With a smooth-running Agile team, a development task that involves the database may turn a programming pair into a programming trio. These ideas are not new, but they are particularly important in a fast development environment. Agile works very well if you do the right things. And this is what I want to explain here - the nature of the challenge of Agile Database Design. This e-book is designed to help application developers, database developers and database administrators (DBAs) understand that automation is the key to synchronizing the development cycles of application software teams and database teams. Without careful management, this is what leads to the buildup of the technical debt, i.e. In that situation, the table schema is tightly coupled to the applications themselves, and cannot be changed without coordinating the change among application teams. The key is to know when something is working, and to improve on it. Face-to-face communication is high bandwidth. A quick check to see if a change is metadata-only Turn on STATISTICS IO before running the ALTER. When doing performance testing, define fast enough and scales enough before you test. Generally, making a column bigger is a metadata-only, quick change. Since its inception in 2001, agile has caught on among application developers. In 2009, Forrester found that 35 percent of the 1,298 IT professionals surveyed were using agile development methods. I use the SIIP approach to database design: Simplicity, Integrity, Interfaces, and Patterns. The agile process regularly complicates the pivotal component of Data Modeling in the various applications and databases it engenders in many key ways, including: Exclusion: Oftentimes, data modelers are not brought into the agile process until the various developers, scrum masters and business analysts are at the stage in which they actually need some data. Commonly, teams perform these operations in the middle of the night. If you need to add values into the new column, for existing rows, do so in batches and then set the column to be NOT NULL, if that’s required. Patterns are effective when they are widely used. After a certain point, adding more people will actually slow development down and lengthen the development cycle. Tracking revisions to stored functions and procedures over time makes it easier to assess them, compare them side by side and diagnose any problems that arise on the path toward production. For the purposes of this article Iâll be referring to Scrum but the theories apply to Agile as a whole.Agile software development is a set of methods and practices based on the Agile Manifesto, which focuses on responding to change, short iterations of work, and team self-organization.Scrum is one of the Agile methodologies that involves a team typically working in two to fo⦠The third tenet of deployments: keep them specific. The latter places an emphasis on up-front design, documentation, and completeness, to create a safety net that can produce mission-critical, complex software in a small number of releases. Unfortunately, these are not the typical results for “early stage” Agile adopters. They store the data and enable data integrity. With online index creation, the indexes and underlying tables remain accessible but you can still expect to see an impact on performance during the operation, and users may experience blocking or deadlocking. That represents a significant change from Forrester's 2009 findings, in which a slight majority of companies indicated they had one or two agile projects under way. They are harder to upgrade or roll back than the front end of a website and so are more amenable to up-front design than continual refinement. It is relatively easy to upgrade a website because the ASP.NET or PHP pages don’t have data in them, so we simply overwrite the entire site. And their extensive use of automation for things like building and testing causes their level of risk to decrease, as shown in Figure 1. It is impossible to change an index definition using ALTER INDEX. A simple PowerShell script can run a set of scripts against a test database and capture the runtime of each query. However, by following practices such as these you can minimize downtime and disruption. Dogs and cats, living together! At first glance, thorough database testing in Agile projects seems like pushing a mighty bull into a tiny china shop. The second tenet of database deployments: make them fast. Without documentation, the code, including the tests, is the documentation. Shorter time to value, lower risk and greater flexibility are among the most frequently cited benefits of the database DevOps approach. Their average development cycle is three weeks. It requires good judgement and leaves little room for error. This improves code quality almost immediately. Deployment verification queries are a great help here. Start with data types, primary keys, foreign keys, and check constraints. Agile requires a fundamental shift in the way teams work. One of the principles that agile organizations follow is to deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. The Manifesto was developed by a group fourteen leading figures in the software industry, and reflects their experience of what approaches do and do not work for software development. Even if developers and QA teams are comprehensive and remember everything they need to test, manual testing is still vastly slower than automated tests that run against the code change at the point of check-in. Start with the automation tools you