DevOps, a cultural and technical approach that emphasises collaboration and automation between software development and IT operations teams, has become a cornerstone of modern software development. While the advances of DevOps are evident and established as we enter 2024, its implementation is not without challenges, experienced by many organisations today. In this insight blog, we’ll explore the key challenges faced whilst embracing DevOps and the strategies to overcome them.
Cultural Transformation
As with many concepts discussed within the data space, DevOps is as much about cultural change as it is about tools and processes. One of the foremost challenges is fostering a culture of collaboration, communication, and shared responsibility across traditionally siloed development and operations teams. This is impacted heavily by the size of the organisation, and how much legacy it experiences, but overcoming resistance to change and ingrained practices requires leadership commitment and continuous communication. It’s one of the biggest challenges any data function faces and requires budget and strategic attention to course correct.
Integration of Automation
Automation is a fundamental tenet of DevOps, facilitating faster and more reliable software delivery. However, theory and practice can often be two very different sides of the same coin; integrating automation into existing workflows can be extremely challenging.
Many organisations struggle with the automation of old legacy systems, and manual processes, and ensuring that automated processes are consistent across the entire development pipeline. There is the real risk that you implement a change in one area, and down the stream, you cause a huge issue that could potentially be very harmful to another part of the business or process. For many organisations, there is no “quick fix” when it comes to automation integration on a more macro scale, but rather quicker wins on a user-case level, which can then be deployed more widely.
Toolchain Complexity
The DevOps landscape is filled with a plethora of tools for different stages of the development lifecycle. Go into any conference or data expo and you will see row after row of vendors selling the latest tech, it can feel like quite the minefield. Selecting, integrating, and maintaining an effective toolchain that aligns with the organisation’s goals can be overwhelming and extremely daunting; not to mention you then have personal preference from the data engineers using the tools (circle back to cultural transformation challenges!)
Organisations and their data teams may face challenges in ensuring that tools work seamlessly together and that the team is proficient in their use. A tool that is only used for part of its capability is never going to experience its full ROI. The practical functionalities of the tools must of course be considered alongside the cost of purchasing, maintaining, and renewing the tool as well. Just as there is a wealth of tools available, the price tags that accompany them can also be vast, too.
Continuous Testing
Ensuring the quality of software in a fast-paced DevOps environment requires continuous testing. Organisations often face challenges in implementing automated testing at every stage of the pipeline, from unit testing to integration testing and user acceptance testing. There will always be a negotiation between balancing the need for speed with comprehensive testing. We all want to rush towards production with the latest product but without continuous and rigorous testing we run the risk of running into bigger challenges than predicted, and in some cases offering only Band-Aid solutions. This challenge isn’t unique to DevOps, it’s experienced all over the data spectrum with other issues such as Privacy by Design, Data Governance, and Management – Businesses will always be in a rush, and after all, it’s how they stay competitive.
Scalability
DevOps practices are required to scale as the organisation grows, and this can be a significant challenge, naturally. Scaling DevOps involves not only accommodating the increasing number of teams but also ensuring that processes, tools, and cultural practices scale seamlessly. Managing this growth without sacrificing efficiency is a permanent concern. Scale too fast and you risk losing data talent and losing touch with the current processes, scale too slow and you risk missing out on business opportunities and a loss of potential revenue. There is a Goldilocks solution for most organisations, but it’s a very difficult balance to maintain.
DevOps is a transformative approach that empowers organisations to deliver high-quality software faster and more reliably. However, its implementation comes with its fair share of challenges. Organisations must navigate these challenges with a strategic mindset, emphasising collaboration, automation, and continuous improvement. By addressing these hurdles head-on, businesses can unlock the full potential of DevOps and stay competitive in today’s dynamic technology landscape.
