SIOS Technology Corp. makes machine learning based analytics solutions that enable IT managers to resolve issues and optimize the performance and efficiency of their business-critical applications in virtual environments.
Immediately Identify and Resolve Application Performance Issues
SIOS takes the time and guesswork out of resolving application and infrastructure performance issues in virtual environments. Advanced machine learning technology in SIOS iQ instantaneously identifies performance problems and provides specific recommendations for resolving them without the need for specialized expertise or interpretation of multiple analyses.
SIOS iQ learns the behavior patterns of interrelated components in your infrastructure, enabling it to automatically identify potential problems and recommend solutions with unparalleled speed and precision. No more thresholds to set and adjust. No more finger pointing or trial-and-error efforts to resolve performance problems. Just accurate answers to key questions: what is the root cause of the performance problem, what components are affected by it, and what specific steps are needed to fix it?
Save Money by Eliminating Wasted IT Resources
Rapid growth of virtual environments can result in unexpected budget overruns and shortages in key IT resources, including CPU and storage. SIOS iQ enables IT to find and eliminate wasted and unused resources such as snapshot waste, undersized/oversized VMs, rogue VMDKs, and idle VMs, which can save thousands of dollars while making budgeting and planning more predictable.
The Fastest, Most Accurate Way to Eliminate the Root Cause of Performance Issues
When application performance issues arise, you need a fast, accurate way to identify the root cause and resolve it. The limitations of existing tools make it particularly difficult and time-consuming to understand how the infrastructure impact application performance. Traditional monitoring tools only provide alerts when a single metric (e.g. CPU utilization or latency) has exceeded a threshold. Alerts are based on intrinsically inaccurate averages of the metrics gathered about individual components in the infrastructure. The result: thousands of alerts that leave IT managers to figure out which are important, what the root cause of the problem is, and how best to resolve it.
Precision. Accuracy. Speed to Resolution.
SIOS iQ automatically identifies and helps you resolve the cause of performance issues in virtual environments with unparalleled precision, accuracy, and speed. Today's tools are narrowly focused on monitoring and reporting alerts found within an infrastructure silo (host, storage, network, application). They miss the important interactions between silos and leave you to do the work using multiple tools to research and find the cause. SIOS iQ uses patented machine learning and deep learning technology to analyze data across the silos and learn the time-based patterns of behavior of interrelated components. This unique approach enables SIOS iQ to identify abnormal patterns and accurately find meaningful problems with their root cause, eliminating noisy alerts entirely. Complex performance issues such as “noisy neighbor” scenarios that IT struggles with today are identified instantaneously by SIOS iQ and recommendations are provided.
See the Root Cause of Performance Problems
SIOS iQ features advanced deep learning based visualization technology that enables users to see all abnormal behaviors between interrelated components in a remarkably easy-to-use interface. It provides color-coded issue prioritization and frequency of anomalous behaviors in a single interactive view. Users can click on individual interactions to drill down into issue details, names of root cause components, and a list of the specific events the interaction is causing.SHOW MORE
Leading retail chain used SIOS iQ to find the root cause of a complex data store latency issue and eliminate unnecessary snapshots.AllSouth Federal Credit Union Saves with SIOS iQ Machine Learning Analytics
Leading retail chain used SIOS iQ improves resource allocation and eliminates performance issues.