November 2020 |

How to Design Your Database Delivery For Faster Release Cycles

Posted on November 30, 2020September 4, 2025 by Yaniv Yehuda

Use source control for your database

Just like with your application code, any database deployment needs to be linked with a source control system. Database schema needs to be in source control, so that any database changes can be tracked, regulated and procedures can be set.

However, CI/CD pipeline processes often don’t reach the database. As a result, database delivery is still managed manually, bringing with it all the problems of manual deployments: configuration drifts, errors, downtimes and unauthorized code deployments.

When planning your source control for the database, make sure you capture everything! Don’t forget to include:

- Tables or Collections
- Constraints
- Indexes
- Views
- Stored Procedures, Functions, and Triggers
- Database configurations
- Roles and permissions policies

Data that controls business logic such as lookup tables also need to be in source control.

In addition, developers need a frictionless way to easily create local databases, while shared databases should only be updated via a build server as a matter of policy.

Track and document database schema changes

Database schema changes should always be documented and tracked. For example, when migration scripts change the database with every version release, you should be able to review previous deployments and revert back to any previous version if necessary. Just like you do with your application code.

Let’s look at another case. In order to deploy a change that adds a NOT NULL constraint to a column with existing data, you’ll need to write a migration script that loads a default value to any NULL columns in the table. But what if you need to know the previous value in the column later on?

Just like with code, the history of any database changes must be stored in source control. Tracking should be incorporated into the automated deployment process.

Monitor and enforce roles/permissions and policies

There are other things that need to be monitored beyond the obvious schema and static data. The security configuration of any database needs special care and roles/permissions have to be managed closely.

At any given time you need to be able to trace any change to the database code, knowing how, when and how to deploy the code.

Prevent the database configuration drifts in advance

Nobody likes to deal with configuration drifts. Unfortunately, configuration drift is the leading reason for errors when introducing database changes rated so by 70% of the companies, according to our survey of over 250 database professionals.

Database configuration drifts increase failure rate of database or application deployments, and causes headaches for both the development, and the DBA teams. Unfortunately, with manual management of database deployments it is nearly impossible to prevent such problems.

Automating Database Schema Changes

Changes happen very fast in DevOps environments. Unfortunately, the database cannot keep up. As DBAs are mostly dealing with lots of manual workflows to manage database deployments, it becomes painfully obvious that in order to solve database delivery problems we must automate the process.

Often development teams write code that requires database schema changes in order to execute, without intending to do so or realizing how much headache they just created for the DBA team.

These changes matter a lot to the database structure, as it makes changes like adding new tables and table columns, while modifying data types. It is easy to make schema changes in a development environment. But when these changes are pushed to production – all hell breaks loose.

When it comes to migrating schema changes from the application code to the database, we are still relying on manual workflows to manage these processes.

This is also where database automation tools come into play. These tools ensure that code developers write is compliant with the database structures, simplifying the communication between the teams and ensuring that if schema changes are required, that they are applied as quickly and accurately as possible.

Top Database DevOps Best Practices

When it comes to DevOps best practices, they must be extended to the database in order to connect the dots throughout the entire release process. By including the database into your CI/CD you can significantly reduce risks, downtime and the need for manual workflows.

Automatically Tracking Changes in Database Code

Automated DB deployment tools, help DevOps teams push database code into source control systems. By keeping track of what, when and how of every change in your database you can ensure a smooth database delivery process.

Database Code Packaging

Developers need to build immutable packages for consistent, repeatable and predictable downstream deployments. To serve this purpose, code packagers enhance applications to create and release automation.

Automatic Database Code Validation and Feedback

Manual SQL code reviews are one of the most hated DBA tasks. The solution is to get it resolved by intelligent automation to get immediate feedback on SQL code (i.e – solutions with review engines).

Add Visibility into the Database

Database deployment automation solutions enable tracking of changes in database code, providing integration with ticketing systems like JIRA to provide database state feedback and stakeholder visibility.

Avoid Pipeline Bottlenecks by Including the Database

A smooth CI/CD pipeline that includes the database helps get into the automated testing cycle, the staging environment, and finally to production faster.

