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Google Cloud Run

Score8.9 out of 10

17 Reviews and Ratings

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What is Google Cloud Run?

Google Cloud Run enables users to build and deploy scalable containerized apps written in any language (including Go, Python, Java, Node.js, .NET, and Ruby) on a fully managed platform. Cloud Run can be paired with other container ecosystem tools, including Google's Cloud Build, Cloud Code, Artifact Registry, and Docker. And it features out-of-the-box integration with Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting to ensure the health of an application.

Categories & Use Cases

Key Features

Learn about the best (and worst!) features Google Cloud Run has to offer, as determined by TrustRadius' reviewers.
Based on 17 ratings of Google Cloud Run's features
View all features

Top Performing Features

  • Security and Isolation

    Product provides effective tools to isolate containers, nodes, and clusters and protect them from threats.

    Category average: 8.5

  • Container Orchestration

    The product’s ability to automate networking, deployment, scaling, and other container management functions.

    Category average: 8.3

  • Resource Allocation and Optimization

    Product’s ability to balance resource requirements, availability needs, and workload intensity to optimize resource usage.

    Category average: 7.7

Areas for Improvement

  • Analytics, Monitoring, and Logging

    Product provides tools to manage performance, health, and other data related to containers or clusters. This could include analytics tools, logging tools, live dashboards, etc.

    Category average: 7.9

  • Cluster Management

    Product’s ability to centralize the management of multiple container or node clusters.

    Category average: 8.1

  • Storage Management

    Product’s ability to allocate storage resources and manage both temporary and persistent data.

    Category average: 8.1

Reviews

What users are saying about Google Cloud Run.
View all reviews

The Best Serverless app hosting platform.

Incentivized
Shivanand Labbi
Senior software engineer in Information Technology at Manhattan (501-1000 employees employees)

Use Cases and Deployment Scope

We use Google Cloud Run in our organization to deploy the majority of containerized applications into it without owning any infrastructure from our end, which is one of the biggest relief with regards to Google Cloud Run because it takes care of auto scaling, manages latency issues, along with good redundancy with very solid backend support. post Cloud Run major infra management has been reduced to core for our team also it gives lot of savings.

Pros

  • Auto scaling is the best one
  • provide direct VPC connectivity and rigid network
  • Cloud SQL and Pub/Sub services
  • Handling latency issues

Cons

  • More detailed documentaion we can expect, current looks bit complex
  • I would say its bit expensive so to run small application also we need to pay more
  • Migration part is bit complex need some impriovement over there
  • starting trouble it has I feel , feel slowness in start slowly it picks up.

Return on Investment

  • Lots of cost savings and less infra resources
  • Esay to use and manage and deployments also so good choice
  • The only negative part is that we will have zero idea of where the app is running, so we will have to be completely dependent on Google when it comes to the security part.

Alternatives Considered

Splunk AppDynamics, Docker, Google Kubernetes Engine, IBM WebSphere Hybrid Edition and IBM DataPower Gateway

Other Software Used

IBM DataPower Gateway, Docker, Splunk AppDynamics, PagerDuty, Google Cloud Platform

Usability

A solid production-ready container application manager

Incentivized
Verified User
Director in Engineering (51-200 employees employees)

Use Cases and Deployment Scope

We're testing the execution of a container version for our Vistadash product. This allow us to estimate costs in a controlled environment, which is also production ready.

Pros

  • Observability Tools
  • DNS mapping
  • Revision management

Cons

  • Docker compose support
  • Tighter integration with Artifact Registry
  • Simplify steps to release a revision

Return on Investment

  • Accelerate testing times for Proof of Concepts
  • Enable cost estimations before release

Alternatives Considered

Amazon Elastic Container Service (Amazon ECS)

Other Software Used

Postman, Windsurf, 1Password

Google Cloud Run is optimal for running container at scale.

Incentivized
Verified User
Engineer in Information Technology (1-10 employees employees)

Use Cases and Deployment Scope

We use a Docker container that converts images to smaller sizes and makes map tiles with large images for indoor maps for navigation. Using just serverless functions was not enough because of the time limit. Making conversions with images takes running time that was only supported using Google Run, which increases the time limit to 24 hours.

Pros

  • Serverless service.
  • Run python scripts.
  • Manage Docker images.

Cons

  • Increase up time.

Return on Investment

  • Make the tasks to standardize the images of the application easier.
  • It is possible to create tile maps that are key to the application.

Google Cloud Run is any developers favourite

Incentivized
Vinaya Kumar BendiView profile
Engineering Lead in Engineering at Kloudle (1-10 employees employees)

Use Cases and Deployment Scope

Most of our platform services are deployed as Google Cloud Run services.

Recently, we have also turned towards Google Cloud Run jobs for performing flow run tasks managed by a job server.

Being an early startup, using Google Cloud Run helps us to keep a tab on our cloud costs based on usage.

Pros

  • Auto scaling
  • Request concurrency
  • Customise memory and CPU resources

Cons

  • Increase request timeout beyond the current 1 hour limit on Google Cloud Run services
  • Support for troubleshooting unexpected Google Cloud Run container exits after running for several hours
  • Support configuration for calling of HTTP endpoints for pull based subscriptions

Return on Investment

  • Built in support for auto scaling helps reduce operational overhead
  • Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
  • Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

Alternatives Considered

AWS Lambda and DigitalOcean Droplets

Other Software Used

AWS Lambda, DigitalOcean Droplets, Google Compute Engine

Google Cloud Run is perfect to run GTM Server Side

Incentivized
Francois SalvertView profile
Web Analytics and Dashboarding senior consultant in Marketing at Dataligent Services Analytiques Inc. (1-10 employees employees)

Use Cases and Deployment Scope

We use Google Cloud Run to host Google Tag Manager server side scripts.

Pros

  • Easy to setup
  • Very cost efficient
  • Quick delivery and scalable options to maintain speedy deliveries if site ever needs it.

Cons

  • The documentation is not always clear and sometimes trial and error is needed
  • The menu system is not user friendly and inconsistent: sometimes it's tabs, sometimes menus and other configuration pages are long to scroll. Could (and will) be improved.

Return on Investment

  • It runs well for GTM server side which enables great marketing campaigns and re-targeting
  • The cost is negligible vs other solutions
  • Easy to maintain and upgrade

Alternatives Considered

Looker, Google BigQuery, Google Analytics and Google Tag Manager

Other Software Used

Google Tag Manager, Meta Pixel, Google Analytics

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