Throughout history, the worlds of business and commerce have been subject to revolutions that dramatically alter how they function. From the industrial revolution in the 18th century to the computer revolution in the 60’s we have examples of organizations that adapted to their changing environment and were able to thrive. Those organizations that weren’t able to adapt were left behind and vanished into the annals of history.
In our current era, we have access to tremendous computing power through public cloud providers. Technology connects us in ways previously thought impossible, and we found ourselves at the dawning of a new and exciting digital age. As in the past, organizations that adapt will thrive, and those that don’t will lose their market share and face extinction.
The term digital transformation describes the process companies need to navigate to adapt. Unfortunately, not all digital transformations are successful. The evidence indicates that an organization is more likely to fail in this endeavor than to succeed. This article will examine the factors that can determine if a digital transformation is successful or not. We’ll take a closer look at using a DevOps approach to digital transformation and the importance of DevOps tools in that approach.
Successful digital transformations take dedication, hard work, and discipline. The organization needs to commit to the process and believe in future success. The transformation starts with a clear vision and commitment from the executive leadership team. Transformation leaders are selected and empowered to enact change, introduce new practices, and adapt as needed. The strategy can involve selecting high-performers in each area to investigate and implement new processes and then disseminate them and change their teams’ culture. Processes evolve alongside a culture of experimentation, agility, and adoption of continual improvement.
Digital transformations generally fail due to a lack of commitment and a lack of flexibility in implementing the changes. An organization might make the changes in some parts of their organization and not in others. They might attempt to change processes without addressing the corporate culture, and failing to change the collective mindset of those who support the day-to-day operations.
A digital transformation involves a lot of risk and a lot of coordinated changes. It requires flexibility and agility. One path that many organizations have used to succeed in their endeavors is using the Agile software movement and DevOps principles.
DevOps is a new way of thinking about developing and supporting software. DevOps breaks down the traditional silos of development, quality assurance and operations, and forms new teams. These teams then own applications and services, – from the design process to deployment, monitoring, and support. DevOps teams typically operate within an agile framework, whereby small units of work are identified and developed within short timeframes. This approach allows teams to deploy new changes rapidly and easily pivot to new business requirements as needed.
Because of the unique combination of skills required to be a DevOps engineer, DevOps teams must have a reliable set of tools and utilities to support their efforts. This support infrastructure utilizes automation and various data sources to test and validate software through the development process. It continues as the applications are deployed and used by consumers, within the organization and externally.
At the core of a successful DevOps, the toolset can gather and analyze data programmatically. The DevOps process produces data in many forms. Data sources can include, but aren’t limited to:
The testing and code analysis results are essential during the build, package, and deployment phases of an application or service. After deployment, the application and system logs and the performance metrics are critical for a concept known as observability. Observability is the external analysis of metrics from a system that provides insights into the health and the performance of that system. Log aggregation and management is another invaluable component that is closely related to observability. Especially in distributed systems, managing logs and metrics from a central control plane is critical.
Log management systems go beyond just aggregation and management. Many modern systems employ machine learning and artificial intelligence to identify anomalies within the system. They provide early warning of degraded performance or error states within the application. These systems are also essential when deploying a new release to ensure that agreed-upon levels of services and functionality are maintained.
Finally, your teams should be able to adopt and use these tools with ease. Adopting a self-service model whereby teams have access to on-demand training and documentation, can easily integrate the tools into their processes imperative to this strategy’s success. The guiding principle is to provide tools and reduce any friction related to DevOps teams’ use.
The DevOps tools’ features that make them effective can be applied to your organization as well. Just as the tools use data as a basis for their decisions, your teams use data to inform their decisions. Data-based decision-making is a crucial part of any digital transformation.
DevOps tools also reduce friction by automating repeatable processes to make them consistent and more efficient. The end goal of a digital transformation is to automate repeatable tasks and improve their efficiency and speed. Automating processes frees your most valuable asset – your people – and allows them to focus on exploring creative and unique ways of solving problems and continuing to revolutionize your business practices.