by Tony Harris • November 25, 2020
Today’s business world is relentless, and competition is intense. The digital landscape is continually shifting across many industries, creating an unprecedented demand for companies to innovate, experiment, and deliver capabilities faster. A robust digital transformation process speeds up business activities, competencies, and models while providing as much value as possible to customers. However, organizations must be cautious in their digital investment strategies. Technologies can become obsolete overnight. A successful digital transformation strategy should design a system capable of hot-swapping technologies at will and avoid vendor lock-in.
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In this article, we’ll cover some key components of a successful digital transformation journey, including:
Adopting a Collaborative Culture
DevOps as a component of Successful Digital Transformation
Best API Management Solution For Successful Digital Transformation
Development and operations are at the heart of modern business innovation. They must continually release new features while fighting hindrances caused by technical debt and legacy code – not to mention maintaining service level agreements with two or three nines.
In a DevOps environment, the entire team is responsible for delivering both new features and stability. The traditional approach of developers firing code over the wall to operations is not compatible in highly collaborative environments. In a collaborative culture, responsibilities are equally balanced, with procedures to ensure both teams have insight and visibility into application performance.
Teams need to build stable, long-lasting relationships by instilling trust, empathy, and team psychological safety. Team members need to promote effective communication, dialectical understanding, and recognition of peers – this builds community, inherently strengthening engineering effectiveness throughout the development and release cycle and supports the wider successful digital transformation agenda.
The tools and processes associated with DevOps enable software teams to deploy stable and reliable code faster and more frequently. According to DORA’s 2019 report, elite DevOps teams deploy code 208 times more often than low performers. Elite teams deploy code more frequently, have a faster lead time for changes, lower change failure rates, and quicker recovery speeds – adopting this culture will invariably force your team to implement a digital transformation in the most efficient route possible.
Cloud: The centralized nature of cloud computing environments facilitates a standardized and centralized platform for DevOps automation pipelines – resolving many of the issues inherent in centralized software deployment due to the distributed nature of enterprise systems. Additionally, most DevOps tooling is cloud-centric. Most providers have baked in tooling with batteries included – this lowers the cost associated with on-premises DevOps automation technology and provides centralized governance.
Infrastructure as Code: Infrastructure as code is a methodology for infrastructure automation based on software development practices. It encourages consistent, repeatable routines for provisioning and changing systems and their configuration, reducing developers’ need to manually provision and manage servers, networking, operating systems, database connections, storage, and various other infrastructure elements. It is possible to represent and manage the system in textual format (usually YAML) within a Version Control System (VCS), such as git. These files can be Ansible playbooks, Chef recipes, or Puppet manifests or used by DevOps tools like Terraform and Kubernetes to automatically provision and configure build servers, testing, staging, and production environments on the fly.
Continuous Integration and Continuous Delivery: Continuous Integration (CI) is the software development practice of regularly integrating code changes into a shared code repository. Once developers push code to the repository, an automatic build process triggers. In most cases, the build produces a docker image that is ready for deployment. Typically developers will push code to the repository several times per day, triggering several builds. Usually, a CI pipeline builds the image and then runs integration tests on the image before signing it off as a green build. Fewer bugs get shipped to production as regressions are captured early by the automated tests. Testing costs reduce drastically as the CI system can run hundreds of tests in a matter of seconds.
Continuous delivery allows a team to release green builds with the click of a button rapidly. In short, Continuous delivery provides an automated delivery pipeline in support of successful digital transformation. In practice, the pipeline automatically deploys green builds to a development environment. After an incubation period on dev, it will progress to staging, and usually, production deployments need to be manually signed off by lead devs. The release cycle complexity reduced significantly; teams don’t have to spend days preparing for releases. The automated pipeline has built-in circuit breakers and protection mechanisms, reducing cognitive load for devs resulting in a faster iteration process.
And of course, Continuous Testing is not possible without the technical path carved by Continuous integration and continuous delivery integration. Implementing automated tests as part of the software delivery pipeline to obtain feedback on the business risks associated with a software release is as rapid as possible.
Rapid digital transformation does not always coincide with robust security practices. InfoSec teams struggle to keep up with rapid code changes; there is usually not enough time for granular code reviews. Unfortunately, rapid deployment can result in poor security hygiene among developers (insecure code, inadvertent vulnerabilities, misconfigurations, hardcoded passwords, etc.) – further aggregated by cloud environments’ inherent openness. DevOps teams utilize new, open-source, and often immature tools to manage hundreds of security groups and thousands of server instances. Misconfiguration errors and security malpractice, such as sharing secrets (APIs, privileged credentials, SSH keys, etc.), is somewhat inevitable and can quickly propagate, causing widespread operational dysfunction or numerous exploitable security and compliance issues.
Optimally, security process should be automated to mitigate against this and to enhance the overall prospects of a successful digital transformation. DevSecOps stands for development, security, and operations. The methodology automates the integration of security at every phase of the software development lifecycle, from initial design through integration, testing, deployment, and software delivery.
Automated security tools for code analysis, configuration management, patching and vulnerability management, and privileged credential/secrets management are crucial. The following is a list of a few techniques you can utilize to become secure.
Docker Image Scanning: Container images have become the standard application delivery format in cloud-native environments. The wide distribution and deployment of these container images require rigorous inspection to validate their integrity. Two robust tools are JFrog X-ray, a universal software composition analysis (SCA) tool, and Clair, an open-source tool that utilizes static analysis to discover vulnerabilities in appc and Docker containers.
Dependency Scanning: Dependency Scanning helps to find security vulnerabilities automatically (e.g., Heartbleed, ShellShock, DROWN attack )in your dependencies while developing and testing your applications. Vulnerabilities in subcomponents often occur when using outdated versions, which may lead to security problems and breaches. For example, the Equifax breach.“Using Components With Known Vulnerabilities,” is now on the Open Web Application Security Project (OWASP) top 10 list of the most critical web application security risks. Snyk, Gitlab, and OWASP have great solutions to get your started.
Secrets Management: Sometimes, the most straightforward security solutions are the most effective. As the IT ecosystem increases in complexity and the number and diversity of secrets explode, it becomes increasingly challenging to store, transmit securely, and audit secrets.
Secrets may include the following:
There are many solutions out there, and it depends on the nuances of the organization’s infrastructure setup; the following are a few recommendations.
Roy Fielding’s dissertation in 2000 proved to be the birth of the modern web APIs movement – his introduction of the Representational State Transfer (REST) architectural style for distributed hypermedia systems changed everything. An API is a set of definitions and protocols for building and integrating application software and enabling your services to communicate with other services in a black-box manner – simplifying app development. The following are several benefits of using APIs.
API management refers to the process of administering these mechanisms to ensure they are adequately developed, deployed, stored, updated, and controlled. API management also pertains to collecting and analyzing usage statistics to report upon and improving performance and is a key enabler to successful digital transformation.
There are many API management solutions on the market. Your choice depends on the organization’s specific and nuanced set of circumstances. The following questions should help your decision-making process.
These questions will help you identify the solution that best suits your needs, both now and in the future. Of the solutions listed above, DreamFactory is perhaps the best all-rounder. With DreamFactory, you can instantly create functional, documented APIs for any data source. Simultaneously, the broad range of integrations allows you to work with almost any data source or authentication service. Try DreamFactory for free today.
Related reading: 5 Digital Transformation Trends for 2021
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