Virtual Elephant

The Impact of Cloud Architecture on DevOps Adoption

DevOps is a software development methodology that enables organizations to deliver software updates quickly and reliably. This article explains the role of cloud architects in enabling the adoption of a DevOps model and provides best practices for successful implementation as well as organizational changes to ensure companies can be successful.

DevOps and Cloud Architecture Overview

Cloud Architects help organizations to design and implement a scalable and secure cloud infrastructure that can support the demands of continuous development. The DevOps model should focus on seven core functions:

  • Collaboration and communication
  • Automation
  • Continuous delivery and deployment
  • Measurement and feedback
  • Experimentation and learning
  • Lean principles
  • Security

DevOps is a software development methodology that combines the traditional roles of Development with Operations. The purpose of combining these traditionally separate teams and organizations within a company is to drive improvement of the applications, by focusing on increased speed, quality, and reliability of software delivery. An organization will typically adopt the DevOps model to bring development and operations teams together to collaborate and communicate more effectively, and adopt a culture of continuous improvement.

When DevOps and cloud architecture are combined, the result is a more efficient and streamlined software development process. The use of cloud infrastructure, either within an organizations own data centers, or through the use of a public cloud provider, should enable more efficient processes around automation and scalability, thus increasing the delivery of software and applications. By integrating DevOps principles and practices into cloud architecture, most organizations will need to transform their typical siloed organizational structure to build a new culture of collaboration and continuous software and infrastructure delivery. This transformation can be painful for larger organizations where fiefdoms exist, as it often requires significant changes to management structures or org charts within a company.

DevOps Adoption Challenges

Adopting a DevOps model within an organization can be a challenging task, as it requires a significant shift in the way teams work, communicate and collaborate. The top three areas where I often see organizations struggle with adopting DevOps, include:

  • Siloed Teams: The absolute biggest challenge organizations face when adopting DevOps is breaking down the traditional silos between development and operations teams, as well as the silos that often exist within an IT organization (i.e. storage, compute, and network). This can result in a lack of collaboration, with each team working in isolation without proper coordination.
  • Resistance to Change: Working hand-in-hand with the siloed teams, oftentimes groups within the development and operations team resist efforts to change. This can be a result of historical “us versus them” mentality, long tenures within the organizations, or managements lack of willingness to give up control of their fiefdoms. Employees, both individual contributors and management, often resist change because they are comfortable with the existing ways of working.
  • Skills Gap: Adopting DevOps requires employees to have new and different skill sets, such as automation, testing, and continuous delivery. Operations teams, especially where hard lines of delineation existed previously, will be require to learn skills traditional outside their are of expertise. For example, a network engineer will need to learn about the skills the storage engineer and vice versa. It is important to remember, when adopting the DevOps model, it isn’t required for each employee to become a subject matter expert in every discipline, but there is an expectation they will expand their knowledge base to at least better understand all of the components and technologies within their DevOps model.

When organizations on solving those top three potential landmines when moving towards a DevOps model, their chances of success increase dramatically. In addition to the top three issues above, there are several other areas when organizations need to focus on as well, including:

  • Lack of Automation: Many organizations struggle with automating their software delivery pipeline, which is a critical component of DevOps. Alongside the issues with automation for software, operation teams often lack automation for building out new infrastructure. Infrastructure-as-Code (IaC) can assist operations teams in the automation of building scalable infrastructure. A lack of automation on both fronts, will lead to manual processes that are time-consuming and prone to error.
  • Technical Debt: DevOps emphasizes the need for continuous delivery and deployment, which can lead to an accumulation of technical debt. Over time, technical debt refers to the cost of maintaining a system, potentially increasing maintenance costs, decreased performance, and lower quality of software. Organizations need to prioritize reduction of technical debt alongside new feature and feature enhancements when planning releases.
  • Lack of Metrics: DevOps relies heavily on data and metrics to track performance and identify areas for improvement. Organizations need to identify the correct metrics, which will lead to better decision-making, as it will be based on correct and complete information.
  • Security Concerns: Because of the fast-paced nature of the DevOps model, which emphasizes speed and efficiency, this is oftentimes at odds with security considerations. Organizations need to find ways to make sure security is a focus within the DevOps teams and given equal priority to speed to ensure the safety of their systems and data.

By taking a structured and thoughtful approach to DevOps adoption, organizations can reap the benefits of improved collaboration, reduced errors, and faster delivery times, while ensuring their employees learn the technology skill-sets of tomorrow.

Cloud Architecture & Infrastructure-As-Code

A cloud architect should leverage Infrastructure as Code (IaC) as a key component of a DevOps transformation by incorporating it into their cloud architecture strategy. In IaC, infrastructure is treated like software and is managed through code, rather than manual configuration. This allows for automation of the entire infrastructure setup and management process, from provisioning to configuration management and deployment. In a DevOps context, IaC enables development and operations teams to work together more effectively and efficiently by making infrastructure setup and management a repeatable, automated process.

Each of the major cloud providers have tools or products to facilitate the adoption of Infrastructure as Code within your cloud architecture:

  • VMware: The VMware Cloud Foundation (VCF) platform has been designed to day one to assist cloud architects in adopting Infrastructure as Code within the private cloud data centers. VCF leverages IaC by providing a programmatic interface for deploying and managing the platform and its components. The SDDC Manager interface can be used to automate the entire process of building and managing infrastructure, including the deployment of virtual machines, storage, and networking. The SDDC Manager helps to ensure consistency, reliability, and repeatability in the infrastructure deployment process and reduces the risk of manual errors.
  • AWS: AWS CloudFormation provides a service which uses templates to enable infrastructure to be defined as code. The service allows organizations to model and setup their AWS infrastructure, including virtual machines, storage, and networking. The templates support both JSON and YAML. In addition, AWS also provides the AWS CLI to facilitate the same automation through a command-line interface.
  • Azure: Azure Resource Manager allows organizations to define, deploy, and manage Azure resources using templates written in JSON. These templates, similar to the AWS CloudFormation templates, allow the deployment and management of Azure resources, including virtual machines, storage, and networking.
  • GCE: Google Cloud Deployment Manager allows organizations to define, deploy, and manage Google Cloud resources using templates written in YAML. Once again, the service is similar to both AWS CloudFormation and Azure Resource Manager, in that it allows the configuration of virtual machines, storage, and networking within Google Cloud.

As a cloud architect, we should be playing a crucial role in our organizations efforts in enabling development teams to adopt continuous deployment through the use of Infrastructure as Code. Our guidance and expertise in cloud infrastructure, security, and operations, should be of paramount importance to our organizations and their efforts to move applications to the cloud. As described above, there are various tools available with each major cloud provider, it is our responsibility to determine which tools and cloud providers will help our organizations be successful based on the business and technical requirements.