Book Image

Hybrid Cloud Infrastructure and Operations Explained

By : Mansura Habiba
Book Image

Hybrid Cloud Infrastructure and Operations Explained

By: Mansura Habiba

Overview of this book

Most organizations are now either moving to the cloud through modernization or building their apps in the cloud. Hybrid cloud is one of the best approaches for cloud migration and the modernization journey for any enterprise. This is why, along with coding skills, developers need to know the big picture of cloud footprint and be aware of the integration models between apps in a hybrid and multi-cloud infrastructure. This book represents an overview of your end-to-end journey to the cloud. To be future agnostic, the journey starts with a hybrid cloud. You'll gain an overall understanding of how to approach migration to the cloud using hybrid cloud technologies from IBM and Red Hat. Next, you’ll be able to explore the challenges, requirements (both functional and non-functional), and the process of app modernization for enterprises by analyzing various use cases. The book then provides you with insights into the different reference solutions for app modernization on the cloud, which will help you to learn how to design and implement patterns and best practices in your job. By the end of this book, you’ll be able to successfully modernize applications and cloud infrastructure in hyperscaler public clouds such as IBM and hybrid clouds using Red Hat technologies as well as develop secure applications for cloud environments.
Table of Contents (16 chapters)
Part 1: Moving to Hybrid Cloud
Part 2: Cloud-Native Methods, Practices, and Technology
Part 3: Elements of Embedded Linux

Developing a roadmap for successful cloud migration and modernization

The proper roadmap for cloud migration makes all the difference between successful and failed cloud transformation projects. This section will discuss the roadmap in depth and show how to define the roadmap for cloud transformation projects.

The roadmap needs to answer the following seven questions step by step:

  1. What is the final benefit of cloud migration?
  2. What is the current state of infrastructure?
  3. How do we collect information regarding the current state of infrastructure?
  4. How do we transform the collected information into a migration process?
  5. What are the different components (such as the delivery model, the service model, the maturity model, resources, and budget) of the cloud migration process?
  6. How do we execute the cloud migration process?
  7. What have we learned from the cloud migration process?

The answer to these questions is understood through the different stages of the cloud migration process, as shown in the following diagram:

Figure 1.13 – The different stages of the cloud migration roadmap

Figure 1.13 – The different stages of the cloud migration roadmap

The different stages of the cloud migration roadmap are described in the following sections.


The main goal of the Discovery stage is to identify the business goals and understand the current state of the workload. Sometimes, the business goal is financial or strategic. In addition, it is also necessary to determine the metrics to measure the success against the goal once the migration process reaches the operations stage.

Once the goal is identified, the next task is to determine the cloud migration approach for decision-making and data collection. There are two main approaches, referred to as top-down or down-top, for information-gathering and decision-making. In the top-down method, decisions are made by the chief technical officer (CTO) and other C-level executives. On the other hand, in the bottom-up approach, the individuals who own certain business functionalities that cloud services can implement make the decisions. The best-case scenario recommends that even in a top-down approach, the CIO collects information from individual business units and incorporates those decisions in their own decision-making. The next task for the discovery phase is to understand the current infrastructure. The following two stages, data collection and analyze, help fully understand the current footprint of the existing workload. First, however, the discovery phase initiates the process of identifying the candidate for migration, based on the following characteristics:

  • Architecture
  • Security
  • The cloud migration maturity model
  • Performance
  • Scalability
  • Strategic importance
  • Plans
  • The agility and diversity of IT operations

Data collection

At this stage, the necessary tools and methods are organized to collect information regarding the current state of the workload and the feasibility of achieving the business goal identified at the discovery stage. The platform, data, network tools, and technologies help collect data regarding the eight characteristics identified at the discovery stage. All functional and non-functional requirements for security, resiliency, HA, and so on are identified at this stage, along with the inventory information about the current state of the workload. All data is collected to answer the following questions:

  • What workloads can move to the cloud?
  • Where should workloads land on the target – private, public, PaaS, or CaaS?
  • What level of cloud enablement and modernization is required to move the workloads?
  • Where to start – identify the priorities for the overall collection period.


Data from the data collection phase is analyzed to understand the current state. The findings at this stage are also used as input for the next planning phase. Another important task at this stage is identifying the metrics for measuring success. At this stage, workloads are classified and suitable candidates or opportunities are identified. The main goal of the data collection and analysis stage of cloud migration is to identify the feasibility of cloud migration. The deliverables of the analyze stage are as follows:

  • Feasibility analysis: Identify all the essential data collected during data collection regarding the inventory of the current workload state, and all the business requirements and business use cases during the discovery phase to analyze the feasibility of cloud migration.
  • Dependency analysis: Identify all the dependencies, risk factors, and possible mitigation plans.
  • Workload classification: Categorize the current workloads into different classes. It is also essential to determine the priorities of a different kind of workload migration.
  • KPI identification: Identify all the KPIs to evaluate the cloud migration and optimize the cloud resources, and evaluate all the workload and target platforms on the cloud.
  • Governance standardization: Identify a standard method for processes, practices, policies, and procedures for the end-to-end project during the analysis of the cloud migration project.


Now that we understand the current platform, we need to plan for the cloud migration process. At this stage, the delivery model, service model, deployment model, maturity model, resource plan, and budget are planned and evaluated. Tools such as Cloud Advisor can prepare a perspective on modernization, combining tooling output and account team insights. These evaluations, as the outcome of Cloud Advisor, are used to review and align modernization outcomes with different evaluation metrics. In addition, the preparation of high-level business cases can provide measurement constraints for success evaluation. The main deliverables of the planning stage are as follows:

  • Design a runbook for test planning for each workload deployment.
  • Design a KPI evaluation plan.
  • Plan a business use case evaluation.
  • Plan resource optimization.
  • Plan cost optimization.
  • All risk factors and mitigation plans for different identified risks.


Once everything is planned and we have a descriptive view of the current platform, we start the cloud migration process. The cloud migration process must be agile and iterative. Therefore, multiple waves of the operation stage are executed iteratively. Each wave consists of six stages – planning, implementation, testing/validation, deployment to production, retrospective evaluation, and learning. Automation is the key to successful smooth operations for the cloud migration project. Cloud migration itself is a complex project. Manual operation is not suitable for such a complex project. Therefore, implementing automation for operations is the fundamental requirement for the success of cloud migration projects.


An overall governance method ensures standard processes, policies, practices, and procedures to optimize cloud resources. The core objective of governance is to establish a precise and structured definition for change, policy, resource, incident, and security management. In addition to the resources and workload governance, it is also essential to establish cultural and collaboration practices and methodologies to ensure overall success.


It is essential to evaluate the roadmap of the cloud migration process continuously. Then, based on the evaluation metrics for success, the roadmap of the cloud migration process is updated. The Learn stage is responsible for running the evaluation of the roadmap of the cloud migration process and providing input to any other stage, such as the discovery and planning of the roadmap. At this stage, one of the essential activities is to optimize the target platform on the cloud.

Cloud migration is a complex problem, and it requires a substantial amount of effort and budget. Therefore, cloud migration needs to be well defined, using best practices and suitable migration patterns. At the same time, it is also essential to be aware of different misconceptions regarding cloud migration. Therefore, the following section will discuss some common misconceptions about cloud migration.