Cloud CDN vs Cloud Run (2026): Pricing, Features & Verdict

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Why choose Cloud CDN

Our data shows no clear advantage over Cloud Run.

C

Why choose Cloud Run

• Has a free plan (Cloud CDN does not)
• Higher Ease of Use score (7/10 vs 4/10)
• Higher Cost score (7/10 vs 5/10)

C

Cloud CDN

Pros

• Connects directly to Google Cloud origins such as Cloud Storage buckets, GKE (including GKE Gateway since April 2026), Cloud Run, and Compute Engine, and it also accepts external origins.
• Cache egress falls to 0.02 USD per GiB above 1,000 TiB in North America and Europe, which makes it competitive at very large volumes.
• Cloud Armor edge security policies inspect all traffic before the cache lookup, so attack filtering and WAF rules sit in front of cached content.
• Invalidation has no per-request fee and supports cache tags, and each invalidation takes effect in about 10 seconds.
• You can automate everything through the REST API, gcloud CLI, and Terraform, and logs export to BigQuery or Cloud Storage.

Cons

• It is not a standalone CDN. You must configure the external Application Load Balancer's URL maps, backend services, and forwarding rules, and reviewers say this is hard for people new to CDNs.
• Billing has several layers (egress, cache fill, per-request lookups on every GET and HEAD, plus load balancer charges), so monthly costs are hard to forecast.
• The cache only fills when requests arrive, and there is no native way to pre-warm content across locations, which users have flagged.
• Reviewers say analytics are complex, and simple downloadable raw access logs are not offered the way some specialist CDNs provide them.
• Large-scale video and download delivery is steered to the separate Media CDN product, and Cloud CDN does not deliver RTMP or WebRTC.

C

Cloud Run

Pros

• Scale-to-zero with request-based billing means idle services cost nothing beyond any minimum instances you set.
• It runs any container image, so there is no language or framework lock-in, and source deploys build images automatically.
• Services, jobs, worker pools, and functions on one platform cover HTTP APIs, batch work, and queue consumers alike.
• Every service gets managed HTTPS on run.app plus custom domains, with WebSockets, HTTP/2, and gRPC support.
• On-demand NVIDIA L4 GPUs billed per second make it practical to serve AI inference without managing GPU VMs.
• A 99.95% monthly uptime SLA applies for non-GPU services in most regions.

Cons

• Cold starts when scaling from zero are the most common complaint, and keeping minimum instances warm adds ongoing cost.
• Internet egress beyond 1 GiB, plus Cloud Build and Artifact Registry, are billed separately and can inflate bills.
• Setup requires a Google Cloud project, a billing account, and familiarity with IAM.
• GPU services must use instance-based billing, get no free tier, and are excluded from committed use discounts.
• Usage-based billing can spike from traffic surges or runaway loops unless you set budgets and alerts.