•Created a Kubernetes monitoring developer tool targeting and acquiring node status data to identify and isolate instances of node failure within k8 clusters.
•Leveraged Prometheus and its query language, PromQL in order to generate queries reflecting node health status in a result dependent drop down to fetch targeted status metrics for users involving selecting a specific replica set to monitor and presenting any abnormal spikes in CPU usage above a 5% average range back to the client.
•Implemented React and React Hooks to utilize useState and useEffect for state management in conjunction with React’s component reusability and unidirectional data flow to pass the state of 1 or more detected CPU usage irregularities to child components.
•Detected anomalies are identified based on desired scraping intervals, increasing effectiveness and accuracy over using Kubectl by over 10%.
•Developed the Kubernetes Integration Platform using Node.js and Express, ingesting a stream of k8 cluster CPU utilization, network latency, and pod runtime metrics for SRE teams to monitor their microservices at scales, achieving a 20% reduction in average response time due to efficient routing and management of HTTP requests.
•Employed Docker images to bundle the application along with its dependencies, enhancing workflow and leveraging its isolation capabilities to mitigate potential conflicts within the application when utilized on more than 1 device.
•Developed under tech accelerator OS Labs.
