Database migrations and upgrades are essential tasks for maintaining and improving your data systems. However, they can also be challenging, risky, and time-consuming. How do you handle them effectively and safely? In this article, we will cover some best practices and tips for planning, executing, and testing your database migrations and upgrades.
Before you start any database migration or upgrade, you should have a clear idea of what you want to achieve and how you will measure it. For example, are you migrating to a new platform, technology, or version? Are you upgrading to fix bugs, enhance performance, or add features? How will you compare the before and after scenarios? Having a well-defined goal and scope will help you plan your resources, timeline, and strategy.
The database is a crucial component that supports large-scale applications. When planning for database migration, it's important to have a clear understanding of several key points. First, it's essential to identify the limitations and pain points of the current database system. Second, it's important to determine the application's requirements, taking into account the expected growth in traffic and volume over the next ten years. Third, it's necessary to conduct a thorough study of different database choices, such as traditional SQL or no-SQL document DB, and analyze their pros and cons to determine the best fit for the application. Finally, it's important to design the migration plan, and ensure no data loss.
Preparation is key in database migrations. As part of the prep, it's vital to have a comprehensive set of metrics ready for the pre and post-migration comparison. Ensure your scripts, SQL commands, dashboards, etc. are operational ahead of time to avoid scrambling post-migration. Post-migration scramble is the worst. Also pay close attention to data backup and recovery plans. No matter thoroughly you've planned, unforeseen hiccups can occur during the migration process. Having a strong backup and a recovery strategy will ensure your data is safe and sound. And finally, LOAD TEST! Test, test, test your new stack to ensure it can handle the traffic. And then test some more.
When it comes to migrate, you need to list out the the pros and cons of different choice of database choices and to-do lists for changing any downstream codebase comprehensively at your planning stage. Choice of new database will have an impact on the workload for downstream application codes managed by different teams. If your choice of new database will cause more work for some team, you have to make sure your choice will have a significant benefits in some scenarios or offering some additional features to try to balance it to reduce the friction. Be well-prepared with a comprehensive plan down to nitty-gritty details, a clear goal with purpose and think in other people's shoes will definitely go a long way.
I believe that firstly understanding whether it is possible to have downtime, to think about the migration strategy. I usually take into account the size of the base, the workload that will run at the time, as this will directly affect the migration. Whether the migration is an upgrade to a newer version or cloud migration, the strategies can be simpler than switching from one technology to another. When a database technology change is made, it is always necessary to see limitations, resources, data types, among other things that can influence it. Even, if necessary, the creation of other technologies to migrate the data, using lambda functions, kafka, among other things.
Other factors to consider are how you want to control your environment. In relational databases referential integrity holds most of the logic of allowed values in a system. In a hierarchical database, base logic in objects or methods determines the valid values that can be placed. Greater care will need to be taken to keep data clean. This applies whether you are in a legacy systems or newer cloud based systems.
Depending on your goal and scope, you may need different tools and methods to perform your database migration or upgrade. For example, you may use a native tool provided by your database vendor, a third-party tool that supports multiple platforms, or a custom script that you write yourself. You may also choose between different methods, such as dump and load, online replication, or incremental changes. Each tool and method has its own advantages and disadvantages, so you should evaluate them carefully and test them in a non-production environment.
When determining the size of the database, make sure that you consider WHY your database may be so large - is it simply a matter of your organization being large? Or is it because it is full of old data that could have/should have been purged or archived a long time ago? Purging or archiving outdated information from a database can make an otherwise time-consuming migration easier. (Keep in mind, if the migration involves moving to a different database brand, you will also have to consider how you will access archived data after the migration)
It's equally as important to understand whether the tool selection is driven by careful analysis of the use cases and desired outcomes, or whether it's driven by an organization-wide strategy to align with current technology trends. Oftentimes, the appropriate tool for the job is the one which will perform the task most efficiently, but will also allow the organization to maintain and handover the maintenance of the code to the internal support team.
Investing in solid migration tools, even if it incurs a cost, is necessary as they simplify the process and reduce risks. Rigorous testing of the migrated data is essential - checking data types, indices, triggers, etc. Once, we encountered a corrupted index in PostgreSQL allowing duplicate unique keys - a massive issue that could have been exploited by a bad actor. Thankfully we caught it before the actual migration took place. Think about your chosen migration method on downtime. It's crucial to inform stakeholders of possible service disruptions in advance, planning for it during off-peak times if possible. Contingency plans are not negotiable, you need them for when the unexpected happens. Document the process, you'll thank yourself.
