The use of applications in which mobile devices interact with cloud-based artificial intelligence (AI) models, such as Large Language Models (LLMs), is rapidly growing in fifth-generation (5G) mobile networks. For these applications, end-to-end Quality of Experience (QoE) reflects user satisfaction by measuring whether a service meets its performance objectives. In 5G networks, however, accurate QoE assessment is challenging because end-to-end encryption limits observability at the application layer. We propose a multi-agent system for QoE assurance in encrypted traffic environments. The first agent analyzes a high-level application description to translate user-level QoE objectives into measurable network and cloud performance requirements. The second agent continuously monitors the network and cloud infrastructure to detect violations of these requirements and triggers corrective actions when necessary. We evaluate our approach using an AI-driven augmented reality (AR) application in which an AR glasses device transmits visual and voice data over a 5G testbed to AI models running in a mobile edge cloud. The models process the incoming streams and return inference results to the device. Our results demonstrate accurate detection of quality-of-experience (QoE) degradations in encrypted traffic across multiple scenarios, as well as clear performance improvements over existing QoE estimation approaches.

The 6G platform will enable communication service providers to take a major step toward delivering more than best-effort communication. By enabling fast and easy introduction of new exposed services, 6G will be a powerful platform for developers to realize advanced use cases such as immersive communication.

Emerging use-cases like smart manufacturing and smart cities pose challenges in terms of latency, which cannot be satisfied by traditional centralized infrastructure. Edge networks, which bring computational capacity closer to the users/clients, are a promising solution for supporting these critical low latency services. Different from traditional centralized networks, the edge is distributed by nature and is usually equipped with limited compute capacity. This creates a complex network to handle, subject to failures of different natures, that requires novel solutions to work in practice. To reduce complexity, edge application technology enablers, advanced infrastructure and application orchestration techniques need to be in place where AI and ML are key players.

In order to fully support emerging use cases such as the Internet of Senses [1], cyber-physical systems and connected intelligent machines [2], the foundation of future network platforms must be built on tight integration between reliable, deterministic connectivity and scalable, affordable and efficient processing capabilities. The result of this tight integration is what we call the network compute fabric.

The cloud is transforming, both in terms of the extent of distribution and in the diversity of compute and storage capabilities. On-premises and edge data centers (DCs) are emerging, and hardware (HW) accelerators are becoming integral components of formerly software-only services.

Virtualization, either at OS- or hardware level, plays an important role in cloud computing. It enables easier automation and faster deployment in distributed environments. While virtualized infrastructures provide a level of management flexibility, they lack practical abstraction of the distributed resources. A developer in such an environment still needs to deal with all the complications of building a distributed software system. Different orchestration systems are built to provide that abstraction; however, they do not solve the inherent challenges of distributed systems, such as synchronization issues or resilience to failures. This paper introduces Nefele, a decentralized process orchestration system that automatically deploys and manages individual processes, rather than containers/VMs, within a cluster. Nefele is inspired by the Single System Image (SSI) vision of mitigating the intricacies of remote execution, yet it maintains the flexibility and performance of virtualized infrastructures. Nefele offers a set of APIs for building cloud-native applications that lets the developer easily build, deploy, and scale applications in a cloud environment. We have implemented and deployed Nefele on a cluster in our datacenter and evaluated its performance. Our evaluations show that Nefele can effectively deploy, scale, and monitor processes across a distributed environment, while it incorporates essential primitives to build a distributed software system.

This demo presents Nefele, a fully distributed, multi-tenant process orchestration system for cloud infrastructures. Nefele is inspired by the Single System Image (SSI) vision and its aim is to hide the heterogeneous and distributed nature of the available resources in a cluster and present them to users and applications as a single unified computing resource. In Nefele, a developer is equipped with a set of SSI-like features and programming interfaces to simplify the complexities of process deployment and Inter Process Communication (IPC) in distributed environments. The developer uses the APIs to simply deploy, execute, connect, and monitor tenants' processes spread over several nodes in a cluster.

