IBM Cloud improves App Availability with Multizone Kubernetes Clusters for AI, BlockChain and IoT

IBM announced on their blog and twitter about the availability of multi-zone clusters for IBM Cloud Kubernetes Service (IKS). Users of IKS can deploy containerized applications across multiple global IBM Cloud zones within a region as a single operation.

IBM had previously joined other cloud providers by expanding IBM Cloud Service to 18 new additional availability zones across North America, Europe and the Asia Pacific.

Multiple availability zones will help users of IBM Cloud Kubernetes Service to manages each piece of a containerized app simultaneously across different zones. On IBM cloud platform, it offers services such as rolling out updates, connecting it into the high-value services the IBM Cloud offers, and finding vulnerabilities.

This week, we announced we're expanding the ease and flexibility of containers even further with multi-zone clusters for #IBMCloud Kubernetes Service. Details: https://t.co/TVWKpnYH7r via @jrmcgee pic.twitter.com/jXtAwAHdOh

— IBM Cloud (@IBMcloud) June 17, 2018

Kubernetes clusters now have a feature called a worker pool. It is a collection of worker nodes with the same flavor. It helps in defining the number of app instances and then let Kubernetes ensure the app is distributed across your zones.

IBM Cloud Kubernetes Service will take care of underlying infrastructure. The container infrastructure is critical to build and scale AI, the blockchain, and the Internet of Things (IoT) use cases. IBM has worked with Google and Lyft to build Istio. These efforts are now helping orchestrate, secure and manage traffic and data flowing through containers and microservices.

IBM Cloud Service capabilities will help developers to increase the availability, ease the deployment and scaling of containerised apps across geographies. Thus making it ideal choice for AI deployments, the announcement said.

Jason McGee, VP and IBM Fellow, IBM Cloud stated in the announcement that "Containers are natural building blocks for the next era of cloud workloads, such as AI and machine learning. We know the benefits of fueling AI with containers firsthand: our own Watson services run on Kubernetes.

The secret to running well-tuned AI lies in containers. When designed correctly, containers offer instant connections into AI tools and address concerns around security, scale, and infrastructure that can distract developers from focusing on improving their code."

Earlier 2018, IBM had launched the option to run our Kubernetes service on bare metal and with GPUs. This feature was critical in enabling AI/ML developers to harness GPUs power. AI and machine learning workloads often require access to the high-performance power of GPUs. 

IBM is also continuing to forge partnerships and Sysdig, a cloud-native intelligence provider, and LogDNA, a container logging and log analyzing platform, will join the IBM Cloud partner ecosystem.