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Posts By : Enzo Signore

How Automation is Transforming IT Service Management

IT Services – Focused on Business Needs

As technology has become more embedded into business processes, organizations have commonly embraced IT service management (ITSM) to improve customer service and help IT services align with business goals. ITSM is a set of policies, processes and procedures to manage the support of customer-oriented IT services throughout their lifecycle. ITSM activities, including problem/incident management, change management, and asset/configuration management, can be used to improve customer service and enable digital transformation initiatives.

With its emphasis on optimizing IT service operation and improvement, ITSM is essentially a framework for supporting business needs. As such, it should evolve and adapt in tandem with enterprise technology requirements. In fact, ITSM has become a key resource for transforming and modernizing IT services.  

ITIL vs ITSM – How Do They Differ

A framework of best practices for delivering effective IT services, the IT Infrastructure Library (ITIL) sounds a lot like ITSM, and they’re related but not the same thing. ITIL is just one of several popular frameworks within the ITSM discipline (other ITSM frameworks include COBIT, Six Sigma, and Microsoft Operations Framework). But as one of the most popular ITSM frameworks, organizations use ITIL defined processes and standards to optimize IT service management. ITIL 4, the most recent version introduced this year, emphasizes the value of automating processes, improving service management and integrating the IT department into the business.

ITIL 4

ITIL 4 is an evolution of ITIL v3 concepts, not a replacement according to Beyond20, a FixStream business partner and expert ITSM consulting firm. The table below, provided by Beyond20, includes a summary of three key differences between ITIL version 3 (also commonly referred to as the ITIL 2011 edition) and ITIL 4:

ITIL 4’s Guiding Principles are as follows:

  • Focus on value: Everything an organization does needs to map to value for stakeholders
  • Start where you are: Do not start from scratch and build something new without considering what is already available to be leveraged; investigate and observe the current state directly to ensure it is understood
  • Progress iteratively with feedback: Do not attempt to everything at once; continuously gather and use feedback—before, during, and after—each iteration to ensure activities are appropriate and focused on the right outputs, even when circumstances change
  • Collaborate and promote visibility: Working together across boundaries produces results that have greater buy-in, more relevance to objectives, and increased likelihood of long-term success; avoid hidden agendas, promote transparency, and share information to the greatest degree possible
  • Think and work holistically: No service, or element used to provide a service, stands alone; outcomes will suffer unless the organization works as a whole, not just on its parts
  • Keep it simple and practical: If a process, service, action, or metric fails to provide value or produce a useful outcome, eliminate it; use outcome-based thinking to produce solutions that deliver results
  • Optimize and automate: Resources of all types should be used to their best effect; eliminate anything that is truly wasteful and leverage technology to its greatest capability

A push for automation

The last point of the guiding principles is a focus on leveraging technology for optimization and automation. 

Why the focus on automation? The digital economy has changed business processes and priorities, and IT service management, including ITSM and ITIL, is changing as well. For example, ITSM/ITIL best practices are being adapted for cloud computing environments. As enterprise IT departments move from legacy systems to cloud-based solutions, they are also looking to automate ITSM processes, incorporating AI-powered functions such as machine learning and natural language processing.

And why not? ITSM automation can help organizations move toward a consistent IT service management practice, eliminating many redundant manual processes that add cost and increase the risk of human error. For example, automating help desk tasks such as ticket routing and change requests can improve accuracy and speed of response, as well as increase employee productivity and satisfaction. Other examples of AI-led ITSM use cases include automated problem-solving, infrastructure provisioning, self-service systems, finding/resolving threats with anomaly-detection algorithms, and better management of dynamic cloud configurations.

An Opportunity to Improve Business Processes

With all the benefits inherent in IT service automation, it’s tempting to jump right in and get started. But, according to experts, that might not be the best approach. ITSM automation is not about speeding up legacy IT services, it’s about improving service delivery processes and meeting the priorities and needs of your user communities. For example, you might consider new ways to structure your IT teams and work modes to facilitate collaboration across siloes and enable agility. 

