Debezium Capture the changes from transaction log and propagate as events to any kind of downstream consumers.
This allows us to take the data from our operational database over to other systems that would like to have the data and process the data.
We can push events the debezium capture from the source operational database directory to the downstream systems like Elasticsearch or to Data-warehouse .
Optimization of code across the entire product is crucial.
Leverage code profilers to identify and optimize code segments.
Assess for memory leaks, CPU optimization, and resource consumption concerns.
Configuration Tuning
Fine-tune configurations system-wide.
Experiment, test, and optimize settings like Tomcat/WebLogic JDBC and thread pools.
Proper configuration with optimal values is vital for overall product performance.
Database Tuning
Optimizes the database by fine-tuning SQL queries, indexing, and connection pooling.
Utilize tools like Oracle's AWR report for in-depth analysis and fine-tuning.
Infrastructure Tuning
Benchmark hardware and instance sizes to align with the workload.
Determine CPU and RAM requirements and the number of Kubernetes pods needed and ensure they meet workload and SLA expectations.
This process involves planning, testing, tuning, and retesting.
Architecture Tuning
Evaluate the architecture and consider changes such as incorporating a CDN for improved performance across various locations or implementing a queuing system to enhance performance in specific areas.
Network Tuning
Focuses on vital aspects in today's distributed systems, addressing issues such as DNS, protocols, latency, and firewall tuning.
Optimization efforts should target effective tuning for better performance, especially when the database is situated in one region and customers are in another.