Google Cloud Run Reviews & Product Details

I like Google Cloud Run because it's very simple and flexible. It helps me deploy containerized applications quickly without worrying about scalability, network, and availability issues. This simplicity allows me to focus entirely on building my applications. I find it very good for accessing various services like Google Map API and the translation API, which makes it easy to integrate different applications. I also appreciate how easy it is to set up and use, making my work more straightforward. Review collected by and hosted on G2.com.

I find debugging somehow an issue, and sometimes, when there are many applications loaded, it feels difficult to get back to where I was. It would be better if there was a trace back option to easily navigate back to the beginning, as I often get lost in the middle of using it. Review collected by and hosted on G2.com.

I appreciate Google Cloud Run for its price and ease of deploying containers. You can stay in a free tier for a long time, and by the time you need to pay, your app is already making money. Deployment is easy as long as you use Docker containers. Review collected by and hosted on G2.com.

I find the build process bad because you cannot provide build context and connecting a GitHub project often doesn't work. Setting up workflow federation is hard and not universal, or I have to use insecure service accounts. Also, the start and entrypoint scripts fail if I provide a path to bash/executable, so you have to adjust Dockerfile to a service, just for that. Docker Compose functionality is lacking since I can't even parse the config from docker-compose.yml to my Cloud Run app. Setting Cloud Run as-code is almost impossible. I wish I had more customization options for builds as Cloud Build is very bad to use. Secrets for Cloud Run are treated as the same as environment variables but are very expensive even though they're easy to manage. The CI pipelines for other runtimes besides Docker seem broken. There's also no easy option to use distroless containers out of the box, though they're made by GCP. Review collected by and hosted on G2.com.

I use Google Cloud Run to deploy and scale containerized applications without managing the infrastructure. I like its simplicity and flexibility as it makes deploying containerized services very straightforward and easy while still offering powerful services. I value the automatic scaling the most, and I also value the built-in HTTPS, traffic splitting for gradual rollouts, and seamless integration with other Google Cloud services. The initial setup was fairly straightforward; once the containers were ready, deploying to Google Cloud Run took minimal configuration. Review collected by and hosted on G2.com.

I don't like the cold start latency for certain workloads, especially for heavier containers or less frequent traffic. Review collected by and hosted on G2.com.

I like Google Cloud Run for its fast shipping and low infrastructure management. I find it to be CI/CD friendly and consistent in its environment, which is a big plus for me. The auto-scaling feature stands out as something I really appreciate, making deployment smoother and more efficient. Review collected by and hosted on G2.com.

I find it hard to debug on Google Cloud Run. It would be better with more structured logging in JSON so I can filter the logs. Also, the initial setup wasn't easy, though there's enough documentation to help out. Review collected by and hosted on G2.com.

The best part of Google Cloud Run is how easy it is to deploy and run containerized applications without managing any infrastructure. It automatically scales based on traffic, including scaling to zero, which helps keep costs low. The integration with other GCP services like Pub/Sub, IAM, and Cloud Logging makes it very convenient for building production-ready services quickly. Review collected by and hosted on G2.com.

One downside is cold starts, especially for services with low or sporadic traffic, which can add latency. Debugging can sometimes be tricky since you don’t have full control over the underlying infrastructure. There are also some limitations around long-running or stateful workloads, which means it’s not suitable for every use case. Review collected by and hosted on G2.com.

I use Google Cloud Run for running containerized applications without managing servers, with automatic scaling and pay-only-for-use pricing. I just deploy a container, and Google handles servers, scaling, security, and HTTPS automatically. It saves a lot of time and cost because you pay only when requests come in, making it perfect for APIs and microservices without operational overhead. The initial setup of Google Cloud Run was very easy. You just need to containerize the app, push the image, and deploy. Google handles networking, HTTPS, scaling, and security automatically, so the service can be live in minutes with minimal configuration. Review collected by and hosted on G2.com.

I find the cold start latency when traffic comes after scale-to-zero a bit annoying. The request time limits make handling long-running jobs tougher. The limited local/persistent storage is a hassle since instances are stateless. I also feel there's less control over the infrastructure compared to GKE or VMs. Overall, it's great for stateless, request-driven apps, but not ideal for heavy, long-running, or stateful workloads. Review collected by and hosted on G2.com.

What I like most about Google Cloud Run is the simplicity combined with powerful features. I can deploy containerized applications in minutes, and it automatically scales based on the traffic, including scaling to zero. The ease of deployment and automatic scaling without managing any sort of server stands out for me. The initial setup was very easy, involving minimal configuration, and I was able to deploy the containerized app quickly. Google Cloud handles the networking, scaling, and security automatically, making the process straightforward. Review collected by and hosted on G2.com.

While Google Cloud Run is very easy to use, improvements can be made around advancing the networking and configuration options. For more complex use cases, having clear visibility around the cold starts, request concurrency, and networking behavior would make it even better. Review collected by and hosted on G2.com.

oogle Cloud Run makes it incredibly easy to deploy and scale containerized applications without having to manage servers or Kubernetes clusters. The ability to deploy directly from a container image and get automatic, request-based scaling—down to zero—removes a huge amount of operational overhead. I also appreciate how quickly services start up, the simple configuration model, and seamless integration with other Google Cloud services such as Pub/Sub, Cloud SQL, and Cloud Storage. Review collected by and hosted on G2.com.

While Cloud Run is powerful, it can feel limiting when you need finer control over networking, scaling behavior, or custom runtimes. Cold starts can still be noticeable for some workloads, especially with heavier container images. Observability is improving, but log navigation and debugging across services can be a bit cumbersome. Pricing is fair, but costs can spike unexpectedly for high-traffic workloads if you don’t set appropriate concurrency or scaling limits. Review collected by and hosted on G2.com.

I like that Google Cloud Run automatically scales my apps without me managing servers. It solves the problem of managing servers because I don’t need to handle infrastructure, scaling, or maintenance—Cloud Run does it automatically. Automatic scaling helps me because I do not have to think about capacity; if there are few users, it scales down and costs almost nothing. If traffic suddenly increases, it instantly scales up and my app keeps working smoothly without any downtime. It just handles the load automatically, which saves time and money. The initial setup was very easy as well since we just built a container image, pushed it, and deployed without configuring any infrastructure. Review collected by and hosted on G2.com.

Sometimes the cold start is slow when the service hasn’t been used for a while, and logging/monitoring can feel a bit complex. Review collected by and hosted on G2.com.

I use Google Cloud Run for deploying and containerizing an inference service that powers an LLM-based agent for dynamic content generation and task automation. I especially love how Google Cloud Run solves the challenge of deploying scalable and secure Gen AI workloads without managing infrastructure. It integrates well with Vertex AI, Cloud SQL, and PubSub, making it a fortress to build fully serverless AI architecture. The initial setup was very easy once the container image was ready, and deploying it was almost seamless, requiring just a few commands. Review collected by and hosted on G2.com.

I don't like that cold starts limit debugging visibility and make things complex. Also, PC networking made the experience less smooth than it could be. Review collected by and hosted on G2.com.