In this cloud migration monitoring demo, we will show how, by collecting change data from source and target and matching transactions applied to each in real time, you can ensure your cloud database is completely synchronized with on-premise, and detect any data divergence when migrating from an on-premise database.
This was originally published as a blog post here.
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Migrating applications to AWS requires more than just being able to run in VMs or cloud containers. Applications rely on data and that data needs to be migrated as well. In most cases, the original applications are essential to the business and cannot be stopped during this process since it takes time to migrate the data and time to verify the application after migration. It is essential the data changes are collected and delivered during and after that initial load. As the data is so crucial to the business and change data will be continually applied for a long time, mechanisms are verified that the data is delivered correctly are an important aspect of any cloud migration. This migration monitoring demo will show how by collecting changed data from source and targets and matching transactions applied to each in real time, you can assure your cloud database is completely synchronized with on premise and it takes any day to divergence where migrating front on-premise database.
The key challenges with monitoring cloud database migrations include enabling data migration without a production outage; with monitoring during and after migration; detecting out of sync data should any divergence occur with this detection happening immediately at the time of divergence; preventing further data corruption; running the monitoring solution, non intrusively with low overhead; and obtaining sufficient information to enable fast resynchronization. In our scenario, we’re monitoring the migration of an on premise application to AWS. A Striim dashboard shows real time status complete with alerts and is powered by continuously running data pipeline. The on premise application uses an Oracle database and cannot be stopped. The database transactions are continually replicated to an Amazon Aurora MySQL database. The underlying migration solution could either be streams, migration solution or other solutions such as AWS DMS. The objective is to monitor ongoing migration of transactions and alerts when any transactions go out of sync, indicating any potential data discrepancy.
This is achieved in the Striim platform through this continuous query processing layer. Transactions are continuously collected from the source and target databases in real time and matched within a time window. If matching transactions do not occur within a period of time, they’re considered long running. If no match occurs in an additional time period, the transaction is considered missing. Alerts are generated in both cases. The number of alerts from missing transactions and long running transactions are displayed in the dashboard. Transaction rates and operation activity are also available in the dashboard and can be displayed for all tables or just for critical tables and users. You can immediately see live updates and alerts where the transactions do that get propagated to the target within a user configured window. With lung running transactions that eventually make it to target, also tracked. The dashboard is used of customizable, making it easy to add additional visualizations for specific monitoring as necessary. You’ve seen how Striim can be used for continuous monitoring of your on premise to cloud migrations. Talk to us today about this solution and get started immediately using a download from our website or test out Striim in the AWS marketplace.