What is the purpose of this article?

The purpose of this article is to make a cron to keep a check on a daily basis whether the orders are getting picked up (for delivery) on time or not. If not, then which all orders have got delayed.
In this article, we will thoroughly discuss Why we are making this cron, What will the cron do, what are the requirements to achieve this cron and its infrastructure diagram.

Why we are making this cron?

Order sync and return sync happen depending on events.
Whenever we get an update in DB ( either in case of order or in case of return), we sync that data and update their values in Algolia. ( either in case of order or in case of return) , we sync that data and update their values in Algolia.
The problem we are facing is that we don't get the updates every day and DB does not get updated every day. Because of this, the last update remains as the latest status in Database.

For eg., Suppose the order scheduled to be RTS on 10th Jan, 2022 did not get picked up by the courier partner. As a result, there will be no update on DB about RTS getting delayed. On 11th Jan, 2022, order should be considered as " RTS delayed " with is a reason known. Meanwhile, in DB, update of 10th Jan or 9th Jan will be visible (i.e.,previous update) as RTS did not happen on expected date. So it's status couldn't be updated.

To handle this condition, we will make a cron. This cron will listen all the RTS events and check whether the order is delayed or not and save them in Database.
This will help us keep a track on all the orders that got RTS delayed .

What are the steps for Event Flow ?

Every day at a particular time the cron should run which will check all the orders that got RTS delayed for past two days.

for example- A cron will run at 10 pm every day. This cron will check that how many orders were there who had to be picked up on the previous and this day.

Now for those orders we will check whether the pickup has been done by the courier partner or not. If not, then we will save their tags (status- "RTS delayed") in Database .
This cron will keep us updated about the orders' shipment status and relieve us from the burden of manually tracking them in case of delay in getting picked up.

Steps for events flow

How will the cron function?

Step 1: Shipment Events are received from ClickPost and uniware at WMS module. From uniware we receive, “created”,”accepted”,”picking”,”picked”,”packed” and “dispatched” status. From Clickpost we receive these statusus- “out for delivery”,”in transit”,”out for pickup”, “picked up”, “delivered”.

Step 2: WMS module publishes the events on a PUBSUB topic.

Step 3: In the Client-Portal module, there are pull-based subscribers against the PUBSUB topic. These subscribers pull events in batches from the PUBSUB topic, till all the events are acknowledged by the subscriber. The shipments events are pulled from these 4 pubsub topics - "/_ah/api/esb/v2/orders/event/wms/shipments/pull", "/_ah/api/esb/v2/orders/event/poe/shipments/pull", "/_ah/api/esb/v2/orders/event/poe/cancelled/pull", "/_ah/api/esb/v2/orders/event/order_items/pull"

Step 4: These events are then published in POST API - v2/orders/event/sync by the subscribers.

Step 5. Now that the list of events are received at v2/orders/event/sync API, we create the Algolia object from the events and update them in Algolia.

Step 6: From POST API - v2/orders/event/sync, we separate RTS events (packed, Ready to Ship) from the list of events.

Step 7: These separated RTS events are published on separate PubSub topic - order_return_events in the eshopbox-client-portal-prod.

Step 8: Pub sub will hit the listener POST - v1/orders/algolia/tags/save. This API will listen the the RTS events from pubsub. It will also check whether the order is delayed or not.

Step 9: After listening events from POST - v1/orders/algolia/tags/save, all the results will be saved in DB.

Table structure.

For the details, to be saved in Database, kindly refer to the link below.

Table Structure for order-return tags, SLA(s), and reasons.