Build One, Deploy Many for Your Database

If the software requires a building step, then that step is executed only once, and the output repeats throughout the pipeline. It helps prevent the problems that arise when the same software gets packed many times.

Dry Run ‘Well Before Pushing To Production

Before pushing code to your database pipeline, especially to production, ensure that it works smoothly with a test database in order to detect errors before any damage is done.

Release Often

Frequent releases are only possible if tested in a production environment and are in a release-ready state using testing methods like A/B testing.

Security First

You have to stay compliant and secure. Make sure you are managing your permissions and policies with a centralized governance solution, which also documents all database activities for future audits.

Use On-Demand Testing Environments

This approach allows the QA teams to reduce the number of environment variables. Its prime advantage is that it adds agility to the CI/CD cycle.

Difference between State/Migration-Driven database Deployments

Posted on November 29, 2020September 4, 2025 by Yaniv Yehuda

“Build your code once, and deploy it many times.” This foundational principle for release automation is widely accepted in the DevOps community as the gold standard. It means that once the binaries are created, they should be applicable to any environment, regardless of its internal configurations.

Why do you need repeatability in your release process?

This rule has a very clear logic behind it: by deploying many times but compiling only once you eliminate the risk of introducing differences that stem from varying environments, third party libraries, different compilation contexts, and configurations.

The same automated release mechanism is deployed for each environment, ensuring that the deployment process itself is not a source of potential issues.

DevOps teams usually deploy frequently to lower environments (Integration, QA, etc.), less frequently to higher environments and—ideally—only once to Production.

But there is considerable risk when the PROD deployment is different from the other environments. After all, can you afford the PROD to be the only untested deployment?

The Database Challenge

The principles above are accepted as the gold standard. But they are only applied to the application code. Databases have been left out of DevOps processes.

Currently, it is well accepted when the release automation and CI/CD processes ground to a complete halt at the database. But the result of treating the database as something out of scope of the CI/CD pipelines are bottlenecks and slowed down release cycles, configuration drifts, errors and downtimes.

It seems that DevOps engineers are mostly resigned to the fact that the database deployments are still managed though manual workflows, take time, and often break the release pipeline. This resigned attitude is due, in part, to the inherent differences between the database and the application code.

Why is the database left in the cold while we automate our app releases to death?

Releasing application code is far simpler than releasing database changes; with application code, you can override your changes with newer or older releases, you can override configuration gaps, and you can reinstall your application from scratch.

Databases, however, are different. They have both configuration and data; and the data is persistent and accumulating. In most cases, when it comes to the database you can’t override QA with DEV data, and you shouldn’t override PROD data with anything else.

As a result, the way to introduce changes is to alter the state of the database from its older structure and code, to its desired new structure—in sync with your application code. This requires a transition code that alters the database’s structure—the SQL script. Again, the app code is just the app code. The database code is the result of running the delta scripts.

Configuration drifts are the leading cause of deployment errors

In theory, upgrading your database with SQL scripts just works. In practice, however, there’s usually something missing: a database configuration tends to drift.

Someone performs a maintenance task, a performance optimization is implemented, or a different team’s work overlaps with your own. As a result, that script that worked in one environment might not work in the next, or worse—it ends up creating damage and downtime.

Configuration drift can present itself as different schema configuration, different code, good code that was introduced by other teams, or plain production hotfixes, that might be blown away by the SQL script you are introducing. Therefore, working with just the change scripts is a risky business. All the stars must be aligned 100% of the time for it to work

I will argue that we can (and we should) be treating the database code exactly the same as we do with the application code when it comes to delivery automation. DevOps best practices, including the “build once, deploy many” rule can be extended to the database.

Clearing the Confusion: State-Driven and Migration-Driven Deployments

We cannot keep treating the database as a discrete area outside of DevOps best practices. The more automated your release pipelines become, the more problematic is the database bottleneck that keeps holding your releases back.

It is time to bring DevOps processes to the database. To create the transition or upgrade database code, we can employ the concepts of state-driven or migration-driven deployments. Let’s review each one of these methods, their pros and cons.

What is state-based database delivery?

