Simplify the complete operational complexity of running production databases on Kubernetes.
Resource provision and dynamic scaling.
Maintenance and failover tasks.
Monitoring and insights.
Security best practices for data and traffic encryption.
A consistent Yaml specification to provision any type of cluster and their internal resources.
Each cluster supports a fine grained configuration of their settings and includes native integrations with other Kubernetes services (i.e. Secrets).
Ensemble ensures that the configuration is always up to date. If necessary, it performs a rolling update or scales transparent to the user to reach the desired configuration.
A common interface based on the Operator pattern to provision, operate and manage a variety of databases on Kubernetes.
Use a single service to model and automate a complete data pipeline solution: databases, queues, schedulers or olap analytical warehouses.
Reduce the complexity of running databases on Kubernetes and ensure high availability and security compliance along your data-layer.
Run a long lived database (e.g. Postgresql or Redis) alongside your application.
Define a complete data-layer (e.g. Kafka and Clickhouse) to support data processing at scale.
Create ephemeral deployments (e.g. Spark) for specific analytical jobs.