When the order item is packed, we get order details as mentioned below : -

{
   resource=shipment, 
   eventType=PUT,
   eventSubType=packed,
   accountSlug=raymond, 
   actor=SYSTEM, 
   version=v1, 
   request_data=[],
   response_data={
       customerOrderNumber=6727469972, 
       orderSiteID=, 
       vendorOrderNumber=6727469972, 
       externalShipmentID=6727469972-1679-12, 
       externalWarehouseID=ESBMUM_112, 
       externalChannelID=CH1679, 
       externalWmsChannelName=MYNTRA_RAYMOND_MUMBAI_MUM, 
       external_wms_channel_id=1649.0, 
       channelLabel=Myntra PPMP_N, integrationType=5, 
       defaultWarehouseCode=ESBMUM_112, 
       facilityLabel=Mumbai (ZMUM), 
       facilityType=unicommerce, 
       orderDate=2022-02-11 21:31:39, 
       portal_id=3.0, paymentType=cod, 
       expectedShipDate=2022-02-13 12:00:00, 
       order_id=4.2466552E7, channel_id=1679.0, 
       warehouse_id=72.0, channel_account_id=209.0, 
       account_id=126.0, 
       region=National, 
       isMetro=0, 
       isSpecialplace=0, 
       invoiceNumber=SRA212242544, 
       boxType=UNKNOWN,
       isPriorityShipment=0, 
       isGift=0, 
       invoice_url=https://storage.googleapis.com/eshopbox_wms_uploads/myntraLabel/20220212102451727152883.pdf, 
       invoiceDate=2022-02-12 00:00:00, 
       label_url=https://storage.googleapis.com/eshopbox_wms_uploads/myntraLabel/20220212102451548873136.pdf,
       labels=, 
       shippingInfo=[], 
       boxAdditionalRecommendation=[],
       dimension_length=350,
       dimension_width=210, 
       dimension_height=30, 
       weight=546, 
       trackingID=ML0834329651, 
       trackingDomain=, 
       packageID=6727469972,
       barcode=, taxAmount=0.0, 
       shipChargeAmount=0.0, 
       courierName=ML, 
       cp_id=0.0, 
       created_at=2022-02-11 21:31:49, 
       updated_at=2022-02-12 10:24:53,
       status=packed, 
       remarks=, 
       warehousePincode=421302, 
       thirdPartyShipping=true, 
       customerName=Samikshya Parida, 
       customerContactNumber=9999999999, 
       email=xyz@gmail.com, 
       status_updated_at=2022-02-12 10:24:53,
       status_log={
              created=2022-02-11 21:31:49, 
              packed=2022-02-12 10:24:53}, 
              status_log_count={
                      created=1.0, 
                      packed=1.0
              }, 
              status_log_id=76256538, 
              orderExternalCreatedAt=2022-02-11 21:31:46, 
              shippingAddress={
              customerName=Samikshya Parida, 
              addressLine1=Dr. Pankaj Parida, 
              Professor colony near Acharya Harihar Cancer center, 
              addressLine2=Medical College  (Cuttack), city=Cuttack, 
              state=OR, 
              postalCode=753007, 
              countryCode=, 
              countryName=India, 
              contactPhone=9999999999, 
              email=xyz@gmail.com
       }, 
       warehouseAddress={
              addressLine1=Survey no 20/1, Global complex, Godown no. A/6,Village-Kukse Borivali, 
              addressLine2=Near Shangrila Resort, Taluka Bhiwandi, Dist Thane, city=Thane, state=Maharashtra, postalCode=421302, gstin=27AAFCB0498R1ZZ
       }, 
       id=1.0418464E7, 
       isCOD=1, 
       track_payload=[], 
       packed_date=2022-02-12 10:24:53, 
       items=[
		       {
			     lineItemSequenceNumber=3.3735162E7, 
                 orderItemID=6727469972-22742422, itemID=8907921267104,
                 sku=BBAPLPU137458_XXL, 
                 asin=, 
                 productName=Park Avenue Solid Medium Red Regular Fit Regular Collar 3/4th Sleeve Shirts, 
                 quantity=1.0, 
                 customerPrice=599.0, 
                 lineItemTotal=599.0,
                 invoiceTotal=599.0, 
                 cashOnDeliveryCharges=0.0, 
                 discount=0.0, taxRate=0.0,
                 taxAmount=0.0,
                 inventoryItemCode=, 
                 giftMessage=, 
                 giftLabelContent=, 
                 lineItemOrderStatus=, 
                 orderItemIDs=[6727469972-22742422], 
                 productImageUrl=https://s3-eu-west-1.amazonaws.com/imagebucketeshopbox/Flipkart_153_Styles/PWSU01679-B8/1.jpg, 
                 shippingCharges=0.0, 
                 isVirtualKit=0,
                 onhold=0,
                 cancellationAdditionalReason=, 
                 cancellationReason=,
                 customerOrderItemID=
			   }
		]
	}, 
    previous_data=[],
    resource_type=shipment.update,
    account_slug=raymond, 
    custom=[]
}

For understanding Logic Implemenation, please find the below link.

Tags and SLA Logic.

What are the steps to achieve the Cron Implementation ?

v2/orders/algolia/sync/rts API will insert the records in the database with status as 0 and create a Task in Cloud Task orderSyncTrigger.
Once a task is created in orderSyncTrigger, the task queue will hit the orderSyncTrigger API v2/orders/algolia/sync/rts/update.
The orderSycnTrigger API will query the database and fetch the RTS Delayed data for last two days from order_returns_tags table. 3.1. If the numbers of RTS Delayed data fetched is 0 then simply return meaning, the cron is not needed to be run. 3.2. If the numbers of RTS Delayed data fetched is greater than 0 :- a) Run a query in database to fetch the pickup capacity of each order b) if picking capacity has exceeded for the day order was created then check in Database if was_unfulliable = 1 or was_unhold = 1 or or not. c) If true, then set delay reason remains empty and set SLA tag as “SLA Not Applicable”. d) If false then set delay reason as “Overcapoacity at FC” and SLA tag remains empty.
Save all the RTS Delayed data fetched for last two days in Algolia.
Update database and set status as 1 ie., is_rts_sync = 1 for the values fetched meaning that these data have been checked through the cron.

Orders and Shipping Engine

Cron implementation for RTS Delayed Reason