Expertise
Jaehyeon worked at the intersection of real-time data engineering and developer education, focused on making Apache Kafka and Apache Flink approachable for platform and data engineering teams.
Experience
Jaehyeon was a Developer Experience Engineer at Factor House, where he created technical content and tooling for platform engineers working with Kafka and Flink. He previously worked at Simple Machines and Cevo Australia, building streaming data platforms for enterprise clients.
Certifications
- Certified Kubernetes Administrator (CKA)
- Generative AI for Software Development
Education
- MSc, University of New South Wales
- MSc, Seoul National University
- BSc, Kyung Hee University
Latest articles
Defense in depth: unifying RBAC and data policies
Balance Kafka velocity and compliance. Learn how Kpow uses RBAC and Data Policies for safe, self-service production debugging without manual tickets.
Foundational Kafka data inspection in Kpow
Stop fighting complex Kafka serialization. Learn how Kpow uses Auto SerDes, kJQ, and transparent queries to streamline data inspection.
Triage, repair, and replay: Kafka remediation
Fix broken Kafka data pipelines fast. Learn how Kpow replaces messy CLI scripts with an intuitive UI to isolate, repair, and re-inject data.
Integrate Kpow with WarpStream
Integrate Kpow with WarpStream in minutes. Gain unified visibility and control over your BYOC Kafka data plane and Schema Registry in the Kpow UI.
KIP-932 queues for Kafka explained
Discover how Kafka's KIP-932 Share Groups bring native queue semantics to your event streaming architecture, and the new complexities engineers must manage.
Beyond JMX: supercharging Grafana dashboards
Move beyond raw JMX noise. Learn how to feed high-fidelity, pre-calculated Kafka metrics from Kpow into Grafana for proactive capacity planning and incident response.
Kafka observability with Kpow
Operating Apache Kafka at scale often leads to reactive maintenance. This article covers three gaps in context, data quality, and governance, and a strategy for operational excellence with Kpow.
Kafka audit trail with Kpow: who changed what, streamed to Slack
Apache Kafka keeps no built-in record of who made an admin change. How Kpow's audit log records user actions and streams them to Slack with a webhook.
Rapid Kafka diagnostics: a unified workflow
Fragmented tools force engineers to manually piece together logs and metrics when troubleshooting Kafka. This guide shows how Kpow's unified workflow finds a stall, inspects data, and resolves it.
Integrate Kpow with StreamNative Cloud
Integrate Kpow with StreamNative Cloud in minutes. Gain unified visibility and control over your managed Kafka brokers and Schema Registry in the Kpow UI.
Self-service Kafka governance with ServiceNow
Implement Just-in-Time Kafka access by integrating Kpow with ServiceNow. Automate approvals and temporary policy management to enhance security and developer self-service.
Integrate Kpow with OCI Streaming for Kafka
Integrate Kpow with Oracle Cloud Infrastructure Streaming with Apache Kafka in minutes and gain unified visibility and control over your OCI brokers and ecosystem components.
Deploy Kpow on EKS via AWS Marketplace using Helm
Deploy Kpow on Amazon EKS via the AWS Marketplace using Helm and eksctl to automate IRSA, enabling secure license validation via AWS License Manager and usage reporting for hourly subscriptions.
Set Up Kpow with NetApp Instaclustr Platform
Integrate Kpow with Instaclustr in minutes. Gain unified visibility and control over your managed Kafka brokers, Karapace Schema Registry, and Kafka Connect through our toolkit.
Introducing Webhook Support in Kpow
This guide shows how to configure Kpow webhooks that send real-time audit log alerts from your Kafka environment into collaboration platforms like Slack and Microsoft Teams.
From batch to real-time CDC with Debezium
This project turns the static "theLook" eCommerce dataset into a live stream. A Python generator simulates activity in PostgreSQL while Debezium captures changes and streams them to Kafka.
Real-time leaderboards with Kafka and Flink
Learn how to build a real-time "Top-K" analytics pipeline using Apache Kafka, Apache Flink, and Streamlit to ingest, process, and visualize live events on an interactive dashboard.
Integrate Kpow with Google Managed Schema Registry
Kpow 94.3 integrates with Google Cloud's managed Schema Registry using native OAuth. This guide covers configuring authentication and using Kpow to manage Avro schemas.
Integrate Kpow with Bufstream
Integrate Kpow with Bufstream in minutes. Gain unified visibility and control over your Kafka-compatible broker and Buf Schema Registry in the Kpow UI.
Integrate Kpow with Redpanda Streaming Platform
Integrate Kpow with Redpanda in minutes. Gain unified visibility and control over your Redpanda brokers and built-in Schema Registry in the Kpow UI.
Integrate Confluent-compatible registries in Kpow
This guide shows how to integrate Confluent-compatible schema registries - Confluent Schema Registry, Apicurio Registry, and Karapace - and manage them all through Kpow.
Set up Kpow with Google Cloud Managed Kafka
Integrate Kpow with Google Cloud Managed Service for Apache Kafka in minutes. Gain unified visibility and control over your managed Kafka brokers and Schema Registry.
Resetting Kafka consumer offsets safely: clear, reset and skip with Kpow
Resetting a consumer group's offsets makes it reprocess or skip records. How to clear, reset and skip Kafka consumer offsets safely, step by step, in Kpow.
Set up Kpow with Amazon MSK
Integrate Kpow with Amazon Managed Streaming for Apache Kafka in minutes. Gain unified visibility and control over your AWS brokers, MSK Connect, and Glue Schema Registry.
Set Up Kpow with Confluent Cloud
Integrate Kpow with Confluent Cloud in minutes. Gain unified visibility and control over your managed Kafka brokers, Schema Registry, Managed Connect, and ksqlDB.
How to query a Kafka topic
Querying Kafka topics is a critical but often complex and time-consuming task for engineers building streaming applications. Kpow's data inspect feature simplifies and speeds up Kafka topic queries.