
Serverless Data Processing with Dataflow: Operations
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance.
Why choose Core Tech?
Course Insight
Designed for advanced/expert practitioners. Designed for experienced practitioners. We recommend having a solid grasp of Data Science fundamentals before starting this specialization.
SKILLS TO
MASTER
💡This course fits perfectly into our comprehensiveData Science Learning Path. Explore the ecosystem to see how it compares to other foundational skills.
Quick Facts
What You’ll Learn
- Introduction : 2mins.
- Monitoring : 17mins.
- Introduction : 2mins.
- Logging and Error Reporting : 7mins.
- Monitoring : 17mins.
- Troubleshooting and Debug : 12mins.
- Logging and Error Reporting : 7mins.
- Performance : 13mins.
- Troubleshooting and Debug : 8mins.
- Testing and CI/CD : 27mins.
- Performance : 13mins.
- Reliabiity : 19mins.
- Testing and CI/CD : 27mins.
- Flex Templates : 10mins.
- Reliabiity : 19mins.
- Summary : 4mins.
- Flex Templates : 10mins.
- Summary : 4mins.
Description
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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