Weather is warmer, days are longer, and birds are chirping! As we begin to clean away our winter woes and jump into the spirit of spring cleaning, we must also consider the clutter of our IT environments. Cleaning your data center helps provide continuity throughout your system and reinforce the effectiveness of your security efforts. That’s why the Garland Technology team came up with 5 recommendations to clean and optimize your data center
This week’s topic is real-time streaming analytics for network monitoring, specifically performance and security. The industry has gradually evolved from network performance monitoring based on a large amount of historical data displayed on charts to a model that performs Network Behavior Analysis (NBA) on real-time streaming data. With the vast amount of data in the network, the trick to perform real-time streaming analytics is the conversion of raw network data into metadata. This summary data can then be absorbed and understood by different analytic models in real-time. Today these models include comparative rule engines and machine learning.
This week’s topic is Data Capture and more specifically, Metadata Capture. In the previous blog we discussed Raw Packet Capture, this week we will discuss the differences in Packet and Metadata capture and the best use cases for Metadata Capture.
Metadata Capture is used to receive summary data from the network, including but not limited to NetFlow, IPFIX, SNMP and Syslog. Metadata has been used for years to provide network monitoring tools the necessary information data for Performance Monitoring, Security, Compliance and Business Analytics. Today, one of the primary forces behind its rise in popularity is the ability to do real-time streaming analysis on the network to identify a performance issue or security breach. Advancements in machine learning now provide promise in the ability to predict performance issues or security breaches.
This is the first in a series of posts on the various techniques for virtual network traffic visibility in the cloud. There are three critical tools for this visibility we will cover in this series: Data Capture, Data Brokering and Streaming Analytics. These tools can provide visualization and understanding of all the packets that travel in and out of virtual environments (North – South) and between applications (East – West) inside the cloud.