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Posts By : Sameer Padhye

How to Predict and Avoid IT Problems and Outages with AIOps

By Sameer Padhye

Originally Posted on NetworkComputing.com

To succeed as digital companies, enterprises need to reconsider their IT ops strategy, including how they think about application and network uptime. System downtime, although common, is no longer acceptable. With business-critical applications as indispensable as the electricity powering office environments, it’s crucial to avoid system outages and the associated business impact.

We all know the difficulties of monitoring dynamic and ever-changing IT environments. Traditional IT operations management processes and assets are ill-equipped to address the challenges of today’s multi-layered, disparate hybrid IT infrastructure, with its extensive set of applications and services (including third party/outsourced ones) and multiple actors. Outdated domain-centric tools force manual data processing by human IT specialists to correlate thousands and thousands of disparate data points, creating painful bottlenecks that prevent the rapid diagnosis and resolution of system issues.

Improve the visibility of your IT environment and its activities with AIOps

Digital applications generate a huge volume, variety and velocity of data. This flood of data generates a vast number of alerts that need to be analyzed and addressed, with only a few requiring actions. How can an IT team find relevant information in so much system noise?

What if there was a solution that could automate big data analytics analysis and build an accurate, real-time view of all the moving parts across your hybrid IT environment? With the insight provided, you could minimize false alarms/redundant events (system noise), identify anomalies, and more accurately identify probable causes of system incidents.

That solution is Artificial intelligence systems for IT operations (AIOps) solutions — software systems that combine big data analytics solutions, visualization, and AI/machine learning functionality to automate IT operational tasks such as performance monitoring and event data correlations. The term was coined by analyst firm Gartner in 2017, and they recommend AIOps to organizations as an enhancement to application performance monitoring (APM) and network performance monitoring and diagnostics (NPMD) tools.

How does it work? By correlating millions of data points across all IT domains, and applying machine learning to detect patterns, AIOps provides a consolidated overview and interpretation of what’s happening across the entire stack. IT ops team can then use the information to uncover and resolve the root causes of outages and performance issues so system availability is increased.

Augment your IT operations with AIOps for better system reliability

Because of its underlying importance to the enterprise, IT teams are under pressure to maintain system availability and performance. With the average cost of system downtime approaching $300,000-400,000 per hour, many enterprises and service providers are adopting solutions such as AIOps to avoid network/server disruptions and minimize their impact. The insight provided by AIOps can help IT teams do their job better and more efficiently.

It’s important to note here that AIOps systems aren’t necessarily meant to replace existing IT service management tools and personnel. Rather, AIOps can augment IT environments, serving as the glue that binds disparate systems together and helps IT teams make sense of the constant flow of data. The goal is to simplify and streamline IT operations management, improve system reliability, and automate tedious manual processes for faster problem resolution.

Many AIOps solutions can work with legacy IT resources and tools, integrating with existing business applications such as ERP and correlating information previously locked in siloes. By ingesting and consolidating information across the IT environment, an AIOps platform can provide an updated, accurate, synchronized view of IT operations. Staff can then spot and react to pertinent issues in real time.

Identify and Resolve IT Problems Before They Happen

Some AIOps platforms can also aid configuration planning, helping IT teams anticipate how system changes might impact the IT environment. Whether you’re planning a technology upgrade, migrating to the cloud, or installing patches, an AIOps platform can maintain an accurate and updated view into system assets, applications, dependencies, and the underlying infrastructure. This information can help you plan for and mitigate potential issues with the updates – before they cause an outage.

Conclusion: Better IT and Business Performance with AIOps

AIOps can ease the difficulty IT teams have in managing their increasingly complex IT environment and keeping it running at peak performance. By providing an end-to-end view across all domains, AIOps solutions can enable rapid data anomaly detection and investigation of IT incidents, quicker root cause analysis, and automated data analysis, enabling optimized IT systems uptime for better business results.

