The ephemerality of an object describes its transient nature where these objects are created—spun up—to serve a specific function and then destroyed—or torn down—when their purpose has been fulfilled. In the cloud-native paradigm, “ephemeral” refers to the short-lived, temporary nature of containerized microservices.
 

Moreover, the scalability of an object refers to the extent to which an application can handle increased workloads by adjusting its resources dynamically, either by scaling up or out. And when the workload decreases, the application scales its resources back down or in.

As seen in this article’s topic, the terms “ephemerality” and “scalability,” go hand-in-hand in the cloud native context. Let’s expand on this topic by considering an example of how they work together to satisfy the requirements of a GHMA—Global Hybrid Multicloud Application.

GHMAs and their Characteristics: Solving the Challenges of Modern Enterprises

First, what is a Global Hybrid Multicloud Application, and what characteristics is it required to have?

In summary, a Global, Hybrid, Multicloud Application—or GHMA—is a “new type of enterprise application that is cloud native and event-driven, running on hybrid multi-cloud architectures across different geographies.”

The Challenges Experienced by Modern Enterprises

It is worth noting that the characteristics of a GHMA are born out of the need to drive sustainable business growth in today’s world and not vice versa. Developing a “best-of-breed” GHMA requires understanding the challenges modern enterprise organizations face. By understanding these challenges, we can find solutions.

These challenges include a need for an application to scale massively to meet rapidly increasing demands, including more users (and accompanying data), AI-based innovations, and a more responsive, interactive UI, irrespective of the number of users using the app at any given point.

Customer and employee requirements evolve rapidly, often faster than traditional software development cycles can push out updates to meet these changing requirements. Additionally, organizations are rethinking their business process and how they can better serve their employees—and customers by digitally transforming how they do business.

Remote work has changed the way businesses operate. Employees can work from anywhere in the world, not only in the country where the organization is registered. However, this is only successful if the application’s characteristics include a global scope. The application’s ability to execute on the global stage extends beyond solving the remote working challenge; it must also allow authorized users worldwide to access the application to interact with it or purchase goods and services.

Organizations, especially enterprise organizations, often tend to have a mixture of on-premises infrastructure and multiple clouds—both private and public. Moreover, these organizations also have a mix of old and new technologies that are part of the organization’s infrastructure and architecture.

There is always a requirement to store and access both customer and employee PII—Personal Identifiable Information, resulting in the challenge of meeting jurisdictional regulatory compliance. Lastly, the application’s ability to deliver real-time data and user interactivity, with zero latency—and lags, will determine the organization’s financial worth.

Solving These Challenges: The Characteristics of a GHMA

The GHMA architecture is an advanced evolution of the enterprise application paradigm, designed to meet the often complex and dynamic requirements of modern organizations by solving the challenges (and more)—described above—facing these organizations.

To begin with, GHMAs are characterized by their cloud-native, event-driven architectures—comprising many small microservices, each encapsulating a single feature (or the smallest unit/part of a feature) —and are deployed across hybrid and multi-cloud environments across different geographic locations.

Other characteristics include the requirement to be highly available with DevOps SLAs—Service Level Agreements—of 99.99% uptime, providing real-time data and interactivity, being dynamic and agile, massively scalable, and complying with regional data security and privacy laws.

The glue that holds these microservices together is Kubernetes, the most popular cloud orchestration platform. However, K8s falls short when it comes to orchestrating and coordinating microservices-based applications hosted on global, hybrid, multi-cloud infrastructure. It is good at orchestrating microservices within a single environment but not multiple different ones simultaneously. The GHMA architecture solves this challenge—as described in the practical use case below.

In summary, the GHMA consists of a number of peer servers—or nodes—each peer located on a specific cloud (or on-premises server) based on the best cloud provider for each service based on performance, regional availability, and cost. The GHMA includes an overarching layer—over all the different peers (each comprising a number of Kubernetes-orchestrated microservices)— abstracting the networking and integration elements, simplifying and automating peer-to-peer communications, supporting autoscaling at scale, resulting in a dynamic application that is agile, responsive, and resilient.

