Description:
Data integrity is vital as it ensures end-user data accuracy and consistency in conjunction with an adequate level of service and availability. In this course, you'll learn how to choose a strategy for data integrity, including how to account for any potential upsides and tradeoffs.
You'll explore various types of failures that lead to data loss and the existence of the many data failure modes. You'll also identify data integrity challenges.
Next, you'll examine in detail the soft deletion, back up and recovery, and early detection layers of defense-in-depth, before investigating the data integrity challenges a cloud developer may encounter in high-velocity environments.
Finally, you'll outline considerations for implementing out-of-band data validation and successful data recovery and identify how the primary SRE principles apply to data integrity.
Target Audience:
Duration: 01:08
Description:
Site reliability engineers (SREs) encounter numerous and varied pipeline technologies and frameworks in their work. When building a pipeline, SREs need to invest considerable time during the design phase to ensure the results work best for the specific case.
In this course, you'll explore the numerous features of a pipeline, such as latency, high availability, development, and operations. You'll also examine the two different pipeline mutations: idempotent and two-phase, as well as the checkpointing technique and various code patterns.
You'll then investigate the five core characteristics of the pipeline maturity matrix and outline how they should be used to design the pipeline technology. You'll then identify potential failure modes, outage causes, and different prevention and response techniques. Finally, you'll outline event delivery system design and operations and how to plan for customer integration and support.
Target Audience:
Duration: 01:04
Description:
Site reliability engineers often find data processing complex as demands for faster, more reliable, and extra cost-effective results continue to evolve. In this course, you'll explore techniques and best practices for managing a data pipeline. You'll start by examining the various pipeline application models and their recommended uses. You'll then learn how to define and measure service level objectives, plan for dependency failures, and create and maintain pipeline documentation. Next, you'll outline the phases of a pipeline development lifecycle's typical release flow before investigating more challenging topics such as managing data processing pipelines, using big data with simple data pipelines, and using periodic pipeline patterns. Lastly, you'll delve into the components of Google Workflow and recognize how to work with this system.
Target Audience:
Duration: 01:12