Predictive autoscaling uses machine learning and historical patterns to pre-scale workloads before traffic arrives, reducing latency and improving cost efficiency compared to reactive scaling.
KAITO streamlines the deployment of large language models on Kubernetes, reducing setup time from days to minutes with automated GPU provisioning and containerized model management.
ClusterSlice introduces a zero-touch deployment platform for automated Kubernetes-centric deployments across the edge-cloud continuum with declarative deployment slice definitions.
Kubernetes Gateway API v1 reaches stable status, delivering modern ingress standard with enhanced features and broad ecosystem support.
Keptn 0.20 delivers application lifecycle improvements, observability enhancements, and integration improvements for cloud-native applications.
Kubernetes 1.29, codenamed 'Mandala,' delivers 49 enhancements with 18 features graduating to stable, including Job lifecycle improvements, NodeLogQuery API (Alpha), KMS v2 as default for secret encryption, PodSecurity Admission enhancements, dual-stack IPv4/IPv6 production readiness, and completed CSI migration. This release emphasizes performance optimization, security hardening, and improved observability for large-scale deployments.
Akri 0.7 delivers edge device discovery improvements, Kubernetes integration enhancements, and protocol support expansion for edge devices.
Thanos 0.32 delivers query performance improvements, storage integration enhancements, and multi-cluster support for highly available Prometheus.
Litmus 2.13 delivers chaos experiment improvements, GitOps integration enhancements, and observability features for chaos engineering.
KubeRay 1.0 provides Kubernetes operator for Ray distributed computing framework, enabling scalable ML workloads and distributed computing on Kubernetes.