Transforming IT Operations Through AIOps-Powered Data Correlation and Visualization

By Sameer Padhye

Originally Posted in Data Center Journal

The digital transformation across enterprises and industries has not only accelerated the pace of business. It’s also led to more organizations adopting more connected applications. That has created greater reliance on underlying enterprise networks on which these critical business applications run. The infrastructure is becoming more distributed, heterogeneous, intelligent, open, and virtualized to support the growth, agility, and scale of the business applications.

With pressure on to deliver solutions as quickly as possible, application architecture is changing to adopt newer technologies such as containers. Containers, with their ability to bundle applications and associated software libraries, enable developers to create “build once, run anywhere” code, for portable applications. It’s easy to understand their popularity. Over 2/3’s of organizations who adopt containers achieve greater developer efficiency, according to a Forrester study. That allows faster deployment of the application entities in multiple data center and cloud environments, which can scale dynamically. (In October 2017, DockerCon Europe reported that 24 billion containers have been downloaded.)

Diverse Systems Create Complexity – and Problems

Business network elements frequently come from a wide variety of hardware and software suppliers. And these networks are only becoming more diverse given the movement by business networking professionals to avoid vendor lock-in, embrace open architectures, and use best-of-breed solutions.

In this heterogenous dynamic application environment, changes can happen very abruptly and obliquely. Using legacy techniques to track the changes and correlate the events in this type of system environment is very challenging. Manual processing of massive amounts of data – which is dynamic across the stacks – to identify patterns, anomaly scenarios, and predict capacity requirements is almost impossible. So much system noise makes it extremely difficult to uncover and resolve the incidents that are impacting system performance. That, in turn, poses tremendous business risks and hinders business innovation.

Finding Insight in a Mountain of Data

It’s tedious and time-consuming for your IT Operations teams to comb through all that data to find useful insights that could improve system reliability and performance. Instead, consider an Artificial Intelligence platform for IT Operations (AIOps) solution that combines the power of machine learning with the ability to auto-discover and correlate entities across critical layers of digital business – business, application, and infrastructure.

AIOps-powered auto-discovery and machine learning can uncover, correlate and analyze all the data from multiple enterprise application and infrastructure domains quickly and accurately, providing visibility into application and infrastructure vulnerabilities. Using machine-learning algorithms to detect patterns and eventually predict potential outages, AIOps can help IT workers thwart system failures, security issues, and performance bottlenecks, so IT departments can enable business continuity and customer satisfaction.  

Augment your IT Staff with AIOps

Artificial intelligence and machine learning are not a replacement for people in this scenario. Rather, they help humans perform day to day IT operational tasks such as troubleshooting, capacity management, migration, and planning. Also, AIOps can offload many menial error-prone tasks from your IT employees, enabling them to focus on more strategic, higher-level activities that improve business operations.

“Most recent advances in AI have been achieved by applying machine learning to very large data sets,” notes McKinsey & Co. “Machine-learning algorithms detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve efficacy over time.”

Data Correlation Feeds Predictive Analytics

Machine learning can correlate and analyze data from multiple enterprise application and infrastructure domains, dealing with the volume, velocity, and varieties of data generated. It can uncover patterns to show what has occurred. It can use current conditions and past learning to spot exceptions and predict the future. Machine learning can even offer suggestions on what to do in various scenarios.

AIOps platforms leverage machine learning to deliver AI capabilities for IT operations. Here are some interesting use cases.

  • Multivariate anomaly detection can identify anomaly scenarios across various dependent entities. Such anomalies may signal that a planned or unplanned business event has taken place. For example, a multivariate anomaly group may represent an unplanned event like a DDoS cyberattack or a planned business effort such as Black Friday event.
  • A time-series sequential pattern detection algorithm can predict business outages triggered by events anywhere in the stack business functions are deployed.
  • It’s also possible to use AI and machine learning to predict when you’ll run out of capacity. For example, it could signal a potential lack of storage disk volume and excessive network bandwidth use of a router. Such information helps IT experts do proactive capacity planning to better meet business needs.

