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Whatever applications or services you might use, you will create data.
Data migrationplanning for data is a big deal.
The potential impact from this kind of project can be massive.
So how can you avoid problems and make migrations run as smoothly as possible?
Valkey Tech Lead, Percona.
Databases all scale differently - for instance, most relationaldatabasesare built around using a single primary server instance.
This could include tracking metrics like tool throughput, latency and patterns in transaction volume over time.
Understanding the full inventory
Understanding the full inventory of components involved in the data migration is crucial.
This includes outlining the potential implications of the migration for each stakeholder.
The impact of the migration will vary significantly depending on the nature of the project.
On the other hand, a complete change of database technology could have far-reaching implications.
This is notoriously difficult and expensive to achieve and having that 100% confidence requires a lot of effort.
There are several techniques that it’s possible for you to employ to improve your chances of success.
The first of these is a canary deployment.
This involves looking at your systems and selecting one that you will migrate over first.
So, looking at why that performance is lower and where this can be fixed is in order.
One additional consideration once you are in the middle of your migration is tracking that performance side.
Comparing reports or dashboards manually is time-consuming and hard work.
To get around this, you’re able to set automated alerts or rules for potential rollbacks.
This approach involves creating specific triggers where your deployment would lead to an automatic rollback to the previous deployment.
As you plan any migration, you will have to take that mix of dependencies into consideration.
We’ve compiled a list of the best data recovery software.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
