An Overview of the New MySQL 8.0

mysql desktop

MySQL remains a valid database option for companies looking for an alternative to Oracle or SQL Server. While it may not offer the enterprise-level horsepower of PostgreSQL, it still works well for many scenarios. This is likely why it maintains its status as the most popular open source database in the industry.

Recently, the folks behind MySQL released version 8.0 of the database. New features and functionality abound. Let’s take a high level overview of this new edition to see if there’s anything to help with your own software development projects.

The New Features in MySQL 8.0

The new version of MySQL added a whole host of enhanced SQL functionality. This includes support for window functions, common table expressions, as well as the NOWAIT and SKIP LOCKED statements. Most notably, window functions provide the ability to perform analytics on stored data; this is long-awaited feature as SQL Server added it in 2003.

They also added support for descending indexes which provides a performance improvement, especially when working with large datasets. The new GROUPING() function lets developers build datasets that distinguish super-aggregate rows from the results of GROUP BY queries. Both of these features were highly requested among the MySQL user community.

Boosting overall application performance becomes essential when using MySQL. Version 8.0 gives developers a new syntax for including optimizer hints. You simply place them using something similar to inline comment blocks after a SELECT, INSERT, UPDATE, REPLACE, or DELETE statement.

Additionally, the new version adds optimizer hints for a variety of INDEX and JOIN statements.  Now developers can control index merge behavior for each individual query or even the table order when performing a join. The MySQL development team feels the new optimizer hint syntax makes it easier to use while also boosting code readability.

MySQL adds Improved JSON Support

The JSON format is essential for web applications that rely on transferring objects expressed as a data structure. MySQL 8.0 improves its support for JSON in a myriad of ways. First, it adds extended syntax for ranges when using JSON path expressions.

The new JSON table functions lets you use regular SQL statements when working with JSON data. This is a boon for developers especially skilled in writing SQL queries. It essentially creates a relational view of JSON data.

Other new JSON features in MySQL 8.0 include aggregation and merge functions. A boost in sorting performance and the ability to perform partial updates are also welcome. The former helps to optimize large applications while the latter makes replication processes faster.

Other New MySQL 8.0 Features

Another significant new feature in MySQL 8.0 is support for GIS, including the Spatial Reference System. This lets applications using the database to easily calculate global distances given a LAT and LONG. The database now supports bitwise operations on binary data types, making the processing of IPV6 addresses easier.

The MySQL query optimizer also gets some improvements beyond the new hint syntax. Histograms and better handing of data buffering help engineers boost overall app and database performance. Finally, the database boasts improved reliability, availability, and reporting with an eye towards being used at companies following DevOps.

In short, MySQL 8.0 adds a host of new features making the database more attractive to organizations with high-demand applications. The improved DevOps support is also welcome. For more detailed information on MySQL 8.0, simply click on this link.

Thanks for reading this edition of the Betica Blog. Keep returning for additional insights on the software development world.

Pitfalls to avoid when adopting DevOps

devops2As DevOps continues to grow in popularity, some organizations still struggle with its successful implementation. Perhaps developers really don’t understand the practice and chafe at being forced to follow its concepts? Maybe the network engineers feel DevOps favors the software team, while automating many of their standard administrative tasks?

Whatever the reasons for its difficulty in adoption, getting things right offers many benefits to software shops of all sizes. DevOps plays a key role in boosting development efficiency to the point it becomes a competitive advantage. So, let’s take a look at a few common pitfalls to avoid when adopting DevOps.

Avoid these Mistakes when adding DevOps at your Software Shop

Rebecca Dodd, from the software development process experts at GitLab, wrote an article for DZone covering these major pitfalls to avoid during a DevOps implementation. She talked with a few people at GitLab responsible for project success with their customer base. They provided interesting food for thought on what issues hamper DevOps adoption.

Focusing Too Much on the Tools

GitLab noted that companies who make too much of an investment on their toolset tend to encounter difficulty when implementing DevOps. GitLab Technical Account Manager, John Woods, commented on the issue. “You think you have it all when you’ve got your issue tracker, version control system, CI/CD service, etc. However, what’s the cost of setting all those up and configuring them to ‘talk’ to each other?” said Woods. 

