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

If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.

Incentivized

Many developers, especially lesser experienced developers, don't have a really good background in setting up containers from the command line. Portainer is invaluable to them. Giving a UI to them gives them much more confidence and allows them to learn properties and capabilities of containers under far less stress. On the flip side of this, giving then a UI on a production system can lead to chaos...never give junior developers access to production servers.

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

• Engine upgrade rollout strategy - well documented and configurable
• Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
• Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)

Incentivized

• Separating server maintenance with application development, providing a clear user interface for developers who don't want to worry about the underlying server.
• RBAC for container deployment linked to a SAML IDP, not something particularly easy in a native Docker instance but point and shoot in Portainer, allowing the use of Azure / Okta etc to provide user access.
• Image management with multiple repositories is super clear and reduces incidents

Incentivized

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

Incentivized

• Support of IPv6.
• Better GitOps.
• A "serverless" Kubernetes so we can install Google config connector will be really awesome.
• Container-native load balancers do not support internal TCP/UDP load balancers or network load balancers.

Incentivized

• When setting up static IPs for a new container, having the used ones for a specific network at hand would be cool or something like a mini IPAM of some sort...
• Using the developertools to see "oh, it's a 40x or 500" when something doesn't seem to load because the ui just states "Didn't work" is kinda annoying. expandable toasts or something would be nice.

Incentivized

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

Incentivized

It is an excellent tool.

• 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

Accessibility for Non-Experts: even with some people having a bit longer on-boarding it is still very simple Quick setup is insanely useful, we can get it running in 10 seconds after installing docker Portainer has once again super clean UI and is very user friendly. Deployment/monitoring and management are super easy. I can tell just from a glance if something is out of date (watching at you Watchtower not doing your job for some reason)

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

One of their staff members jumped on a video call immediately with me and led me through the problem and solution during a quick session of screen sharing. In this day and age that is above and beyond, especially when it comes to software. It took approximately 5-10 minutes to diagnose and fix, including pleasantries!

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

Incentivized

It is really easy. Just follow the documentation.

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

Portainer takes the cup in terms of usability and features. It is also more useful for smaller deployments, whereas Kubernetes in our opinion and experience, could probably be more suited to certain other use cases. Portainer is also a fresh feel among all the preexisting container management solutions and brings positivity and a new breeze in the industry.

• 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

• Reduced cloud computing costs.
• Easier management of applications.
• Extra time investment to learn how to setup applications in Google versus Amazon.

Incentivized

• Increased productivity: Portainer's user-friendly interface and streamlined container management can help increase the productivity of IT teams.
• Cost savings: By simplifying container management, Portainer can help reduce the time and resources required to manage container environments, potentially leading to cost savings.

Incentivized

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

Incentivized