By Raghav K.
The escalation of the DevOps pipeline is the topic for today. DevOps evolved and made the industrial approach and new organization onboarding more persistent. Full-stack DevOps enables multiple scenarios with practices, including CI/CD, automation, security, testing, and infrastructure orchestration based on multi-cloud concepts.
By now, almost all cloud concepts include some form of hybridization. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and DevOps have opened up multiple possibilities for CIOs and IT professionals to implement and leverage high scalability and feature-full deployments with hybrid cloud and multi-cloud setups. DevOps has offered a different level of perspective to organizations that enable them to work with different solutions easily.
Many new initiatives are emerging that enable a full-stack DevOps workflow, including public and private cloud platforms. These initiatives showcase a lot of potential for the future but comprehending the current state of these initiatives would be jumping the gun. All multi-cloud initiatives are an infant state, and building large-scale enterprise solution requires more.
That doesn’t mean you need to wait to implement your DevOps solution based on a multi-cloud platform. Technologies and tools will mature and provide functionality that will extract value from your solution.
Multi-cloud is a part of the enterprise chain with DevOps. It is already a seasoned practice for organizations to leverage significant benefits of an optimized development to delivery process. The first challenge is to optimize multiple cloud provider services and standardize them according to the practice-set associated with one or many cloud providers.
The second challenge is toolchain optimization. Different DevOps tools continue to work in a multi-cloud environment since most cloud providers support open-source tool integration. Alibaba Cloud uses Kubernetes and Docker for containers, Packer for automation, and Terraform for Infrastructure-as-Code (IAC). However, multi-cloud requires an effective toolchain that can stabilize the distributed environment structure to provide a nest of operations.
Hundreds of remote applications and infrastructure models are the driving forces for multi-cloud. A common understanding suggests that more working components in a single derivation can clog the system and destabilize it with varying operational effectiveness. The integration of proper tools is necessary and comes with the highest recommendation to enable a functional CI/CD practice.
There is no better time to adopt a multi-cloud-based DevOps pipeline to enable continuous integration and continuous delivery (CI/CD) than right now. If you manage a DevOps pipeline, you need to enable development to deployment cycles that integrate testing and security within the pipeline. It is not as simple as following a plug and play option to deploy a DevOps solution.
You need to understand the multi-cloud architecture intricacies to accelerate the development cycle with DevOps. Resource hybridization, understanding containerization, and other fundamentals within your architecture and pipeline are important when adopting DevOps within multi-cloud.
After you have all of the necessary reports and performance graphs, you can start to consider cloud-native tools to build an automated DevOps workflow based on a distributed architecture like multi-cloud. You need to understand the extent of your code and work with AI-based machine-learning models to discover the potential of your multi-cloud-based DevOps solution.
Different solutions can work when implementing a multi-cloud setup. Today, cloud providers are offering standardized solutions that enable an organization to work through the most complex architectural systems to provide a seamless and unified experience. There is also an increasing use of serverless computing to enable Function as a Service (FaaS) scenarios, such as Alibaba Cloud Function Compute.
Similarly, container services, such as Kubernetes or Docker, are provided as a Platform as a Service (PaaS) solution. Enabling hybridization at this level can help your organization utilize container orchestration across different clouds. When I mention different clouds, I mean the combination of public-public, public-private, and so on.
Alibaba Cloud has developed virtualization 2.0 as a standard offering with its solutions. Using a hypervisor based on this technological upgrade enables an organization to deploy virtual machine images that work at an infrastructure level. Within an end-to-end multi-cloud DevOps workflow, machine images have to be managed and contained to represent a service or infrastructure that may be required to drive the multi-cloud-based DevOps pipeline efficiently.
When you begin to manage a multi-cloud-based DevOps pipeline, you will face challenges. It’s not because the technological framework isn’t in place; it is because the whole architecture is in its infant stage and will take time to mature. If you have requirements for expansion, you don’t need to wait for the technology to mature. On the contrary, you should adopt multi-cloud with your DevOps pipeline right away. Adopting as early as possible allows your organization to grow with the technology and to reap endless benefits in the future.
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