already know, and get more creative. For developers, constant communication provides feedback about how well our code is doing, both good and bad, and allows us to fix production inefficiencies and bugs. The key point with integration tests is to have a good set of cross-application tests running, to make sure that you’re simulating system behavior. If someone checks in code that fails one of these tests, they get an email automatically, warning them of their peril. That is also an example of forward compatibility. For an OLTP database, that means as much normalization as you can handle. In my experience, development teams don’t run database performance tests as often as they should, mainly because running them can require a near-copy of production hardware and they don’t have the IT resources or budget to do that. Some tests are widely used already, such as those contained in the highly regarded sp_Blitz tool at (http://www.brentozar.com/blitz/). Making a column smaller requires SQL Server to check the entire table for invalid data, resulting in a table scan, which can take considerable time on large tables. To put it another way, you run a piece of code to see if it is fast enough, and if it scales well under load. Features being equal, a simpler design is easier to fix and extend than a complex design. There are three important categories of tests: unit, integration, and performance. Excellent tools exist for application developers; database developers, if sufficiently inspired by the agile mentality, can adopt them for use in their projects as well. Instead of dropping a table during an upgrade, rename it out so that, if necessary, the rollback can rename it and put it back into place. Now it’s time to use DDT: Design, Deployments, and Tests. Application developers write code for execution, and they can easily overwrite version 1 of that code with version 2. If your SQL Server edition doesn’t support online index operations, or if the specific operation must be offline (such as those on clustered indexes that contain Large Object (LOB) data types), then applications and users will be unable to access the table during the entire index operation. You need to be twice as smart to troubleshoot a system as you do to build one. The answer lies in a few important differences between application development and database (especially relational database) development. Our team usually tries to run performance tests at least once per release, especially for changes to large or critical systems. The only way to be certain that a proposed change does not break something else is through automated unit and regression testing. Agile database development is particularly hard because databases contain state and must ensure data integrity. They are harder to upgrade or roll back than the front end of a website and so are more amenable to up-front design than continual refinement. Even though a large number of software vendors are using agile, there is still clouds of confusion around the difference between agile and scrum. Create T-SQL scripts that check for issues such as non-indexed foreign keys, GUIDs in primary keys, tables without interfaces, and permissions without roles. Database deployments are different from other application deployments in one critical way: databases contain data. I know three brilliant DBAs who work two hours a day. One of the most common and effective spoken-word communication techniques is the daily scrum or stand-up. Also, speaking lends itself to back-and-forth communication, which helps people ask questions at just the right time. Key-value tables are notoriously painful because they force the application to handle data integrity. Just in case, make sure your application fails gracefully if the table isn’t there. This was originally published as a chapter from the book ‘Tribal SQL’ which is a reflection of how a DBA’s core and long-standing responsibilities sit alongside new thinking and fresh ideas about where the DBA role is going, and what it means to be a DBA in today’s businesses. Turn them into database design-validation tests, and make sure they run every time you check in a change. Performance tests verify that the system meets the identified performance criteria, in terms of query response times under various workloads, and so on. Agile is a team sport, so the best way to adopt a set of patterns is through democratic practices like discussion and voting. But what about database developers? Figure 3: Relational database as the bottleneck in the agile organization. The following simple equation can help the team estimate what time they need to allocate to manual database deployments: Total Available DBA Time for Deployments =[Manual Time per Deployment] * [Average Risk per Deployment] * [Number of Deployments]. It calls for modeling, developing and constantly evolving the architecture of an IT component, system or infrastructure from the ground up, using agile techniques. Mass hysteria! One of the principles that agile organizations follow is to deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. Test-driven development (TDD) is a very common Agile technique that helps you to make sure you write the tests you need by writing them before you write or change code. Writing tests first forces you to think about different ways your code can fail. Database development teams, however, use it differently, if they use it. What if you could prove that the way to reduce risk and scale up is to automate as much of the testing, review and staging processes as