Build a Data Analytics Platform with Bitnami Deployment Blueprints
For enterprise organizations to stay competitive, there is an ongoing drive to optimize and scale the delivery of products and services. Data has become a critical solution component for achieving these goals.
As part of enterprise cloud adoption, application architecture and deployment patterns evolve into distributed systems with inter-connected software runtimes (micro-services). Similarly, following cloud-native deployment principles, modern data platform implementations require deploying a distributed system of stateful software runtimes.
Despite the benefits of horizontal scale and deployment agility, modern data platforms also introduce new deployment challenges. This series explores cloud-native deployment patterns for data platforms and solutions to simplify the deployment complexity that comes along with them, together with a practical example of using a deployment blueprint to set up a "small" data platform with Apache Kafka, Apache Spark, Apache Solr and Tanzu Observability.
What will you learn?
Learn about cloud-native deployment patterns for data platforms and solutions
Understand deployment challenges for data platforms
Learn about the advantages of using blueprints for deployment
Create a data analytics platform with Apache Kafka, Apache Solr and Apache Spark using a blueprint