OpenShift Container Platform 4.4 构建（build） 在 OpenShift Container Platform 中执行构建并与之交互 Last Updated: 2021-03-11 OpenShift Container Platform 4.4 构建（build） 在 OpenShift Container Platform 中执行构建并与之交互 . . . . . . . . . . . . . . . . . . . . . . . . . 目 目录 录 第 第 1 章 章 理解 理解镜 镜像 像构 构建 建 1.1. 构建（BUILD） 第 第 2 章 章 了解 了解构 构建配置 建配置 2.1. BUILDCONFIG 第 第 3 章 章 创 创建 建构 构建 建输 输入 入 3.1. 构建输入 3.2. DOCKERFILE 87 87 87 88 88 89 93 OpenShift Container Platform 4.4 构 构建（ 建（build） ） 2 目 目录 录 3 第 1 章 理解镜像构建 1.1. 构建（BUILD） 构建 (build)是将输入参数转换为结果对象的过程。此过程最常用于将输入参数或源代码转换为可运行的镜 像。BuildConfig 对象是整个构建过程的定义。

Using Istio to Build the Next 5G Platform David Lenrow Open Source Service Mesh Evangelist Neeraj Poddar Co-founder & Chief Architect, Aspen Mesh February 22, 2021 2 ©2021 Aspen Mesh. All rights reserved Observability, Debugging Uniform metrics and tracing for all CNF traffic Enforcement Primitives to Build Zero Trust Strong identity for users, workloads, devices, etc. Encrypting inter-CNF traffic via

a child’s play to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg to build and manage Data Lakehouse with pure SQL for both data processing lake in cloud storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, Delta Lake or/and Paimon. • Logical data warehouse sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg [https://iceberg.apache.org/] to build and manage Data Lakehouse with pure SQL for data lake in cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg [https://iceberg.apache.org/] to build and manage Data Lakehouse with pure SQL for data lake in cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg [https://iceberg.apache.org/] to build and manage Data Lakehouse with pure SQL for data lake in cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

a child’s play to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg to build and manage Data Lakehouse with pure SQL for both data processing lake in cloud storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

a child’s play to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg to build and manage Data Lakehouse with pure SQL for both data processing lake in cloud storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

a child’s play to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg to build and manage Data Lakehouse with pure SQL for both data processing lake in cloud storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high

a child’s play to combine some of the components above to build a modern data stack. For example, you can use Kyuubi, Spark and Iceberg to build and manage Data Lakehouse with pure SQL for both data processing lake in cloud storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide sheet can be used individually or all together. For example, you can use Kyuubi, Spark and Flink to build a streaming data warehouse. And then, you can use Zookeeper to enable the load balancing for high