The JusDB Database Engineering Blog

Monitor ETL pipelines with data freshness checks, row count reconciliation, dbt data quality tests, and Slack alerting. Detect silent failures before users do.

Operate Kafka Connect database pipelines with current JDBC and Debezium settings, protected REST access, deliberate DLQ handling, and task-level monitoring.

Use Apache Flink CDC to capture MySQL and PostgreSQL changes — stateful processing, exactly-once semantics, and Kubernetes deployment

Apply GitOps principles to database changes — PR-based schema reviews, automated migrations, and rollback strategies

A production guide to zero-downtime database migrations — why ALTER TABLE causes downtime, the Expand-Contract pattern, safe migration patterns for PostgreSQL and MySQL, and tooling with Flyway, Liquibase, pt-osc, and gh-ost.

Add data quality checks to your pipeline — row count validation, schema drift detection, and anomaly alerting with Great Expectations

UUIDs as primary keys can destroy database performance. Learn why 50M rows went from 0.5ms to 2.3ms inserts, and how to fix it with hybrid approaches.

A production guide to PostgreSQL Row Level Security — policy creation, USING vs WITH CHECK clauses, performance implications with indexes, and multi-tenant SaaS patterns with real schema examples.

Go beyond basics with Debezium — handle schema evolution, manage connector offsets, and build resilient CDC pipelines

Debezium reads MySQL binary logs and PostgreSQL WAL to stream every row-level change as a Kafka event in near real-time — replacing nightly batch ETL with sub-second data propagation.

Stream PostgreSQL changes to Kafka using pgoutput and Debezium — setup, monitoring, and lag management

Implement schema change management with versioning, peer review, and automated validation for safe deployments