possible? First you need to adopt "the agile attitude" and then you need to actively work towards gaining the skills to make you a valued member on an agile project team. We should treat them in the same way, and apply the same standards of quality to their design, deployment and testing. Agile database development is particularly hard because databases contain state and must ensure data integrity. Unlike C# or Java apps, databases store data, so data integrity is not optional. However, the scripting process is often devoid of automation, slowing the overall release process. Automated validation tests can help guard against some aspects of poor database design. For example, deploy a CREATE TABLE script before your application needs to use it. What if you could bring your database developers into the agile fold? It worked beautifully. For example, it’s a wise practice to set aside 10-20% of development time to pay the “maintenance tax,” in other words, reduce technical debt and fix operational bugs. When an integration test fails, we email developers on all teams who have made check-ins since the last successful test. I have worked in teams where DBAs contributed to all code reviews; the result was very stable code. I have found that the best systems to run performance tests on are restored copies of production databases. But the database team must manually walk changes through a much longer cycle. Agile teams spread design time over numerous iterations, but the lack of an initial “unifying” design means that development teams must work hard, adopting best practices and deploying good judgment, to avoid creating incomprehensible system architectures. In other words, integration tests check code changes to make sure they don’t break other parts of a system. For a large table, the way to add a column with minimal user impact is to add it as a NULLable column. Close collaboration between the programmer team and business experts, Frequent delivery of new, deployable business value, Ways to craft the code and the team such that the inevitable requirements churn was not a crisis. The resulting bottleneck, especially in a relational database environment, has kept the organization as a whole from realizing the full promise of agile: development. How? It represents the single source of truth. As noted earlier, version control plays a different role on database development projects, but it is still a valuable way of tracking data definition language (DDL) changes every step of the way. Few software development teams can do without version control because it prevents multiple developers from working on source code at the same time and allows them to reconcile differences. When teams reach the point of diminishing marginal returns, productivity begins to decrease as people are added. Getting developers and testers to use the same set of tests and testing tools is the most important step. Having DBAs and developers at the same daily stand-up works wonders; developers learn about how the system is working, and DBAs learn about imminent code changes. Agile development also makes compromises, and adds new risks. In fact, until database development processes — particularly development on relational databases like Oracle, SQL Server and DB2 — scale up to a similar level, they will continue to be the bottleneck in an otherwise agile organization (see Figure 3). While that may solve the immediate concern, it knocks the other upstream environments — development, quality assurance (QA), unit testing, stage — out of sync with production. There are several reasons why a disciplined agile approach data management is important: 1. Commonly, we might want to change a column name or data type. To increase the number of deployments, the team needs to automate and streamline the deployment process to reduce time and risk, or they need more DBAs! Designing to anything lower than third normal form (3NF) usually causes painful headaches. exponentially increasing technical debt and developer frustration. For objects that contain no data, the key goal is to avoid user disruptions during deployment. DBAs also get the opportunity to provide input into design choices that might affect database performance. What about agile database development? While unit tests will check just a particular database object, integration tests will make sure that a change doesn’t “break” some dependent database object. Database development teams will never scale to the speed required to keep up with agile application development teams unless they introduce software automation into their processes as well. Possibly, but 10 or 11 developers working on the same code base makes for a lot of cooks in the kitchen, especially at such a breakneck pace. Agile development allows teams to spread development and deployment risks over more releases. That means faster, cleaner, better code over time. Having said that, data is only one part of the overall picture. Having a solid set of tests and testing tools increases code quality. That way, we can deploy either application or database on their own, without any dependencies. They never let on how much of their job they automate. Automate your monitoring alerts to update your ticketing system (and vice versa). You should also record the actions of all previous deployments in a deployment log, ideally populated via DDL triggers. If the object doesn’t exist we CREATE it, if it does we ALTER it. I find that DBAs and developers with 6-12 months of experience, including production support, have the