Bluedata Epic 2.0 is a Docker-based platform released on September 23, 2015, that offers flexible deployment options and improved resource management for big data applications. It supports multi-host setups, enhanced Apache Spark integration, and features a big data app store for one-click deployment of analytics tools. The platform emphasizes agility, cost savings, and faster insights while accommodating traditional Hadoop and Spark functionalities.

1. INTRODUCING
BLUEDATA EPIC 2.0
September 23, 2015

2. Big Data Traditional
Assumptions
Bare-metal
Data locality
HDFS on local disks
New Realities
with BlueData
Docker containers
Compute and storage
separation
In-place access on
remote data stores (e.g.
HDFS, NFS, Object)
New Benefits
and Value
Elasticity and improved
utilization
Agility and cost savings
Faster time-to-insights
Big Data – New Realities

3. BlueData EPIC Software Platform

4. BlueData EPIC 2.0 Highlights
• Docker-based platform for deployment flexibility
– Multi-host deployments: supports physical servers and virtual machines
– Single operating system: containers inherit host OS updates
– Simplified packaging distributions and apps: Docker images
• Apache Spark notebooks and other innovations
– Enhanced self-service Spark deployment
– Clusters pre-integrated with web-based notebooks (Zeppelin)
– SparkR, Spark Streaming, MLlib, Spark SQL, and Spark Streaming-SQL
• Big Data App Store with one-click deployment
– Packaged with Hadoop and Spark distributions, new analytics tools
– One-click deployment for select ISV partner applications
– Application Workbench to create and test images

5. Docker Deployment Flexibility
Physical
Machines or
VMs as HOSTS
Docker
containers as
NODES

6. Big Data Innovation with Containers
• Docker containers for transparent, lightweight virtualization
– Enables multi-node Hadoop/Spark clusters on physical servers or in VMs
– Customizable container flavors/sizes for CPU, memory and storage
– Configurable root disk sizes (local storage for containers)
– Pre-integrated Docker images for Hadoop ecosystem products
• IP management and networking specific to Big Data use cases
– Container provisioning and orchestration across multiple hosts
– Leveraging hosts with single network interface
– Retaining IP address after container (e.g. Hadoop node) re-boot
– DHCP management
• Policy engine for multi-tenancy
– Controlling resources available for containers based on tenant quotas

7. Spark 1.4 and Zeppelin Notebooks

8. Big Data App Store

9. One-Click Big Data App Deployment

10. www.bluedata.com