SIOS Technology today announced the newest version of its SIOS iQ IT
analytics platform, which harnesses the power of machine learning and
deep learning analytics to optimize the performance and efficiency of
VMware environments. A new flexible, API-driven integration architecture
enables SIOS iQ to integrate data from a range of sources, including
application monitoring tools and data aggregation fabrics such as
Splunk, Hadoop and Elasticsearch. Providing a more comprehensive view of
the IT infrastructure, SIOS iQ empowers IT to automatically and
instantaneously identify and correct the root causes of application
performance issues and to predict future application performance with
unparalleled precision and ease-of-use.
As
IT teams move more business-critical applications into virtual
environments, they are becoming increasingly overwhelmed with reactive
firefighting of performance issues. They are still working and
problem-solving in operational IT silos (network, computer, storage, and
application) and using threshold-based tools to measure specific
qualities (i.e. CPU utilization) that may indicate a problem. This
fragmented approach is outdated in today's complex, dynamic virtual
environments.
Meeting the Need for Fast, Accurate Resolution and Prevention of Application Performance Issues
SIOS
iQ replaces the alert storms, inaccuracies, and manual effort
associated with legacy tools with simple, precise, and clear
recommendations for problem solving. By applying patented machine
learning/deep learning analytics to a broad range of data from across IT
silos, SIOS iQ learns the patterns of behavior observed across
interrelated components over time. It correlates this anomalous behavior
to application performance issues and changes in the infrastructure.
SIOS iQ not only detects problems earlier with greater precision and
clarity than traditional tools, but also identifies the root cause of
issues, reveals unknown problems, and predicts future performance
issues. IT can also use SIOS iQ to look at "what if" scenarios to
understand the potential impact that a planned change will have on
application performance before the change is actually implemented.
Finding the Root Cause of Performance Issues
"The
exponential growth of modern IT infrastructures in both scale and
complexity is pushing IT teams to their limits," said Jerry Melnick,
president and CEO of SIOS Technology Corp. "SIOS iQ frees IT from the
daily grind of reactive problem handling to proactively operate and
innovate in order to add value to their core business operations. Deep
learning technology in SIOS iQ analyzes tens of thousands of real-time
metrics to accurately identify the root causes of performance issues and
recommend specific steps to resolve them. Advanced predictive analytics
in SIOS iQ forecasts future performance challenges so IT can avoid or
prevent them before they occur."
SIOS
iQ can be operated as a standalone tool to find and forecast
infrastructure issues and their root cause or as a foundational platform
of an enterprise analytics architecture that integrates with a wide
variety of application performance monitoring tools.
New Features and Benefits
In addition to the flexible machine learning architecture, this update of SIOS iQ includes the following features:
- Software Developer Kit (SDK) for Broad Integration to
include data from a wider range of sources including application and
network monitoring tools and data aggregation fabrics such as Splunk.
This SDK enables IT to query Splunk data more easily and to apply SIOS
iQ machine learning-based analysis for more precise and comprehensive
insights into application performance issues.
- Meta-analysis Provides Industry's Most Accurate Root Cause Identification. New
deep learning technique identifies patterns of incidents related to
application quality of service (QoS) reducing these to a small number of
recurring infrastructure behaviors underlying the problem, revealing
the root cause and providing precise recommendations for fixing them
using a powerful new visualization technique.
- VM Packing and Placement: Recommends
placement of workloads on VMware hosts to optimize VM density without
the recurring thrashing and constant rebalancing caused by traditional
tools.
- Enhanced Recommendations: Provides specific steps IT admins can take to solve complex performance issues and optimize efficiency.
- ROI Savings Analysis: Identifies
wasted resources including rogue VMDKs, idle and oversized VMs,
snapshot waste, unnecessary software licenses and wasted labor costs.
- Service Analytics: Allows
IT admins to logically group and prioritize resources according to
business importance. It correlates application service alerts with
abnormal infrastructure behavior for fast, precise problem solving.