How is artificial intelligence – and its prominent discipline, machine learning – helping deliver better business insights from big data? Let’s examine some ways – and peek at what’s next for AI and big data analysis.
Why DevOps and cloud are essential to digital transformation
Many companies remain stuck in a bureaucratic quagmire that relies on the waterfall model of software development
The qualities that make the cloud so attractive – such as speed, agility, efficiency, and economies of scale – are particularly well-suited for the hyper-fast-paced and ever-changing digital business environment.
But harnessing the cloud for digital transformation isn’t as easy as it may seem. CIOs and the rest of the C-suite face a dual challenge – one technological, the other involving company processes, culture, and even organizational structure.
The first challenge is all about re-designing IT architectures to speed delivery of innovative products and services, improve market position, and create operational efficiencies. Complicating this effort are the older, purpose-built systems still in use in many enterprises that can’t simply be ripped out because they still service mission-critical needs.
The second challenge shares the same objective – speed and agility in the digital era – but centers on eradicating the slow, cumbersome ways of doing things that may be deeply embedded in the company’s organizational fabric.
Companies are often surprised to learn that the second can be the more formidable obstacle to a successful digital transformation.
A typical example: Digital transformations are increasingly being managed and consumed through cloud technologies as the public clouds make big strides in data protection and their ability to isolate tenants from one another for better security and performance. This convergence is giving enterprise IT greater choice in placing workloads and data where it makes most business sense, rather than being forced by technology considerations.
Yet many companies still operate in functional siloes within IT that run counter to the greater flexibility that the technology provides.
Take the development, testing, and deployment of new applications. Companies today can take advantage of the public and private cloud to weave new applications and services quickly and seamlessly.
However, many companies are still stuck in a bureaucratic quagmire that relies on the “waterfall” model of software development, in which a project flows downhill from development to testing to quality assurance to integration to production in sluggish, rigid stages.
The benefits of adopting DevOps
This is why DevOps adoption is so important to the digital transformation journey. By breaking down walls between development and operations, DevOps enables software to be developed in shorter cycles and deployed into production faster. But it requires a horizontal view of the organization that goes against decades of IT thinking.
What are the best ways to get started on DevOps?
First, IT leaders must be clear in their support for DevOps as an institutional standard while also evangelizing its value to gain buy-in from the techies in the trenches.
To give teams a good feel for DevOps processes and tools, CIOs should consider doing pilots with significant but non-business critical applications such as marketing sites, brochure sites, and short-lived campaigns. Through an iterative cycle of develop/deploy/retrospective-learning, companies can find their own rhythm, cadence, and best tools.
After the pilot period, the processes can be scaled up to go from non-business critical to mission critical. At this point, it is key to have a solid DevOps and operational automation strategy and implementation to ensure repeatable and reliable deployment pipeline processes.
Other cloud considerations
While CIOs need to tackle significant cultural and organizational challenges, leveraging the cloud for digital transformation also requires some crucial technology decisions.
For example, a complete, clear inventory of existing systems and processes needs to be done, and decisions made as to whether current applications and data systems: a) stay where they are and are maintained, b) are moved to cloud architecture and frameworks, perhaps through PaaS or other application tooling, c) sunsetted and retired, or d) re-implemented as cloud-native applications.
Orchestration automation is a valuable tool in allowing the existing systems to continue running seamlessly while investing development and operational resources toward the new or re-architected systems.
Cloud system management, orchestration, and automation tooling are increasingly allowing multiple data centers and disparate cloud infrastructures to be part of an overall enterprise IT solution. This is a great thing for enterprises because it gives them the governance, insight, and control they need to accelerate their business but will allow multi-sourced cloud solutions that prevent lock-in and provide pricing leverage.
By adopting the right approaches to the technology and bringing fresh thinking to organizational factors, CIOs can achieve great results by marrying two of today’s mega-trends: the cloud and digital transformation.