Managing Cloud Native Data on Kubernetes Architecting Cloud Native Data Services Using Open Source Technology 1st Edition by Jeff Carpenter, Patrick McFadin ISBN 9781098111380 1098111389

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Product details:

ISBN 10: 1098111389
ISBN 13: 9781098111380
Author: Jeff Carpenter, Patrick McFadin

Managing Cloud Native Data on Kubernetes Architecting Cloud Native Data Services Using Open Source Technology 1st Edition Table of contents:

1. Introduction to Cloud Native Data Infrastructure: Persistence, Streaming, and Batch Analytics

Infrastructure Types

What Is Cloud Native Data?

More Infrastructure, More Problems

Kubernetes Leading the Way

Managing Compute on Kubernetes

Managing Network on Kubernetes

Managing Storage on Kubernetes

Cloud Native Data Components

Looking Forward

Getting Ready for the Revolution

Adopt an SRE Mindset

Embrace Distributed Computing

Principles of Cloud Native Data Infrastructure

Summary

2. Managing Data Storage on Kubernetes

Docker, Containers, and State

Managing State in Docker

Bind Mounts

Volumes

Tmpfs Mounts

Volume Drivers

Kubernetes Resources for Data Storage

Pods and Volumes

PersistentVolumes

PersistentVolumeClaims

StorageClasses

Kubernetes Storage Architecture

Flexvolume

Container Storage Interface

Container Attached Storage

Container Object Storage Interface

Summary

3. Databases on Kubernetes the Hard Way

The Hard Way

Prerequisites for Running Data Infrastructure on Kubernetes

Running MySQL on Kubernetes

ReplicaSets

Deployments

Services

Accessing MySQL

Running Apache Cassandra on Kubernetes

StatefulSets

Accessing Cassandra

Summary

4. Automating Database Deployment on Kubernetes with Helm

Deploying Applications with Helm Charts

Using Helm to Deploy MySQL

How Helm Works

Labels

ServiceAccounts

Secrets

ConfigMaps

Updating Helm Charts

Uninstalling Helm Charts

Using Helm to Deploy Apache Cassandra

Affinity and Anti-Affinity

Helm, CI/CD, and Operations

Summary

5. Automating Database Management on Kubernetes with Operators

Extending the Kubernetes Control Plane

Extending Kubernetes Clients

Extending Kubernetes Control Plane Components

Extending Kubernetes Worker Node Components

The Operator Pattern

Controllers

Custom Resources

Operators

Managing MySQL in Kubernetes Using the Vitess Operator

Vitess Overview

PlanetScale Vitess Operator

A Growing Ecosystem of Operators

Choosing Operators

Building Operators

Summary

6. Integrating Data Infrastructure in a Kubernetes Stack

K8ssandra: Production-Ready Cassandra on Kubernetes

K8ssandra Architecture

Installing the K8ssandra Operator

Creating a K8ssandraCluster

Managing Cassandra in Kubernetes with Cass Operator

Enabling Developer Productivity with Stargate APIs

Unified Monitoring Infrastructure with Prometheus and Grafana

Performing Repairs with Cassandra Reaper

Backing Up and Restoring Data with Cassandra Medusa

Creating a Backup

Restoring from Backup

Deploying Multicluster Applications in Kubernetes

Summary

7. The Kubernetes Native Database

Why a Kubernetes Native Approach Is Needed

Hybrid Data Access at Scale with TiDB

TiDB Architecture

Deploying TiDB in Kubernetes

Serverless Cassandra with DataStax Astra DB

What to Look for in a Kubernetes Native Database

Basic Requirements

The Future of Kubernetes Native

Summary

8. Streaming Data on Kubernetes

Introduction to Streaming

Types of Delivery

Delivery Guarantees

Feature Scope

The Role of Streaming in Kubernetes

Streaming on Kubernetes with Apache Pulsar

Preparing Your Environment

Securing Communications by Default with cert-manager

Using Helm to Deploy Apache Pulsar

Stream Analytics with Apache Flink

Deploying Apache Flink on Kubernetes

Summary

9. Data Analytics on Kubernetes

Introduction to Analytics

Deploying Analytic Workloads in Kubernetes

Introduction to Apache Spark

Deploying Apache Spark in Kubernetes

Build Your Custom Container

Submit and Run Your Application

Kubernetes Operator for Apache Spark

Alternative Schedulers for Kubernetes

Apache YuniKorn

Volcano

Analytic Engines for Kubernetes

Dask

Ray

Summary

10. Machine Learning and Other Emerging Use Cases

The Cloud Native AI/ML Stack

AI/ML Definitions

Defining an AI/ML Stack

Real-Time Model Serving with KServe

Full Lifecycle Feature Management with Feast

Vector Similarity Search with Milvus

Efficient Data Movement with Apache Arrow

Versioned Object Storage with lakeFS

Summary

11. Migrating Data Workloads to Kubernetes

The Vision: Application-Aware Platforms

Charting Your Path to Success

People

Technology

Process

The Future of Cloud Native Data

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Tags: Jeff Carpenter, Patrick McFadin, Cloud Native Data, Kubernetes Architecting, Source Technology