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Enterprise Reporter 3.2.1 - Installation and Deployment Guide

Product Overview Installation Considerations for Enterprise Reporter Installing and Configuring Enterprise Reporter Managing Your Enterprise Reporter Deployment Troubleshooting Issues with Enterprise Reporter Appendix: Database Content Wizard Appendix: Encryption Key Manager Appendix: Log Viewer

Failover Recovery using SQL Clusters

Using a SQL cluster instead of a single server allows for automatic failover recovery in the event that a SQL Server® is down. Tasks are automatically passed to another SQL Server®. Your cluster can be configured with Always On.

Cluster Deployment Considerations

The following sections can help you get the most out of Enterprise Reporter:

Consider the Data to Collect Before Deploying Nodes

There is a relationship between the design of your discoveries and the physical deployment of your clusters and nodes. By understanding what you want to collect, and what network and hardware resources you have available, you can deploy Enterprise Reporter in a way that makes sense for your environment. When you create a discovery, you assign it to a cluster. The actual work of the collection can be done by any node in the cluster, load balanced by the Enterprise Reporter server. This means that each node should:

You may not have this insight before you start using Enterprise Reporter, however you can modify your deployment at any time. If you are creating a discovery with targets that are not near the nodes of any of your clusters, consider creating a new cluster to support this.

See also:

Fine Tune Each Cluster and Node

A discovery is resolved to a number of tasks. Each task is then automatically assigned to a node in the cluster by the server, depending on the node’s availability. If you are collecting from many targets at the same time, you can increase performance by adding more nodes to the cluster and by ensuring that each node is configured to allow the node to optimize how many concurrent tasks it can process (by setting the maximum number of concurrent tasks to a value of zero).

You can see the amount of time it took to run each instance of the discovery in the history view. If you drill down, you can see how the time was distributed across the targets, and what node did the processing. This information can aid in your decisions about how to scale up your deployment.

Adding nodes and optimizing concurrent tasks can only speed things up if there are multiple tasks to assign to the node. When a large amount of data is collected from an individual target, only one task will be created. In that case, you can improve performance by increasing the CPU, the available disk space, and the memory of the node host computer, or by looking at other factors, such as network latency.

The discovery type determines what the targets are and helps you decide on your options for speeding up collections. Clusters that handle large targets will benefit from increasing the CPU, available disk space and memory of the node host computers, or being dedicated to a smaller number of discoveries. The following table outlines how each discovery type is broken down into tasks:

Table 17. Discovery Types

Active Directory®

Each domain, or per object type by domain

Azure Active Directory

Each tenant

Azure Resource

Each tenant

Computer

Each computer

Exchange®

The Exchange Organization, or per object type, or per object type per server

Exchange Online™

The Office 365 tenant

File Server Analysis

Each computer

Microsoft SQL

Each computer

Microsoft Teams

Each tenant

NTFS

Each computer or per share by computer

OneDrive

Each tenant

Registry

Each computer

See also:

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