On November 3, ExtraHop announced the fifth version of its platform for real-time analytics on all data in motion. Version 5.0 of ExtraHop expands the platform’s functionality to empower customers to perform advanced analytics on all data that crosses the wire with a view to identifying root causes associated with anomalous, unusual or noteworthy behavior. Version 5.0 enables users to perform correlations between multiple datasets to obtain a more granular understanding of performance within an infrastructure. Importantly, the ability of the ExtraHop platform to perform historical analytics on multiple streams of wire data is enabled, in this release, by an enhanced user interface that allows users to leverage dynamic tables and data pivots in conjunction with a visual query language as illustrated by the graphic below:
As shown above, ExtraHop version 5.0 sports a rich visual interface featuring dashboards that allow drill-down capability as well as the ability to customize widgets and analytics to align with the interests of business and IT stakeholders. The multi-dimensional analytics and correlation functionality exhibited in ExtraHop’s dashboards are strengthened by the platform’s support for the Open Stream Data For Kafka that facilitates the distribution and correlation of multiple, disparate data sets. In addition, version 5.0’s ExtraHop Explore appliance gives users the ability to query historical metrics related to wire data. The combination of analytics from the ExtraHop Explore appliance and the ExtraHop Discover appliance gives customers a holistic and granular picture of IT operations and business data. The ExtraHop Explore appliance allows customers to mine data at rest and in motion, which means that any data that flows through the network can be mined, thereby empowering business users to use ExtraHop version 5.0 for incident management use cases that generate alerts when a rule or condition has been met. All this means that ExtraHop can now viably support business analytics as well as IT and network analytics in ways that bring the power of search, correlation and root cause analysis to all data running through a customer’s network. By bringing advanced analytics to IT data as well as business data, ExtraHop gives customers unprecedented abilities to understand the intersection of technology with business operations. Expect version 5.0 to expand ExtraHop’s purview dramatically, particularly as it now stands poised to embrace use cases for the Internet of Things and to subsequently understand correlations between data from IoT devices and business trends.
Wire data analytics leader ExtraHop and machine data analytics vendor Sumo Logic recently announced a partnership whereby ExtraHop’s wire data will complement machine data aggregated by Sumo Logic’s cloud platform. The partnership brings together ExtraHop’s leadership in wire data analytics and Sumo Logic’s recognized machine data analytics platform to create a unified framework for event detection and management. As a result of the collaboration, ExtraHop’s Open Data Stream delivers real-time, streaming feeds of wire data to Sumo Logic’s platform for aggregating and analyzing machine data. Meanwhile, Sumo Logic customers enjoy access to a more comprehensive universe of data about an IT infrastructure and its constituent set of applications and networking topology. ExtraHop’s real-time wire data enhances Sumo Logic’s cloud-based machine data platform with L2-L7 wire data as illustrated below:
The ExtraHop dashboard depicted above elaborates the ability of the ExtraHop platform to analyze wire data that contains insights regarding application performance, security and infrastructure availability. The Sumo Logic dashboard shows the integration of ExtraHop’s wire data into its platform and its corresponding user interface. ExtraHop’s partnership with SumoLogic delivers real-time data feeds to Sumo Logic’s cloud platform that are ingested into Sumo Logic’s cloud platform for the purpose of delivering actionable business intelligence about the health of IT infrastructures based on the aggregation of log and wire data. The graphics differentially illustrate how ExtraHop’s wire data enriches Sumo Logic’s aggregation of machine data by providing it with an additional dataset that Sumo Logic’s cloud platform can integrate into its massive, multi-tenant unstructured cloud database built on Amazon Web Services to deliver advanced analytics and data visualization regarding the detection of infrastructure and application related events.
Mark Musselman, Vice President, Strategic Alliances at Sumo Logic, remarked on the significance of the partnership between ExtraHop and Sumo Logic as follows:
Adding ExtraHop data as a new source into the Sumo Logic service for proactive analysis against other feeds enables IT teams to gain deeper performance, security and business insights from across IT infrastructure. Sumo Logic’s cloud-native architecture means the service serves an aggregation point for diverse data sources. The result is an IT team that acts on timely information from within their infrastructure – even information they did not know to ask for. A critical piece to the puzzle lies in Sumo Logic’s Anomaly Detection, a proprietary capability that delivers insight from patterns in data and insights beyond what IT teams themselves know to query.
Here, Musselman comments on the way in which ExtraHop’s data facilitates “deeper performance, security and business insights” by serving as an additional data source that enables advanced analytics about enterprise IT architectures. The integrated data repository marked by the confluence of ExtraHop wire data and Sumo Logic log data leverages Sumo Logic’s proprietary advanced analytics and machine learning technology to deliver notifications about events of interest within the infrastructure while iteratively refining those same alerts in correspondence with the actions initiated by the recipients of those same notifications. In all, the partnership between ExtraHop and Sumo Logic underscores the significance of wire data for analytics related to machine data analytics and the internet of things while concurrently enriching the capabilities of Sumo Logic’s cloud-based log management and analytics platform. With ExtraHop’s real-time wire data now streaming into the Sumo Logic platform, the case for a Sumo Logic IPO grows stronger while ExtraHop similarly benefits from enumerating the value of its wire data aggregation and analytics technology.
Splunk recently announced the general availability of the Splunk App for Stream, an app that delivers a software-based solution for the capture of real-time streaming wire data. Defined as data transmitted between networked infrastructure components, wire data has the potential to deliver insights about performance, security and IT operations. The Splunk App for Stream represents the first product that Splunk has released as a result of its acquisition of CloudMeter last December. Unlike appliances, the app constitutes a non-intrusive solution that boasts greater ease of deployment than other hardware-based approaches toward the collection of wire data. Moreover, the solution claims particular import for the monitoring of data from cloud environments as noted below by Leena Joshi, Splunk’s senior director of solutions marketing:
Unlike traditional and appliance-based solutions, which are difficult to deploy, especially in public cloud infrastructures, the Splunk App for Stream enables customers to gain immediate wire data access on-premises or in public, private or hybrid cloud infrastructures. It opens up for our customers a whole new class of data sets to provide continuous IT, security and business insights.
Customers can implement filters and aggregation parameters on incoming data in order to understand details of “transaction response times, transaction traces, transaction paths and network performance.” The Splunk App for Stream additionally enables customers to understand correlations between application performance and infrastructure data. Wire data can be used in conjunction with other application management tools without disruptions to the application or modifications of application logs. The point worth noting is that the Splunk App for Stream provides yet another tool for cloud administrators to understand infrastructure and application performance that focuses on data transmitted between networking components. The app’s ability to collect wire data from virtual machines in public clouds gives IT administrators visibility into public cloud deployments that complements the performance monitoring software provided by the cloud vendor itself. Cloud adopters can selectively leverage the app for performance management or security and fraud use cases as dictated by their needs. Overall, Splunk App for Stream punctuates and enhances Splunk’s positioning in the cloud monitoring space and sets the stage for Splunk to release more products derived from its Cloudmeter acquisition.