We know that open source is well established as the place where software innovation happens. Today enterprises are looking at open source even more closely for pro-active, adaptive and innovative technologies to deliver better customer experience. As we move into 2019, we see open source technology further making its mark in some of the key trends we are already experiencing.
Software Defined Approach to Data Management
Industrial IoT, smart cities and wearables are bringing together and producing more sophisticated data than ever before. While the proliferation of data is nothing new, the volume of unstructured data and the way in which it is managed is. Additionally, many enterprise IT teams are moving to hybrid-environments that have on-premise systems and cloud environments, creating additional challenges for these teams. In 2019, more companies will adopt software-defined storage (SDS) to address the performance and availability challenges caused by the data explosion.
Public Cloud for Industry-Specific Needs
Many industry leaders predicted that the public cloud landscape would diversify at a quicker pace this year, but the sheer size of the main players is making it difficult for newcomers to find space in the market. Additionally, the rapid innovation taking place with large US public clouds providers has made it challenging for others to compete. Providers are starting to focus more on verticals with specific industry regulations, such as streaming companies and the telecoms industry. The trend of niche providers with vertical expertise will continue in 2019, as well as regional cloud providers.
Machine Learning and Open Data
In 2019, we will see the adoption rate of Machine Learning (ML) increase but at a measured pace so that companies can focus on implementing the technology in a way that improves business processes and delivers tangible results. A more cautious implementation also allows for the cultural shift to happen, giving IT and business professionals alike a chance to embrace these next-gen solutions.
However, without access to sufficiently large and diverse amounts of data, ML can’t fully succeed. While open source has been recognized for its flexibility and interoperability of technologies to accelerate innovation, the data on the other hand hasn’t shared the same benefit. This year, we will see the concept of ‘open data’ emerge as a way to share and aggregate data. Projects such as the Community Data License Agreement (CDLA) – a development announced by The Linux Foundation – are currently underway and encourage organizations to share data openly and transparently. CDLA will be a key enabler of data sharing that can be used to accelerate the accuracy and use of machine learning.
Security at Developer Level
Security has become a central requirement for most IT professionals, a trend that will continue to grow essentially. As an industry, we’ve realized that security should lie at the heart of any digital transformation initiative and should never be an afterthought but built-in by design. From the beginning through to completion, it should infiltrate every part of the project. The code should be secure, as well as the design and processes. DevSecOps should be applied for applications as well as the cloud, infrastructure and work with partners. Education around security will continue to be vital, especially with human error continuing to be a major security threat. Organizations will look to create more security ambassadors this year who can advocate for employee awareness around the individual role in overall security.
Peter Lees, Chief Technologist, SUSE Asia Pacific authored this article.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends.