Community Blog DevOps and Multi-Cloud Management – Part 2

DevOps and Multi-Cloud Management – Part 2

Part 2 of this blog series discusses the challenges with DevOps and multi-cloud, enabling a full-stack DevOps pipeline, and managing it within a multi-cloud environment.

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.

Multi-Cloud DevOps Workflow

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.

In this blog, I will discuss the challenges with DevOps and multi-cloud, enabling a full-stack DevOps pipeline, and managing it within a multi-cloud environment.

Multi-Cloud and DevOps Challenge

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.

Starting With DevOps on Multi-Cloud – Right Now

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.

  • The very first step is always to assess what your organization requires and aspires to deliver. If your organization is already working with traditional DevOps solutions, figure out how your DevOps pipeline will change when using two or more private and public clouds.
  • The second step is to understand the upcoming expectations and why you have considered moving to a multi-cloud setup from a single provider setup. A diverse set of containerization scenarios, virtualization, and other processing scenarios have to be considered.
  • The third step is to identify the scope of your current tools used for continuous integration and continuous delivery and how well they can perform in a multi-cloud setup.
  • The fourth step is to remember Infrastructure as Code (IAC) and how well you can implement its tools to your multi-cloud DevOps solution.
  • The fifth step is to assess the current workflows for infrastructure management and understand the application components that constitute your solution.
  • The sixth step is to analyze how efficient your build code is and how well you can implement containers and microservices. If you are using a hybrid cloud model for your DevOps pipeline, you need to analyze the load distribution associated with your practice.

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.

Hybrid Multi-Cloud

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.

In the End - What Matters?

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.

Upcoming Articles

  1. Cloud-Native Application Management Like a Pro
  2. Managing Multi-Cloud DevOps Like a Pro
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