Microsoft has made generally available Azure Kubernetes Fleet Manager to make it simpler to centrally manage multiple clusters in a way that can be staged along with a set of tools for optimizing costs.
At the same time, Microsoft is making it simpler to deploy large language models (LLMs) on the Azure Kubernetes Service (AKS) using a Kubernetes AI toolchain operator in addition to previewing an extension to the Azure Container Apps platform that adds support for an event-driven framework to train AI models alongside support for open source Qdrant, Milvus and Weaviate vector databases.
Announced at the Microsoft Ignite conference, Microsoft is also previewing an Azure Container Apps code to cloud capability to enable developers to package application code without needing to know how containers function.
Microsoft has also made generally available an Azure Container Apps landing zone accelerator to make it simpler to provision Azure infrastructure.
Scott Guthrie, executive vice president for cloud and AI at Microsoft, told conference attendees that organizations such as Lego have decided to rely on Microsoft to streamline the management of their Kubernetes environment.
These additions come on the heels of a flurry of recent updates to the Microsoft AKS portfolio that include an update to the resource reservation algorithms to enable as much as a 20% in memory requirements, a preview of an Artifact streaming tool that eliminates the need to wait for container images to be fully loaded into Kubernetes clusters and a Kubernetes event-driven autoscaling capability.
Microsoft is also now making available a public preview of an Istio service mesh add-on, an Azure CNI Overlay for AKS update that adds support for both IPv4 and IPv6 addresses to co-exist within a single cluster and an add-on to enable application routing.
Previews of an Azure Container Storage service for AKS to scale out volume and reduce pod failover times for applications accessing block storage…
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