Scalability

Scalability and Management

XpoLog allows for easy scalability by using a shared storage between different servers. You can deploy as many instances/servers as you need at any given time, and then if you grow, you just add more servers. You are essentially unlimited, as you can deploy as many servers as you want.

 

  • Logical Data Structure

 

The XpoLog log management platform organizes all your data in a logical structure. This makes log management, browsing, and searching much more efficient.
The XpoLog log management platform organizes all data nodes in logical context and structure in the form of a logical tree. You can redefine those virtual structures to present your own system architecture in your own logical tree. This makes your data node management, browsing, and searching much easier.
With the nodes arranged in a tree, they are flexible, very easy to find, and easier to know their origin.

 

  • Advanced Data Tagging

 

The XpoLog tagging engine makes it possible to cluster information, group sources by Apps, types, or business entities.
Adding AppTags to your logs in XpoLog can make any search, simple or complex, extremely powerful. Already when adding a log to XpoLog, you have the option of tagging it to one or more applications, and you can also create new AppsTags at any point. Our advanced tagging engine will later index the tags along with their data sources and make it usable during searches and analysis. You can look through all your logs by using this tag to find it fast.

 

  • Distributed Architecture

 

XpoLog can be deployed as stand alone server, a cluster of data processing nodes and Web UI serving servers, or scale as a grid of agents.
For small environments, we recommend deploying XpoLog as a stand alone server. For larger environments the cluster-option is more suitable, so that you can easily separate the data processing from the user activity, to avoid your CPU slowing down during busy times.
XpoLog knows how to “make itself at home” within any type of organization, large or small, local or in cloud. XpoLog can be deployed as stand alone server, a cluster of data processing nodes and Web UI serving servers, or scale as a grid of agents, clusters, and nodes for unlimited log data collection and analysis.

 

  • Clusters or MapReduce

 

XpoLog can be deployed across shared storage as clusters of processing and UI servers. Some organizations choose to deploy XpoLog as a network of nodes to function in a MapReduce architecture.
XpoLog clusters allow us to work with vast amounts of data and many users. XpoLog detects dynamic changing log data and manages references to the sources to ensure complete data collection. As part of the XpoLog cluster, it contains a self-monitoring mechanism to avoid any outages and informs system administrators on issues that should be addressed.
The XpoLog cluster also works in fail-over mode, meaning that if a node in the cluster fails, another node automatically identifies it, alerts on it, and continues data processing to avoid data loss.
XpoLog scales easily to support high volumes of daily data. XpoLog’s recommended deployment is a cluster of several nodes that work together as a cluster. Data load balancing (MapReduce) is recommended in cases where a regular cluster is insufficient. It is possible to manage several XpoLog instances on several separate machines, and each will manage a selected group of logs, and on top of all instances, there will be an instance where users can have access to view all the logs from all instances.

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