The following table is the recommended specification for FST Network's Logic Operating Centre (LOC). The cluster have 3 nodes running on either third party cloud providers or on-premise servers. Each node should meet the following specification: Item Minimum Requirements CPU 20 cores (8 cores x 2 nodes + 4 cores x 1 node)

Introduction In this topic, we are going to introduce how to (1) parse XML, (2) use the file storage agent, and (3) emit and search events. To explain briefly, we are going to parse ++Headline XML++ through the file storage agent and emit these data as events. Afterwards, we will search these emitted events with respect to the category code of the headlines (queried by API) and extract the filtered file names from these events. With these file names, we are going to compose URLs and use the file storage agent again to retrieve the news contents from ++News Content XML++ as our final output. The reason why we only keep the headlines as events is because through this way we could reduce the burden to query the existing system whenever there is a need to search certain news.

In this "MVWAP" data process demonstration, in addition to logic writing, we will be focusing on the ++design thinking of the entire process++ and the ++use of agents++. Before LOC Setup At the beginning of the entire process, we need to go through the analysis process(BA/SA) to clarify the needs to help developers build up data processes. After we specify our requirements in BA/SA process, we have designed where/what/how users can get MVWAP index and mapped these requirements back to design: What Trigger point does the user use to execute a data process? Which Data Source should the user read/write? Finally, what kind of Output does user want?

In this section, we are using a simple example to demonstrate how to build a "Hello World" data process. After executing this data process, we are going to complete these 3 things (1) parse JSON data from the request body (payload) to print out name (2) print out "Hello World" (3) print out the result of calculations Create Data Process To being with the 1^st^ logic (namely, 1.js), we are going to create a few variables and keep them in the session storage for later use, including a string that is parsed from the request body, a hello variable, and a number.

In the previous courses, we have provided the event usage of "Lakeside" and "MA". By now, you should have understood what an event is and be more familiar with events through coding and implementations. In this topic, we start to share "how" FST designs events to keep reference records so as to create an anchor. Usually, events are used to keep transaction/status/time series data (with timestamp nature) centralise reference data record(data exchange between heterogeneous systems) create data anchor for analyzing create data lineage for auditing

For more details of searching and emitting event, please refer to ++Agent List++ Also, you might need a reference table for the variable differences when it comes to searching and emitting events. ++Event Fields Comparison Table++ In the previous course, we have showcased the use case of Lackeside Oasis Café to demonstrate how to emit events (as well as searching events) and show some practical usages through events via LOC. In this course, we will extend that use case and introduce you a more advanced usage of events. In this topic, we extend the "MA" use case that we have mentioned in the previous topics, so as to make you master in events. One of the merits of LOC as a framework is to allow developers to easily maintain highly readable events when implementing the operations or services. For the reason that, integration and auditable lineage can be designed and developed in one framework, which might require more than two softwares/system tools to implement in the past. In this topic, we will reuse the MA example and extend the data process and logics in order to achieve these things below: search events

In this session, we are using a simple example to demonstrate how to configure an API route as an endpoint by connecting to a basic "Simple Moving Average (SMA)" data process, with the data source from MySQL to compute the SMA for a specific time period from today. That is, when a user triggers this data process with the input of Stock No. and a Window, it will read the data of that specific stock, calculate MA corresponding to the required window, and lastly return an MA value for that stock. In this example, in addition to logic writing, we focus more on the design thinking of the entire process and the use of agents. First of all, we need to specify our requirements. In this example, we want to provide additional information into the data process on top of the existing data. Based on this, we begin to imagine where/what/how users can get this information through the API. To recap, we have mentioned these design ideas of "building a B/D process" in the previous topic, and we are mapping these design requirements back to that: What Trigger point does the user use to execute a data process? Which Data Source should the user read/write? Finally, what kind of Output does user want?

Use Case: Lakeside Oasis Café Data Process Pre-Planning A fast food restaurant, Lakeside Oasis Café, has just opened and the manager of the café wants to use LOC CLI to monitor the orders between the counter and the kitchen. :::success You can click Details to see more codes. :::

1.1.0 Login theme updated Data Process and Logic Tag Administration menu containing Audit Log for Logic and Data Process New Data Discovery design New Repositories added to Data Discovery (Logic & Data Process) LOC Studio synced with CLI Data Processes and API Routes

0.6.0 New Features tag CRUD deploy data process along with tags message queue client CRUD & init publisher CRUD & init subscriber CRUD & init Scheduler

FST LOC CLI Guidebook LOC CLI v0.6.0 Latest Release Date: 1 August 2022 (Release Note) Introduction Concepts LOC CLI Installation LOC CLI Commands Getting Started - Hello World Local Simple Runtime Execution

Back to LOC CLI Guidebook Setup LOC CLI Environment Getting Started - JavaScript Getting Started - TypeScript LOC CLI Commands Local Simple Runtime Execution Here we will use Pure-FTPd to run a local FTP server so that we can test the file storage agent. Modify saffron-evenstore.yaml