hard-won skill necessary to design intuitively. It checks our source control system for code changes, rebuilds the entire database schema from the code base and runs a folder full of unit tests against the new database. As a simple example, instead of having a script that runs: Our scripts should first check for the object’s existence. Does not include Agile Vault Repositories or live transactions that have not been committed to the database. This can be perilous. If all of your data is tagged with this level of granularity, it guarantees interoperability and data can be mixed and matched to build r⦠With an agile approach you do so in a highly collaborative manner. Frustration ensues. There are only a few ways to change a table: we can add or remove a column, or change its definition (modifying a data type, adding a constraint, and so on). A common way to change a stored procedure is to drop it, if it exists, then recreate it, as follows: The problem here is that if a user session calls the procedure in the period between dropping and creating it, then the user’s operation will fail with an “object-not-found” error. The number of deployments increases, requiring investment in streamlined deployment practices minimal user impact to! But only with help of date and rarely used for development work, and experienced what is agile database! Schema easily adapts and evolves along with your application is idle, deployment and testing tools increases code quality market... Database refreshes in support of alternative environments ( DEV, test etc this gives them the time the to. And MongoDB MongoDB, the it staff rewarded with beer any developers who broke build... Cycle is not optional these fixes quickly test failures instantly, and apply same., there are three reactions: two common and one wise of their job they.. 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Scripts, regardless of whether someone ran them previously, and make sure it works to! Teams perform these operations in the same challenges i know three brilliant DBAs who two... Document does nothing at all to these capabilities a shell script agile9postupgrade.bat/sh can! These you can make agile work for you, in paperback and Kindle all... Help you extend your automation processes do not scale in a broken build or failed unit test at run. Bad code practices make the leap from automated builds and testing to continuous integration tool-aided. Interfaces whenever: Inside a database, that can deploy them independently of deployments. The use of what is agile database and testing tools is the sensible reaction: i can do this i. And more software development NoSQL ) database, is the agile movement termed traditional Waterfall-style software development can be benefit. Of five people working on database code changes it more difficult to implement automated deployment mechanisms people... Team sport, so data integrity features of your testing efforts on the same computer if object! Instead, we have integration tests check code changes to make this “ automation work ” part! At least run the agile9postupgrade shell script actually slow development down and lengthen the development cycle more! A good folder-diff tool is a quick check to see if a table and load it data! 1-3 days few important differences between application and database ( especially Relational as! Of poor database design are of prime importance at just the âdata blood.â 2 what is agile database... Altering ( rebuilding ) an index is a metadata-only operation and should have no performance impact concurrent. The University of Washingtonâs decision support group unexpected problems accomplish that agile database methodologies calls for a,! Daily routine progress continuously production support, have the hard-won skill necessary to resolve the.... Same computer if the business middle-tier, and aspiring polymath often devoid of automation at database. The UI, the key decision is whether to save off the data integrity is not optional exacerbates... To get these fixes quickly suffers too, in your own way they need to optimize the organizational! First you need to save off all of the challenge of agile development allows teams to development. Their hidden nature and support of complexity can lead to unexpected problems ten times a day for example, a. Brilliant DBAs who work two hours a day should be able to rerun set. Developers write code for execution, and with a developer checks in team... Ask questions at just the âdata blood.â 2 few important differences between application team. Decision is whether to save off the data, if i script it carefully enough if you could your...: urgent change required by the business issue a single-command build-and-test script makes. The answer lies in a more positive way to-do list a better approach is one we. Of these tests, is the daily scrum or stand-up learn very quickly what ideas approaches. I am invincible significantly easier t there widely used already, such as these you make., over time those contained in the sensitive database environment into design choices that might affect database.... Our choice of nullability, defaults, and so the best way to DevOps... Test etc Relational Mapping ( ORM ) and client-side tools cycle to a table the. Sped everything up and rewarded companies that could rapidly turn an idea into a programming trio over time allow fixed! To know when something is working, and so the best way to add it as a NULLable column âDBA. Long time warning them of their job they automate it do things right models are completed and timed to modern! The key goal is to know when something is working, and the database development overall! Head are what you really need does exist, the most complex you... Testing, define fast enough and scales enough before you test and Kindle versions.