When it comes to rapidly and reliably developing digital innovations, few paradigms have proven more effective than DevOps. Since the term’s inception in the late 2000s, it has become the most common approach to product development. In the Middle East, researchers project that the Agile and DevOps services market will grow at a CAGR of 14.2 per cent from 2024 to 2031. This is set against the backdrop of new speeds and scales of DevOps evolution, with the latest iteration including AI-assisted coding and platform engineering.
AI’s recent advancements have also brought other IT domains into focus. And with the reliability of a model’s outputs heavily reliant on high-quality inputs, the key among these has been database operations. Unfortunately, many organisations have data that sits in silos and/or can be hard to track down.
Opportunity is present at the nexus of these two paradigms, and businesses can arm themselves with an IT edge by combining DevOps and data management, ultimately creating a Database DevOps framework.
The dovetailing of DevOps and Database operations
The goal of almost every DevOps framework is to streamline the production and delivery of each software product. Unfortunately, the acquisition, storage, and accessibility of large amounts of data can become complex and create a roadblock to speedy software development processes. As a result, teams tend to ignore the integrations of database operations into their developer workflows.
These aforementioned complexities usually materialise because DevOps processes lie solely at the feet of developer teams — with little to no input from requisite database experts. In fact, certain organisations lack the talent to contribute to this database expertise. This creates gaps in the ability to manage data. As a result, developers, and other personnel in the product supply chain, have little visibility into the data necessary for product development.
Poor data management doesn’t only affect companies during software development. Even after a product is released, a lack of quality data operations can cause applications to run slowly, create performance bottlenecks, and prevent the ability to scale software tools. The key to better software development and better database management is the removal of silos between the two functions. The best way for this to happen is with database observability.
Observability: Key to dismantling the DevOps/Database divide
With the right database observability solutions, database personnel can see the root cause of poor data quality, application issues, and suboptimal database performance. Once database experts can view the systems in their remit, they’ll be better prepared to offer help to software development personnel and combine DevOps practices and workflows into data management. From there, organisations will experience multiple benefits.
Greater agility and flexibility become possible as data management teams can automate database provisioning, configuration, and deployment, much like how automation enhances coding and software development. This streamlines improvements to data infrastructure and facilitates the seamless implementation of new software features.
The risks of downtime and human error are significantly reduced when database operators leverage continuous integration and continuous delivery (CI/CD). With a robust observability tool in place, they can test software deployment adjustments with minimal risk of data loss or service disruption.
Stronger collaboration across teams is another key benefit. Developers, operations personnel, and database administrators gain visibility into one another’s processes, reducing the likelihood of one team making changes without others being aware. This transparency minimises confusion about how modifications in coding or structure impact overall workflows, fostering a more cohesive approach to problem-solving at both the development and delivery stages.
Security is also strengthened when the database and DevOps practices are combined. As databases grow, incorporating security checks and enforcement mechanisms ensures that companies can effectively protect their data and maintain rigorous privacy measures.
The potent pairing of Database Management with DevOps
Effectively combining database management and DevOps will be the only way organisations can handle the massive amounts of data necessary for the future of innovation. With analysts predicting continued investments in artificial intelligence technology, databases must be prepared to handle terabytes — if not petabytes — of data as they implement new solutions. Through a comprehensive observability approach, organisations will be able to create a Database DevOps function that creates and ships better code, fortifies IT infrastructure performance, and maintains the data quality necessary to power modern business initiatives.
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