All You Need To Know About Database DevOps

When you operate a car, you need to keep it well-maintained. It won't run if you don't service the car with oil changes and tune-ups. You can think of your DevOps as a car that drives your enterprise's development and operations. It helps bring together IT, development and QA (quality analytics), automate the processes and increase the efficiency of software development operations to accelerate software releases and always ensure high-quality code. 

For a smoother drive, it is essential to evaluate each manual operation in the delivery pipeline, which includes working with databases, i.e., the engine. Databases provide a structured layer of information storage and retrieval and management services on top of source files or other data stores. They allow developers to manage data efficiently with built-in security features that restrict access to only authorized users.

Operating a database requires maintenance and monitoring to prevent issues from arising. What are these maintenance tasks? Database DevOps facilitate collaboration between developers and database administrators. They streamline the application development and release process and keep your database (read engine) healthy and productive throughout its lifespan.

So, fasten your seatbelts as you are about to get on an exciting ride of Database DevOps.

What Is Database DevOps?

DevOps and databases are two pillars of modern software engineering. DevOps is an approach to software development that brings together people, processes and technology to accelerate software delivery and achieve operational excellence. An operational database is a set of technologies that provides various services for storing and accessing data on databases. It plays a vital role in any application's life cycle. It can be either a relational or non-relational database. 

The adoption of Database DevOps practices has transformed enterprise IT organizations and accelerated the pace of software innovation across the entire organization. In other words, Database DevOps helps make your organization more agile by breaking down organizational silos between different departments and making them work in unison. Database DevOps bridge the gap between developers and operators as efficiently as possible to release new features faster with less risk. Besides, Database DevOps have simplified the approach to database change and deployment so your enterprise can reap the full benefits of DevOps.

Database DevOps have been through a brief phase of evolution that has fuelled its present; let's explore exactly how!

How Did Database DevOps Evolve?

 
It was the year 2007 when Patrick Debois was frustrated with projects that required a lot of switching back and forth between development and operations. So, he began learning about IT from multiple perspectives and coined the term DevOps. In 2014, Nicole Forsgren, Gene Kim, Jez Humble and others began publishing the annual State of DevOps report. They realized the adoption of DevOps was accelerating. In 2016, Gartner predicted that DevOps would transition from a niche strategy to a mainstream one. 

Forrester Research named 2017 as the “year of DevOps” and also reported up to 50% of organizations are implementing DevOps. Although DevOps improved the software delivery process, the process 'database' critical aspect was still untouched. Database DevOps helped teams identify and streamline application development with their emergence.

That was all about the evolution of Database DevOps; it's time to find out it drives multiple organizational functions.  
 

What Is The Process Of Database DevOps?

 
Database DevOps play a significant role in ECG – equipping, cognizing and growing the organizations and how!
 

• Step 1 – Standardizing Team-based Development

  Database DevOps is all about collaboration, communication and trust. In other words, Database DevOps is about breaking down silos between software engineers, QA engineers and production operations teams. Database DevOps brings these three groups together by standardizing database processes to give visibility into databases throughout the software development life cycle.

 

• Step 2 – Automating Database Deployments

  Database DevOps is the combination of processes, tools and practices that help you deploy your database faster, more efficiently and with less risk. However, implementing these processes can feel like a lot of work. After all, the last thing you want to do is spend even more time on databases! 

 

• Step 3 – Preserving Data

  Several risks are involved even if you keep your data on a company server and not on an individual computer. The good news is that you can reduce the threat of data breaches and attacks by implementing DevOps for database operations. You can also increase efficiency throughout your databases' creation, storage and retrieval processes.

 

• Step 4 – Monitoring Performance

  Database DevOps is a culture that emphasizes collaboration and continuous improvement. To achieve continuous improvement, you need to monitor your databases. Monitoring database performance enables you to detect issues before they impact users. It also helps you track the health of your database over time and detect anomalies so you can take action to correct them.

 
Now it's time to head to the next section and figure out about engine-ous benefits of Database DevOps. 
 

What Are The Benefits Of Database DevOps?

 
So, this is how the benefits of Database DevOps are speeding up the efficiency of organizations. 
 

• Collaborative, Efficient And Agile Software Development

  Database DevOps aims to make software development more collaborative, efficient and agile by integrating practices from operations and software development streams into one workflow. It also helps engineers focus on monitoring applications instead of only checking boxes on a list. 

 

• Helps You Understand The Challenges

  To understand the challenges companies are currently facing it is essential to implement Database DevOps practices effectively. Many struggles with inefficient workflows that lead to slow build cycles, lack of visibility into release readiness, manual testing procedures and fragmented documentation across services and environments.

 

• Streamlines Processes And Tackles Challenges

  Database DevOps is a methodology that aims to shorten the time between database changes and their deployment into production. As Database DevOps continues to reshape the software development industry, developers are looking for ways to streamline processes and tackle challenges faster. It combines elements of both database and DevOps practices to help you develop applications more quickly, deploy changes more efficiently and monitor databases more effectively. 

 
Brace yourself as we are about to break the bubble of what the future of Database DevOps beholds. 

What Are The Future Trends Of Database DevOps?

Machine Learning (ML) and Artificial Intelligence (AI) are the breakthroughs in the domain of Database DevOps. Every business will want to extract some value from their data by monitoring, learning and using predictive analytics to their data. It will help companies to gain more insights from the data. Besides, it will help with consistent performance so that the models that businesses release and their data are helpful.

Another exciting news is the future is opening gates for DevSecOps. Wait, does that sounds too technical to understand? Put simply - it's a merger of DevOps and security. With all the security threats, breaches and risks running loose, it has become essential and protection regulations (like GDPR); security has become the focal point. It is anticipated that Database DevOps will be more involved with security and auditing aspects.
 

Summing It Up!

Congratulations! You reached your destination. In this article, we learned that Database DevOps integrates database services into the continuous integration and delivery processes that are critical components of DevOps. It involves using automation and monitoring tools to detect issues, proactively monitor performance and take measures to avoid future problems in production databases. With that, it's time to call it a wrap.