Tech Talk 2016

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2016 has been a fruitful year for me in software development. Apart from my day job in Sitecore as a lead developer, I also have a lot fun with services in Azure cloud in my spare time.

Another new “adventure” I tried in 2016 is speaking for Tech Talk in local tech communities – from my own office, university, Microsoft office to being an online panelist in Google Hangout discussion.

Microsoft Malaysia Level 26, Tower 3

Scaling SQL Server @ Microsoft Malaysia Level 26, Tower 3

multimedia-university

Software Industry Career Advice @ Multimedia University, Computing Faculty Lecture Hall, Cyberjaya

Sitecore Malaysia - Daniel Foo on Azure Search

Working with Azure Search @ Sitecore Malaysia, Level 18

Standardizing DevOps Across Organization @ Continuous Discussions (#c9d9) Google Hangout

It has been a rewarding experience to contribute and making a difference in tech communities through Tech Talk. It amazed me when some audiences asked me follow up questions based on what I have shared earlier. It is truly satisfying to learn that I have inspired some audiences with useful information or ideas in general which they can benefit from.

It has been an honor to share the stages with many of the knowledgeable speakers. As much as I enjoyed sharing, I have learned equally a lot from them. Thanks to those who invited me over to speak, those who helped me out to make the Tech Talks possible and those who came and supported me. Thank you! I am truly lucky to have you all amazing people as friends in the tech communities.

Signing off for 2016… It has been a fantastic year, looking forward to 2017!

Continuous Integration and Continuous Delivery with NuGet

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Continuous Integration (CI) is a development practice that requires developers to integrate codes into a shared repository. Each commit will then be verified by an automated build and sometimes with automated tests.

Why Continuous Integration is important? If you have been programming in a team, you probably encountered situation where one developer committed codes that cause every developer’s code base to break. It could be extremely painful to isolate the codes that broke the code base. Continuous Integration serves as a preventive measurement by building the latest code base to verify whether there is any breaking changes. If there is, raise an alert perhaps by sending out an email to the developer who last committed the codes or perhaps notify the whole development team or even to reject the commit. If there isn’t any breaking change, CI will proceed to run a set of unit test to ensure the last commit has not modify any logic in an unexpected manner. This process sometimes also known as Gated CI, which guarantees the sanity of the code base in a relatively short period of time (usually within few minutes).

CI

The idea of Continuous Integration goes beyond validating the code base in a team of developers working on. If the code base utilizes other development teams’ components, it is also about continuously pulling the latest components to build against the current code base. If the code base utilizes other micro-services, then it is about continuously connecting to the latest version of the micro-services. On the other hand, if the code base output is being utilized by other development teams, it is also about continuously delivering the output so that other development teams can pull the latest to integrate with. If the code base output is a micro-service, then it is about continuously exposing the latest micro-service so that other micro-services can connect and integrate to the latest version. The process of delivering the output for other teams to utilize leads us to another concept known as Continuous Delivery.

Continuous Delivery (CD) is a development practice where development team build software in a manner the latest version of software can be released to production at any time. The delivery could mean the software being delivered to a staging or pre-production server or simply a private development NuGet feed.

Why Continuous Delivery is important? In today software development fast pace of change, stakeholders and customers wanted all the features yesterday. Product Managers do not want to wait 1 week for the team to “get ready” to release. Business expectation is as soon as the codes are written and functionalities are tested, software should be READY to ship. Development teams must establish an efficient delivery process where delivering software is as simple as pushing a button. A good benchmark is the delivery can be accomplished by anyone in the team. Perhaps to be done by a QA after he has verified the quality of the deliverable or by Product Manager when he thinks the time is right. In complex enterprise system, it is not always possible to ship codes to production quickly. Therefore complex enterprise system is often broken into smaller components or micro-services. In this case, the components or micro-services must be ready to be pushed to a shared platform so that other components or micro-services can consume the deliverable as soon as available. This delivery process must be at READY state at all time. The decision of whether to deliver the whole system or the smaller component should be a matter of business decision.

Note that Continuous Delivery does not necessary mean Continuous Deployment. Continuous Deployment is where every change goes through the pipeline and automatically gets pushed into production. This could lead to several production deployments every day, which is not always desirable. Continuous Delivery allows development team to do frequent deployments but may choose not to do it. In today’s standard for .NET development, NuGet package is commonly used for either delivering a component or a whole application.

NuGet is the package manager for the Microsoft development platform. A NuGet package is a set of well-managed library and the relevant files. NuGet packages can be installed and be added to .NET solution from GUI or command line. Instead of referencing to individual library in the form of .dll, developers can reference to a NuGet package which provides much better management in handling dependencies and assemblies versions. In a more holistic view, a NuGet package can even be an application deliverable by itself.

Real life use cases

Example 1: Micro-services

In a cloud based (software as a service) solution, domains are encapsulated in the respective micro-service. Every development team is responsible for their own micro-services.

microservices

Throughout the Sprint, developers commit codes into TFS. After every commit, TFS will build the latest code base. Once the building process is completed, unit tests will be executed to ensure existing logic are still intact. Several NuGet packages are then generated to represent several micro-services (WCF, Web application, etc). These services will be deployed by a deployment tool known as Octopus Deploy to a Staging environment (hosted in AWS EC2) for QA to perform testing. This process continues until the last User Story is completed by the developers.