State-driven database delivery is generally referred to as a compare and sync tool. The idea is simple: all we need to do is to use a compare tool to auto-generate the scripts required to upgrade any existing database to the next environment.

That tool will always push changes from lower environments upward, such as from DEV, to QA, to PRE-PROD and finally PROD.

A model-based delivery method is another variant for state-driven delivery. In this case, defining a model—with either UI diagrams (a designer) or XML representation (translator)—enables you to define the desired database structure, and then compare and sync to the target environment.

The pros of state-based delivery

The compare or model tools do the heavy lifting: offering a script to make the target database look like your source database or your model.

The cons of state-based delivery

The biggest problem is that the change process is not repeatable: the script generated to one environment might be different from the one generated for the next environment, as the environments might be different (drifted). This means that the process is not repeatable and does not follow a ‘build once’ model.

Another issue is that the tool will push changes forward (from source to target) unless manually reviewed and explicitly directed to do otherwise. This can present high risk in an automated process.

In this scenario, changes originating from the target environment will be overridden with older code or conflicting code from the source (e.g. dropping an index that was added to PROD to deal with performance).

This is a great example of a mistake that would be very easy to make and very costly to fix.

The script is generic and designed for a broad audience. You must review it, adjust it, and change or fine-tune it to fit your specific case with every iteration and environment (useless you fall under the generic case).

The bottom line: this approach creates a situation where you ‘build many’ for each environment and eliminate repeatability.

Migration-driven database delivery

In migration-driven database delivery approach migration steps are created to transition a database from one version to the next, mostly implemented as plain SQL scripts. Upgrade scripts can be executed on the database.

The pros of migration-based database delivery

Hallelujah – the perfect repeatability! With migration-based delivery the same code is executed in all environments. So we can finally implement a classic ‘build once’ approach in the database delivery, we discussed earlier. The script is honed to fit your coding style, specific needs, performance variations and your application requirements.

The cons of migration-based database delivery

Well, here comes the biggest problem – In most cases, you’ll have to build the migration code manually.

Another issue is increased risk. In the face of drifted database environments, the SQL script might produce results that vary from undesirable to catastrophic—these can include anything from overriding someone else’s changes (if the script is not properly synced with other development efforts), to overriding hotfixes targeted for production.

The bottom line: Build once, deploy many – but with manual work and increased risk at the deployment phase.

State-based vs migration-based: why not both?

As I showed above, both state-based and migration-based approaches have drawbacks when it comes to automating database delivery. So why not combine the two approaches to get the best of both worlds?

That is exactly what DBmaestro does. By combining the power of both approaches, DBmaestro brings “Build once, deploy many” principle to your database, while increasing the frequency and the quality of your releases:

Automate and get full visibility and insights into your database release pipelines—at enterprise scale.
Easily define and run continuous delivery pipelines with high security and compliance with organizational policies.
Seamless integration with all sources of database changes
Dry-run the code and predict the success of database deployments before PROD
Get alerts for configuration drift or non-policy actions.

DBmaestro Release Automation enables you to publish releases quickly, prevent accidental overrides of changes, and reduce application downtime caused by database-related errors, all while maintaining stability, scalability, and security.

Want to learn more about our approach to database delivery? Download the whitepaper below for a detailed overview

Database Release Automation for DevOps: 11 Best Practices

Posted on November 24, 2020February 25, 2026 by Yaniv Yehuda

Database DevOps: Top 11 Best Practices

Not extending your CI/CD pipelines to the databases can lead to a wide range of technical issues and delivery bottlenecks that eventually affect the quality and time-to-market. If you are ready to bridge the gap between your DevOps processes and the database, follow these 11 best practices for the best results.

Release Automation for Database Best Practices

Detect and Prevent Configuration Drifts in Advance
DevOps is all about frequent and iterative updates, but when it comes to databases, the process is still dependent on manual workflows, resulting in configuration drifts and errors.

Configuration drifts are a common cause for release-related issues when it comes to databases. These drifts can present themselves as new schema configurations due to out-of-process changes, conflicting changes from different teams, or production hotfixes altered by SQL scripts. These configuration drifts are a recipe for disaster.