The important first step is to determine the size of the database to be migrated. In cases where the database size is comparetively small, the migration can be made easier by simply connecting the target database platform to the source (yes, database platforms these days have evolved to let you pull data from almost any kind of database source). This will prevent a lot of unnecessary hassle to go through the entensive steps of database migration. Dump and load is also a popular method used for smaller databases. However, if the database size is large, a tool might be required. However, before jumping into a third-party tool, but that is only if a default bulk migration feature is unavailable, which is rare these days.
I find it very helpful to have a very clearly defined timeline. You can't just say we are going to do the migration on this date and here all of the things we need to get done before then. There needs to be iterations to check progress along the way.
One of the most important steps in any database migration or upgrade is to prepare a backup and rollback plan. A backup plan ensures that you have a copy of your data and schema before you make any changes, so you can restore them in case of any errors or failures. A rollback plan outlines the steps and commands you need to execute to undo the changes and revert to the previous state. You should test your backup and rollback plan before you proceed with the migration or upgrade.
Having a backup plan not only with migrations but also for other non-obvious (sometimes unintentional) accidents of data can save everyone a great amount of pain and headaches. In these instances, documentation can help but will not cover the use case that caused the problem to begin with. If all else fails, make sure you have replicas and an image of the database before you begin your migration.
Comprehensive documentation, encompassing all details from connection protocols to tool versions, is essential. Documenting both successful and unsuccessful attempts provides insights that can prevent future errors. Also, maintaining a change log and versioning your migration scripts can be invaluable when troubleshooting. It helps keep track of what changes have been made and enables easy rollback to a previous state if needed. I'll say it again, just in case - document *everything*.
Successful deployment criteria should be defined ahead of any go-live activities. In the case of an unsuccessful deployment, a full rollback may not be required if the issue can be resolved with a hotfix. Rollback activities should be incorporated into the project plan with different scenarios outlined, their respective owners, and their impact on business operations.
The essence of rollback lies in saving the database structure and data at one point in time as the golden state. If the migration fails, you should know what point in time (in terms of state of the database) you have to reach back to. Thus, before beginning with the migration steps, make sure to have a saved version with timestamp of the database that can be restored at any point in future to regain the original state and begin afresh.
Always aim for automation, if and when you need to rollback, human mistake is the last thing you want to deal with. Having an automated rollback process helps your services and your services' consumers to face less impact.
A database migration or upgrade can affect many people and processes, such as developers, users, administrators, and applications. Therefore, you should communicate and coordinate with all the relevant stakeholders before, during, and after the migration or upgrade. You should inform them about the purpose, scope, timeline, risks, and impacts of the migration or upgrade. You should also get their feedback, approval, and support. You should also establish a clear communication channel and escalation process in case of any issues or emergencies.
I believe there should always be a "test" environment that everything should be done in prior to utilizing the prod environment. Have your rollback carefully planned and documented and then use the second environment to migrate into. If using a second environment make sure it is the same version as your live (prod) with the same data.
The above bit about 'stakeholders' is honestly shoehorned into this article to its detriment. Rather you should look at the present scenario and consider the if parties involved need to be informed to serve project viability for shareholders, who either are you or pay you. You don't need to blast out a mailer to every person in the app's ecosystem. Importantly, you did not do this on a live production database so there is not going to be a service interruption. Get your test database up fully. When staging tests pass, then you can swap which database the production environment points to. Using database clusters, shards or similar horizontal scaling it is very possible to migrate with zero downtime and no disruption to users.
Try to do this during the day without downtime. With distributed teams this means doing this when you expect key stakeholders to be working and available. If your plan requires downtime you'll end up with doing this on a saturday night and if things start going wrong you'll have a tough time getting hold of people. Stress leads to people quitting and also more chances of mistakes.
It's often advisable to create a working test environment as early on in the project as possible, and allow the business group to use this environment in order to identify any issues which could potentially jeopardize the desired outcomes from the migration.
This one is extremely simple. Err on the side of over-communication. Timely updates and transparency foster trust and cooperation.
Once you have everything ready, you can execute your migration or upgrade according to your plan. You should follow the best practices and guidelines of your chosen tool and method. You should also monitor the progress and performance of your migration or upgrade using logs, metrics, alerts, and reports. You should also check for any errors, warnings, or anomalies that may indicate a problem. If you encounter any issues, you should troubleshoot them quickly and decide whether to continue, pause, or abort the migration or upgrade.
