Orchestera provides managed Apache Spark clusters directly within your AWS environment, ensuring you avoid compute markup costs. You can leverage built-in autoscaling and fault tolerance to optimize your data processing tasks. The platform includes integrated pipeline monitoring to help you manage and track your workflows efficiently.
You can get started for free to explore how this solution streamlines Spark deployments on Kubernetes - no Data Infrastructure Engineering experience required to provision the cluster!
Features:
- Integrated AI Debugger for Spark pipelines
- Spark History Server
- JupyterHub to launch Spark notebooks as Spark drivers
- Data Lakehouse Ready with Apache Iceberg
- End to end provisioning of Apache Spark clusters on EKS in your own AWS accounts
- Workload based scale in/out so you never pay beyond what's needed
- Orchestera CLI for simplified configuration of your AWS accounts and permissions
For a limited time, you can provision one cluster completely for free with no cpu / memory limits on your AWS resources.
Comments (1)
Excited to launch Orchestera - a PaaS that allows you to orchestrate Apache Spark clusters in your own AWS account. Unlike Databricks and EMR, we don't charge additional markup on EC2 compute.