Improving the Scalability and Ephemerality of a GHMA: A Use Case

Circling back to this article’s opening statements, the dual concepts of scalability and ephemerality go a long way toward ensuring a GHMA has the rest of its mandatory characteristics.

In other words, improving the scalability and ephemerality of a GHMA is critical for organizations seeking to adapt rapidly and efficiently to changing market demands, specifically in sectors like logistics, where real-time data, global reach, and operational flexibility are paramount.

Let’s study the following use case demonstrating how a logistics company can enhance the ephemerality and scalability of its GHMA.

Imagine you own a global logistics company and aim to optimize your supply chain management system, improving real-time tracking, predictive analytics for delivery optimization, and seamless integration across your stakeholders—manufacturers, warehousing, transportation, and end consumers—worldwide.

Note: At this juncture, the supply chain management system is monolithic. It still needs to be converted into a GHMA.

To increase ephemerality and improve scalability, the application must spin up additional resources and tear them down again to manage the fluctuating demands across global markets, such as peak shopping seasons—Black Friday, Singles Day, Cyber Monday, or Christmas—sudden supply chain disruptions—severe weather events, global pandemics, or freak accidents—as well as rapid market expansion or contraction.

Practical Steps Improve Ephemerality and Scalability

Improving ephemerality and scalability is a step-by-step workflow beginning with converting the monolith into a microservices-based architecture.

Here is a broad-strokes overview of this workflow:

• The first step is to divide the monolith into microservices, each responsible for a specific element of the logistics operation, such as inventory management, order tracking, customer communication, route optimization, and demand forecasting.
• Once you have redesigned your application as a set of microservices, the second step is to convert the existing functionality into individual microservices or create new microservices that upgrade the functionality simultaneously.
• Package each microservice into a Docker container with its database, libraries, and everything else the microservice requires to function as a separate unit.
• Deploy and orchestrate with these containers across a hybrid multicloud environment—with K8s orchestrating the microservices located on a specific cloud (a peer server) and Fiorano’s GHMA infrastructure abstracting the underlying networking and infrastructure details so that the multiple peers (server nodes) interacting with each other, supporting distributed autoscaling. Fiorano utilizes Kubernetes auto-scaling functions—Horizontal Pod Autoscaler and Cluster Autoscaler—as its foundation for autoscaling functions, managing the containers’ lifecycles and automatically scaling them up or down based on real-time demand.
• Implement an event-driven model to trigger real-time processes, improving the application’s responsiveness, resource efficiency, and effectiveness.
• Decouple services even further by implementing APIs with smart endpoints (and smart pipes). In other words, these APIs have business logic built into them, preventing the duplication of logic and ensuring data consistency and reliable communications between microservices.
• Include serverless functions for ephemeral—or short-lived tasks—requiring intense compute resources temporarily, such as demand forecasting utilizing GenAI or machine learning models.
• Incorporate data governance, compliance, and security protocols to manage and protect sensitive data, as well as comply with global regulations such as GDPR and CCPA.

By following the steps in this workflow, your supply chain logistics application will evolve into a highly scalable and ephemeral GHMA that responds dynamically to global supply chain demands, not only improving operational efficiencies and customer satisfaction metrics but also uniquely positioning the company to leverage emerging technologies and market opportunities.

In Conclusion

Improving the ephemerality and scalability of cloud native, microservice-based applications, especially those that fit the definition of a GHMA, is crucial for organizations desiring to optimize performance, manage resources efficiently, and ensure service continuity across global, hybrid architectures and infrastructures.

Furthermore, a significant part of this process involves embracing cloud native principles and leveraging the latest technologies, infrastructure, and architectural patterns to adapt to changing demands continuously. 

Consequently, GHMAs exemplify the convergence of multiple advanced technologies and architectures aligned with strategic business objectives to facilitate sustainable growth, global scope, scalability, dynamic and rapid adaptability, as well as real-time interactivity and data analytics.