So far in this chapter, we have concentrated on the application side to ensure IT reliability. But there is a crucial role to play by the underlying IT infrastructures. We have clusters, grids, and clouds to achieve high availability and scalability at the infrastructures level. Clouds are being touted as the best-in-class IT infrastructure for digital innovation, disruption, and transformation. For simplifying, streamlining, and speeding up the cloud setup and sustenance, there came a number of enabling tools for automating the repetitive and routine cloud scheduling, software deployment, cloud administration, and management. Automation and orchestration are being pronounced as the way forward for the ensuing cloud era. Most of the manual activities in running cloud centers are being precisely defined and automated through scripts and other methods. With the number of systems, databases, and middleware, network and storage professionals manning cloud environments has come down drastically. The total cost of ownership (TCO) of cloud IT is declining, whereas the return on investment (RoI) is increasing. The cost benefits of the cloud-enablement of conventional IT environments is greatly noticeable. Cloud computing is typically proclaimed as the marriage between mainframe and modern computing and is famous for attaining high performance while giving cost advantages. The customer-facing applications with varying loads are extremely fit for public cloud environments. Multi-cloud strategies are being worked out by worldwide enterprises to embrace this unique technology without any vendor lock-in.
However, for attaining the much-needed reliability, there are miles to traverse. Automated tools, policies, and other knowledge bases, AI-inspired log and operational analytics, acquiring the capability of preventive, predictive, and prescriptive maintenance through machine and deep learning algorithms and models, scores of reusable resiliency patterns, and preemptive monitoring, are the way forward.
A resilient application is typically highly available, even in the midst of failures and faults. If there is any internal or external attack on a single application component/microservice, the application still functions and delivers its assigned functionality without any delay or stoppage. The failure can be identified and contained within the component so that the other components of the application aren't affected. Typically, multiple instances of the application components are being run in different and distributed containers or VMs so that one component loss does not matter much to the application. Also, application state and behavior information gets stored in separate systems. Any resilient application has to be designed and developed accordingly to survive in any kind of situation. Not only applications but also the underlying IT or cloud infrastructure modules have to be chosen and configured intelligently to support the unique resilient goals of software applications. The first and foremost thing is to fully leverage the distributed computing model. The deployment topology and architecture have to purposefully use the various resiliency design, integration, deployment, and patterns. Plus, the following tips and techniques ought to be employed as per the infrastructure scientists, experts, architects, and specialists:
- Use the various network and security solutions, such as firewalls, load balancers, and application delivery controllers (ADCs). Network access control systems (NACLs) also contribute to security. These help out in intelligently investigating every request message to filter out any ambiguous and malevolent message at the source. Furthermore, load balancers continuously probe and monitor servers and distribute traffic to servers that are not fully loaded. Also, they can choose the best server to handle certain requests.
- Employ multiple servers at different and distributed cloud centers. That is, disaster recovery capability needs to be part of any IT solution.
- Attach a robust and resilient storage solution for data recovery and stateful applications.
- Utilize software infrastructure solutions, such as API gateways and management suites, service mesh solutions, additional abstraction layers, to ensure the systems resiliency.
- Leveraging the aspects of compartmentalization (virtualization and containerization) have to be incorporated to arrive at virtualized and containerized cloud environments, which intrinsically support the much-needed flexibility, extensibility, elasticity, infrastructure operations automation, distinct maneuverability, and versatility. The software-defined environments are more conducive and constructive for application and infrastructure resiliency.
- Focus on log, operational, performance, and scalability analytics to proactive and preemptively monitor, measure, and manage various infrastructure components (software, as well as hardware).
Thus, reliable software applications and infrastructure combine well in rolling out reliable systems that, in turn, guarantee reliable business operations.
In summary, we can say the following:
- Reliability = resiliency + elasticity
- Automation and orchestration are the key requirements for a reliable IT infrastructure
- IT reliability fulfilment—resiliency is to survive under attacks, failures, and faults, whereas elasticity is to auto-scale (vertical and horizontal scalability) under a load
- IT infrastructure operational, log, and performance/scalability analytics through AI-inspired analytics platforms
- Patterns, processes, platforms, and practices for having reliable IT Infrastructure
- System and application monitoring are also significant
