Google Cloud Run vs. Mirantis Kubernetes Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud Run
Score 9.2 out of 10
N/A
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.N/A
Mirantis Kubernetes Engine
Score 9.4 out of 10
N/A
The Mirantis Kubernetes Engine (formerly Docker Enterprise, acquired by Mirantis in November 2019)aims to let users ship code faster. Mirantis Kubernetes Engine gives users one set of APIs and tools to deploy, manage, and observe secure-by-default, certified, batteries-included Kubernetes clusters on any infrastructure: public cloud, private cloud, or bare metal.
$0
per year
Pricing
Google Cloud RunMirantis Kubernetes Engine
Editions & Modules
No answers on this topic
Free
$0.00
per year
Basic
$500.00
per year
Offerings
Pricing Offerings
Google Cloud RunMirantis Kubernetes Engine
Free Trial
YesYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsThese pricing options are compatible with Linux or Windows Server and are per year, per node. The basic version requires maximum online purchase not to exceed 50 nodes. Support/professional services are not included.
More Pricing Information
Community Pulse
Google Cloud RunMirantis Kubernetes Engine
Features
Google Cloud RunMirantis Kubernetes Engine
Container Management
Comparison of Container Management features of Product A and Product B
Google Cloud Run
7.3
Ratings
6% below category average
Mirantis Kubernetes Engine
-
Ratings
Security and Isolation8.60 Ratings00 Ratings
Container Orchestration8.40 Ratings00 Ratings
Cluster Management6.40 Ratings00 Ratings
Storage Management2.70 Ratings00 Ratings
Resource Allocation and Optimization8.10 Ratings00 Ratings
Discovery Tools7.70 Ratings00 Ratings
Update Rollouts and Rollbacks8.10 Ratings00 Ratings
Self-Healing and Recovery8.20 Ratings00 Ratings
Analytics, Monitoring, and Logging7.50 Ratings00 Ratings
Best Alternatives
Google Cloud RunMirantis Kubernetes Engine
Small Businesses
Portainer
Portainer
Score 9.6 out of 10
Portainer
Portainer
Score 9.6 out of 10
Medium-sized Companies
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Enterprises
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud RunMirantis Kubernetes Engine
Likelihood to Recommend
8.2
(0 ratings)
8.3
(0 ratings)
Likelihood to Renew
-
(0 ratings)
9.1
(0 ratings)
Usability
6.4
(0 ratings)
8.0
(0 ratings)
Support Rating
-
(0 ratings)
7.8
(0 ratings)
User Testimonials
Google Cloud RunMirantis Kubernetes Engine
Likelihood to Recommend
Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.
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Docker is great for when you would want to use a VM for any given application, but don't need the overhead of the whole OS. Docker containers use very little computing resources, boot up very quickly, and are very easy to set up. An instance where Docker may not be appropriate would be for an application that requires good security. If in this situation, a true VM would probably be your best bet.
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Pros
  • Real-time autoscaling. Escalamento automático em tempo real
  • Simplified Continuous Deployment. Implantação contínua simplificada
  • Running tasks in the background. Execução de tarefas em segundo plano
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  • Containerization - allowing multiple micro-services to function together without in-depth orchestration at the VM level.
  • Rapid deployment - a developer with appropriate access can simply push to the correct remote and the deploy happens automatically from there
  • Decouples provisioning from VM administration - allows containers to be deployed (more) regardless of VM set up.
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Cons
  • Cloud Run doesn't allow you to redeploy an already existing revision which can be inconvenient in some use cases
  • Tricky to get the deployment working to start but once it's working that's great
  • The actual deployment is not the fastest but it's not too bad
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  • Docker has a bit of a learning curve, and it takes some time to become familiar with the tooling and syntax. Transitioning an existing architecture to docker can represent a significant investment.
  • Docker attempts to provide some level of cross-host container orchestration via swarm, but it falls short of third-party solutions like kubernetes.
  • We occasionally run into stability issues when the docker daemon is subjected to high load (many applications starting/stopping frequently). In these cases, docker hangs and we have to restart or replace the node.
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Likelihood to Renew
We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features
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No answers on this topic
Usability
The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.
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Docker's CLI has a lot of options, and they aren't all intuitive. And there are so many tools in the space (Docker Compose, Docker Swarm, etc) that have their own configuration as well. So while there is a lot to learn, most concepts transfer easily and can be learned once and applied across everything.
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Reliability and Availability
Not seen any major issues when we run applications its good
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No answers on this topic
Performance
Initially we felt slow but slowly it picked up and easy to manage
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No answers on this topic
Support Rating
No answers on this topic
The community support for Docker is fantastic. There is almost always an answer for any issue I might encounter day-to-day, either on Stack Overflow, a helpful blog post, or the community Slack workspace. I've never come across a problem that I was unable to solve via some searching around in the community.
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Implementation Rating
I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical
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Alternatives Considered
AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.
Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.
Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.
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I have not used any other software as a container management solution. Its containerized apps allow the usage of less memory, thus
they start and shut down very fast. This tool is helping the enterprise
software to work quickly against the changing conditions thus offers great
scaling by simultaneously allowing me to meet the demands, which also leads to
easy implementation of the strategies.
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Scalability
It has good auto scale feature and reliable also
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No answers on this topic
Return on Investment
  • It has saved us some costs since we now do not require a live server and have moved to a serverless workflow for these services
  • Breaking changes do not affect the entire application now that we have separated our concerns using a serverless service
  • Much easier to debug since we can now isolate our services and reduce the search space for finding/fixing bugs
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  • We are able to try things very quickly compared to before. If you need to debug it, changes on X/Y/Z will have an impact on the way your app works, and changing libraries or configurations of the environment easily can improve your development cycles.
  • In case someone new arrives, the onboarding is pretty easy thanks to Docker. We have tried many configs and images until we reached a point were we have what we want. We don't have to painfully do that again for every new user. We just send him the image.
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ScreenShots