analytics Archives - SIOS SANless clusters

You may think that the words “artificial intelligence” or “machine learning” sound like trendy buzzwords. In reality, much of the hype about this technology is true. Unlike past periods of excitement over artificial intelligence, today’s interest is no longer an academic exercise. Now, IT has a real-world need for faster solutions to problems that are too complex for humans alone. This includes identifying the root causes of performance issues in virtual infrastructures.

Today, almost every large enterprise has virtualized part, or all, of their data centers. With virtualization, IT teams gain access to a huge variety and volume of real-time machine data they want to use to understand and solve the issues in their IT operations environments. However, the complexity of managing virtual IT environments is stressing out traditional IT departments. As a result, IT pros are discovering that the solution lies in the data and in the artificial intelligence-based tools that can leverage it.

Data Science to the Rescue

As worldwide digital data levels continue to climb, companies are working to find the business value in their data, and to adapt their computer science strategies to the evolving data science market. Legacy management and monitoring tools used the same approach they used for physical server environments — that is, by looking at discrete silos (network, storage, infrastructure, application). They used multiple manually-set thresholds to focus on individual metrics — CPU utilization, memory utilization, network latency, etc., within each silo.

This threshold-based approach originated in a relatively static, well-understood physical server environment which has proven ineffective in handling the complexity of today’s virtual environments. Unlike their counterparts in physical server environments, components in virtual environments share host resources, creating complex, highly interdependent relationships between them. They are also highly dynamic, enabling IT to continually create and move workloads across VMs. IT pros can no longer make informed decisions using manual computer science approaches of yesterday and analyzing alerts from a single silo at a time. This is why companies are turning to “data science” approach that leverages sophisticated AI disciplines of machine learning and deep learning to get a holistic, automated solution to eliminate the time-consuming, manual process of problem-solving performance issues and optimizing virtual environments.

Machine Learning Analytics Tools Provide the Answers

Rather than monitoring individual metrics as threshold-based tools do, advanced machine learning-based solutions learn the complex behavior of interrelated components as they change over time. They can consider multiple metrics of related components simultaneously. As a result, they deliver much more precise, accurate information about virtual environments than either primitive machine learning tools or traditional threshold-based tools. Instead of creating “alert storms”, they identify the meaningful incidents associated with abnormal behavior at a specific time of day, week, month and year. And because machine learning is central to the design, there is no manual configuration required. Advanced machine learning solutions, can be up and running in minutes and learning behaviors immediately. As a result, this shift to a data-centric, behavior-based approach has major implications that significantly empower IT professionals. IT pros will always need domain expertise in computer science, but what analytical skills will IT need to become effective in this new AI-driven world?

Instead of spending their days reacting to and reworking application performance issues, IT will shift their focus from diagnosing problems to proactively predicting and avoiding them in the first place. Freed of the need to over-provision to ensure performance and reliability, they will be able to look for ways to optimize efficiency and spend their time focusing on the larger goals at hand. This allows IT to provide true business value, and work on projects that drive company objectives forward. Generally, that kind of value gives IT an important voice in senior management, bringing them into the decision making process and closing the gap between IT and operations. And as IT pros understanding and use of machine learning-based analytics tools advance, they will be on the forefront of building the foundation for automation and the future of the self-driving data center.

Jim’s Bio:

Jim Shocrylas is the Director of Product Management at SIOS. Jim has more than 20 years in the IT industry, most recently as Portfolio Manager for EMC’s Emerging Technologies Division.

Guest Blog: Jason Bloomberg, Intellyx

Virtualization has unquestionably become a critical and ubiquitous feature of the enterprise operational environment, and VMware clearly predominates. Enterprises rely upon their VMware technology to support mission-critical infrastructure, including the systems of record that run the business.

Avoiding VMware-related performance issues – especially when such issues may lead to downtime – has thus become a mission-critical priority. And yet, finding the root cause of application performance issues in VMware vSphere environments can be difficult and costly.

The interrelated nature of infrastructure and applications – particularly for systems of record like Microsoft SQL Server – can obscure the root cause of performance issues. As a result, SQL database administrators, VMware infrastructure managers, network managers and perhaps other domain experts have to collaborate to find the real cause and devise a solution.

Implementing a solution in such complex, distributed VMware installations, however, is itself difficult to achieve in practice. Such solutions often take an expert – but such experts can be hard to find, and many shops find themselves making do with less skilled VMware professionals.

