¿Cómo dará forma el desarrollo nativo de la nube al futuro de la computación en la nube?

Cloud-native development will drive agility and efficiency in cloud computing. By building modular, scalable applications, businesses can deploy features faster, react quicker to changes, and optimize resource use. This, along with advancements like AI integration, will lead to a more dynamic and cost-effective cloud experience.

I completely agree with that. My Experience from telecom background, Cloud native development is the only way to help end customers and meet the exponential growth

Cloud-native Entwicklung bezieht sämtliche Möglichkeiten und Best-Practises des jeweiligen Cloudanbieters auch unter Berücksichtigung der Kosten mit ein. Durch die Angebote der Anbieter können Lösungen schneller und kostengünstiger Erstellt und betrieben werden. Lift-and-shift Szenarien machen nur begrenzt Sinn und sollten nicht der Fokus in Bezug auf Cloud sein.

Along with the great points about TTM and different scaling/pricing models, a great thing to understand about cloud computing is the ability to automate everything without the limitations and overhead costs of hybrid and on-prem computing. With the power of IaC(Infrastructure as code) cloud services can be spun up and down at will and/or within any schedule deemed necessary to extend efficient cost management and budget automation for any business or team size.

Cloudanbieter abstrahieren Komplexität und ermöglichen eine leichtere und schnellere Entwicklung von hochverfügbaren guten Softwareplattformen und -systemen. Ein einfacher Lift-and-shift macht kaum Sinn und führt häufig zu sehr hohen Kosten, da die Architekturen anders designed wurden.

One of the biggest issues with cloud-native development is the inability or difficulty in recreating the deployed infra on local. While some Cloud providers like AWS have open source projects like localstack to help with this, it's a lot difficult to do on other Cloud Providers. A good practice would be to have a full access sandbox environment for debugging. And a much better solution would be to use Cloud Provider Agnostic tools like Docker. The architecture will be a little different and will need more time but for really large-scale projects where issues like vendor lock-in, debugging are critical, Cloud agnostic is the way to go.

One of the top challenges for engineers working in cloud-native systems is identifying bugs and errors. When the system has many moving parts, it can take time to understand what is going wrong. At the beginning of every service, there should be a defined strategy for logging and alerting. This would help engineers see the issues arising in the working system. Alerts should be visible in emails, Slack, or Microsoft Teams, where people communicate daily.

Cloud-native development challenges include the fact that every cloud engineer needs to also be a cost engineer. There are a lot of ways to implement a specific application pattern - if the wrong cloud services are implemented, the cost of the application stack may be much higher than necessary if a different set of services were selected. This is especially challenging when individuals are reskilling to cloud native or refactoring an existing application to cloud native is in view because it is a very natural thing to simply pick the services that mirror past experience or the existing non-cloud application. A rule of thumb is "In the cloud you only pay for what you use, but you also pay for every millisecond you use."

In my experience, the three biggest challenges of cloud-native development are: - Cost - Security - Knowledge Cost is one of the biggest challenges, not just because of the outright billing issue, but finding out *what* that bill might be. With so many providers, services, and products to use, development is no longer "how do we build this?" it's "how do we build this most cost effectively?" Security is the next biggest challenge. As many have said, cloud is just "someone else's computer". With that in mind, security as you build your networking to and from the cloud infrastructure, keeping it secure is more complex. Lastly, knowledge. Tech is always evolving, this is not news to anyone in the field, and the challenge is keeping upskilled.

Despite its many advantages, cloud-native development comes with its own set of challenges. One of the primary obstacles is the steep learning curve associated with adopting new technologies and practices, such as microservices, container orchestration, and Infrastructure as Code (IaC). Developers must also navigate the complexity of managing distributed systems, where issues like service discovery, load balancing, and network latency become critical concerns. Furthermore, ensuring consistent security and compliance across a dynamic and often multi-cloud environment can be daunting, requiring robust governance frameworks and continuous monitoring.

Cloud-native development relies on software defined compute resources. This requires a new automation capability to deploy and configure such resources. It is known as Infrastructure as Code. If an application team has not had to deal directly with infrastructure deployment, this is a new and unknown skill to them. For many application developers Infrastructure as Code (IaC) may also be their first substantial exposure to declarative coding languages. It can take time to onboard the new model as they have opposite expectations in areas of sequencing, branching and looping. Declarative languages seek to minimize and eliminate theses structures that are so common in imperative coding languages.

Choose Cloud Strategy and Provider: Selecting the right cloud strategy and provider is pivotal in ensuring compatibility and scalability for your applications. Consider factors like compliance requirements, data sovereignty, and the services offered by each provider. Adopt Cloud-Native Principles and Practices: Embracing cloud-native principles involves leveraging technologies like microservices, containers, and serverless functions to build scalable and resilient applications. Implementing DevOps methodologies. Continuous Learning and Community Engagement: Stay abreast of the latest developments in cloud-native technologies by engaging with online resources, communities, and industry events.

The most significant trend in cloud computing Infrastructure from Code, or universal backend development. Infrastructure-from-Code (IfC) simplifies cloud-native development by automating cloud resource setup from application code, allowing developers to focus on building rather than infrastructure. In the IfC world the infrastructure works *for* the application, not the other way around. It ensures faster, more reliable development that adapts easily to new technologies and guarantees application and infrastructure alignment by design. Some of the tools spearheading this space are Klotho, WingLang and Encore.

Cloud native development is increasingly abstracting and embedding Infrastructure as Code so that developers do not have an added coding burden in getting to cloud native. This can be seen in things such as Serverless.com Framework, AWS Serverless Application Model (SAM) and AWS Application Composer. This trend removes an important learning curve barrier to cloud native adoption.

Es werden zunehmend mehr Serverlessprodukte vorgestellt und eingesetzt, da diese den Betrieb stark vereinfachen. wenn es sich nicht um eine Anwendung handelt die wirklich 24/7 Last erzeugt können so auch preislich interessante Vorteile ergeben.

There are several emerging trends. Edge computing is gaining traction, allowing applications to process data closer to where it is generated, reducing latency and improving performance. The integration of AI/ML in cloud-native applications is becoming more prevalent, enabling advanced analytics, automation, and personalized user experiences. Multi-cloud strategies are also on the rise, giving organizations the flexibility to leverage the strengths of different cloud providers while avoiding vendor lock-in. Additionally, tools like Infrastructure-from-Code (IfC) are simplifying the development process by automating the creation of cloud resources directly from application code, further streamlining cloud-native adoption.

As cloud-native applications evolve, security challenges grow, leading to an emphasis on DevSecOps. This approach integrates security into all stages of development, ensuring continuous monitoring and the use of tools like container scanning. Concurrently, there's a focus on sustainability in cloud-native development, aiming to reduce energy consumption and select eco-friendly cloud providers. Additionally, organizations are experiencing a cultural shift, breaking down barriers between development and operations, fostering continuous learning, adaptation, and collaboration. These developments represent a significant transformation in the cloud-native landscape.

Man sollte sorgfältig überlegen welche Technologien eingesetzt werden, denn cloud-native Softwareentwicklung und auch Microservices sind kein Allheilbringer. Auch wenn die Kosten im Betrieb deutlich geringer sind, steigt doch die Komplexität, denn es sind deutlich mehr Schnittstellen und Produkte involviert. Es gibt auch kein One-fits-all, sondern man sollte sich Gedanken über eine sinnvolle Cloud-Architektur machen.