Organizations have invested millions on infrastructure to capture and store network packet data. These solutions include appliances built in house for real-time packet capture and third party “network sniffers” offered by a variety of commercial vendors. As a result, most organizations have potentially 100s of terabytes of stored network data.
But the power of this network data has previously been difficult to unlock and use effectively to meet real-time business requirements. Expert users are required who have detailed knowledge across multiple network and application layers. Troubleshooting tasks using this data store can consume days and even weeks, while finding and locating the pertinent data is difficult and can involve searching terabytes of data.
The Corvil Stored Data Analyzer module running on a Corvil Appliance can read stored network data in standard PCAP formats and analyze multiple terabytes per day. From this data, Corvil first automatically discovers, decodes, and reconstructs all details of application and business flows. All Corvil analytics and application/network performance results are then reported from your stored network data including, for example:
- Reporting of business transaction success or failure
- Correlation of end user experience issues with performance problems in the application or network infrastructure
- Key data center metrics, application clusters, web pages, cloud services, etc.
- Decoded contents of all application transactions
- Network and packet layer decodes
- Analysis of TCP flows and issues
- Reporting of application and network microbursts
- Reads stored network data in standard PCAP formats
- Analyzes multiple terabytes per day
- Presents reports from raw PCAP data
The output from the Stored Data Analyzer results in an enriched version of the data containing application and network performance and event analytics. You now have instant access to your stored network packet data with results that have been proven to reduce troubleshooting application performance issues from weeks/days to hours/minutes.