How does Spring Batch Make a Batch Developer’s Life easier? I explain the details in the next section. Spring Batch takes care of most of these issues. This is a considerable amount of work on the developer’s side.
Cloud-native batch applications should be scalable by design.Īll these aspects should be taken into consideration when designing and developing cloud-native batch applications. Correctly processing large volumes of distributed data is probably the most challenging point. We are dealing with an unprecedented amounts of data, which is impossible to handle on a single machine any more. Other questions about how things are going.īeing able to have these KPIs at a glance on a dashboard is vital for efficient operations.ObservabilityĪny modern batch architecture should be able to know at any point in time some key metrics, including: In case of failure, It would be inefficient to not be able to restart a job from where it left off and “lose” the cpu/memory/bandwidth usage of the previous run (and hence be billed twice or more!). Cost EfficiencyĬloud infrastructures are billed by cpu/memory/bandwidth usage. A cloud native batch application should be ready to deal with this kind of issues by design. Moreover, some platforms, such as Kubernetes, have some known limitations about the eventuality of running the same job twice. It is not uncommon that the human error of running a batch job twice has some big financial consequences (such as what happened to Walgreens, ANZ Bank, and NatWest, to name a few). Cloud native batch applications should be designed in a fault-tolerant way. Moreover, even the nodes on which those processes are run can die at any time and be replaced with healthy nodes. Fault Toleranceīatch processes typically interact with other services (such as databases, messages brokers, web services, and others) which are, by nature, flaky in cloud environments. Challenges of Designing and Running Batch Workloads in the Cloudĭesigning cloud-native batch applications might seem easy compared to web applications, but this is not true. In this blog post, I introduce some of the challenges a batch developer or architect may face when designing and running batch applications at scale and show how Spring Batch, Spring Boot and Kubernetes can tremendously simplify this task.
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Nowadays, the modern cloud computing era comes with a whole new set of challenges for how to develop and operate batch workload efficiently in a cloud environment. Batch processing has been a challenging area of computer science since its inception in the early days of punch cards and magnetic tapes.
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