How can you design a portable, scalable, and efficient container-based architecture?

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I have found Container Orchestration very useful as it enforces best practices: Utilize a container orchestration platform like Kubernetes or Docker Swarm to manage and scale your containerized services. These platforms provide automated deployment, scaling, and load balancing capabilities, ensuring the efficient utilization of resources. Pitfall I've encountered: Insufficient resource allocation or improper scaling can lead to performance bottlenecks and degraded application performance. Gotchas on scaling out services: Monitor resource utilization, performance metrics, and workload patterns to optimize resource allocation and scaling strategies. Implement auto-scaling based on metrics like CPU, memory, and request rates.

In today’s world where we have multiple cloud platforms that are rapidly evolving and new technologies coming up every day, portability is essential for applications to stand the test of time.

Pour garantir la portabilité d'une application, il faut suivre au maximum les standards établis. La conteneurisation peut effectivement être une solution mais il faut l'utiliser les fonctionnalités natives que l'on pourra retrouver chez tous les providers (Azure, AWS, GCP voir on-prem) Cela veut dire faire des applications les plus standards et donc faire moins de "Cloud native" et donc ne pas utiliser les fonctionnalités intéressantes d'un AKS ou EKS pour ne citer qu'eux.

In my experience container orchestration is the best way to implement portability. One can use Docker Swarm or Kubernetes for container orchestration. These platforms can ease the pain of setting up several development environments. They are easy to use, easy to deploy, and more of all there are so many services in AWS as well as GCP that can create a production-ready app in a few minutes. Applications using these platforms are also easy to scale. So, is it all so smooth with orchestration? Not really. One needs to have a clear picture before orchestrating containers, or else they can easily Gulp up resources and create resource overflow.

Scalability is key with the ever growing on-demand and high availability for apps. Microservices Architecture: Adopt a microservices architecture to break down your application into smaller, loosely coupled services. Each service can be containerized independently, allowing for easier scalability and portability. Ensure that each microservice is responsible for a specific business capability, and avoid tightly coupling services. Cons: Avoid creating too many microservices with fine-grained functionality, as this can lead to increased complexity and performance overhead due to inter-service communication. Gotchas: Use domain-driven design principles to identify and define meaningful microservices boundaries based on business capabi

An orchestration system like kubernetes is a must have, breaking the system or components up into their respective domains based on usage (scaling components based on skewed demand could cause unwanted downtime in other areas and unwanted cost) and managing each one's scale parameters separately will enable great flexibility and agility in what (components) should scale how (horizontally/vertically) and when (schedule/demand/pre-emptive demand). Some consideration can be made around when to use vertical and horizontal scaling, for example consider vertical scaling when each container will have mandatory overheads which will consume storage, memory and compute, increasing cost with no performance or throughput benefits.

Build smaller and with fast delivery is the mojo of lean and agile approach. This kind of approach and methodology has to be taken into consideration along the technical aspect. Yes you have to build micro services and break down monolith, build stateless apps etc. But you shouldn’t minimize the impact of the organisation that should be align with your approach (Conway law)

In discussing scalability, especially in container-based architecture, it's vital to emphasize the dynamic adaptability of system resources. Scalability is not just about handling increased load; it's about doing so efficiently and cost-effectively. This efficiency is achieved through strategies like load balancing and auto-scaling, which distribute traffic across multiple containers and automatically adjust resources in response to real-time demand. As the system scales, maintaining consistent performance and uptime becomes challenging. This requires robust monitoring and management tools to anticipate and mitigate potential issues.

Algo a acrescentar é que com escalabilidade e um bom proveito dos recursos de cada instância, garante otimização dos custos, que é dos principais fatores em decompor sistemas (garantir que estamos pagando apenas pelos recursos que efetivamente estamos utilizando).

I think everyone is touching the realm of docker containers but, still I have hardly seen organisation’s paying attention towards writing the effective Docker file and this disappoint me a lot. Docker file is a powerful building block of containers/micro-service architecture if you neglect it you are in big big trouble be it security, portability, patch management, container size etc. Democratising the effective way of writing docker file is very much needed and organisation should always think towards putting guardrails around Dockerfile while building the docker image. Your CI system should be powerful enough to detect these anomalies in Dockerfile and fix it at the inception only instead of reworking when security team flag it.

Efficiency is the backbone of top-notch applications in container-based architecture. It's about smart resource use and cutting down on waste. Think of it like a well-oiled machine – design with a multi-stage build process, layer your containers for Docker cache perks, and secure connections with a network overlay or service mesh. Following these best practices ensures your architecture is not just efficient but also stays ahead in the ever-evolving tech landscape.

Observability is a key aspect of maintaining such systems from performance to availability through security and scalability, as there are many moving parts that spins up and down fast.If you want to keep track of whats happening and from where the failure's are coming,this is a crucial part of what you need to add to the design. If there are application events that can be sent and integrated as well as infra stats metrics and logs. Another topic that is missing here is the security of the process and the components that now days should be handled in the CI/CD pipelines.

Efficiency spans various concerns in my experience these have served me well: Load Balancing: This ensures high availability, improves performance, and enables horizontal scaling. Caching and Content Delivery Networks (CDNs): Caching mechanisms reduce the load, improve response times, caching serve static assets, reducing the latency for geographically. Efficient Communication Protocols: These protocols offer high-performance, low-latency communication, and support efficient data serialization. Monitoring and Observability: Monitor key metrics like resource utilization, response times, error rates, and scaling events. Continuous Integration and Deployment (CI/CD): Automate the build, testing, and deployment of containerized services.

Efficiency, in a general sense, refers to the ability to achieve maximum output with minimum input or resources. It's a measure of how well a system or process utilizes resources to produce a desired outcome. In the context of a container-based architecture or any technology infrastructure, efficiency can be evaluated in various aspects: Resource Efficiency, Performance Efficiency, Operational Efficiency, Cost Efficiency, Development and Deployment Efficiency, and Flexibility and Adaptability.

One thing to consider is also ease of reuse. We dont have to reinvent the wheel everytime if we design the systems appropriately. An efficient well architected system will also have components which are reusable ans scalability also ensures that they can be an easy fit for the same purpose in a different system. An eg: is a microservice for thumbnail generation in a video ingestion service can do the same for profile images as well as catalog as well as images shared in chat.

Observability of containers is difficult to achieve correctly and should be considered. It is tough to deploy an after-the-fact monitoring and observability stack if the developers don't consider it from the get-go as part of feature requirements. Without it, you will have holes in the visibility of what happens within your container environment.

Fala-se muito em soluções distribuídas em microservices. Porém, é importante frisar que um microsserviço não significa um micro desenvolvimento - impressão que adquirimos com serviços em nuvem -, porém, tal qual, este deverá ter uma microfunção.

I find the question puts the emphasis in the wrong place. Containers and container management system are important to achieve your goal, but the important point is design. If your goal is portability, for many systems, containers will help. Scalability can be achieved if your system was designed for it - putting the wrong things in containers or using the containers wrong won't make your system scalable. My point is do the high level design first and use containers as a tool to achieve it, if they fit.

To utilize containers optimally, architecting a microservices app could be an useful option. In addition to scalability and resiliency, using microservices provides opportunity to use multiple technology stacks based on specific requirements instead of being locked into a single technology for the entire application. Careful design, service coordination and data management is required to reap the maximum benefits of a microservices architecture.