D2iQ Mesosphere vs. Google Cloud Run

Mesosphere is well suited for orchestrating workloads. It supports Docker as a container as well as support others. It is highly suitable for running resilient and auto recovering big data/application containers. Mesosphere has proven time and again to be production ready at a massive scale. It supports native single button/API call scale up and scale down and supports various deployment patterns like Blue-Green and others.

Incentivized

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.

Incentivized

• Deploying mesosphere and friends (e.g. marathon)
• Deploying applications (e.g. Cassandra, Jenkins, Spark) on to mesosphere
• Providing value add components such as velocity, and marathon-lb

Incentivized

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

Incentivized

• Setting up is a bit of a hassle, especially ZooKeeper state management and mesos and marathon quorum.
• Occasionally, I observed some failures when deploying something onto Marathon. Logging or detailed error reporting can help.
• Stale containers and inconsistent states resultant of the cluster failure are hard to solve and need a complete system restart to get it back to normal state.

Incentivized

• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

Incentivized

We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

Incentivized

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.

Incentivized

Not seen any major issues when we run applications its good

Incentivized

Initially we felt slow but slowly it picked up and easy to manage

Incentivized

I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

Incentivized

I happen to like mesosphere because it integrates well with a Jenkins based workflow, Deis is a little more Heroku like and it's not clear how to fit that model into a continuous-integration process. Kubernetes has also been criticized for being complicated.

Incentivized

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.

Incentivized

Not part of purchase.

Incentivized

It has good auto scale feature and reliable also

Incentivized

We have very good support when needed

Incentivized

• I see mesosphere as having a positive impact overall on the industry trending Docker and containers in general.
• Seeing how mesosphere helps and simplifies things for the developer and ops, it is definitely a game changer.
• Native support of on demand scaling up and down as per the need is one of the best features.

Incentivized

• 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

Incentivized