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