Different post-migration support levels are usually required to ensure system stability. With many migration projects, system performance tends to deteriorate over time as a result of design deficiencies, so examining system performance over time is imperative.
Ensure monitoring dashboards are all built and readily accessible to key stakeholders. Have a team ready to interpret this real-time data, promptly addressing any anomalies that surface during the migration. It's also important to have *predetermined* thresholds that will trigger whether to continue, pause, or abort the operation. Keeping these criteria crystal clear can help make fast, informed decisions in case of issues.
Make sure to include operational and performance metrics of the upstream and downstream services in the execution process. It is highly recommended to have clear instructions on steps you need to take in case any of these metrics get impacted by the migration.
I agree; two basic factors are critical in any database migration: a good backup of your existing database, and a test environment that mimics your final target environment in all measurable factors. Testing after laying down your database onto the test environment is key in order to find any potential pitfalls. Also after migrating the test environment can be converted to a UAT environment for use with future data loads and testing. But having a good, recent, sound backup of even a database you are not thrilled with can save you if things go sideways during a migration.
After you finish your migration or upgrade, you should test and validate the results. You should verify that your data and schema are consistent, accurate, and complete. You should also check that your applications and users can access and use the data as expected. You should also compare the before and after scenarios using the criteria you defined in your goal and scope. You should also document the outcome and lessons learned from your migration or upgrade.
Performance testing is needed to ensure that the migrated/upgraded system meets all expected performance standards. By conducting performance tests that evaluate the system's response time, throughput, and resource utilization under various scenarios and workload conditions you can proactively identify any performance bottlenecks/issues that may have arisen during the process.
Considering your source and destination database collations and how they handle Datetime values is also important including the locations where users will be accessing the database from
In addition to testing and monitoring applications, consider background jobs that may become active later, as you may not be able to observe it at the time of vaidating your upgrade.
We are currently migrating from one system into another system and have decided that the first migration pass will be just enough easy data to get stakeholders working in the new system, test environment. We have found decision points to bring before the stakeholders prior to bringing them into the next migration. I never expect less than 4 migrations into a new system to see the best results.
Rich metadata schematic layer that describes the structure, relationships, and attributes of all data being migrated. This provides a deeper understanding of the data and its context, ensuring consistency and accuracy throughout the migration/upgrade process. It enables data governance, lineage tracking, and improves the overall quality of the underlying data. A continuous feedback loop is essential to gather feedback from users/stakeholders post migration/upgrade. This feedback helps identifying any issues/gaps in the data, schema, or applications. It facilitates iterative improvements and features/enhancements based on real-world usage and user experiences ensuring the process can remain dynamic and respond to evolving business needs.
In my experience- 1. Understand the purpose of migration, make sure all the stakeholders are aligned on the purpose. Get a formal approval. 2. Ensure all the upstream and downstream system are compatible with migration and upgrades. 3. Brainstorm common challenges in migration- data garbling, inconsistency or missing data, Dates and Null values in data, space required in database, additional/who columns. 4.Chose the right database - SQL, NoSQL on Cloud or Local. It depends on several factors. 5.BACKUP - There are several ways to take backup. Make sure you understand the recovery process before you take the backup. You don't want to miss any transaction. there are multiple ways to take backup. Continued...
Database systems may remain central to many usages and not only for products but also for organization-wide data usage. For example, database administrators may generate reports for sales and marketing. There may be integrations with other systems such as ERP (Enterprise Resource Planning) which may need an upgrade as well to take advantage of the newly migrated database systems and their features as well as to remain compatible. A thorough evaluation of dependencies is a must before any migration.
continued.. 6. Start migration in batches, test it thoroughly before you jump to second batch. Test from all the perspective because a single mistake will require a lot of rework.(important) 7. Migrate the second batch and test the data to make sure if everything looks okay. 8. Keep the migrated database and original database up and running and disconnect original database after running the migrated database in live system for 2 months or so. Hope this will help.
It can be quite easy in the technical field to think "We are migrating these servers to XYZ". However those servers often host multiple databases, support multiple applications and users groups, not to mention admin staff for them. It often helps to take an application-centric view of migration projects and treat [app+database+users+admins] as a unit. This also allows you to plan the migration around varying compatibility issues, security and accessibility questions, etc. It may be that you end up having to split up those servers to meet those different requirements either over time scales, or even the destination that they end up at, especially if you are porting to a cloud based infrastructure.