- Reduced deployment time by **66%** by [implementing ability](https://github.com/apache/incubator-kie-kogito-operator/commit/175a6356c5474f2360ccb8ae835e0b9b2d653cf1) to
- Reduced deployment time by **66%** by [implementing ability](https://github.com/apache/incubator-kie-kogito-operator/commit/175a6356c5474f2360ccb8ae835e0b9b2d653cf1) to
using only command-line (**GoLang** used for this and below).
using only command-line (**Kubernetes/GoLang** used for this and three below).
- Implemented ability for Kubernetes operator to fetch data
- Implemented ability for Kubernetes operator to fetch data
from a deployed service and update config with data.
from a deployed service and update config with data to
deprecate reliance on startup script.
- Added startup probes to handle starting legacy application containers that require additional startup time.
- Added startup probes to handle starting legacy application containers that require additional startup time.
- Refactored probes to [have default values](https://github.com/apache/incubator-kie-kogito-operator/commit/af4977af228ec8648be28779259d4552246b656f) assigned based on
- Refactored probes to [have default values](https://github.com/apache/incubator-kie-kogito-operator/commit/af4977af228ec8648be28779259d4552246b656f) assigned based on
deployed YAML while also fixing reconciliation issues.
deployed YAML while also fixing reconciliation issues.
- Rewrote the **Jenkins** nightly pipeline to run [in a GitHub
- Rewrote the **Jenkins** nightly pipeline to run [in a GitHub
- Wrote [documentation](https://github.com/apache/incubator-kie-kogito-operator/blob/1534c03d1d26bec08a16608a775782bf8b305de9/docs/GUIDE_FOR_KOGITO_DEVS.md) on how to get started with the project to onboard new
using a trigger keyword to test all submitted PR's.
- Took initiative to write [documentation](https://github.com/apache/incubator-kie-kogito-operator/blob/1534c03d1d26bec08a16608a775782bf8b305de9/docs/GUIDE_FOR_KOGITO_DEVS.md) on how to get started with the project to onboard new
- Web app to give rarity rankings to NFT's within minutes of their metadata being revealed and check which are listed (based on rarity and price filters) on the OpenSea marketplace using their API.
- Web app to give rarity rankings to NFT's within minutes of their metadata being revealed and check which are listed (based on rarity and price filters) on the OpenSea marketplace using their API.
- Reverse engineered the ranking algorithm to match the
- Reverse engineered the ranking algorithm to match the
leading rarity ranking site's rankings (scraped using
leading rarity ranking site's rankings ([scraped](https://github.com/Kevin-Mok/rarity-surf/blob/django/rarity_check/project/scrape.py) using
Selenium) with a **discrepancy of <0.25%**.
Selenium) with a **discrepancy of <0.25%**.
- Used app to frontrun purchases of **top 5%** rarity NFT's
- Used app to frontrun purchases of **top 5%** rarity NFT's
against competing buyers.
against competing buyers.
- Wrote **Django (Python)** backend to fetch metadata from IPFS, store rarity rankings in PostgreSQL and serve rarity data using GraphQL.
- Wrote **React** frontend with hooks to dynamically load rarity data. Styled with Tailwind.
- Wrote **Django (Python)**[backend](https://github.com/Kevin-Mok/rarity-surf) to fetch metadata from IPFS, store rarity rankings in PostgreSQL and serve rarity data using GraphQL.
- Wrote **React**[frontend](https://github.com/Kevin-Mok/rarity-surf-frontend) with hooks to dynamically load rarity data. Styled with Tailwind.