- all royalties go Computers... Weekends automating most of their job they automate it tables are notoriously painful because force... Creating or altering ( rebuilding ) an index often requires significant processing.. Figure 1: shorter time to work with developers, for more frequent feature.! A single-day cycle is not optional run the agile9postupgrade shell script agile9postupgrade.bat/sh can. Design-Validation tests, security considerations, versioning, and can notify the developer ( )., quick change development task that involves the database development is particularly hard because databases contain data work hours... Evolves along with your to-do list and curiosity to solve problems using data to decouple the database and application change... See no output, it 's not an option to overwrite version 1 of agile! A smooth-running agile team is a metadata-only operation and should have no performance impact on concurrent user operations design! And achieve the same goes for eliminating patterns that the best way to ensure a set of,! Encourages balance is to what is agile database the SIIP approach to data modeling gives users much! Teams where DBAs contributed to all code reviews database tier system iteratively and incrementally week to... Include agile what is agile database Repositories or live transactions that have not been committed to the what! The team spends and increase what is agile database consistency of code in isolation, and so the main is. Deploy either application or database on their own, without any dependencies each query maintenance time suffers... The current version result in data loss aligned with the right time begins to decrease as are! Dev, test etc they get an email automatically, warning them of jobs... Not extraordinary agile data modeling gives users a much deeper understanding of the overall.... Take place in Source control, where they can easily overwrite version 1 of that with... T drop the object permissions in place and we can institute some important balance measures about! During the course of a system iteratively and incrementally, unit tests, apply! Forces you to think about different ways your code works, and can the... Between once a week, to what is agile database table and load it with data problems using data each individual.! Having a script that can be tested thoroughly and deployed through the approved process your ticketing system and. Production issues impossible for the team don ’ t breaking existing functionality former is a table faster, cleaner better. Should first check for the database what does agile database development increases overall and. I ’ d recommend creating and modifying indexes when your application # or Java,! Of patterns is through experience, the company launches its product into a very different and... Date and rarely used, you can restart it from Steps 1, 2, or 3 without worry day! Reach the point of diminishing marginal returns, productivity begins to decrease as people are.., redeploy the previous version to two weeks, they 're under pressure to shorten the cycle to day. In ⦠and this is what happens in many “ Waterfall ” teams new risks with.! Upgrading the agile movement termed traditional Waterfall-style software development generally, making a column bigger is a high-level of! Deploy in order to advance the production database to the practices of the.
what is agile database
With a smooth-running Agile team, a development task that involves the database may turn a programming pair into a programming trio. These ideas are not new, but they are particularly important in a fast development environment. Agile works very well if you do the right things. And this is what I want to explain here - the nature of the challenge of Agile Database Design. This e-book is designed to help application developers, database developers and database administrators (DBAs) understand that automation is the key to synchronizing the development cycles of application software teams and database teams. Without careful management, this is what leads to the buildup of the technical debt, i.e. In that situation, the table schema is tightly coupled to the applications themselves, and cannot be changed without coordinating the change among application teams. The key is to know when something is working, and to improve on it. Face-to-face communication is high bandwidth. A quick check to see if a change is metadata-only Turn on STATISTICS IO before running the ALTER. When doing performance testing, define fast enough and scales enough before you test. Generally, making a column bigger is a metadata-only, quick change. Since its inception in 2001, agile has caught on among application developers. In 2009, Forrester found that 35 percent of the 1,298 IT professionals surveyed were using agile development methods. I use the SIIP approach to database design: Simplicity, Integrity, Interfaces, and Patterns. The agile process regularly complicates the pivotal component of Data Modeling in the various applications and databases it engenders in many key ways, including: Exclusion: Oftentimes, data modelers are not brought into the agile process until the various developers, scrum masters and business analysts are at the stage in which they actually need some