Cloud offerings have over the years been transformed from bare-metal to virtual machines, to containers, and most recently to serverless functions. Each of these execution context abstractions has been accompanied by a new layer of centralized management, but these extra management layers have led to a confusing and fragile system, that wastes developer time on managing execution contexts with little contribution to the application. We argue that it is time to revisit ideas of Single System Image (SSI) concepts to simplify the management of Cloud execution contexts. An SSI abstraction for Cloud provides easy and convenient developer access to resources without recourse to programming multiple levels of execution contexts. We propose a novel set of design principles inspired by earlier distributed operating system and SSI research. We also present a first corresponding service, realizing fully decentralized resource management, folding multiple layers of centralized management stacks into a single layer spanning across data-center resources. As a result, developers never see individual execution environments, but deal with processes and IPC familiar from local development machines.

Next generation network services will be realized by NFV-based microservices to enable greater dynamics in deployment and operations. Here, we present a demonstrator that realizes this concept using the NFV platform built in the EU FP7 project UNIFY. Using the example of an Elastic Router service, we show automated deployment and configuration of service components as well as corresponding monitoring components facilitating automated scaling of the entire service. We also demonstrate automatic execution of troubleshooting and debugging actions. Operations of the service are inspired by DevOps principles, enabling quick detection of operational conditions and fast corrective actions. This demo conveys essential insights on how the life-cycle of an NFV-based network service may be realized in future NFV platforms.

5G mobile communication systems will need to accommodate a variety of use-cases, resulting in a diverse set of requirements. To meet these requirements, 5G systems take advantage of modern virtualization possibilities offered by Network Function Virtualization (NFV), enabling deployment agility and dynamicity of virtualized network functions. With the transformation of telecom towards virtualized environments, advanced observability possibilities gain increasing importance as one of the essential prerequisites, especially for successful DevOps operations. However, deployment agility also puts specific requirements on monitoring solutions in order to adapt automatically and continuously to frequent changes in service deployments. In this short-paper, we establish and discuss essential properties of observability systems for virtual network functions in a 5G context. We take these properties as guiding design principles for our software-defined monitoring framework and outline how to evolve our existing components towards a flexible, scalable, and programmable observability solution for microservice-based NFV with features for increased manageability.

This experience paper describes the process of leveraging the NFV orchestration platform built in the EU FP7 project UNIFY to deploy a dynamic network service exemplified by an elastic router. Elasticity is realized by scaling dataplane resources as a function of traffic load. To achieve this, the service includes a custom scaling logic and monitoring capabilities. An automated monitoring framework not only triggers elastic scaling, but also a troubleshooting process which detects and analyzes anomalies, pro-actively aiding both dev and ops personnel. Such a DevOps-inspired approach enables a shorter update cycle to the running service. We highlight multiple learnings yielded throughout the prototype realization, focussing on the functional areas of service decomposition and scaling; programmable monitoring; and automated troubleshooting. Such practical insights will contribute to solving challenges such as agile deployment and efficient resource usage in future NFV platforms.

—Next generation network services will be realized by NFV-based microservices to enable greater dynamics in deployment and operations. Here, we present a demonstrator that realizes this concept using the NFV platform built in the EU FP7 project UNIFY. Using the example of an Elastic Router service, we show automated deployment and configuration of service components as well as corresponding monitoring components facilitating automated scaling of the entire service. We also demonstrate automatic execution of troubleshooting and debug- ging actions. Operations of the service are inspired by DevOps principles, enabling quick detection of operational conditions and fast corrective actions. This demo conveys essential insights on how the life-cycle of an NFV-based network service may be realized in future NFV platforms.

SummaryNetwork function virtualization (NFV) allows to model network services as graphs interconnecting virtual network functions (VNFs), which may include nested VNFs, modeled as subgraphs of VNFs or end points. To query the performance data of network services modeled as abstract and high‐level graphs is challenging because of the recursivity of the NFV architecture and the elasticity and dynamicity provided by the NFV infrastructure. We propose to use Datalog, a declarative logic programming language, to build a framework that supports efficient data aggregation for performance metrics of recursively modeled network services. We present our recursive query language for automatic and flexible decomposition and aggregation of NFV performance metrics and describe example use cases for both compute and network metrics. We also describe the design and implementation of a proof‐of‐concept query engine using the language. Our performance evaluation shows that the total query latency is dominated by retrieval times of performance metrics from infrastructure databases, and the time for execution and automatic decomposition of high‐level queries by the query engine itself increases linearly with the size of the service graph up to 1000 nodes. Hence, our evaluations show that the query engine scales well, bounded mainly by the limited execution capabilities of our test environment. Furthermore, it can handle multiple concurrent queries up to the concurrency limits of the backend database in use. The proposed query language and engine are thus effective in recursively retrieving performance metrics of NFV environments supporting large‐scale service graphs and large numbers of query requests.