Bringing the database into the CI/CD loop can help developers avoid those problems.

By verifying all code updates in the database before the release via a centralized dashboard where every change is tracked, documented, and monitored, you can detect and react to all database configuration and application code conflicts as they happen. Before the release.

Enforce Company Policies and Standards

When it comes to applying company policies and standards in the application code, developers have plenty of tools to enforce those standards. But with databases, developers often work in the dark, running into issues only after the release has been pushed to production. At the same time, DBAs rely on manual workflows to integrate latest changes into the database. As a result, the database becomes the bottleneck that significantly slows down your releases.

It is a no-brainer that database release and delivery must also be automated to comply with policies and standards. Just like with application code, this involves blacklisting of specific database activities, while determining desired code naming conventions and acceptable times for deployments to production.

Once you have automated compliance with company policies and standards in the database, you can quickly verify all release packages that are in your release pipeline and kick out all bad code before it creates downtime, bottlenecks, and other issues.

Anthem’s move to an agile development environment turned the database into a critical development bottleneck. DBmaestro helped automate database releases, while decreasing change and release times by 75%. It also eliminated code drifts and other technical issues. LEARN MORE

“We needed to be able to control changes made to the database and promote those changes in an easy and controlled way.” – Tim McKean, Data Architect

Version Control for Database: Best Practices

Besides being extremely time and resource consuming, traditional tracking and monitoring methods are proving to be ineffective in managing database version releases and changes. What we need today is a release automation process that involves the database, giving you the ability to move fast.

Enforce Database Change Policy, Inside the Database
Hoping that there will be no human errors in your DevOps pipeline when the database is involved is a gamble you will always lose, especially in today’s dynamic coding environment. The only way to get the job done is by creating and enforcing a robust database change policy for all teams involved.

Once your policies have been established, use an automated solution to validate all code changes that include your database.

Keep a Detailed History of all Changes Made
Keeping track of versions and changes and having a detailed history of all database changes that have been made by all stakeholders at any given time is invaluable.

Having an audit trail of all changes made to the database is another pain point that many DBAs have to waste countless hours of manual work to achieve.

Automatically documenting all actions that have been made is a key to proper compliance in the database. When the history of each and every code change is automatically documented and can be accessed with just a few clicks, your job becomes that much easier.

Minimize Errors and Time-Consuming Manual Fixes
To minimize errors, dry-run the code before release in order to detect errors before they happen.

Check for inconsistencies. You’ll want to make sure the release will be successful in real-life scenarios before you push your code to production. The key is to recognize potential drifts and errors and configuration drifts before they happen, not after.

Make sure to perform Integration tests. A developer might have developed a great change that ticks all the boxes, but it might create conflict with some other code in the system which you won’t know until release. That is why integration testing, and dry-running your integrations is critical.

ING Bank Slaski had been encountering database deployment errors on a nightly basis, until DBmaestro entered the picture .

“DBmaestro was a clear winner for our needs. The version control inside the database was what our team required for the smooth deployment of database packages and substantial decrease of nightly interventions.”

Mariusz Narewski, Head of Management and Reporting Apps Team

Security and Governance for Database: Best Practices

Define Who Can do What. And Where
Roles and permissions management for databases is a must. Least privilege policy mindset is key when it comes to end-to-end compliance, and leaving the database out of this practice is simply dangerous.

If you write an unsecure code that involves your database you need to get an alert for that. Maybe actions hackable in run time or you grant permissions that are too wide or too deep – leaving potential for exploitation.

Just like with code, a solution that can monitor insecure actions in the database and provide alerts in real-time is key.

In short, having a centralized roles and permissions management solution with customizable activity alerts and audit trail significantly simplifies the database compliance.

Customize Database Activity Policies
Different organizations will have different role management requirements, but from a security perspective, you want to limit the access to the database as much as possible without making the process difficult.

Your developers might not need to deploy to production. Define who can deploy database changes and go as granular as possible. Set permissions for specific changes to the database code and control access to the database.