Improved System Performance

Machine learning automates IT operations and can notify operations teams of potential business outages before they happen. It also can detect security issues, identify infrastructure performance bottlenecks, and recommend capacity augmentation and optimization.

IT teams can then set systems to trigger actions for remediation. Executing remediation scripts or integrating with other orchestration and automation tools to take actions minimizes human tasks.

By proactively detecting and fixing system issues with AIOps, you can enable business continuity and assure customer satisfaction. In the age of digital transformation, such capabilities and AIOps solutions are an absolute must.

With machine learning, IT staff can continually and completely look for traffic exceptions. As a result, IT experts can be far more effective in preventing and quickly responding to cyberattacks. So, businesses can stay up and running, and stay out of the headlines.

AI – Driving Digital Transformation Forward

These are just a few reasons why AI and machine learning have become key components of digital transformation. And that’s only going to accelerate moving forward.

“During the next few years, the technologies associated with this [digital transformation] wave — including artificial intelligence, cloud computing, online interface design, the Internet of Things, Industry 4.0, cyberwarfare, robotics, and data analytics — will advance and amplify one another’s impact,” note PwC analysts Leslie H. Moeller, Nicholas Hodson, and Martina Sangin.

Many businesses are already on board with AI, and others are planning to implement it. Forrester Research says more than half of organizations already have implemented some form of an AI project. And it says another 20 percent are planning AI projects in the near future.

Machine Learning – the Air Traffic Control System for Your Data

Machine learning is to network operations as air traffic control is to airline operations. Consider that each hour of the day, there are about 5,000 airplanes flying in the sky just within the U.S.  With that much air traffic, using manual processes to track the planes as they move around would be nearly impossible and just plain dangerous. So instead, we use air traffic controllers to manage the chaos. The air traffic control system helps experts keep track of all the traffic (airplanes) among the different domains (various airports and airlines). By bringing together the various data points and presenting a complete view of what’s happening, air traffic control helps avoid mishaps and enables smoother traffic flow.

Machine learning likewise enables data correlation and analytics. That way, IT experts can keep the network and its applications running safely and on time. And that allows organizations to deliver better and safer customer experiences, make better use of their human and technological resources, and keep their applications and businesses moving forward.

Succeeding at IT/LOB Collaboration

Succeeding at IT/LOB Collaboration

By Sameer Padhye

The digital transformation of core business processes is helping organizations of all sizes become more agile, customer-centric, and efficient. It also underpins the importance of IT’s investment in digital technologies, which is exploding. However, these investments must support the organization’s business strategy, emphasizing the need for IT and LOB managers to be on the same page when it comes to digital priorities.

These investments underscore the commitment IT leaders have made to designing innovative new business models and customer experiences. In the State of the CIO 2018 study conducted by IDG World1, 88% of IT leaders confirmed that their emphasis has become more digital and innovation-focused, and 37% said their IT departments can play a critical role in this area.

Unleash IT’s Potential Value to the Business

LOB managers may not know that their IT department is already moving past “business as usual”. The CIO study reveals that IT departments are investing in various technology areas, including enterprise applications (35%), data and business analytics (33%), cloud computing (28%), and security/risk management (28%).

Given the impact of digital business processes on corporate success, it’s vitally important for IT and LOB managers to collaborate on IT project planning and budgets. This collaboration is easier to facilitate in areas where IT and business priorities align, and where there is shared oversight. In the CIO survey, most respondents already recognize this and reported on specific business initiatives driving IT investments at their firms. These initiatives include increasing operational efficiencies; improving customer experiences; increasing cybersecurity protection; and transforming existing business processes.

Start with the Foundation – Collaboration

LOB can help set IT priorities and get budget dollars to fund specific technologies. In turn, IT can help LOB managers by spearheading prioritized projects, recommending appropriate technology solutions, and adopting agile development/delivery practices. Of course, these priorities must be backed up by adequate resources, including budgets and the latest tools to improve IT productivity and accuracy. IT managers can also help their LOB peers build a business case for investing in new technology initiatives.

