Reviews (1-11 of 11)
- Quick Updates, Highly Scalable. We keep adding nodes when needed.
- Never spent a minute on any maintenance activities for our Kube Cluster.
- Zero Downtimes in last 2 years.
- Helm inventory is somewhat lacking.
- Little confusing when it comes to PVCs.
- Networking between our Kube Clusters and our other VMs is very difficult due to lack of documentation
1) Running an application which is built on a microservice architecture.
2) Running NodeJs services, proxy services.
1) For running DB engines.
- Help to orchestrate the containers on with we have deployed our micro services
- Auto scaling
- It makes it super easy to deploy applications
- Much better integration with the log analysis
- Make it easy to retrieve the logs and search through them
- Gives the scale we need
- Bundled with Dev Ops it becomes easier to deploy and operate
- Gives us the portability across cloud providers
- Dev Ops reference templates are not available for organizations to quickly adopt
- Organizations want to focus on developing business features but wanted a pipeline which takes the code all the way to deployment without much human intervention. Wanted to see quick set up of Kubernetes platform along with Dev Ops capabilities as Service.
Not well suited: legacy monolithic applications
- Sends data from IBM Data Connect to Data Analytics in one click.
- Manages coding in the cloud IDE with continuous integration.
- Has tool chains which aggregate different services together into a complete process.
- Has a dashboard that is far more in-depth and intuitive than AWS or Azure.
- Basics like DNS and routing can be challenging.
- Uptime is not at the same level as AWS.
- Phone support is not at the level of AWS.
- Absolutely for prototyping.
- Ideal for inter-company data exchanges.
- Great for shared managed coding by dispersed teams.
- Excellent suite of starter code.
- Excellent AI integration via Watson, Node-Red including for IOT.
Bluemix gave us the ability to iterate on multiple initiatives and micro-services with limited resources.
- Prepared environment - the preparation of the platform was easy for us to spin up
- Selection of services that we would implement. Limited need to search for varied sources
- Our developers felt that the documentation was difficult to navigate. Time spent in the platform cleared the problem for the team.
Our team built the forms and services they wanted in days without the need to manage a local environment and across geographical regions.
- Local install options.
- Often for large companies IBM is already on the network and it is an easier sell.
- Kubernetes is comparatively new there, needs maturing.
- Getting your app available as a third party is a longish process, needs streamlining.
- Still some shifting around and renaming of elements of the Watson APIs that can throw off development, hopefully, all is now set.
- Good documentation and examples for integrating APIs.
- Wonderful technology from an infrastructure POV, nearly on par with AWS.
- Watson APIs are some of the most robust turn-key ML packages out there. Furthermore, one can take these out of the box in minutes and have a working cognitive app very easily.
- Great support when needed.
- Pricing tiers for larger volumes should be included. Also, costs should be evaluated on a use-case basis, pricing these types of services by number of API calls can be prohibitive for some applications.
- Lagging in dev speed to compared to AWS.
- Need to support batch processing for Watson APIs (I'm told this is on the road map).
- Rapid implementation for IoT platform
- Rapid implementation of a micro service environment
- Deep learning facilities available in the value stream
- Surprisingly complex to implement some features, like port forwarding within the PaaS architecture without implementing IaaS layer features.
IBM Cloud Kubernetes Service Scorecard Summary
About IBM Cloud Kubernetes Service
A managed Kubernetes offering to deliver powerful tools, an intuitive user experience and built-in security for rapid delivery of applications that you can bind to cloud services related to IBM Watson®, IoT, DevOps and data analytics. As a certified K8s provider, IBM Cloud Kubernetes Service provides intelligent scheduling, self-healing, horizontal scaling, service discovery and load balancing, automated rollouts and rollbacks, and secret and configuration management. The Kubernetes service also has advanced capabilities around simplified cluster management, container security and isolation policies, the ability to design your own cluster, and integrated operational tools for consistency in deployment.
IBM Cloud Kubernetes Service Integrations
IBM Cloud Kubernetes Service Competitors
IBM Cloud Kubernetes Service Customer Size Distribution
|Small Businesses (1-50 employees)||0%|
|Mid-Size Companies (51-500 employees)||50%|
|Enterprises (> 500 employees)||50%|
IBM Cloud Kubernetes Service Support Options
|Free Version||Paid Version|
|Video Tutorials / Webinar|
|Slack Channel to Development Team|
IBM Cloud Kubernetes Service Technical Details
|Supported Languages:||A managed Kubernetes offering to deliver powerful tools, an intuitive user experience and built-in security for rapid delivery of applications that you can bind to cloud services related to IBM Watson®, IoT, DevOps and data analytics. As a certified K8s provider, IBM Cloud Kubernetes Service provides intelligent scheduling, self-healing, horizontal scaling, service discovery and load balancing, automated rollouts and rollbacks, and secret and configuration management. The Kubernetes service also has advanced capabilities around simplified cluster management, container security and isolation policies, the ability to design your own cluster, and integrated operational tools for consistency in deployment. Visit our Docs pages for pricing and support information.|