Comply with Federal and International Regulations
This one is no brainer, but often easier said than done. General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), and Sarbanes-Oxley Act (SOX) are just a few regulations that have become mandatory in recent years. Achieving these by managing database releases manually has become almost impossible.

Regardless of the exact sector your company belongs to, you will need to ensure that regulations are being met at all times.

Keep a Complete Audit History
Lack of a complete audit history can become a huge roadblock when it comes to establishing compliance, or troubleshooting.

With multiple developers working on projects and thousands of changes to the code before every release, creating any sort of documentation ahead of your audit is a nightmare.

Manual audit management is not effective. Creating a clear audit trail is best automated. Not only are all database changes automatically documented (exportable for offline scrutiny), but all access patterns and identities are fully transparent.

Monitoring for Database: Best Practices

Monitoring is a must to track KPIs that you can act on – how many releases, what they achieve – so that you can improve your processes.

Measure your KPIs so that you can improve your metrics
Everything that you can measure you can improve. If you don’t know what is happening you can’t improve on it.

You don’t know what you don’t know. When you have a process that is running and you are not measuring it – you can’t see the bigger picture. You might miss repeatable errors, for example one team can run more errors, maybe you have delays at certain points.

There is no magic bullet to maximizing your release pipelines. But measuring is the first step towards improving your process. So as a first step, you need to determine the right performance KPIs for your specific environment. These metrics have to be established early on.

Tech Stack Integration with Database: Best Practices

We all use multiple tools in our CI/CD toolchains. From Jenkins to Jira and all the way to multiple databases – Oracle, MySQL, RDS, to mention just a few. The key is to ensure that all these tools work nicely with each other.

Always consider integration pains when choosing your tools
The database needs to be treated as an integral part of your DevOps release pipeline. Unfortunately, it is still often left out in the cold and worked upon in silos, creating a bottleneck that routinely slows down releases.

Make sure you are automating your database with a solution that is flexible and compatible with the tools you already use. Fragmentation leads to more work. More work leads to more coding. More code requires more maintenance (and updating). A vicious cycle you must avoid.

Improved ROI with Database Automation

Continuous Integration and Continuous Delivery (CI/CD) for databases is no longer optional. Just like application release automation before it, the database needs to be integrated into the overall DevOps process. Siloed approach might have worked 5 years ago. But it is no longer sustainable.

By bridging the gap between the database and your code you can achieve faster release cycles, which is at the core of DevOps, without sacrificing code quality and without increasing the stress on your testing/QA teams. Simply put, you will be able to do more with less, while also achieving elevated (and sustainable) compliance and security standards.

Then there is ROI. if you have a 30-member team, you can enjoy a productivity gain of 15% along with savings of around 2000 team member hours a year ( 130,000 USD). Check out our DevOps for Database ROI Framework infographic to learn more about the monetary benefits of automating your database.

Automating your database release and delivery is no longer a luxury. It is a best practice.

Zero Downtime Database Deployment

Posted on November 17, 2020September 4, 2025 by Yaniv Yehuda

Unfortunately, Zero Downtime is something that many organizations are failing to achieve. Things like database migration and database changes are causing a wide range of technical and logistical problems that create bottlenecks in the DevOps pipeline. This article will look at the various issues and address them.

The Problem

It’s tough to believe, but the fact is that many companies are still not able to properly protect themselves against the costs of database downtime, which can become devastating in today’s torrid Covid-19 atmosphere. Database and software interruptions can bring entire businesses to a complete stop.

Instead of taking the hands-on-approach and tackling the problem, many companies today are calculating the cost of these downtimes and learning to live with them. But unfortunately, the damage goes beyond that. Brand damage and lower customer satisfaction levels are just a couple of them.

As per a comprehensive ITIC survey, 52% of respondents identified human error as the leading issue affecting database downtime in their organization. This can happen due to coding errors, misspellings, or accidental overrides that needlessly bring down systems during scheduled maintenance or new releases.

This can become a serious problem if you are trying to create a smooth DevOps pipeline, which as you know requires constant release and testing capabilities.

Did You Know?
80% of outages are due to human error and half of them occur during change configuration and release integration.

