Hybrid Cloud Analytics: Scaling analytics workloads on on-premise to public clouds with Alluxio

This whitepaper details how to leverage any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) to scale analytics workloads directly on on-prem data without copying and synchronizing the data into the cloud. We will show an example of what it might look like to run on-demand Starburst Presto, Spark, and Hive with Alluxio in the public cloud using on-prem HDFS.

The paper also includes a real world case study on Two Sigma, a leading hedge fund based in New York City, who deployed large clusters of Google Compute Engine VMs with Spark and Alluxio using on-prem HDFS as the underlying storage tier.

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Running Spark & Alluxio in Kubernetes

The data orchestration layer bridging the gap between data locality with improved performance and data accessibility for analytics workloads in Kubernetes, and enables portability across storage providers.
An overview of Alluxio and the cloud use case with Spark in Kubernetes. Learn how to set up Alluxio and Spark to run in Kubernetes.

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Alluxio on EMR: Fast Storage Access and Sharing for Spark Jobs

Traditionally, if you want to run a single Spark job on EMR, you might follow the steps: launching a cluster, running the job which reads data from storage layer like S3, performing transformations within RDD/Dataframe/Dataset, finally, sending the result back to S3. You end up having something like this.
If we add more Spark jobs across multiple clusters, you could have something like this.

Running Spark & Alluxio in Kubernetes

Alluxio Community Office Hour *

The latest advances in container orchestration by Kubernetes bring cost savings and flexibility to compute workloads in public or hybrid cloud environments. On the other hand, it introduces new challenges such as how to move data to compute efficiently, how to unify data across multiple or remote clouds, how to co-locate data with compute and many more. Alluxio approaches these problems in a new way. It helps elastic compute workloads realize the true benefits of the cloud, while bringing data locality and data accessibility to workloads orchestrated by Kubernetes

Accelerate Spark workloads on S3

Alluxio Webinar *

Register for this webinar to learn how to run EMR Spark on Alluxio as a distributed file system cache for S3.

How do you run Spark on On-Premise S3?

Introducing S3 and Spark S3 has become the de-facto standard API for digital business applications to store unstructured data chunks. To this end, several vendors have S3-API compatible offerings that allow app developers to standardize on the S3 API’s on-premise, and port these apps to run on other platforms when ready. So, what is S3 and … Continued

Recap: Spark+AI Summit 2019

Alluxio is a proud sponsor and exhibitor of Spark+AI Summit in San Francisco.
What’s Spark+AI Summit? It’s the world’s largest conference that is focused on Apache Spark – Alluxio’s older cousin open source project from the same lab (UC Berkeley’s AMPLab – now RISElab).

Two Sigma Case Study: Cloud bursting with Spark for on-premise Hadoop

Two Sigma, a leading hedge fund with more than $50 billion under management, turned to Alluxio for help with bursting Spark workloads in a public cloud to enable hybrid workloads for on-premise HDFS. With Alluxio, Two Sigma sees better performance, increased flexibility and dramatically lower costs with the number of model runs per day increased by 4x and the cost of compute reduced by 95%.

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