Technologies and operational systems in businesses tend to evolve every 6 months. Certainly, matching up with the market trend every time there’s a turn is a humongous task. Imagine how much cost and effort would be saved if they were auto-scalable.
While there are many ways to enhance the scalability of a system, this article will talk about AWS serverless technology that is known to take businesses to a new level of productivity and scalability. The next big question that arises here is why is it called serverless? There are servers in the serverless but the term is used because it describes the customer’s experience of the servers, which is invisible and is not present physically in front of the customers. The customer doesn’t have to manage them or interact with them in any way.
We can dive deeper only after we have understood the true meaning of serverless computing.
What Is Serverless Computing?
It is a cloud computing execution model that provisions computing resources on demand. It enables the offloading of all common infrastructure management tasks such as patching, provisioning, scheduling, and scaling to cloud providers and tools, allowing engineers to focus on the customization required for applications required for the client.
Features of serverless computing
It does not require monitoring and management, which helps developers more time to optimize codes and find out innovative ideas to add features and functionalities to the application.
Serverless computing runs codes on-demand only, typically in a stateless container only when there’s a request. The scaling too is transparent with the number of requests being served.
Serverless computing charges only for what’s being used and not for idle capacity.
Benefits of Serverless Computing
The serverless market is estimated to grow around $20B USD by 2025. The striking figures are owed to the innumerable disadvantages of serverless computing as compared to traditional cloud computing, server-centric infrastructure. Below mentioned are some of the important benefits offered by top serverless cloud computing service providers.
No worries about server maintenance
Managed by the vendors completely, this can reduce the investment necessary in DevOps. This not just lowers the expenses but also frees up developers to create and expand the applications without being held behind by server capacity.
Codes can be used to reduce latency
Since the application is not hosted on an original server, its code can be run from anywhere. Depending on the servers, it can thus be used to run applications on servers that are close to the end-users. This reduces latency because requests from the user no longer have to travel all the way to the origin server.
Serverless architecture is scalable
Applications built on serverless architecture scale up automatically during spike season and scale down during the lean period. Additionally, if the function needs to be run in multiple instances, the vendor’s server will start, run and end when the requirement is over. This is done often using containers. A serverless application, thus, can handle a high number of requests as well as single requests.
Quick deployments are possible
There is no need for the developer to upload codes or do any backend configuration in order to release a working application. Uploading bits of code all at a time or one function at a time can help release an application quickly. This can be done because the application is not a single monolithic stack but rather a collection of functions provisioned by the vendor. This also helps in patching, fixing, updating new features to an application.
They are fault-tolerant
It is not the responsibility of the developers to ensure the fault tolerance of the serverless architecture. The cloud provider assigns the IT infrastructure that will be automatically allocated to account for any kind of failure.
No upfront costs
Users need to pay only for the running code and there are no upfront costs involved while deploying the serverless cloud infrastructure to build an application.
Why Would You Need Help?
Every technology has its own set of drawbacks which needs expert consultation and technology expertise. Some of the disadvantages of using serverless applications are as follows:
Debugging and testing become tough
It is difficult to replicate the serverless environment in order to check for bugs and see how the code will perform once deployed. Debugging is extremely difficult because developers are not aware of the backend process. Moreover, applications here are broken up into separate, smaller functions.
Solution: Businesses planning to use serverless applications should look for serverless cloud infrastructure providers of vendors who are experts in sandbox technology who can help in reducing the difficulties in testing and debugging.
Be prepared for a new set of security concerns
When applications are run on serverless platforms, the developers do not have access to the security systems or might not be able to supervise the security systems, which could be a big issue for platforms handling crucial and secret data. Since companies do not have their own assigned servers, serverless providers will often be running code from several of their customers. This scenario is also known as multitenancy. Interestingly, if not performed properly, this can lead to data exposure.
Solutions: Software service providers that sandbox functions avoid the impacts of multi-tenancy. They also have a powerful infrastructure that avoids data leaks.
Not best for long-term processes
Most of the applications do not fit the bill because clients would want a long-standing application, which would charge more on serverless architecture than on traditional ones. This is because providers charge for only the time when the code is running.
Solution: IT consultancy can help businesses understand whether their business requirements will be fulfilled by serverless architectures or not. It is advisable to get IT consultants cum solution providers to help businesses get the right guidance. This will not just save money but also time for businesses.
Risk of cold-start
Since the servers are not constantly used, the code might require ‘boot up’ when it is used. This startup might affect the performance of the application. But if the code is used regularly, the serverless provider is responsible to keep it ready for whenever it needs to be activated. A request for this ready-to-go code is called a “warm start”.
Solution: Experienced serverless cloud service providers will be able to avoid the cold start by using the Chrome V8 engine, which can restart the application in less than 5 milliseconds. The experts having good exposure to such a setup can easily manage the performance lag without the customers even noticing.
Serverless cloud applications are often branded as type-set, unable to sync in with another vendor in time of transition. This is because the architecture and the workflow vary from one vendor to another.
Moving to serverless? Get the best help you need from trained developers and expert cloud consultants. Learn all about data pipeline architecture and sync serverless deployments while speeding migration times and reducing costs.
分布式事务是指事务的参与者、支持事务的服务器、资源服务器以及事务管理器分别位于不同的分布式系统的不同节点之上。例如在大型电商系统中，下单接口通常会扣减库存、减去优惠、生成订单 id, 而订单服务与库存、优惠、订单 id 都是不同的服务，下单接口的成功与否，不仅取决于本地的 db 操作，而且依赖第三方系统的结果，这时候分布式事务就保证这些操作要么全部成功，要么全部失败。本质上来说，分布式事务就是为了保证不同数据库的数据一致性。
CAP 原则又称 CAP 定理，指的是在一个分布式系统中， Consistency（一致性）、 Availability（可用性）、Partition tolerance（分区容错性），三者不可得兼。
以实际效果而言，分区相当于对通信的时限要求。系统如果不能在时限内达成数据一致性，就意味着发生了分区的情况，必须就当前操作在 C 和 A 之间做出选择。
CAP 原则的精髓就是要么 AP，要么 CP，要么 AC，但是不存在 CAP。如果在某个分布式系统中数据无副本， 那么系统必然满足强一致性条件， 因为只有独一数据，不会出现数据不一致的情况，此时 C 和 P 两要素具备，但是如果系统发生了网络分区状况或者宕机，必然导致某些数据不可以访问，此时可用性条件就不能被满足，即在此情况下获得了 CP 系统，但是 CAP 不可同时满足。
BASE 理论指的是基本可用 Basically Available，软状态 Soft State，最终一致性 Eventual Consistency，核心思想是即便无法做到强一致性，但应该采用适合的方式保证最终一致性。
BASE，Basically Available Soft State Eventual Consistency 的简写：
BA：Basically Available 基本可用，分布式系统在出现故障的时候，允许损失部分可用性，即保证核心可用。
S：Soft State 软状态，允许系统存在中间状态，而该中间状态不会影响系统整体可用性。
BASE 理论本质上是对 CAP 理论的延伸，是对 CAP 中 AP 方案的一个补充。
不同于 ACID 的刚性事务，在分布式场景下基于 BASE 理论，就出现了柔性事务的概念。要想通过柔性事务来达到最终的一致性，就需要依赖于一些特性，这些特性在具体的方案中不一定都要满足，因为不同的方案要求不一样；但是都不满足的话，是不可能做柔性事务的。