In a matter of clicks, the earlier NuGet package can also be deployed to Pre-production environment (hosted in AWS EC2) for other types of testing. Lastly, with the blessing from Product Manager, DevOps team will use the same deployment tool to Promote the same NuGet packages that were tested by QA earlier into Production. Throughout this process, it is very important that there is no manual intervention (such as copying a dll, changing a configuration, etc) by hands to ensure the integrity of the NuGet package and deployment process. The entire delivery process must be pre-configured or pre-scripted to ensure the process is consistent, replicatable, and robust.

Example 2: Components

In a complex enterprise application, functionalities are split into components. Each component is a set of binary (dll) and other relevant files. A component is not a stand-alone application. The component has no practical usage until it sits on the larger platform. Development teams are responsible for their respective component.

Throughout the Sprint, developers commit codes into a Git repository. The repository is monitored by Team City (build server). Team City will pull the latest changes and execute a set of Powershell script. From the Powershell script, an instance of the platform is setup. The latest code base will be built and the output is placed on top of the platform. Various tests are executed on the platform to ensure the component functionality is intact. Then, a set of NuGet package will be generated from the Powershell script to be published as the artifacts. These artifacts will be used by QA to run other forms of tests. This process continues until the last User Story is completed by the developers.

When QA gives the green light and with the blessing from Product Manager, the NuGet packages will be promoted to ProGet (an internal NuGet feeds). This promotion process happens in a matter of clicks. No manual intervention (modifying the dependencies, version, etc) should happen to ensure the integrity of the NuGet package.

Once the NuGet package is promoted / pushed into ProGet, other components update this latest component into their components. In Scaled Agile, a release train is planned on frequent and consistent time frame. Internal release happens on weekly basis. This weekly build will always pull all of the latest components from ProGet to generate a platform installer.

Summary

From the examples, we can tell that Continuous Integration and Continuous Delivery are a fairly simple concepts. There is neither black magic nor rocket science in both the use cases. The choice of tools and approaches to accomplish largely depend on the nature of the software we are building. While designing software, it is always a good idea to keep Continuous Integration and Continuous Delivery in mind to maximize team productivity and to have quick and robust delivery.

Json Data in SQL Server

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The rise of NoSQL database such as mongoDb is largely due to the agility to store data in non-structured format. A fixed schema is not required like traditional relational databases such as SQL Server.

However, NoSQL database such as mongoDb is not a full-fledged database system. It is designed for very specific use cases. If you don’t know why you need to use NoSQL in your system, chances are you don’t need to. For those who find it essential to use a NoSQL database, often they only use NoSQL database for certain portion of their system and then use another RDBMS for the remaining part of their system that have more traditional business use cases.

Wouldn’t it be nice if RDBMS is able to support similar data structure – having the ability to store flexible data format without altering database tables?

Yes, it is possible. For years, software developers have been storing various JSON data in one table column. Then, developers will make use of library such as Newtonsoft.Json within the application (data access layer) to deserialize the data to make sense out of the JSON data.

Reading / Deserializing JSON

This works. However “JsonConvert.DeserializeObject” method is working extremely hard to deserialize the whole JSON data to only retrieve a simple field such as Name.

Imagine there is a requirement for searching certain Genres on a table that has 1 million row of records, the application codes will have to read 1 million row of records, then perform filtering on the application side. Bad for performance. Now imagine if you have a more complex data structure than the example above…

The searching mechanism will be much efficient if developers can pass a query (SQL statement) for database to handle the filtering. Unfortunately SQL Server does not support querying JSON data out of the box.

It is impossible to directly query JSON data in SQL Server until the introduction of a library known as JSON SelectJSON Select allows you to write SQL statement to query JSON data directly from SQL Server.

How JSON Select Works

First you need to download an installer from their website. When you run the installer, you need to specify the database you wish to install this library at:

JsonSelect

What this installer essentially does is to create 10 functions in the database you have targeted. You can see the functions at:

SSMS > Databases > [YourTargetedDatabase] > Programmability > Functions > Scalar-valued Functions

functions

Next, you can start pumping in some JSON data in your table to test it out.

I create a Student table with the following structure for my experiment:

table

In my StudentData column, I enter multiple rows of records in the following structure:

For demonstrating the query purpose, I have entered multiple rows as following:

all-rows

If you want to write a simple statement to read the list of student names in JSON data, you can simply write:

You will get result as following in SSMS:

name

How about more complex query? Does it work with Aggregate Functions?

If you want to find out about how many students come from each city and what is their average age, you can write your SQL Statement as following:

You will get result as following in SSMS:

complex-query

It appears the library allows you to query any JSON data in your table column using normal T-SQL syntax. The only difference is you need to make use of the predefined scalar-valued functions to wrap around the values you want to retrieve.

Few Last Thoughts…

  1. The good about this library is it allows developers to have hybrid version of storage (NoSQL & relational database) under one roof – minus the deserialize code at application layer. Developer can continue using the classical RDBMS for typical business use cases and leverage on the functions provided in the library to deal with JSON data.
  2. The bad about this library is it lacks proven track record and commercial use cases to demonstrate the robustness and stability.
  3. Although the library is not free, the license cost is relatively affordable at $AU 50. However the library is free for evaluation.
  4. SQL Server 2016 provides native support for JSON data. This library is only useful for SQL Server 2005 to 2014 where upgrading to 2016 is not a feasible option.