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Salesforce DevOps for Architects

Salesforce DevOps for Architects

By : Cowell, Lars Malmqvist
4.8 (11)
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Salesforce DevOps for Architects

Salesforce DevOps for Architects

4.8 (11)
By: Cowell, Lars Malmqvist

Overview of this book

Rob Cowell is a Salesforce DevOps Advocate with extensive experience as a Salesforce Developer and Architect, guiding best practices for Salesforce DevOps. Lars Malmqvist, a 32x certified Salesforce CTA, has 15 years of experience building advanced Salesforce solutions and is the author of two books, Architecting AI Solutions on Salesforce and Salesforce Anti-Patterns. As the Salesforce Platform evolves, architects face increasing demand for advanced solutions. This book serves as your definitive guide to mastering effective DevOps practices crucial for successful Salesforce projects. Beginning with cultivating a DevOps mindset focused on collaboration and communication, it emphasizes governance, visibility, and accountability. You'll delve into tools and techniques, leveraging the robust capabilities of SFDX to craft your strategy efficiently. This book stands out for its practical approach to Salesforce packaging and CI/CD stack creation, guiding you to build a seamless automated change delivery system with freely available software. It addresses critical operational concerns such as ticket management, backups, change monitoring, and data seeding. In the final chapters, you'll discover third-party solutions to expedite your Salesforce DevOps journey, empowering you to deliver sophisticated and efficient projects.
Table of Contents (20 chapters)
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Seeding data in your environments

Seeding development and testing environments with large volumes of high-fidelity, realistic data is indispensable for emulating the behavior of live production systems on Salesforce’s inherently data-centric platform. Thoroughly seeding sandboxes with representative data enables comprehensive validation under real-world conditions. However, accomplishing this efficiently at scale requires thoughtful implementation of robust tools, automation, and data modeling best practices.

There are several approaches to providing your environments with data, and we’ll look at each of them in turn. We’ll start with the decision to either mirror your production data or generate dummy data, then look at options available for loading that data. By the end of this section, you should be in a strong position to get your environment data ready.

Working with production data

Seeding development environments with data is a crucial task to ensure...

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