Blue Green Deployment

Blue Green deployment is a release methodology that transfers user traffic from a previous version of an app or microservice to a nearly identical new release, with both of them running simultaneously in production. The old version is typically the blue environment while the new version is the Green one.

Only one of the environments is live at any given time while serving all of your traffic. When the new version of your software is ready, deployment and the final stage of testing takes place in the Green environment. Once you have deployed and fully tested the new code, you switch the router to Green instead of Blue.

This is a popular approach that is allowing organizations to be more dynamic and embrace DevOps properly for faster and smoother iterations. In other words, this technique can minimize database downtimes that are caused by app deployment. Rollbacks are also easier to make due with this methodology.

But like with every methodology, Blue Green cannot address the various governance, security, and compliance challenges caused by remote work.

Release Automation to the Rescue

Modern release automation solutions are allowing organizations to completely eliminate database downtime issues, when done with Blue Green deployment.

Enhanced Visibility – This functionality can allow you to package, verify, deploy, and promote the database delivery pipeline. It’s now possible to catch errors and fix them on-the-go. You can now spot configuration drifts, conflicts, and other errors in your database before they go live and cause you headaches.

Besides the obvious benefits you gain for performing your daily tasks, the enhanced visibility and transparency allows all stakeholders in your organization to scrutinize the pipeline at all times, improve cross-department communication, and eventually achieve optimal quality standards.

Version Control – Hotfixes and versioning misalignment happen more often than not. These often lead to configuration drifts, which are especially hard to contain. With Release Automation, you can identify configuration drift instances that will potentially hamper your next release (there are many everyday).

You can now define and enforce version control best practices and change policy for your database development. These solutions essentially validate database changes against schemas and relevant content, while preventing unauthorized changes. All changes are properly logged and documented.

Security and Compliance – Automated governance solutions help you implement the Least Privilege Policy, which essentially means that all users and third-party apps get the least possible privileges required to get the job done. This is a very effective technique for achieving 24/7 database compliance.

DBAs and other responsible stakeholders can now use these solutions to create dynamic privacy rules to meet GDPR, HIPPA and SOX requirements. Only people with the right passwords and privileges can access the database. These permissions can also be revoked or modified via a centralized dashboard.

Final Words

Besides the big hard revenue loss caused by database downtime, the damage to reputation can be even more significant in today’s hyper-connected social media world where every malfunction or error is reported in real time. You need to have a proactive approach to try and achieve zero database downtime.

Yes. Small updates may require your system to be offline for a matter of minutes or seconds, but you can handle that. When a planned downtime has been set, administrators can schedule at a time that would be least disruptive or postpone it so that it doesn’t occur during peak season or when usage is high.

When it comes to DevOps related issues, you can now use best practices and release automation systems to achieve zero downtime database deployment.

All You Need to Know About Legacy Database Migration

Posted on November 10, 2020February 25, 2026 by Yaniv Yehuda

The motivation to do so is obvious. Cloud based databases allow the creation of a centralized platform for all kinds of activities – testing, deployment, and production being the main ones. Also, the plug-and-play nature of these solutions allow companies to focus on what is really important – quality.

To put things bluntly, legacy database migration is going to happen, no matter how much you decide to drag it. This article will delve into the specifics of the migration process and show you how to tackle potential issues that may arise while making this significant and life-changing move.

Why Move to the Cloud?

In a nutshell, companies today want quick results. This can be enabled only by faster and more frequent deployments that allow incremental builds. This also allows more frequent testing, also known as continuous testing. Cloud-based delivery models offer speed and agility to businesses.

In other words, the emergence of this methodology is due to its ability to combat traditional challenges that are introduced by legacy databases.

Here are just a few:

Scalability – You will need to constantly tweak your app and/or network configurations while scaling up in the future. When up in the cloud, your infrastructure can scale up dynamically (on-demand). Unlike legacy systems, you will also be wasting less time on detecting and fixing errors.

Cost Efficiency and Better ROI – Legacy databases come at a cost. Besides the hardware purchase and maintenance expenditures, organizations spent a lot of time and resources training and onboarding their IT teams. Moving to the cloud essentially eliminates most of the aforementioned factors and issues.

