The document describes the new DevOps Center feature in Salesforce for managing the lifecycle of tasks (work items) from definition to deployment. It outlines the process of launching a development environment from DevOps Center, editing metadata, creating a pull request for review, merging changes, and deploying to production. The goal is to integrate metadata changes to a git repository and deploy them from the command line interface.
This one sentence document thanks the reader for using Omni-Channel for Beginners. It provides a concise summary of the document in a single sentence as requested.
The document describes the new DevOps Center feature in Salesforce for managing the lifecycle of tasks (work items) from definition to deployment. It outlines the process of launching a development environment from DevOps Center, editing metadata, creating a pull request for review, merging changes, and deploying to production. The goal is to integrate metadata changes to a git repository and deploy them from the command line interface.
This one sentence document thanks the reader for using Omni-Channel for Beginners. It provides a concise summary of the document in a single sentence as requested.
This document discusses Salesforce and ETL integration with Salesforce. It begins with an overview of Salesforce as the leading CRM platform and its features. It then discusses ETL processes which extract, transform and load data from various sources into Salesforce. The benefits of integrating data into Salesforce are provided as better insights, increased efficiency, improved data quality and deeper analytics capabilities. A demo of ETL and Salesforce integration is included at the end.
Heroku is a platform as a service built on Amazon Web Services that allows developers to focus on building apps while Heroku manages the infrastructure. The Heroku platform provides dynos for running app processes, teams for managing access and collaboration, Postgres for database services, Connect for integrating with Salesforce, and an elements marketplace. Workflows can be structured using Heroku Flow which integrates Pipelines, Review Apps, CI/CD, and GitHub.
This document provides an overview of unlocked packages in Salesforce, including what they are, their benefits compared to other package types, and how to use them. It explains that unlocked packages allow adding, editing, and removing metadata in a trackable way and are well-suited for internal business apps. The document also demonstrates how to create an unlocked package, create versions, install packages, promote releases, and manage package dependencies.
This document provides an overview of asynchronous Apex processing in Salesforce, including future methods, queueable Apex, batch Apex, and scheduled Apex. It defines synchronous vs asynchronous processing, explains when to use each type of asynchronous Apex, and provides examples of how to implement them. Key limits for each type are also outlined, such as limits on queued jobs, executions, and callouts allowed.
This document discusses design patterns including singleton, facade, composite, and strategy patterns. It provides problems each pattern addresses, UML diagrams for some patterns, and code examples. The document aims to cover these patterns at a high-level to encourage participation and discussion on how to implement them in code.
Spring Batch is a framework for writing batch processing applications. It provides reusable functions for processing large volumes of records, including logging, transactions, restarts and resource management. A typical batch job reads data, processes it, and writes the results. It supports various processing strategies like normal processing, concurrent processing, parallel processing and partitioning. The core components are jobs made up of steps, which use readers, processors and writers to operate on chunks of data in a configurable flow.
This document discusses Salesforce and ETL integration with Salesforce. It begins with an overview of Salesforce as the leading CRM platform and its features. It then discusses ETL processes which extract, transform and load data from various sources into Salesforce. The benefits of integrating data into Salesforce are provided as better insights, increased efficiency, improved data quality and deeper analytics capabilities. A demo of ETL and Salesforce integration is included at the end.
Heroku is a platform as a service built on Amazon Web Services that allows developers to focus on building apps while Heroku manages the infrastructure. The Heroku platform provides dynos for running app processes, teams for managing access and collaboration, Postgres for database services, Connect for integrating with Salesforce, and an elements marketplace. Workflows can be structured using Heroku Flow which integrates Pipelines, Review Apps, CI/CD, and GitHub.
This document provides an overview of unlocked packages in Salesforce, including what they are, their benefits compared to other package types, and how to use them. It explains that unlocked packages allow adding, editing, and removing metadata in a trackable way and are well-suited for internal business apps. The document also demonstrates how to create an unlocked package, create versions, install packages, promote releases, and manage package dependencies.
This document provides an overview of asynchronous Apex processing in Salesforce, including future methods, queueable Apex, batch Apex, and scheduled Apex. It defines synchronous vs asynchronous processing, explains when to use each type of asynchronous Apex, and provides examples of how to implement them. Key limits for each type are also outlined, such as limits on queued jobs, executions, and callouts allowed.
This document discusses design patterns including singleton, facade, composite, and strategy patterns. It provides problems each pattern addresses, UML diagrams for some patterns, and code examples. The document aims to cover these patterns at a high-level to encourage participation and discussion on how to implement them in code.
Spring Batch is a framework for writing batch processing applications. It provides reusable functions for processing large volumes of records, including logging, transactions, restarts and resource management. A typical batch job reads data, processes it, and writes the results. It supports various processing strategies like normal processing, concurrent processing, parallel processing and partitioning. The core components are jobs made up of steps, which use readers, processors and writers to operate on chunks of data in a configurable flow.
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