Although there is consensus that software defined networking and network functions virtualization overhaul service provisioning and deployment, the community still lacks a definite answer on how carrier-grade operations praxis needs to evolve. This article presents what lies beyond the first evolutionary steps in network management, identifies the challenges in service verification, observability, and troubleshooting, and explains how to address them using our Service Provider DevOps (SP-DevOps) framework. We compendiously cover the entire process from design goals to tool realization and employ an elastic version of an industry-standard use case to show how on-the-fly verification, software-defined monitoring, and automated troubleshooting of services reduce the cost of fault management actions. We assess SP-DevOps with respect to key attributes of software-defined telecommunication infrastructures both qualitatively and quantitatively, and demonstrate that SP-DevOps paves the way toward carrier-grade operations and management in the network virtualization era.

As Software Defined Networks (SDN) deployments are reaching mainstream, network performance becomes a key concern for success. Service Providers (SPs) rely on network management capabilities, such as packet loss monitoring, to observe the network status and thereby facilitate service-level agreements. On one hand, SPs seek tools providing greater visibility into the status of their networks, but on the other hand, they are keen to limit the overhead of management capabilities in their operational networks. To meet these conflicting requirements, Efficient Passive Lightweight Estimator (EPLE) takes advantage of existing network traffic and SDN signaling, without the need of extra monitoring traffic or facilities. EPLE does not introduce any data plane overhead and the signaling overhead is reduced by locally creating microflow descriptors out of aggregated flow definitions. Our proof-of-concept prototype shows that EPLE can estimate packet loss rates accurately while keeping the processing and signaling overheads small compared to existing active measurement methods.

In Network Function Virtualization (NFV), a network service is created by combining interconnected virtual network functions (VNF), which may include nested VNFs or end points. Querying the performance of a high-level, abstract network service is challenging due to the recursivity of the NFV architecture and the elasticity and dynamicity provided by the NFV infrastructure, typically realized by Cloud virtualization technologies. In this paper, we propose to use Datalog, a declarative logic programming language, to build a query engine which can provide recursive query capabilities on performance metrics of network services. We present the language and describe some example use cases for both compute and network metrics. We describe the design of a query engine utilizing the language, based on which we implemented a proof of concept system. The resulting experimental system has shown the effectiveness of the query language to recursively retrieve monitoring results of NFV environments.

Carrier-grade network management was optimized for environments built with monolithic physical nodes and involves significant deployment, integration and maintenance efforts from network service providers. The introduction of virtualization technologies, from the physical layer all the way up to the application layer, however, invalidates several well-established assumptions in this domain. This draft opens the discussion in NFVRG about challenges related to transforming the telecom network infrastructure into an agile, model-driven production environment for communication services. We take inspiration from data center DevOps regarding how to simplify and automate management processes for a telecom service provider software-defined infrastructure (SDI). Among the identified challenges, we consider scalability of observability processes and automated inference of monitoring requirements from logical forwarding graphs, as well as initial placement (and re-placement) of monitoring functionality following changes in flow paths enforced by the controllers. In another category of challenges, verifying correctness of behavior for network functions where flow rules are no longer necessary and sufficient for determining the forwarding state (for example, stateful firewalls or load balancers) is very difficult with current technology. Finally, we introduce challenges associated with operationalizing DevOps principles at scale in software-defined telecom networks in three areas related to key monitoring, verification and troubleshooting processes.

This report presents the results of the UNIFY Service Provider DevOps activities. First, we present the final definition and assessment of the concept. SP-DevOps is realized by a combination of various functional components facilitating integrated service verification, efficient and programmable observability, and automated troubleshooting processes. Our assessment shows that SP-DevOps can help providers to reach a medium level of DevOps maturity and allows significant reduction in OPEX. Second, we focus on the evaluation of the proposed SP-DevOps components. The set of tools proposed supports ops and devs across all stages, with a focus on the deployment, operation and debugging phases, and allows to activate automated processes for operating NFV environments. Finally, we present use-cases and our demonstrators for selected process implementions, which allowed the functional validation of SP-DevOps.