Better Quality – The centralized nature of cloud computing provides DevOps automation with a dynamic out-of-the-box platform for testing, deployment, and production procedures. This basically solves the distributed complexity challenge, a problem on-premise ecosystems have always failed to address.

In a nutshell, cloud-based databases are easier to maintain, allow you to save resources, and enables you to deploy your software to testing and production environments with the push of a button. This allows you to get fast feedback on the quality of your software, while also eliminating bottlenecks and errors.

Cloud Release Automation – Optimized DevOps

Moving your legacy systems to the cloud is just the first step towards optimizing your DevOps pipeline. There are a wide range of advantages that come into play when you automate your cloud releases and development pipeline in general. Here are just a few changes you will see instantly.

Seamless Development – The Cloud Release Automation process includes infrastructure provisioning, making builds, running test cases, and generating reports with mailing alerts and so on. Automating processes by leveraging the cloud will make everything run smoothly, with minimal errors and code drifts.

With legacy databases, automation becomes extremely challenging due to the numerous scripts that are required to be written and modified constantly.

Easy Monitoring – You will also probably find all of your security, governance and administration tools in a centralized place for faster access and ease-of-use. Besides the common email alerts, you can implement customized alarms and monitoring alerts to optimize your resource utilization.

These monitoring capabilities eventually make your pipeline transparent to all stakeholders, enabling offline scrutiny for further optimization.

More Iterations – DevOps solves infrastructural problems with custom logic and writing capabilities. It helps automate entire processes with just a few clicks.

You can now easily trigger the build once the new code is pushed to the version control system, pull the latest code from the version control system, run automation test cases for code sanity, and build deployable artifacts if the test cases are passed. This is the power of automated cloud development.

Related: Top 7 Cloud Databases for 2020

Database Migration Essentials

Before even getting started with the database migration process, its highly advised to nominate a dedicated stakeholder to handle and oversee all aspects of the process. There are going to be many of them for a DBA to randomly handle smoothly with zero delays and hiccups.

The Migration Architect needs to make sure all logistic and technical provisions have been made, while also establishing requirements and priorities.

Define Dummy Data – It’s safe to assume that your app is going to introduce new functionality. It’s also safe to assume that every field is not going to have an equivalent in the legacy app. However, if your new application is expecting data, it can lead to exceptions that didn’t come up in testing.

Therefore, it’s important to agree on defaults and dummy data you can use as placeholders during the database migration. Also, it’s highly recommended to conjure a comprehensive (and well documented) plan to retire the aforementioned data types to avoid confusion after the migration is over.

Perform Regression Tests – The legacy database data can often be incomplete and lead to errors that didn’t come up during your regular testing that you have been performing for years. That’s why you should ideally migrate the data to a staging environment as early as possible to start rigorous testing.

A full regression functionality test should be performed on the legacy data to ensure that all Create/Read/Update/Delete functionally, validations, and API calls from third-party applications return the expected data. This will save you a lot of time and effort going ahead. Not doing so can cause serious problems.

Secure the Database – Security and governance are major concerns in all kinds of databases – legacy ones and also cloud based solutions. You will not be able to secure your data without seamless permissions and policy management in place. This is where the aforementioned database automation comes into play.

By automating your database management, you will be able to manage and edit permissions and policies with just a few clicks. Only relevant stakeholders will get access to specific tasks/roles, which can be edited or revoked upon the completion of their tasks. Doing so manually is literally impossible.

Final Thoughts

Regardless of what kind of solution you are choosing to migrate to, you must get the Best Service Level Agreement (SLA) possible. For example, most cloud vendors offer pre-determined maintenance downtimes. If you have an application that needs to be up at all times, make sure this is taken care of.

You should also make sure your new database is scalable, since the primary benefit of moving to the cloud is the ability to do so with minimal effort.This functionality should be available on-demand and is something that should be negotiated beforehand. Business plans should be communicated frequently.

Needless to say, you will need to train your staff. Database migration e to the cloud is a bigger move than it may seem initially. All relevant stakeholders should be aware about their upcoming tasks and responsibilities. They should also be given some intensive training and practice time in sandboxes.