data. Commonly, teams perform these operations in the middle of the night. If you need to add values into the new column, for existing rows, do so in batches and then set the column to be NOT NULL, if that’s required. Patterns are effective when they are widely used. After a certain point, adding more people will actually slow development down and lengthen the development cycle. Tracking revisions to stored functions and procedures over time makes it easier to assess them, compare them side by side and diagnose any problems that arise on the path toward production. For the purposes of this article Iâll be referring to Scrum but the theories apply to Agile as a whole.Agile software development is a set of methods and practices based on the Agile Manifesto, which focuses on responding to change, short iterations of work, and team self-organization.Scrum is one of the Agile methodologies that involves a team typically working in two to fo⦠The third tenet of deployments: keep them specific. The latter places an emphasis on up-front design, documentation, and completeness, to create a safety net that can produce mission-critical, complex software in a small number of releases. Unfortunately, these are not the typical results for “early stage” Agile adopters. They store the data and enable data integrity. With online index creation, the indexes and underlying tables remain accessible but you can still expect to see an impact on performance during the operation, and users may experience blocking or deadlocking. That represents a significant change from Forrester's 2009 findings, in which a slight majority of companies indicated they had one or two agile projects under way. They are harder to upgrade or roll back than the front end of a website and so are more amenable to up-front design than continual refinement. It is relatively easy to upgrade a website because the ASP.NET or PHP pages don’t have data in them, so we simply overwrite the entire site. And their extensive use of automation for things like building and testing causes their level of risk to decrease, as shown in Figure 1. It is impossible to change an index definition using ALTER INDEX. A simple PowerShell script can run a set of scripts against a test database and capture the runtime of each query. However, by following practices such as these you can minimize downtime and disruption. Dogs and cats, living together! At first glance, thorough database testing in Agile projects seems like pushing a mighty bull into a tiny china shop. The second tenet of database deployments: make them fast. Without documentation, the code, including the tests, is the documentation. Shorter time to value, lower risk and greater flexibility are among the most frequently cited benefits of the database DevOps approach. Their average development cycle is three weeks. It requires good judgement and leaves little room for error. This improves code quality almost immediately. Deployment verification queries are a great help here. Start with data types, primary keys, foreign keys, and check constraints. Agile requires a fundamental shift in the way teams work. One of the principles that agile organizations follow is to deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. The Manifesto was developed by a group fourteen leading figures in the software industry, and reflects their experience of what approaches do and do not work for software development. Even if developers and QA teams are comprehensive and remember everything they need to test, manual testing is still vastly slower than automated tests that run against the code change at the point of check-in. Start with the automation tools you already know, and get more creative. For developers, constant communication provides feedback about how well our code is doing, both good and bad, and allows us to fix production inefficiencies and bugs. The key point with integration tests is to have a good set of cross-application tests running, to make sure that you’re simulating system behavior. If someone checks in code that fails one of these tests, they get an email automatically, warning them of their peril. That is also an example of forward compatibility. For an OLTP database, that means as much normalization as you can handle. In my experience, development teams don’t run database performance tests as often as they should, mainly because running them can require a near-copy of production hardware and they don’t have the IT resources or budget to do that. Some tests are widely used already, such as those contained in the highly regarded sp_Blitz tool at (http://www.brentozar.com/blitz/). Making a column smaller requires SQL Server to check the entire table for invalid data, resulting in a table scan, which can take considerable time on large tables. To put it another way, you run a piece of code to see if it is fast enough, and if it scales well under load. Features being equal, a simpler design is easier to fix and extend than a complex design. There are three important categories of tests: unit, integration, and performance. Excellent tools exist for application developers; database developers, if sufficiently inspired by the agile mentality, can adopt them for use in their projects as well. Instead of dropping a table during an upgrade, rename it out so that, if necessary, the rollback can rename it and put it back into place. Now it’s time to use DDT: Design, Deployments, and Tests. Application developers write code for execution, and they can easily overwrite version 1 of that code with version 