are paying for traffic Private Google Access carries for $0. One subnet flag and a private DNS zone fixes it. 2. Multi-region buckets quietly convert free reads into billed ones. A VM in us-central1 reading from a us-central1 bucket: free. The same VM reading from the US multi-region bucket: different location, ~$0.02/GB. Multi-region is a durability choice, not a performance one. Plenty of hot paths are pointed at one by default. 3. Cloud VPN gets no egress discount. VPN egress is billed at standard internet rates plus tunnel hours. Only Interconnect gets the cheaper SKU. If you moved to VPN to save on egress, you did not. The reason this hides for years is that none of it shows up as a line item you can attribute. The bill says Network Inter Zone Egress: $487. It does not say which service. VPC Flow Logs do - if you enable them with sampling (0.1-0.5, 30-second aggregation, custom metadata including src_instance, dest_instance and src_gke_details), sink them to BigQuery with --use-partitioned-tables, and classify each flow by the boundary it crosses.

This infographic breaks down the core parts of GCP in a simple way:→ Compute→ Storage→ Networking→ Security→ Analytics→ AI & Machine Learning A good reminder that modern cloud infrastructure is much bigger than just virtual machines. Which GCP service do you use the most? 👇

If you've never touched cloud before, this is where you start. We're going to create a storage bucket on GCP using the browser console — no CLI, no code, no credit card (GCP has a $300 free trial). Step 1 — Create a free GCP account Go to cloud.google.com → click "Start free" → sign in with Google → activate the $300 free trial. Step 2 — Open Cloud Shell In the top right of the GCP console, click the terminal icon >_ to open a browser-based Linux terminal. No setup needed. Step 3 — Create a storage bucket Run this in Cloud Shell: gsutil mb -l europe-west1 gs://my-first-bucket-$(date +%s) Step 4 — Upload a file echo "Hello from GCP!" > hello.txt gsutil cp hello.txt gs://my-first-bucket-[your bucket name]/ Step 5 — Verify it's there gsutil ls gs://my-first-bucket-[your bucket name]/ You just used the Google Cloud CLI to create cloud storage and upload a file. Now do this: Ask ChatGPT — "What else can I do with Google Cloud Storage? Give me 5 practical examples for a sysadmin." Post your output in the comments. That's your first AI-assisted cloud task done.

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