Tabla de Contenidos: “…-- Moving, Saving, and Opening iCloud Documents -- Putting Handoff to Work -- Expanding Your Horizons with Sidecar -- Configuring iCloud -- Managing Your iCloud Storage -- Chapter 10 Your Laptop Goes Multiuser -- Once Upon a Time (an Access Fairy Tale) -- Big-Shot Administrator Stuff -- Deciding who needs what access -- Adding users -- Modifying user accounts -- I banish thee, mischievous user! …”

Tabla de Contenidos: “…239 8.4 Bayesian Model Selection 274 8.5 SMC Samplers Estimators of Model Evidence 276 8.6 Multiple Risk Dependence Structure Model Selection: Copula Choice 277 9 Flexible Parametric Severity Models: Basics 289 9.1 Motivation for Flexible Parametric Severity Loss Models 289 9.2 Context of Flexible Heavy Tailed Loss Models in OpRisk and Insurance LDA Models 290 9.3 Empirical Analysis Justifying Heavy Tailed Loss Models in OpRisk 292 9.4 Flexible Distributions for Severity Models in OpRisk 294 9.5 Quantile Function Heavy Tailed Severity Models 294 9.6 Generalized Beta Family of Heavy Tailed Severity Models 321 9.7 Generalized Hyperbolic Families of Heavy Tailed Severity Models 328 9.8 Halphen Family of Flexible Severity Models: GIG and Hyperbolic 338 10 Modelling Dependence 353 10.1 Dependence Modelling Within and Between LDA Model Structures 353 10.2 General Notions of Dependence 358 10.3 Dependence Measures and Tail Dependence 364 10.4 Introduction to Parametric Dependence Modeling Through a Copula 380 10.5 Copula Model Families for OpRisk 387 10.6 Copula Parameter Estimation in Two Stages: Inference For the Margins 416 10.7 Multiple Risk LDA Compound Poisson Processes and Levy Copula 420 10.8 Multiple Risk LDA: Dependence Between Frequencies via Copula 425 10.9 Multiple Risk LDA: Dependence Between the k-th Event Times/Losses 425 10.10 Multiple Risk LDA: Dependence Between Aggregated Losses via Copula 430 10.11 Multiple Risk LDA: Structural Model with Common Factors 432 10.12 Multiple Risk LDA: Stochastic and Dependent Risk Profiles 434 10.13 Multiple Risk LDA: Dependence and Combining Different Data Sources 437 10.14 A Note on Negative Diversification and Dependence Modelling 445 11 Loss Aggregation 447 11.1 Introduction 447 11.2 Analytic Solution 448 11.3 Monte Carlo Method 454 11.4 Panjer Recursion 457 11.5 Panjer Extensions 462 11.6 Fast Fourier Transform 463 11.7 Closed-Form Approximation 466 11.8 Capital Charge Under Parameter Uncertainty 471 12 Scenario Analysis 477 12.1 Introduction 477 12.2 Examples of Expert Judgements 480 12.3 Pure Bayesian Approach (Estimating Prior) 482 12.4 Expert Distribution and Scenario Elicitation: learning from Bayesian methods 484 12.5 Building Models for Elicited Opinions: Heirarchical Dirichlet Models 487 12.6 Worst Case Scenario Framework 489 12.7 Stress Test Scenario Analysis 492 12.8 Bow-Tie Diagram 495 12.9 Bayesian Networks 497 12.10 Discussion 504 13 Combining Different Data Sources 507 13.1 Minimum variance principle 508 13.2 Bayesian Method to Combine Two Data Sources 510 13.3 Estimation of the Prior Using Data 528 13.4 Combining Expert Opinions with External and Internal Data 530 13.5 Combining Data Sources Using Credibility Theory 546 13.6 Nonparametric Bayesian approach via Dirichlet process 556 13.7 Combining using Dempster-Shafer structures and p-boxes 558 13.8 General Remarks 567 14 Multifactor Modelling and Regression for Loss Processes 571 14.1 Generalized Linear Model Regressions and the Exponential Family 571 14.2 Maximum Likelihood Estimation for Generalized Linear Models 573 14.3 Bayesian Generalized Linear Model Regressions and Regularization Priors 576 14.4 Bayesian Estimation and Model Selection via SMC Samplers 583 14.5 Illustrations of SMC Samplers Model Estimation and Selection for Bayesian GLM Regressions 585 14.6 Introduction to Quantile Regression Methods for OpRisk 590 14.7 Factor Modelling for Industry Data 597 14.8 Multifactor Modelling under EVT Approach 599 15 Insurance and Risk Transfer: Products and Modelling 601 15.1 Motivation for Insurance and Risk Transfer in OpRisk 602 15.2 Fundamentals on Insurance Product Structures for OpRisk 604 15.3 Single Peril Policy Products for OpRisk 609 15.4 Generic Insurance Product Structures for OpRisk 611 15.5 Closed Form LDA Models with Insurance Mitigations 621 16 Insurance and Risk Transfer: Pricing 663 16.1 Insurance Linked Securities and Catastrophe Bonds for OpRisk 664 16.2 Basics of Valuation of Insurance Linked Securities and Catastrophe Bonds for OpRisk 679 16.3 Applications of Pricing Insurance Linked Securities and Catastrophe Bonds 709 16.4 Sidecars, Multiple Peril Baskets and Umbrellas for OpRisk 726 16.5 Optimal Insurance Purchase Strategies for OpRisk Insurance via Multiple Optimal Stopping Times 733 A. …”

