Kaseya Announces Release Of Kaseya Traverse 9.3, Machine Learning-based IT Management Platform For Hybrid Cloud Infrastructures

On May 9, Kaseya announced the release of Kaseya Traverse 9.3, an IT management platform for service providers that supports the management of hybrid cloud infrastructures. Kaseya’s proprietary machine learning and predictive analytics technology enables customers to identify the root cause of performance issues within their infrastructure. The Kaseya platform proactively identifies causes of performance degradation by means of analytics on infrastructure and application performance. The machine learning-based qualities of Kaseya’s infrastructure allows the platform to recognize the specificity of each customer’s infrastructure and iteratively refine analytics on anomalous or aberrant behavior that can embrace the heterogeneity of IT infrastructures and their corresponding implementations. Mike Puglia, chief product officer of Kaseya, remarked on the value of Kaseya Traverse with respect to hybrid cloud deployments as follows:

In today’s complex hybrid cloud environments, MSPs, SMBs and large enterprises alike require a solution such as Traverse to help them reduce downtime for their IT services. The days of monitoring servers and routers in an isolated silo are gone. Businesses today require tools such as Traverse that offer real-time tracking and correlation of the business impact these devices have on overall IT services.

Here, Puglia comments on how Kaseya delivers a holistic approach to cloud monitoring that dispenses with siloed methods of understanding the performance of servers and routers as illustrated by the graphic below:

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The screenshot above gives  customers visibility into network traffic within a hybrid cloud infrastructure across multiple environments and infrastructure components. Kaseya Traverse 9.3 supports more than 40 new devices and continues to enhance its monitoring and analytic capabilities for Managed Service Providers and small to midsize businesses. The platform currently supports the Amazon Web Services public cloud in addition to other vendors such as Nimble Storage and Dell Compellent. As the space dedicated to cloud-based monitoring solutions continues to evolve, Kaseya Traverse 9.3 will need to continue sharpening its product differentiation in order to effectively complete against a proliferation of vendors that offer IT management solutions for hybrid cloud infrastructures. In the here and now, however, the platform’s impressive machine learning capabilities enable it to scalably embrace the radical heterogeneity of contemporary IT infrastructures in ways that swiftly support root cause analytics and the proactive resolution of IT performance issues.

Kaseya Launches SaaS Monitoring Tool For Hybrid Clouds And Distributed Computing Environments

Today, Kaseya announces the general availability of Kaseya Traverse, its SaaS cloud monitoring solution for on premise, private cloud and public cloud environments. The uniqueness of Kaseya Traverse consists of its ability to “traverse” a multitude of cloud infrastructures while delivering centralized, integrated reporting for the entire ecosystem in question. Whereas proprietary cloud monitoring solutions such as CloudWatch by Amazon Web Services deliver performance reporting and monitoring solutions specific to their own, native cloud infrastructure, Kaseya Traverse can be configured to monitor a heterogeneous cloud environment marked by the coexistence of several hosting technologies and platforms. The Kaseya solution provides a diverse range of performance monitoring and analytics on hardware, networks, applications and usage patterns as illustrated by the dashboard below:

Kaseya leverages an architecture designed for distributed analytics, data processing and data gathering that fittingly corresponds to the task of monitoring the infrastructures of dispersed, heterogeneous IT environments. The platform features SLA monitoring, issue identification and resolution with respect to application performance and machine learning-based analytics that identify true anomalies in traffic or usage related patterns as opposed to organic variations and cycles. Given that the current state of enterprise cloud computing almost invariably features some combination of on premise, private cloud and public cloud deployments, Kaseya Traverse is likely to be well received by customers that are seeking a centralized monitoring, reporting and analytics solution in contrast to an amalgamation of discrete reporting applications. Moreover, its ease of deployment as a SaaS application and distributed computing capabilities render it a particularly attractive cloud monitoring tool insofar as its architecture is designed with the specific needs of heterogeneous cloud computing environments in mind.