Google Kubernetes Engine vs. Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

The Google Kubernetes Engine clusters are very good at being a managed cloud K8s platform - lots of documentation, features, and updates are available. It's also newbie-friendly - for both administrators and developers. Unfortunately, currently, it cannot reach true zero scale - thus, costs (rent for the service) are still involved even if you are barely using it. Thankfully, it's possible to have alternatives in Google Cloud:

• Your own K8s cluster on Compute Engine VMs - you manage it completely; it will have access to a lot of Google Cloud services.
• Cloud Run cluster - less documented but more flexible
• Anthos clusters - you can use this service for a lot of types of K8s clusters - Google Kubernetes Engine, Cloud Run, on-prem, AWS, Azure

Incentivized

If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.

Incentivized

• Deployment of a new GKE cluster is really fast in comparison to other cloud providers.
• GCP is ahead other vendors and always provide the most up to date Kubernetes version.
• GKE automation for master upgrade and the worker nodes pool works really well.

Incentivized

• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

Incentivized

• Not as intuitive as it could be
• Documentation could be better, especially for people using other Google Cloud tools
• Not the preferred Kubernetes Engine for many apps

Incentivized

• Running on Azure is a little more difficult.
• Synchronization with Kafka may be a little easier.

Incentivized

• Google Kubernetes Engine has a good UI and documentation that facilitates setup and helps get projects moving along quickly
• Its built-in logging integrations with StackDriver make it easier to monitor the application and log issues quickly
• Automated orchestration, deployment, and scaling of nodes and networking are all easily configurable with yaml files

Incentivized

Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.

Incentivized

They were very helpful. We needed support for initial implementation.

Incentivized

GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.

Incentivized

• When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.

Incentivized

• Positive: Allowed us to start and produce working software regardless of our experience level.
• Positive: Integration with other Google Cloud services that we wanted to use anyway.
• Negative: It's kinda clunky, and some scenarios seem Google Kubernetes Engine-specific instead of being more integrated with other Google Cloud services or the web UI.

Incentivized

• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

Incentivized