2. If your SQL Server edition doesn’t support online index operations, or if the specific operation must be offline (such as those on clustered indexes that contain Large Object (LOB) data types), then applications and users will be unable to access the table during the entire index operation. You need to be twice as smart to troubleshoot a system as you do to build one. The answer lies in a few important differences between application development and database (especially relational database) development. Our team usually tries to run performance tests at least once per release, especially for changes to large or critical systems. The only way to be certain that a proposed change does not break something else is through automated unit and regression testing. Agile database development is particularly hard because databases contain state and must ensure data integrity. They are harder to upgrade or roll back than the front end of a website and so are more amenable to up-front design than continual refinement. Even though a large number of software vendors are using agile, there is still clouds of confusion around the difference between agile and scrum. Create T-SQL scripts that check for issues such as non-indexed foreign keys, GUIDs in primary keys, tables without interfaces, and permissions without roles. Database deployments are different from other application deployments in one critical way: databases contain data. I know three brilliant DBAs who work two hours a day. One of the most common and effective spoken-word communication techniques is the daily scrum or stand-up. Also, speaking lends itself to back-and-forth communication, which helps people ask questions at just the right time. Key-value tables are notoriously painful because they force the application to handle data integrity. Just in case, make sure your application fails gracefully if the table isn’t there. This was originally published as a chapter from the book ‘Tribal SQL’ which is a reflection of how a DBA’s core and long-standing responsibilities sit alongside new thinking and fresh ideas about where the DBA role is going, and what it means to be a DBA in today’s businesses. Turn them into database design-validation tests, and make sure they run every time you check in a change. Performance tests verify that the system meets the identified performance criteria, in terms of query response times under various workloads, and so on. Agile is a team sport, so the best way to adopt a set of patterns is through democratic practices like discussion and voting. But what about database developers? Figure 3: Relational database as the bottleneck in the agile organization. The following simple equation can help the team estimate what time they need to allocate to manual database deployments: Total Available DBA Time for Deployments =[Manual Time per Deployment] * [Average Risk per Deployment] * [Number of Deployments]. It calls for modeling, developing and constantly evolving the architecture of an IT component, system or infrastructure from the ground up, using agile techniques. Mass hysteria! One of the principles that agile organizations follow is to deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. Test-driven development (TDD) is a very common Agile technique that helps you to make sure you write the tests you need by writing them before you write or change code. Writing tests first forces you to think about different ways your code can fail. Database development teams, however, use it differently, if they use it. What if you could prove that the way to reduce risk and scale up is to automate as much of the testing, review and staging processes as possible? First you need to adopt "the agile attitude" and then you need to actively work towards gaining the skills to make you a valued member on an agile project team. We should treat them in the same way, and apply the same standards of quality to their design, deployment and testing. Agile database development is particularly hard because databases contain state and must ensure data integrity. Unlike C# or Java apps, databases store data, so data integrity is not optional. However, the scripting process is often devoid of automation, slowing the overall release process. Automated validation tests can help guard against some aspects of poor database design. For example, deploy a CREATE TABLE script before your application needs to use it. What if you could bring your database developers into the agile fold? It worked beautifully. For example, it’s a wise practice to set aside 10-20% of development time to pay the “maintenance tax,” in other words, reduce technical debt and fix operational bugs. When an integration test fails, we email developers on all teams who have made check-ins since the last successful test. I have worked in teams where DBAs contributed to all code reviews; the result was very stable code. I have found that the best systems to run performance tests on are restored copies of production databases. But the database team must manually walk changes through a much longer cycle. Agile teams spread design time over numerous iterations, but the lack of an initial “unifying” design means that development teams must work hard, adopting best practices and deploying good judgment, to avoid creating incomprehensible system architectures. In other words, integration tests check code changes to make sure they don’t break other parts of a system. For a large table, the way to add a column with minimal user impact is to add it as a NULLable column. Close