A recent survey conducted by McKinsey and Company2 shows many executives expect IT to become a more valuable contributor to business results. And 80% of those surveyed backed up the findings in the CIO study, reiterating the need for business and technology leaders to actively collaborate on digital strategy. Yet just over half of them are doing so now. What’s the hold up? In some cases, there’s a disconnect between IT and LOB leaders. Better communication and joint ownership can help them resolve differences on what and where IT should focus to meet ongoing business needs.

The Importance of Partnering with IT

LOB managers should actively partner with IT so that business priorities are met with appropriate IT budgets and resources. Recommendations include:

  • Giving CIO’s a “seat at the C-level table” to better understand the needs of their organization, such as revenue growth, risk reduction and improved agility.
  • Agreeing on business priorities and hiring enough talent, which will help IT improve their effectiveness within the organization.
  • Empowering IT leaders to shift their time and resources to areas the business values most, such as e-commerce, analytics and cybersecurity.

Improve IT Effectiveness, Increase Its Value to the Business

A frequent criticism of IT Departments is their inability to meet business demands and resolve technical issues, but it’s understandable why. The scale at which IT needs to monitor data and identify problems cannot be effectively managed by humans. With today’s complex, dynamic and distributed technology stack, diagnosing and resolving system and performance issues can become a sinkhole, draining manpower away from more productive and impactful initiatives.

The answer is Artificial Intelligence for IT Operations (AIOps), a one-stop solution which can streamline a variety of IT operations processes and tasks. Leveraging artificial intelligence and machine learning applications, AIOps can help businesses with proactive system planning and identify business-impacting issues before they occur. By helping them better manage the “nuts and bolts” of IT operations, and avoid system outages, AIOps can dramatically free up IT departments to work on more high-value digital transformation projects.

Ready to learn how AIOps solution can help modernize your IT department? Download the FixStream white paper here.

Sameer Padhye is founder and CEO of FixStream.


1CIO’s Shift Digital Transformation into High Gear, State of the CIO 2018, @IDGWORLD
2IT’s Future Value Proposition, McKinsey and Company, July 2017

Uncovering and Improving Control of IT Assets

Uncovering and Improving Control of IT Assets

By Sameer Padhye

The demise of the CIO has been greatly exaggerated. In fact, at one point, CIO stood for Career Is Over. Most people in the job can tell you that their focus and responsibilities has significantly evolved in the past several years in response to new business challenges and disruptive technologies. As technology has become embedded in most parts of the business, the position of the CIO has expanded. In fact, a 2018 Forbes Insight paper (The Challenges for Tomorrow’s CIO) reveals that…

“over four out of five CIOs believe their role has increased in importance over the last five years”.

CIO’s are more essential than ever.

While they are driving IT strategy across the enterprise, CIO’s are still responsible for day-to-day operations and budgets of the IT department. Maintaining a balance between these competing priorities can be a challenge.

Keeping a Lid on IT Assets and Investments

In response to the digitization of business processes, organizations are investing millions of dollars in IT infrastructure and tools, often without a clear view what they already own. This lack of visibility increases system vulnerabilities and security risks, as well as squander IT budgets and personnel.

Keeping tight controls on IT assets and infrastructure is one way that innovative CIO’s can safeguard and manage their complex disparate system environment.  To start, they need full disclosure and listing of their IT assets, including hardware, network, software, and IoT devices. But today’s distributed and hybrid IT infrastructure has become too complex and opaque to manage manually.

Auto discovery of data from all the disparate sources and devices across the IT environment helps IT leaders build and maintain a reliable, up-to-date inventory of resources. This knowledge will enable better budgeting, troubleshooting, capacity planning, maintenance and effective management of all system assets.

