Google Cloud Run
A fully managed containerized application deployment platform offered by Google Cloud. It supports per-request or per-instance billing, can attach GPUs, and supports scaling to zero.
Core Facts
Timeline (last 90 days)
Spinachi AI's backend is deployed on Google Cloud Run.
FalconX's infrastructure is deployed on Google Cloud Run.
Specreel's categories cover open source, marketing, developer tools, GitHub and Google Cloud Run, and its target users span three roles: developer relations, product marketing and engineering efficiency.
Table Canon is deployed on Google Cloud Run, with elastic scaling capability to handle audio processing needs of different scales.
This Rambox launch involved Ramiro Saenz, and the product is categorized under Productivity with a Google Cloud Run tag
Mira Tours' backend uses a Google Cloud Run containerized cloud service architecture.
Google Cloud Run is a fully managed containerized computing platform provided by Google Cloud, belonging to the Serverless category, with per-request billing and scale-to-zero characteristics.
Exodus inspects the application's current state on the local machine, calculates the current running cost and the estimated bill after migrating to Cloud Run, and lists the places that need to be changed.
In the Cloud Run benchmark tests, cpu-original (251ms) costs $8.93 per million queries and $39.05 per million documents; cpu-repack (121ms) costs $3.91 and $25.87 respectively; l4-original (56ms) costs $16.27 and $0.87 respectively.
On Google Cloud Run, the minimum instance specification required to attach a GPU to an L4 service is 4 vCPU plus 16 GiB of memory.
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All Facts (15)
Google Cloud Run is a fully managed containerized computing platform provided by Google Cloud, belonging to the Serverless category, with per-request billing and scale-to-zero characteristics.
70%UnverifiedSpinachi AI's backend is deployed on Google Cloud Run.
50%UnverifiedFalconX's infrastructure is deployed on Google Cloud Run.
50%UnverifiedTable Canon is deployed on Google Cloud Run, with elastic scaling capability to handle audio processing needs of different scales.
50%UnverifiedMira Tours' backend uses a Google Cloud Run containerized cloud service architecture.
50%UnverifiedExodus inspects the application's current state on the local machine, calculates the current running cost and the estimated bill after migrating to Cloud Run, and lists the places that need to be changed.
50%UnverifiedCloud Run reserves paths ending in 'z', so '/healthz' cannot reach the container, and health check routes should instead use '/health'.
50%UnverifiedOn Google Cloud Run, the minimum instance specification required to attach a GPU to an L4 service is 4 vCPU plus 16 GiB of memory.
50%UnverifiedOn Cloud Run, per-request billing and per-instance billing are two fundamentally different cost models: per-request billing allocates and charges CPU only during request processing, while per-instance billing charges every second from instance startup to shutdown.
50%UnverifiedIn Cloud Run, GPU instances can currently only use per-instance billing, not per-request billing.
50%UnverifiedCloud Run's GPU quotas are divided by region; us-central1 may not have non-redundant L4 quota, and the author of this article switched to us-east4 to complete the deployment.
50%UnverifiedWhen deploying an MCP server to Cloud Run, at least 2 GB of memory must be allocated, because the MCP server loads a large amount of content into variables at startup.
50%UnverifiedIn serverless inference scenarios such as AWS Lambda and Google Cloud Run, instances are frequently recycled and rebuilt, making cold-start issues especially prominent and typically requiring model weights to be pre-cached to same-region object storage or local SSDs.
50%UnverifiedThree Agents are deployed as Google Cloud Run Jobs and run on a scheduled basis each day via Google Cloud Scheduler
50%UnverifiedThe recommended path for engineering research papers into production: wrap the model as a RESTful API using FastAPI or Flask, package the environment with Docker, implement CI with GitHub Actions, deploy to platforms such as AWS Lambda, Google Cloud Run, or HuggingFace Spaces, and integrate Prometheus + Grafana monitoring.
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