Scalable Software Defined Monitoring for Service Provider DevOps

John, Wolfgang; Meiroşu, Cătălin; Pechenot, Bertrand; Skoldstrom, Pontus; Kreuger, Per; Steinert, Rebecca

doi:10.1109/ewsdn.2015.62

Cited by 14 publications

(11 citation statements)

References 7 publications

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“…Some monitoring databases (eg, OpenTSDB) provide certain aggregation functions although limited, which can be used to reduce the database query latency when the size of the NFV service is really huge. In addition, optimized placement and preaggregation methods of monitoring components can also be used to reduce the size of the collected monitoring data, hence, the database query latency.…”

Section: Evaluation and Discussionmentioning

confidence: 99%

Automatic data aggregation for recursively modeled NFV services

2017

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Summary Network 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.

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Section: Evaluation and Discussionmentioning

confidence: 99%

Automatic data aggregation for recursively modeled NFV services

2017

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“…• Service-specific monitoring intents are annotated to the NF-FG in the MEASURE language. • A novel, secure and carrier-grade message bus (Dou-bleDecker [11]) is used for communication between orchestration, service, monitoring, and troubleshooting components in the UNIFY platform (more details in Section IV-B.) This also shows that further standardization regarding service descriptors is needed.…”

Section: A Customized Decomposition and Scalingmentioning

confidence: 99%

NFV service dynamicity with a DevOps approach: Insights from a use-case realization

Rossem

Cai

Cerrato

et al. 2017

2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)

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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 DevOpsinspired 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. S. Sharma has changed affiliation to NEC Labs Europe since project end. 1 https://www.fp7-unify.eu/

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“…To detect undesired conditions, the framework uses two metrics: the CPU load (gathered by cAdvisor), and the overload risks of the Data Plane components. The latter is a statistical estimation by RAMON, giving the risk of the byte-rate reaching an upper limit (e.g., the line-rate) [5]. In the following, we walk through the main life-cycle events of the service.…”

Section: The Demo Setupmentioning

confidence: 99%

“…It supports the deployment of different VNF types, specified in the NF-FG it receives. It is also capable of starting and configuring a set of monitoring components [5], as specified in a special NF-FG annotation (MEASURE) expressing monitoring intents for the service components. To sustain communication between the different components, a secure message bus (DoubleDecker) distributes control and monitoring information including scaling or troubleshooting triggers.…”

Section: The Demo Setupmentioning

confidence: 99%

NFV service dynamicity with a DevOps approach

Rossem

Cai

Cerratoz

et al. 2017

2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)

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Abstract-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.

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Scalable Software Defined Monitoring for Service Provider DevOps

Cited by 14 publications

References 7 publications

Automatic data aggregation for recursively modeled NFV services

Automatic data aggregation for recursively modeled NFV services

NFV service dynamicity with a DevOps approach: Insights from a use-case realization

NFV service dynamicity with a DevOps approach

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