Tabla de Contenidos: “…-- Moving, Saving, and Opening iCloud Documents -- Putting Handoff to Work -- Expanding Your Horizons with Sidecar -- Configuring iCloud -- Managing Your iCloud Storage -- Chapter 10 Creating a Multiuser MacBook -- Once Upon a Time (an Access Fairy Tale) -- Big-Shot Administrator Stuff -- Deciding who needs what access -- Adding users -- Modifying user accounts -- I banish thee, mischievous user! …”

Tabla de Contenidos: “…Beyond the basics -- 7 Performance and scaling -- 7.1 Threading and processes to scale with workers -- 7.1.1 Seeing workers in action -- 7.1.2 Worker constraints -- 7.1.3 Controlling output plugin threads -- 7.1.4 Memory management optimization -- 7.2 Scaling and moving workloads -- 7.2.1 Fan-in/log aggregation and consolidation -- 7.2.2 Fan-out and workload distribution -- 7.2.3 High availability -- 7.2.4 Putting a high-availability comparison into action -- 7.3 Fluentd scaling in containers vs. native and virtual environments -- 7.3.1 Kubernetes worker node configuration -- 7.3.2 Per-cluster configuration -- 7.3.3 Container as virtualization -- 7.3.4 Sidecar pattern -- 7.3.5 Options comparison -- 7.4 Securing traffic between Fluentd nodes -- 7.4.1 TLS configuration -- 7.4.2 TLS not just for encryption -- 7.4.3 Certificate and private key storage -- 7.4.4 Security is more than certificates -- 7.5 Credentials management -- 7.5.1 Simple credentials use case -- 7.5.2 Putting certification into action -- Summary…”

“…You will: Set up a Kubernetes cluster in GCP Deploy simple Docker images using monolithic Pods Arrange highly available and highly scalable applications using Deployments Achieve zero-downtime deployments using the Service controller Externalize configuration using ConfigMaps and Secrets Set up batch processes and recurrent tasks using Jobs and CronJobs Install horizontal (sidecar pattern) services using DaemonSets Implement distributed, stateful backing stores using StatefulSets…”

“…You'll be able to identify their specific functionalities, from traffic management, security, and certificate authority through to sidecar injections and observability. By the end of this book, you will have developed the skills you need to effectively manage modern microservices-based applications. …”

“…Some of them are Service Registry and Discovery, Service Mesh, Apache Cassandra ETCD (coordinator managing Kubernetes clusters), Apache Kafka, Idempotent service design, retry logic, Sharding, and Consistent Hashing, Client-side Load Balancing, Distributed Tracing, Canary Deployment, Sidecar Pattern, Circuit Breaker, and many more. Finally, you will also see the principles of various distributed systems designs; for example, master-less versus with leaders, poll-based versus push-based, immediate versus eventual consistency. …”