Monitoring logs is vital for system performance and issue identification. Splunk offers powerful log management and analytics, enabling comprehensive log analysis. In this blog, we explore exporting YugabyteDB logs to Splunk, providing a step-by-step guide.
Ensure robust security and secure access to sensitive data for Spring Boot applications using YugabyteDB’s advanced security features, including TLS encryption, and native cloud secret management services like AWS Secrets Manager, GCP Secret Manager, Azure Key Vault, or Hashicorp Vault.
Source code versioning is important, but what about data? This blog covers how to use Flyway in conjunction with YugabyteDB xCluster replication to manage data version control across multiple data centers.
This blog provides steps to easily stream CDC data from YugabyteDB Anywhere to Azure Synapse Analytics workspace with the help of Azure offerings such as Event Hubs and Azure Data Lake Storage (ADLS) Gen2.
Learn how to configure content-based routing for the YugabyteDB Change Data Capture (CDC) connector. Instead of streaming all change data capture events from a table into a single Kafka Topic, you can reroute an event to other Kafka Topics based on its content. An example use case for this is complying with GDPR regulations, where data needs to be geolocated based on an event’s content.
In this blog, we’ll walk through how to integrate YugabyteDB with a real-time OLAP database-Apache Pinot-using the YugabyteDB Change Data Capture (CDC) connector.
This blog provides a guide to building Spring Boot applications with YugabyteDB using GraalVM’s ahead-of-time (AOT) compilation to generate a native image. The guide covers the necessary prerequisites and steps to trigger the native build, including how to handle dependencies lacking reachability metadata with explicit runtime hints.
There is now support for YugabyteDB in Testcontainers. This blog explores how to use Testcontainers to write integration tests for a Spring Boot application with the Yugabyte database.
In this blog, we will explore how YugabyteDB Change Data Capture (CDC) and open table formats like Apache Iceberg can be used to build data lakes in Amazon S3 using a single copy of the data and achieve low data ingestion latency while avoiding costly rewrites to support updates/deletes and schema evolution.
In this blog, we explore how to stream data from YugabyteDB’s Change Data Capture feature to Snowflake using SnowflakeSinkConnector on Confluent cloud via Kafka connect.