blue-bg-header-size.png

Deployment

​

deploy.png

Overview

Fire Insights can be deployed on cloud or on-premise. It can be deployed on AWS, Azure, Google Cloud, Databricks, Cloudera, Hortonworks.

AWS_SPARKFLOWS_ARCHITECTURE.png

AWS

Fire Insights can be deployed on AWS. It can be deployed on a standalone EC2 machine. It can then read data from S3, Redshift etc. process them and write out the results to S3, Redshift etc.

​

Or it can be deployed on the edge node of an EMR cluster. In this case it would submit the jobs to the EMR cluster for processing.

sparkflows_azure_hdinsights.png

Azure

Fire Insights can be deployed on Azure. It can be deployed on a standalone  machine. It can then read data from ADLS, SQL Server etc. process them and write out the results to ADLS, SQL Server etc.

​

Or it can be deployed on the edge node of an HDInsight cluster. In this case it would submit the jobs to the HDInsight cluster for processing.

sparkflows_cloudera.png

Cloudera

Fire Insights can be deployed on the edge node of a Cloudera Cluster. It then submits the jobs to the Cluster. Fire interacts with HIVE, HDFS, Kafka etc.

sparkflows_azure_databricks.png

Databricks

Fire Insights can be deployed on one or more machines. The jobs get submitted to the Databricks cluster.

SPARKFLOWS-STANDALONE-ARCHITECTURE.png

Laptop

Fire Insights can be deployed on a standalone machine.

  • Facebook - White Circle
  • LinkedIn - White Circle
  • Twitter - White Circle