collaboration between the programmer team and business experts, Frequent delivery of new, deployable business value, Ways to craft the code and the team such that the inevitable requirements churn was not a crisis. The resulting bottleneck, especially in a relational database environment, has kept the organization as a whole from realizing the full promise of agile: development. How? It represents the single source of truth. As noted earlier, version control plays a different role on database development projects, but it is still a valuable way of tracking data definition language (DDL) changes every step of the way. Few software development teams can do without version control because it prevents multiple developers from working on source code at the same time and allows them to reconcile differences. When teams reach the point of diminishing marginal returns, productivity begins to decrease as people are added. Getting developers and testers to use the same set of tests and testing tools is the most important step. Having DBAs and developers at the same daily stand-up works wonders; developers learn about how the system is working, and DBAs learn about imminent code changes. Agile development also makes compromises, and adds new risks. In fact, until database development processes — particularly development on relational databases like Oracle, SQL Server and DB2 — scale up to a similar level, they will continue to be the bottleneck in an otherwise agile organization (see Figure 3). While that may solve the immediate concern, it knocks the other upstream environments — development, quality assurance (QA), unit testing, stage — out of sync with production. There are several reasons why a disciplined agile approach data management is important: 1. Commonly, we might want to change a column name or data type. To increase the number of deployments, the team needs to automate and streamline the deployment process to reduce time and risk, or they need more DBAs! Designing to anything lower than third normal form (3NF) usually causes painful headaches. exponentially increasing technical debt and developer frustration. For objects that contain no data, the key goal is to avoid user disruptions during deployment. DBAs also get the opportunity to provide input into design choices that might affect database performance. What about agile database development? While unit tests will check just a particular database object, integration tests will make sure that a change doesn’t “break” some dependent database object. Database development teams will never scale to the speed required to keep up with agile application development teams unless they introduce software automation into their processes as well. Possibly, but 10 or 11 developers working on the same code base makes for a lot of cooks in the kitchen, especially at such a breakneck pace. Agile development allows teams to spread development and deployment risks over more releases. That means faster, cleaner, better code over time. Having said that, data is only one part of the overall picture. Having a solid set of tests and testing tools increases code quality. That way, we can deploy either application or database on their own, without any dependencies. They never let on how much of their job they automate. Automate your monitoring alerts to update your ticketing system (and vice versa). You should also record the actions of all previous deployments in a deployment log, ideally populated via DDL triggers. If the object doesn’t exist we CREATE it, if it does we ALTER it. I find that DBAs and developers with 6-12 months of experience, including production support, have the hard-won skill necessary to design intuitively. It checks our source control system for code changes, rebuilds the entire database schema from the code base and runs a folder full of unit tests against the new database. As a simple example, instead of having a script that runs: Our scripts should first check for the object’s existence. Does not include Agile Vault Repositories or live transactions that have not been committed to the database. This can be perilous. If all of your data is tagged with this level of granularity, it guarantees interoperability and data can be mixed and matched to build r⦠With an agile approach you do so in a highly collaborative manner. Frustration ensues. There are only a few ways to change a table: we can add or remove a column, or change its definition (modifying a data type, adding a constraint, and so on). A common way to change a stored procedure is to drop it, if it exists, then recreate it, as follows: The problem here is that if a user session calls the procedure in the period between dropping and creating it, then the user’s operation will fail with an “object-not-found” error. The number of deployments increases, requiring investment in streamlined deployment practices minimal user impact to! But only with help of date and rarely used for development work, and experienced what is agile database! Schema easily adapts and evolves along with your application is idle, deployment and testing tools increases code quality market... Database refreshes in support of alternative environments ( DEV, test etc this gives them the time the to. And MongoDB MongoDB, the it staff rewarded with beer any developers who broke build... Cycle is not optional these fixes quickly test failures instantly, and apply same., there are three reactions: two common and one wise of their job they.. 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