using Terraform, this new approach allows Tanzu customers to define clusters as code and to be more agile. This new feature is restricted to deploy workload clusters. 3.3.2.4 Anthos Anthos enables users Integration and/or Continuous Delivery pipeline. A robust CI/CD pipeline is critical to ensure agile development and rapid delivery of new software releases to customers. • Advanced monitoring

programming • CustomResourceDefinition (CRD) • Built on Kubernetes APIs • Kubernetes repo support • Agile, flexible and convenient Node-Operator: Overview • User: SREs who can scale & offline Nodes through

building, evolving and operating rapidly-changing resilient systems at scale” (Jez Humble) • Applying Agile practices to operations • Infrastructure as code • Ops teams embracing source control (git) • Automated

Cloud “Serverless”/ FaaS On-premise Middleware / PaaS ● ● Cloud Native Hybrid ● ● ● Up Agile Portable Elastic Transform Efficient Secure Pay for use Out ● ● Migrate Move up, out or both

The digital solutions group at Booz Allen quickly recognized Ku- bernetes’ ability to drive a more agile, cloud native and microservices-centric strategy, in solving the most complex of infrastruc- ture

platform building for internet scale companies. Vishal is a DevOps practitioner, likes to work in Agile environments with focus on TDD. Vishal's interests span continuous delivery, enterprise DevOps, containers

without pre-trained word2vec embeddings) as they are trained over 10 epochs. The gap between the two approaches is even wider in the case of CNN models, with the pre-trained embedding model achieving a top accuracy up 47-71% of the number of parameters of large NLP models15. In this situation, embedding-free approaches like pQRNN16 are a viable alternative. pQRNN uses the projection operation which maps a given input arXiv:1409.0473 (2014). 23 Luong, Minh-Thang, Hieu Pham, and Christopher D. Manning. "Effective approaches to attention-based neural machine translation." arXiv preprint arXiv:1508.04025 (2015). 22 Vaswani

which performs the best is chosen for full training. In the next section, we'll discuss various approaches for hyperparameter optimization. Hyperparameter Optimization Hyperparameter Optimization improves number of epochs. The algorithms like HyperBand bring the field of HPO closer to the evolutionary approaches which are based on biological mechanisms like mutation and natural selection. The promotion of architectural designs which surpass the current state of the art. Along with the architectures, the approaches to tune the training parameters are evolving as well. In the HPO section, we discussed strategies

frameworks like Tensorflow and Tensorflow Lite. An Overview of Compression One of the simplest approaches towards efficiency is compression to reduce data size. For the longest time in the history of computing function, which is 1 if x is positive, 0 otherwise. The promise with such extreme quantization approaches is the theoretical 32x reduction in model size of larger networks like Inception without substantial However this approach needs to be evaluated on small networks like the MobileNet. While these approaches (and other schemes like Ternary Weight Networks6) can lead to efficient implementations of standard

(back-pressure, flow control) 2 ??? Vasiliki Kalavri | Boston University 2020 Load management approaches 3 ! Load shedder (a) Load shedding (b) Back-pressure (c) Elasticity Selectively drop records: operator selectivities and heuristics are unsuitable for frequent load fluctuations. • Naive approaches can lead to system instability or unnecessary load shedding. • In window-aware load shedding