The accuracy and availability of data has become critically important to the day-to-day operation of businesses. Similar to the practice of site reliability engineering as a means of ensuring consistent uptime of web services, there has been a new trend of building data reliability engineering practices in companies that rely heavily on their data. In this episode, Egor Gryaznov explains how this practice manifests from a technical and organizational perspective and how you can start adopting it in your own teams.
Interview
- Introduction
- How did you get involved in the area of data management?
- What does the term “Data Reliability Engineering” mean?
- What is encompassed under the umbrella of Data Reliability Engineering?
- How does it compare to the concepts from site reliability engineering?
- Is DRE just a repackaged version of DataOps?
- Why is Data Reliability Engineering particularly important now?
- Who is responsible for the practice of DRE in an organization?
- What are some areas of innovation that teams are focusing on to support a DRE practice?
- What are the tools that teams are using to improve the reliability of their data operations?
- What are the organizational systems that need to be in place to support a DRE practice?
- What are some potential roadblocks that teams might have to address when planning and implementing a DRE strategy?
- What are the most interesting, innovative, or unexpected approaches/solutions to DRE that you have seen?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Data Reliability Engineering?
- Is Data Reliability Engineering ever the wrong choice?
- What do you have planned for the future of Bigeye, especially in terms of Data Reliability Engineering?
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