Overview
This document contains the results of testing Fiscal year rollover in scope of ticket
| Jira Legacy | ||||||
|---|---|---|---|---|---|---|
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- 8 m6i.2xlarge EC2 instances located in US East (N. Virginia)us-east-1
- 2 instances of db.r6.xlarge database instances: Writer & reader instances
- MSK ptf-kakfa-3
- 4 kafka.m5.2xlarge brokers in 2 zones
Apache Kafka version 2.8.0
EBS storage volume per broker 300 GiB
- auto.create.topics.enable=true
- log.retention.minutes=480
- default.replication.factor=3
Modules memory and CPU parameters:
Modules | Version | Task Definition | Running Tasks | CPU | Memory | MemoryReservation | MaxMetaspaceSize | Xmx |
|---|---|---|---|---|---|---|---|---|
| mod-orders | 12.6.6 | 10 | 2 | 1024 | 2048 | 1440 | 512 | 1024 |
| mod-orders-storage | 13.5.0 | 5 | 2 | 128 | 1024 | 896 | 128 | 768 |
| mod-finance | 4.7.1 | 5 | 2 | 128 | 1024 | 896 | 128 | 768 |
| mod-finance-storage | 8.4.1 | 8 | 2 | 128 | 1024 | 896 | 128 | 700 |
| okapi | 5.0.1 | 6 | 3 | 1024 | 1684 | 1440 | 512 | 922 |
| nginx-okapi | 2022.03.02 | 6 | 2 | 128 | 1024 | 896 | - | - |
| pub-okapi | 2022.03.02 | 6 | 2 | 128 | 1024 | 896 | - | 768 |
Methodology/Approach
Before each fiscal year rollover data should be preapred.
Before data importing next schemas should be truncated:
- mod_finance_storage.budget
- mod_finance_storage.transaction
- mod_finance_storage.budget_expense_class
- mod_finance_storage.expense_class
- mod_finance_storage.fund
- mod_finance_storage.fund_type
- mod_finance_storage.fiscal_year
- mod_finance_storage.ledger
- mod_finance_storage.group_fund_fiscal_year
- mod_orders_storage.purchase_order
- mod_orders_storage.po_line
- mod_orders_storage.titles
- mod_notes.note
To import data (100K orders: 50% open, 50% closed) backup of DB schemas was created. It can be found in "Finance" folder on the host.
For other orders quantity and data structure JMeter script should be used (perf-testing/workflows-scripts/fiscal_year/FY_rollover_preparation on the GitHub). But in this case data generation will take a lot of time.