Energy Savings &amp; Resiliency with Closed Loop Platform Automation

Browne, John; Kepka, Krzysztof; Kutch, Patrick; Ranganath, Sunku

doi:10.23919/tma.2019.8784669

Cited by 1 publication

(2 citation statements)

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“…Existing scheduling and workload migration mechanisms address synchronization issues in single-cluster environments, focusing on specific aspects [53]. For example, the Intel Telemetry Aware Scheduler (TAS) [54] supports telemetry-aware scheduling and intelligent workload placement in Kubernetes, enforcing a user-defined telemetry policy based on computing node health metrics. The lightweight Kubernetes-based Event Driven Autoscaler (KEDA) 34 allows pods to be invoked based on external events, extending the native autoscaling capabilities of K8s.…”

Section: B Adaptive Scheduling and Workload Migrationmentioning

confidence: 99%

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A Framework for Cognitive, Decentralized Container Orchestration

Sofia,

Salomon,

Ferlin-Reiter

et al. 2024

IEEE Access

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This perspective paper introduces a novel framework for container orchestration called CODECO. The CODECO orchestration framework relies on a data-network-computing approach to define the best infrastructure that can support the operation of next-generation Internet applications across a mobile, heterogeneous Edge-Cloud continuum. The selection of such an infrastructure is aligned with target performance profiles defined by the user, such as resilience or greenness. CODECO proposes to rely on decentralized Artificial Intelligence approaches in an attempt to provide the most suitable infrastructure to an application deployment, considering infrastructural challenges, such as intermittent connectivity and node failure. This paper explains the current CODECO framework and provides insight into operational use-cases where CODECO is being deployed, as relevant examples of application for such a framework. Recent developments in the creation of the open-source CODECO framework are described and explained, allowing the use of the framework by the research community. The paper then provides a thorough analysis of CODECO's features in comparison with existing orchestration frameworks, explaining the benefits introduced with this dynamic orchestration approach.INDEX TERMS Edge-Cloud; Orchestration; Kubernetes; AI/ML; heterogeneous networks; data observability.

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Section: B Adaptive Scheduling and Workload Migrationmentioning

confidence: 99%

“…It also provides K8s-specific APIs for efficient management of network traffic. In addition, we also consider the Link-Layer Secure connectivity for microservice platforms (L2S-M) 54 as a starting point. L2S-M is a Kubernetes operator that enables virtual networking using an SDN-based data plane.…”

Section: Cross-layer Network Management and Adaptationmentioning

confidence: 99%