Cloud Vendor Product Matrix#

Choosing between cloud vendors requires mapping equivalent services across providers. AWS has 200+ services. Azure has 200+. GCP has 100+. Cloudflare has 20+ but they are tightly integrated and edge-native. This article maps the services that matter for most applications – compute, serverless, databases, storage, networking, and observability – across all four vendors with pricing, availability, and portability for each.

How to Use This Matrix#

Each section maps equivalent products across vendors, then provides:

Grafana Mimir for Long-Term Prometheus Storage#

Prometheus stores metrics on local disk with a practical retention limit of weeks to a few months. Beyond that, you need a long-term storage solution. Grafana Mimir is a horizontally scalable, multi-tenant time series database designed for exactly this purpose. It is API-compatible with Prometheus – Grafana queries Mimir using the same PromQL, and Prometheus pushes data to Mimir via remote_write.

Mimir is the successor to Cortex. Grafana Labs forked Cortex, rewrote significant portions for performance, and released Mimir under the AGPLv3 license. If you see references to Cortex architecture, the concepts map directly to Mimir with improvements.

Zero-Egress Architecture with Cloudflare R2#

Every major cloud provider charges you to download your own data. AWS S3 charges $0.09/GB. Google Cloud Storage charges $0.12/GB. Azure Blob charges $0.087/GB. These egress fees are the most unpredictable line item on cloud bills – they scale with success. The more users download your data, the more you pay.

Cloudflare R2 charges $0 for egress. Zero. Unlimited. Every download is free, whether it is 1 GB or 100 TB. R2 uses the S3-compatible API, so existing tools and SDKs work without changes. This single pricing difference changes how you architect storage, serving, and cross-cloud data flow.

The Retention Problem#

Prometheus stores metrics on local disk with a default retention of 15 days. Most production teams extend this to 30 or 90 days, but local storage has hard limits. A single Prometheus instance cannot scale disk beyond the node it runs on. It provides no high availability – if the instance goes down, you lose scraping and query access. And each Prometheus instance only sees its own targets, so there is no unified view across clusters or regions.