In essence, the time spent configuring and integrating multiple tools takes up valuable time and resources. GitLab calls this the “DevOps Tax.” Make it a point to ensure you use tools that support your DevOps policies and procedures; not the other way around.

In a similar fashion, some companies simply become too attached to their development tools. This adds difficulty if those tools aren’t really compatible with the unique DevOps methodology. GitLab notes some customers try to wrench decades-old tools into their fledgling modern workflow.

Ultimately, the smartest tack involves finding the right integrated toolset compatible with how software gets written in a DevOps world.

Deployment and Monitoring are as Important as Development and Testing

Another pitfall noted by Dodd involves companies not covering the entire SDLC when adopting DevOps. Instead, the only follow its principles for software development and QA, ignoring it for the deployment and monitoring processes. Ultimately, this isn’t a true DevOps implementation.

In most cases, companies leverage DevOps to achieve continuous integration or continuous delivery. Reaching these goals isn’t possible without a full adoption of the methodology. In short, go hard or go home!

Security needs to be part of the DevOps Equation

We previously talked about the importance of information security as part of any DevOps implementation. This is one of the reasons DevSecOps is a hot buzzword. In these days, cybersecurity needs to be a core concept within any software development practice – DevOps or not.

GitLab notes that companies adopting DevOps who still treat security as an afterthought ultimately struggle with its implementation. Valuable resources end up making security-related fixes at the last minute. Consider a DevSecOps approach.

Ultimately, steer clear of these pitfalls to ensure your DevOps adoption goes great!

Keep coming back to the Betica Blog for additional insights and dispatches from the wide world of software development. Thanks for reading!

A Deep Learning AI Routine learns how to Code

AI

The end of April is nigh, which means another edition of our software development news digest. These intriguing stories hopefully provide a measure of insight to your own application engineering efforts. If interested in checking out last month’s digest, just click on the following link. Thanks for reading!

A Deep Learning AI Routine learns how to Code

AI and machine learning continue to make an impact throughout the technology industry. These innovations are found in everything from data analysis to self-driving automobiles. In a similar matter as with robotics, some professionals wonder if their jobs are going to be taken over by a computer in the next decade.

Recently a team at Rice University developed a deep learning routine actually able to write some code. The good news for current developers is the prime directive for this AI application involves helping software engineers more easily handle interfacing with poorly documented APIs. News about this AI innovation appeared earlier this week at Tech Xplore.

The application – called Bayou – performs a deep analysis of APIs in online source code repositories, like GitHub and others, attempting to learn about the API’s usage idioms. The application is focused on the Java language at this time. Swarat Chaudhuri, associate professor of computer science at Rice and one of the creators of Bayou, commented on the tool’s genesis.

“People have tried for 60 years to build systems that can write code, but the problem is that these methods aren’t that good with ambiguity. You usually need to give a lot of details about what the target program does, and writing down these details can be as much work as just writing the code. Bayou is a considerable improvement. A developer can give Bayou a very small amount of information—just a few keywords or prompts, really—and Bayou will try to read the programmer’s mind and predict the program they want,” said Chaudhuri.

Most notably, it analyzed millions of lines of Java code as part of its self-training process. If you want to try the application for your own purposes, just simply ask Bayou.

Fannie Mae makes Software more Secure with Lean

We’ve previously talked about the Lean methodology. Considered a variant of Agile, Lean actually grew out of the manufacturing world in an attempt to make operational processes more efficient. Now, mortgage lender Fannie Mae is leveraging Lean to make its software development process faster and more secure. News about their efforts appeared this week in CSO.

Since implementing Lean in 2013, Fannie Mae’s development cycle decreased by half. Working more efficiently allowed the software engineering team to subsequently make their applications safer from hackers and other nefarious agents. They also saved hundreds of millions of dollars over that time, according to company VP, Michael Garcia.

Writing safer code from the beginning is a core principle of Lean applied to software engineering. Other Agile techniques, like smaller increments and faster testing, improve overall efficiency. The company explored applying the principles Six Sigma to their development process, but ultimately felt Lean made a better fit.

Lean is definitely an Agile variant worthy of evaluation for larger software development shops. A more efficient process simply brings many advantages, including more secure applications and an increase in business value. Dive into the CSO article for a further exploration of the use of Lean at Fannie Mae.

Stay tuned to the Betica Blog for additional news and insights from the constantly evolving world of software development.