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This article shows you how to understand Serverless technology selection, the content is concise and easy to understand, it will definitely brighten your eyes. I hope you can get something through the detailed introduction of this article.

Below, through this article, I will introduce to you what Serverless products Aliyun has for you to choose from.

Serverless products and layering

As we all know, AWS was the first to propose Serverless, and its flagship product in the field of Serverless is function compute. Similarly, Aliyun also has function computing products to help users build Serverless functions. However, Serverless is not just a function, as shown in the figure below. In fact, users will expect to enjoy the benefits of Serverless at the application, container and other levels, including pay-by-quantity, extreme flexibility, etc., which is more in line with users' original habits.

In the figure above, you can see that Aliyun has launched corresponding Serverless products for functions, applications and containers, and users can choose different products according to their own usage scenarios.

Function calculation 1. Introduction to function calculation

The figure above shows how function calculations are used. From the user's point of view, all he needs to do is code and upload the code to the function calculation. There is no charge at this time, only when it is called. It can be called through the API/SDK provided by the product or through some event sources, such as the OSS event of Aliyun. For example, users upload a file to a bucket in OSS in the hope that the file will be processed automatically; for example, upload a zip package and hope to decompress it to another bucket automatically. These are typical function scenarios.

In addition, function calculation can provide very good flexibility, the final cost is based on the length of time and memory, if the amount of call is small, there will be only a small cost. And it is also very rich in language, which is directly supported by nodejs, php, python and java. At the same time, it provides a custom running environment that can support any executable language.

two。 Typical scenarios of function calculation

In terms of usage scenarios, there are three main categories:

Web application. It can be written in a variety of languages, it can be a new program written using the Serverless framework, or it can be an existing application. For example, Mini Program backend, or API backend applications released to the API market, etc.

An application that has a strong flexible demand for computing power. Such as AI reasoning, audio and video processing, document conversion and so on.

Event-driven applications. For example, scenarios driven by other Ali Cloud products, Web Hook, scheduled tasks, etc. Function computing has been connected with many products, such as object storage, table storage, timer, CDN, log service, cloud monitoring and so on, which can assemble some business logic very quickly.

3. Core competence of function calculation

One of the greatest values of function computing to customers is that it allows users to focus only on their own business logic development, without the need to manage operation and maintenance, such as computing resources, network settings and so on. In terms of isolation, it provides vm-level isolation to ensure users' data security and runtime security; in terms of availability, it provides 3az's high-availability architecture by default, ensuring that customers default to a highly available best practice architecture; in terms of elasticity, it can achieve millisecond elastic efficiency to meet customer sudden traffic shocks. It is also very flexible in billing, charging according to users' requests and supporting a prepaid model that is more friendly to long run applications.

Serverless Application engine 1.Overview of SAE

SAE is the industry's first application-oriented Serverless Paas platform. From an application-oriented perspective, this product helps users bring inventory applications to the cloud without making any changes. In the resource layer, users no longer need to manage, operate and maintain machines and clusters, but only need to pay attention to the specifications and number of instances they need to use for their applications, and no longer need to care about whether the underlying layer is a virtual machine or a container.

SAE provides computing resources, flexibility, isolation and other capabilities from the resource level, so that users only need to pay attention to their own applications. In the application layer, SAE provides monitoring, logging, micro-service governance and other capabilities to help users address application observability and governance needs. At the same time, it provides network configuration and traffic control capabilities, and provides good integration with CICD. Users can use the existing CICD to deploy to SAE, such as jenkins, cloud effect, etc., which can be said to cover the complete cloud scenario on the application.

2. Typical SAE scenarios

There are several typical usage scenarios for SAE. One is cloud-based inventory business, especially micro-services and java applications, as well as monolithic applications in other languages, which can be run on Aliyun through the SAE platform without any code changes. In terms of industry, SAE is especially suitable for online businesses with large traffic fluctuations, such as e-commerce promotion, online education and other industries. In addition, as an application platform, SAE can also be integrated by the upper industry Saas to help users build industry Saas more quickly.

3. SAE characteristics

From the above scenario, we can see that in addition to the extreme flexibility and OPS-free features brought about by the Serverless experience, SAE focuses on providing users with full-stack capabilities at the application layer, including enhanced support for micro-services, and integration of application-related capabilities, including configuration, monitoring, logging, flow control, and so on. Coupled with the change of user zero code, it is a very good choice for enterprise online business smooth cloud.

Serverless Kubernetes1. Overview of ASK

Another Serverless product offered by Aliyun is Serverless K8s. But how can K8s still Serverless? This requires an understanding of the evolution of the technical architecture.

In the earliest days, everyone deployed Docker images in virtual machines. Users need to purchase ECS, then deploy images, and finally, some network configurations, such as SLB, EIP and so on. In this process, users need to complete the deployment actions themselves, and to expand capacity, they need to repeat the above actions, or build a set of automated scripts, which is relatively low in cost and stability.

After that, there is K8s to help you solve the problem of container arrangement. This standardized approach has indeed greatly improved everyone's productivity. Users orchestrate and deploy by using the standard K8s such as deployment and service. However, the operation and management of K8s is still relatively complex, and the skill requirements are relatively high. Users need operation and maintenance ECS and K8s built through ECS. Another pain point is that the ECS in the K8s cluster needs to be purchased in advance. If the customer's load fluctuates greatly, there will be more waste of resources. Although there are technical solutions, such as the flexibility of worker node, this still has a high complexity for beginners.

Is there a solution that allows users to enjoy the container orchestration capabilities provided by K8s without having to care about the operation and maintenance, management and flexibility of ECS and K8s? This is the solution of Serverless K8s. The product corresponding to Aliyun is ASK. In ASK's scenario, users create an ASK cluster without specifying any ECS nodes, and then deploy images through standard K8s container orchestration, deployment, and so on. ASK automatically builds and scales the required POD in the underlying resource pool according to users' load needs. Users no longer need to care about LaaS layer issues such as capacity planning, ECS machine operation and maintenance, and resource restrictions.

2. Typical ASK scenarios

What are the main scenarios where ASK is used? First of all, it can be used to run online business, and the deployment mode is flexible. It can be all the native K8s modes such as deployment, helm chart and so on. In particular, it is able to cope with sudden traffic and is extremely flexible. It can achieve the flexibility of 500 container instances in 30 seconds. This flexibility and efficiency can well support big data's computing tasks, such as Spark, Presto, etc., and can also obtain resources immediately when needed, support more than 10000 of Pod specifications, and effectively reduce customer costs.

Another well-suited scenario is to build build tasks that start on demand, such as running jenkins, Gitlab-Runner, and so on in ASK. When there is a build task, start it immediately. Zero consumption when there is no task, and the cost is the lowest. Here are just some examples of scenarios, in fact, based on this feature of ASK, users can run a lot of K8s native workloads that require extreme flexibility.

3. ASK characteristics

ASK is fully deployed in containers and is isolated through containers. In the process of use, users do not need to operate and maintain ECS or K8s cluster, and do not need to consider cluster upgrade, capacity planning, OS and system software problems, which can provide unlimited flexible capacity in theory. Because it is charged entirely according to usage, there is no need to pay for limited resources.

The above is how to understand the selection of Serverless technology. Have you learned any knowledge or skills? If you want to learn more skills or enrich your knowledge reserve, you are welcome to follow the industry information channel.

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