Load Balancing Multi and Hybrid Cloud Solutions

Load balancers are a fundamental component in any distributed application architecture. In this course, you'll explore what load balancers do and where they are used. Then, you'll discover how they have evolved into modern day application delivery controllers. You'll learn about the different types and features available in modern load balancing solutions. You'll then move on to explore standard network topologies that incorporate load balancing, as well as how to effectively introduce Layer 4 and Layer 7 load balancers. You'll learn how a load balancer in the cloud can vary from on-prem and examine load balancing across different cloud platforms. Finally, you'll learn how to deploy both a Layer 4 and a Layer 7 cloud-native load balancing solution on the Microsoft Azure platform.

Understanding design theory, network design, and how load balancers work is critical to an effective network deployment. In this course, you'll learn about design theory and how to apply it to build a reusable patterns. Then, you'll explore network design concepts and methods, where you'll examine how an enterprise network is structured for maximum efficiency. Next, you'll move on to learn about where a load balancer fits into the network architecture. You'll explore capacity planning and how to right-size your load balancer deployments, as well as considerations and best practices for load balancer deployments. Finally, you'll explore the methods and algorithms used in load balancing.

The cloud brings many opportunities, but it also brings challenges to network design and operational workload placements. In this course, you'll learn about the private, public, hybrid, and multi-cloud models. You'll explore the challenges and opportunities of adopting the cloud and how to plan for a migration. Next, you'll examine design patterns, architectures, and topologies of cloud deployments, as well as best practices to use when selecting a topology. You'll explore options available for DNS routed load balancing across data centers. Finally, you'll learn how to design a cloud architecture and how to incorporate load balancers for various stages of data flow.

As multi-cloud and hybrid cloud architectures become more popular, solutions such as service mesh promise to integrate widely distributed services. Today's cloud technology professional benefits from a well-rounded understanding of session management in multi-cloud and hybrid cloud environments. In this course, you'll learn how sessions are maintained in load balancing scenarios using sticky sessions, and what the benefits and challenges are of sticky sessions. You'll then explore best practices for load balancing in multi-cloud and hybrid cloud scenarios. Next, you'll examine common techniques for managing session information, including the JSON Web Token-based session management technique used by most cloud solutions. You'll learn the fundamentals of multi-cloud and hybrid-solutions, as well as how identity is managed in both multi-cloud and hybrid environments. Finally, you'll explore some modern strategies for identity management in multi-cloud and hybrid cloud environments, including service mesh and identity fabric.

Securing a private data center has its challenges but it is made easier by the fact that single data centers are centralized. Cloud systems, on the other hand, expose a much larger risk surface, and this surface is only larger and more complex for multi-cloud and hybrid cloud environments. Today's cloud engineers and operators require more advanced knowledge of risk factors that are specific to various cloud configurations. In this course, you'll learn about cloud security challenges, vulnerabilities inherent in moving your organization to the cloud, and how to tailor operations in the cloud for resiliency. You will learn to create a virtual network in the Azure environment. You will also discover some of the repercussions of security failures in the cloud. Finally, you will learn about cloud backup and disaster recovery.

Data management has added complexity in today's multi-cloud and hybrid cloud architectures. Furthermore, managing compliance with data privacy is increasingly difficult. In this course, you'll learn the challenges of data privacy in multi-cloud architectures. You will also learn challenges and strategies for data protection in a hybrid cloud, including maintaining data integrity and availability and planning for disaster recovery. Then you will learn how security is maintained in a hybrid cloud environment. Finally, you'll learn about multi-cloud authentication and federated cloud.

Final Exam: Multi-cloud Load Balancing Principles will test your knowledge and application of the topics presented throughout the Multi-cloud Load Balancing Principles track of the Skillsoft Aspire Load Balancing Multi and Hybrid Cloud Solutions Journey.

Traditionally, disaster backup and recovery involved backups being stored on special hardware such as tape and in multiple off-site locations. Disaster recovery often involved manual intervention and downtime. With cloud and multi-cloud configurations, new techniques take advantage of scalable resource, load balancing, and failover for easier replicated backup and disaster recovery while maintaining business continuity. In this course, you'll learn the history of disaster backup and recovery, both prior to the cloud and relating to cloud and multi-cloud. You'll learn how responsibilities are managed for disaster backup and recovery in the cloud, as well as how various large public cloud providers manage data backup. You'll explore how to configure disaster backup for the various public cloud providers, challenges of implementing cloud disaster backup and recovery, and application load balancing with multi-cloud. Finally, you'll learn how load balancing applies to data backup and recovery and contrast this with application load balancing.

Docker Swarm provides all the tools necessary to spin up Docker Swarm clusters with relative ease. It is also readily available, being integrated directly into Docker Engine, which means Docker itself now provides orchestration. Docker Swarm's routing mesh networking model is excellent. But it lacks availability, visibility, security and control that more complex, production deployments require, so some help is needed to fill in the missing components. In this course, you'll explore Docker components and objects, as well as how Docker deployments differ from traditional deployments, with a focus on the microservices architecture afforded by Docker's container technology. You'll also learn how microservice architecture has changed load balancing deployments. Next, you'll investigate fully versus self-managed cloud services, Docker load balancing scenarios including Docker Swarm, NGINX open-source load balancing, and using an external edge router in a Docker Swarm cluster. Finally, you'll learn how to install Docker and configure load balancing for various example scenarios.

Kubernetes is the de facto standard orchestration technology for containerized workloads. The Kubernetes networking model is implemented using network plugins that adhere to the Container Network Interface specification designed for interoperability. In this course, you'll explore Kubernetes clusters and examine the various components and objects that make up a typical Kubernetes cluster. You'll explore the challenges commonly encountered with Kubernetes load balancing scenarios and Kubernetes services. Next, you'll learn to analyze how Kubernetes networking and services incorporate load balancing and how Kubernetes Ingress integrates load balancing in various real-world scenarios. You'll learn how to work with real a Kubernetes cluster by installing and then bootstrapping a real Kubernetes cluster. Lastly, you'll gain experience with network traffic management in Kubernetes by configuring Pod distribution, applying network policies, and configuring Kubernetes Ingress.

Different scenarios require different types of load balancers and there are various vendors available for each type. It is beneficial to know how the various load balancer providers compare when planning a cloud-based architecture with load balancing. In this course, you'll learn about the benefits and limitations of the different types of load balancers, including hardware, virtual, and cloud-based. You'll explore the features and technologies provided by the various load balancer vendors and how they compare with one another. You'll also examine the different types of cloud-based load balancers available. Finally, you'll learn about the role of failover in cloud architectures and how it relates to load balancing.

The complexities of multi-cloud environments can make it difficult to monitor and manage performance. Multi-cloud experts need to be able to monitor multi-cloud performance as well as tune that performance via strategies such as load balancing. Learn more about the importance of performance monitoring through this course. Examine performance challenges faced when moving to multi-cloud and how to monitor performance in a multi-cloud environment. You'll discover how load balancers can help manage performance, the performance data that can be gathered from a multi-cloud load balancer, and how to mitigate multi-cloud overload. This course will also help you delve into important load balancer metrics, configuring Azure Traffic Manager for geographical load balancing, and using Amazon Cloud Watch to monitor and publish metrics. After completing this course, you'll have a solid grasp of the basics of monitoring and managing consistent performance and load balancing across clouds.

Final Exam: Solutions for Multi-cloud Load Balancing will test your knowledge and application of the topics presented throughout the Solutions for Multi-cloud Load Balancing track of the Skillsoft Aspire Load Balancing Multi and Hybrid Cloud Solutions Journey.