Today’s guest is Pierig Le Saux, an expert in Service Reliability Engineering and Systems Administration, providing architectural guidance on complex issues and leading technical projects here at Pythian. Pierig joins us to talk to us about his experience in a massive cloud migration, which he managed recently for Blackberry Messenger and Emtek. This process included migrating a 10,000 server database across continents, in addition to all sorts of challenges which were only amplified by the scale of the project.
During our chat we go through some background to the work, how it was made possible and some of the lessons and methodologies that were learned and implemented by Pierig and his team. Most listeners will not be undertaking a migration of this magnitude, but the information and lessons are applicable to any data transfer, and its scale and difficulty only serve to amplify the lessons. And for those of you who might approach a task similar to this, well it helps to have heard from someone who has done it before!
Key points from this episode:
- A little about the huge migration that was made for Blackberry Messenger.
- The size of the infrastructure of the database that was moved.
- Dividing the task into smaller units to make it possible.
- The fail safes and updates that were necessary for this particular project.
- The human resources and time constraints of the whole migration.
- Tools and DevOps technology that assisted the team with these tasks.
- Challenges and hurdles that constrained the work.
- Google Cloud technologies and how they came into the project.
- Using Google BigQuery in this process and the size of the load it can handle.
- The realm of language and how a multi-language application poses its own problems.
- The methodology that arose in the process and finding the path of least resistance.
- Highlights of the process for Pierig.
- Pierig does the Lightning Round
- And much more!
Links Mentioned in Today’s Episode:
Pierig LeSaux on LinkedIn
Blackberry Messenger
Data Flow
Google Dataproc
Google BigQuery
Microsoft Azure
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