containerized network functions (CNFs) have seen recent increase in adoption due to the success of orchestration platforms and the natural flexibility of containers for deployment to heterogeneous, resource constraine...
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ISBN:
(纸本)9798350368543;9798350368536
containerized network functions (CNFs) have seen recent increase in adoption due to the success of orchestration platforms and the natural flexibility of containers for deployment to heterogeneous, resource constrained environments like the edge. However, the weak isolation model of containers makes them susceptible to performance degradation due to interference from other containers. The interference manifests as stress on various resources like CPU, memory, cache, bandwidth of a CNF. While identifying the exact resource that is under stress is essential to employ the right remediation strategies, it is a challenging problem given the wide spectrum of applications, platforms and hardware, especially with the high performance requirements of CNFs with stringent SLAs. We present SARI, a first of a kind practical NF-agnostic framework leveraging temporal patterns in syscalls. SARI works for multi-service NFs and generalizes to a wide range of conditions. We leverage supervised time series classification and achieve performance upto 98.9% with minimal captures at runtime (starting from 25ms). SARI's prediction error is 63.33% lower than any existing stress identification framework for VNFs and to the best of our knowledge, the first to address the problem for CNFs.
As the adoption of softwarized networkfunctions (NFs) keeps growing, we evaluate the performance benefits of SDN-aware data-plane implementations when compared to diverse acceleration and process-based NFV frameworks...
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ISBN:
(纸本)9781665406949
As the adoption of softwarized networkfunctions (NFs) keeps growing, we evaluate the performance benefits of SDN-aware data-plane implementations when compared to diverse acceleration and process-based NFV frameworks. Typical networkfunctions have been implemented using four alternative frameworks scenarios, an SDN-aware software switch (data-plane), a virtual machine (VM), a Data-Plane Development Kit (DPDK) NF, and a containerized NF. Results from our experiments show that the data-plane NF implementation yields much higher bandwidth and packets per second (pps) rates. The bandwidth obtained is 14% more than the user-space scenario while retaining CPU utilization. The DPDK NFs in our evaluation can process packets at a much higher rate for 64B packets, on a single CPU core, which is 7 times higher than the containerized NF implementations, also tied to a single core. Our results also show the performance gains from deploying virtual networkfunctions on heterogeneous frameworks.
Service meshes factor out code dealing with inter-micro-service *** overall resilience of a cloud application is improved if constituent micro-services return stale data, instead of no data at all. This paper proposes...
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ISBN:
(纸本)9781665405225
Service meshes factor out code dealing with inter-micro-service *** overall resilience of a cloud application is improved if constituent micro-services return stale data, instead of no data at all. This paper proposes and implements application agnostic caching for micro services. While caching is widely employed for serving web service traffic, its usage in inter-micro-service communication is lacking. Micro-services responses are highly dynamic, which requires carefully choosing adaptive time-to-life caching algorithms. Our approach is application agnostic, is cloud native, and supports gRPC. We evaluate our approach and implementation using the micro-service benchmark by Google Cloud called Hipster Shop. Our approach results in caching of about 80% of requests. Results show the feasibility and efficiency of our approach, which encourages implementing caching in service meshes. Additionally, we make the code, experiments, and data publicly available.
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