In other cases, VMware shops turn to third-party consultants for the proper configuration. Even assuming the consultants do their job properly, once they hand over the environment to their customer then maintaining it once again requires skills that may be in scant supply.

For today’s enterprises that depend upon VMware, however, there are rarely any viable alternatives. Their environments continue to grow in size and complexity, and their businesses increasingly depend upon them as the mission-critical infrastructure they are.

SIOS: Addressing VMware Complexity

This growth in complexity combined with scarce expert VMware skills is the challenge that SIOS addresses with their SIOS iQ product. SIOS fills this gap in the existing VMware management tools used to address infrastructure problems in complex, dynamic virtualized environments.

SIOS continues to enhance the capabilities of SIOS iQ since launching the product in 2015, helping its customers understand complex IT operations and resolve issues in dynamic VMware environments.

SIOS focuses on the needs of IT Operations Managers and application administrators to address the root causes of performance problems, identify underused resources, and optimize configurations to help them get the most value from their virtualized environment.

SIOS was among the first in the industry to integrate machine learning into its infrastructure analytics as well as deep database performance analytics. It uses advanced machine learning to eliminate false positives and alert storms, thus providing customers with the information they need in an easy to use, graphical interface.

SIOS iQ can also provide instantaneous root cause analytics and recommendations with deep database performance monitoring and optimization. In essence, SIOS iQ is a system that is able to learn about an organization’s virtual infrastructure and how it operates on a day-to-day basis. It can identify anomalies before they become serious issues, thus the chance of false alarms without human intervention.

New Capabilities from SIOS iQ

SIOS is now announcing additional capabilities for predicting and forecasting performance and capacity utilization in complex VMware environments. In addition, SIOS iQ users can now more clearly define Microsoft SQL Server application-specific root causes of performance issues by leveraging SQL Sentry Performance Advisor.

SIOS iQ supports the integration and correlation of Performance Advisor’s custom and standard events out of the box. As a result, users can immediately know where a problem started and whether it is infrastructure or application-specific. Instead of spending time gathering and reviewing data or arguing between departments, users can now directly take action to correct the problem before it becomes critical.

SQL Server is among the most popular databases that run on the VMware platform, explaining why SIOS leveraged its partnership with SQL Sentry to implement SQL Server-specific performance analysis. In addition, SIOS is planning on supporting a variety of systems of record, as the diagram below illustrates.

SIOS iQ Application-Specific Performance Monitoring and Root Cause Analysis (Source: SIOS)

The new capabilities from SIOS iQ directly correlate observed performance anomalies with intelligent performance-related events from deep within the SQL Server platform. It is now possible to link from a SQL performance alert within SIOS iQ to SQL Sentry in context.

Furthermore, SQL Sentry users can create their own events with description and appropriate tags for correlation with SIOS iQ, thus correlating events from the applications down to the infrastructure.

In addition to its newly added support for SQL Server, SIOS iQ also filters for selective analysis across vSphere Clusters. SIOS iQ shows the environment by each cluster, enabling users to select which cluster to view in the SIOS Dashboard. As a result, they can observe all environments together or isolate the view to individual cluster – even to specific events taking place within the cluster.

The Intellyx Take

The more complex the VMware environment, the more important it becomes to have a platform like SIOS iQ in place – and many of today’s enterprise VMware deployments are extraordinarily complex.

The fact that many enterprise systems of record now run on VMware environments ups the stakes for VMware performance. Systems of record are mission critical – and as organizations become increasingly software-driven, digitally transformed enterprises, this mission criticality only becomes more central to the viability of the business itself.

Complexity, however, is the enemy of mission criticality. Whether it be gaps in high availability, misconfigured VM instances, or other issues with capacity, performance, or availability, the list of things that can go wrong continues to explode. And as is particularly true in virtualized operational environments, what can go wrong eventually will.

With SIOS iQ, SIOS is bringing together all the elements that make up a monitoring and root cause analysis platform that modern enterprises with such complex, important VMware investments require. And in spite of the challenges with VMware’s complexity, it’s not going anywhere any time soon – and neither is SIOS.

Copyright © Intellyx LLC. SIOS is an Intellyx client. At the time of writing, none of the other organizations mentioned in this paper are Intellyx clients. Intellyx retains full editorial control over the content of this paper.