An e-commerce company utilizes Azure Data Lake Storage (ADLS) Generation 1 for Data Analytics.
Your new assignment is to plan and design the migration of ADLS Generation 1 to ADLS Generation 2
You are deciding on the migration pattern to be used.
The following are key considerations in this decision.
->workload cannot afford any downtime -> least migration effort Which of the following is the most suitable pattern?
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: C
No downtime consideration will remove the Lift and Shift and incremental copy option from the list of suitable migration patterns.
Dual Pipelines are the best for scenarios where the workload and application are mission critical and cannot afford downtime, and when ingest can be done to both storage accounts.
Bidirectional sync is ideal for complex scenarios involving many pipelines and dependencies where a phased approach might make more sense.
But the migration effort will be high.
So, this will shortlist Dual Pipeline as the most suitable pattern.
Option A is correct: No downtime consideration will incremental copy from the list of suitable migration patterns.
Option B is incorrect: No downtime consideration will remove the Lift and Shift from the list of suitable migration patterns.
Option C is correct: Dual Pipeline can migrate sufficing both conditions.
Option D is incorrect: Bidirectional sync is ideal for complex scenarios involving many pipelines and dependencies where a phased approach might make more sense.
But the migration effort will be high.
To know more about migration approaches, please refer to the doc below:
When migrating Azure Data Lake Storage (ADLS) Generation 1 to Generation 2, several migration patterns can be used, each with its own advantages and disadvantages. However, the most suitable migration pattern would be the one that fulfills the key considerations of having zero downtime and requires the least migration effort.
The four migration patterns that can be used for ADLS Generation 1 to Generation 2 migration are:
A. Lift and Shift: This migration pattern involves copying the data from ADLS Generation 1 to ADLS Generation 2 using Azure Data Factory without making any changes to the data structure or format. It requires minimal effort and is suitable for situations where downtime is not acceptable. However, it may not take advantage of the new features and improvements offered by ADLS Generation 2.
B. Incremental copy: This migration pattern involves copying the data from ADLS Generation 1 to ADLS Generation 2 in small increments, typically using Azure Data Factory or Azure Databricks. It allows for continued access to the data during the migration process and provides more control over the migration process. However, it may require more effort than the lift and shift pattern.
C. Dual Pipeline: This migration pattern involves running both ADLS Generation 1 and Generation 2 in parallel and synchronizing them using Azure Data Factory or Azure Databricks. This approach allows for zero downtime and minimal disruption to the existing data workflows, but it can be more complex to set up and maintain.
D. Bidirectional Sync: This migration pattern involves keeping both ADLS Generation 1 and Generation 2 in sync using Azure Data Factory or Azure Databricks until all data has been migrated to ADLS Generation 2. This approach is suitable when there are ongoing changes to the data in ADLS Generation 1 that need to be reflected in ADLS Generation 2. However, it requires more effort and may result in increased complexity.
Based on the key considerations of zero downtime and minimal migration effort, the most suitable pattern would be Lift and Shift (option A). It requires the least effort and allows the company to continue accessing the data during the migration process without any disruption. However, if the company wants to take advantage of the new features and improvements offered by ADLS Generation 2, they may need to consider using other migration patterns in the future.