Detecting and Taming Technology Sprawl

When IT does not have full visibility into their environment, it exposes the business to risks and additional expenses. The problem is made worse by:

  • LOB Funding IT Purchase Decisions– In many businesses, funding for technology solutions has spread throughout the business. In the Forbes Insights survey mentioned above, 54% of CIOs noted that their company’s business units are more involved in selecting their own technology, and 74 percent say it’s more important to align with business stakeholders on IT acquisitions.
  • Shadow IT acquisitions– If IT isn’t providing a solution that employees want, chances are they will go off and obtain it anyway, without IT being involved in the decision. These “shadow IT” tools can create ongoing security, compliance and workflow vulnerabilities, along with driving up IT costs and workloads. Once those solutions become outdated or unsupported, they require expensive maintenance and don’t adapt to new business needs. And, while IT may not own all the IT purchase decisions, they are still responsible for making sure nothing goes wrong.
  • Redundant Solutions Drive Up Expenses– Point and/or redundant solutions are not just expensive to purchase, but to maintain and support. This diverts IT staff from value-creating activity; redundant technology can also waste money on software licenses that don’t deliver the right functionality to the business.
  • Overly complex IT environments are messy and vulnerable to problems– When business acquire new divisions, set up transactions with partners/vendors, or bring in new enterprise applications, some legacy solutions may be duplicated and no longer needed. They also drive the need for system interfaces and the number of platforms that must be supported. The more interfaces you have, the more fragile your system, and the harder that system is to maintain.

Key to Success: Gaining Insight into the full IT system architecture

The proliferation of IT systems and tools across the enterprise has created a more complex integration environment. But there are new tools available to help uncover system assets and simplify IT management. Auto discovery solutions can identify all the physical and virtual infrastructure components in a hybrid IT environment by automatically collecting data across the IT domain.

With auto discovery, you can develop a complete picture of the network, the IP devices on the network, the applications and services, along with their relationships and interdependencies. The result is an application map that illustrates the relationships among all IT entities, which will help with system diagnostics, migration planning, and root cause analysis down the line.

Updated insight into your organization’s application and IT infrastructure resources can lead to a better understanding of the interdependencies between system components. This Use Case illustrates how FixStream’s Auto Discovery solution helped a global semiconductor company increase visibility and develop dynamic topology maps of all their datacenters worldwide.

Sameer Padhye is founder and CEO of FixStream.

I worked at Cisco for 20 years, calling on some of the largest Service Provider and Enterprise organizations in the world…

I worked at Cisco for 20 years, calling on some of the largest Service Provider and Enterprise organizations in the world, delivering complex IT and telecom solutions to thousands of customers. One of the biggest challenges they faced was understanding the relationship between applications and infrastructure. In the past few years, this is even more difficult as application environments are shared, distributed, multi-tiered, virtualized, containerized and now run in a hybrid cloud.

IT organizations spend millions for full end-to-end visibility but most find solutions lacking because each vendor defines its own “end-to-end”. One tool might show only the entire network, another tool might produce only service performance metrics, other tools might show servers, database, and application services but not the network or the end-user transactions processed by the applications. Some are domain-specific and others are vendor-specific. As a result, determining the root cause of an application performance problem can take hours, sometimes days; migration and changes may affect unexpected applications because of some unknown dependency, and compliance reporting is a nightmare.

Seeing customers face these challenges, and wanting to help them, I started FixStream.

With our Meridian product, data is ingested by Data Collector Modules (DCM) and a Normalization Correlation Engine (NCE), resulting in an Algorithmic IT Operations (AIOps)
Platform that correlates, analyzes and visualizes multi-domain, multi-vendor hybrid IT environments.

With Meridian, you have visibility you can’t get anywhere else. From a converged view of the health of your entire application environment, to business transactions, applications, and infrastructure entities, we’ve helped customers reduce MTTR from hours/days to minutes, as well as de-risk migration and automate compliance.

Sounds too good to be true? We get that comment a lot–but you can find out for yourself–visit our site, read this EMA interview with a customer, or request a demo.

And stay tuned–over the next few weeks we will dive deeper into our patented Flow2PathTM Analytics, our ITOA ecosystem connectors and much more.

Sameer Padhye
FixStream
CEO & Founder

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