An ITSM automation project is a great opportunity to modernize IT service delivery and strengthen the link between IT service providers and their cohorts. Before launching such a project, take time to finetune processes as needed to optimize workflow, remove redundant steps or complexities, and identify needed improvements. Otherwise, you’ll end up with the same outdated, faulty processes – just done more quickly. 

Beyond20 agrees with the need to proactively plan for an ITSM project, starting with a clear vision of the desired results. They recommend taking time to examine IT processes to ferret out hidden problems and implement best practices. Recognizing the complexities involved, Beyond20 offers a free ITSM Assessment Readiness Kit to help clients clarify objectives in order build an actionable roadmap for ITSM automation.

FixStream AIOps and ITSM Transformation

FixStream, a leader in AIOps solutions, sees the synergy with bringing ITOM domains closer to ITSM automation with AIOps capabilities to further enrich the core ITSM capabilities for root cause analysis, change management, asset management etc. AIOps solutions help with dynamic discovery and correlation of on-prem and public cloud application and infrastructure entities, correlation of massive amount of events and metrics collected from existing ITOM tools or infrastructure devices, and detecting the root cause of incidents, identification of impacts from changes and anomalies and feeding this insights into ITSM tools uplifts the value of ITSM automation framework to the next level. Without the insights from AIOps tools, it’s is difficult and almost impossible to implement ITSM automation due to the volume, varieties and velocity of dynamic information collected from modern hybrid IT.

Enzo Signore, CMO at FixStream, points out the value of AIOps-based automation in a recent article. He notes “it’s extremely hard to correlate events across the IT stack, and the amount of data involved makes it impossible for humans to do it. Companies need to automate the process to correlate event data across all the IT domains so that they can quickly locate the problem and avoid disasters. This is the foundation of AIOps solutions.”

Learn more about how FixStream’s new AIOps+ platform can help modernize and automate your IT Operations.

Rev Up Your Digital Transformation Engine with AIOps

Digital transformation is a mandate for the online business world, and it’s at the top of every CIO’s agenda. More than just an IT challenge, digital is changing economic fundamentals, business dynamics, and competition on a global scale.

To support the scope and scale of digital-driven change on the organization, IT executives are spending big money on solutions. Industry analyst firm IDC estimates spending will exceed $2 trillion in 2019, and 40 percent of all technology spending will be for digital transformation technologies. And for good reason. Sixty-four percent of IT executives surveyed expect to derive significant value from digital technologies over the next two years.

Yet, despite the investment, IDC also predicts that 75% of CIOs and their enterprises will fail to meet all of their digital objectives in 2018. There are many reasons why digital initiatives fail, but one reason is that they create a whole new set of issues for IT. The level of complexity created by digital has never been seen before, and it continually drains resources and budget.

IT is Drowning in Complexity

It’s easy to see why digital transformation is falling short. IT teams are bogged down by the sheer complexity of today’s hybrid, dynamic IT environments. Along with steep learning curves and lightning-fast changes to new technology, IT departments must cope with soaring consumer expectations, supporting legacy systems, lack of skilled talent, disparate tool sets, and opaque physical and virtual IT infrastructures. These factors complicate IT staff’s ability to oversee operations and optimize system performance.

To demonstrate how data complexity impairs IT operations, a recent IDC article describes how data analysts spend over 80% of their time on data collection, preparation, and governance, versus just 20% of their time on data analytics, where the real business value lies. The problem is compounded by the growth in data volumes as well as the increasing complexity of the data itself. The article points out possible solutions, noting that “machine learning has the potential to significantly change the way data is managed and automate many of the tasks related to data.”

Blinded by the Details

Despite continued investments in system resources, IT cannot holistically see what’s in their physical and virtual infrastructure. And without a clear view of the entire IT environment and the ability to make sense of the mountain of data being served up by various system tools, Ops teams can’t figure out what’s wrong – or how to fix it.

We have seen this challenge repeatedly at our prospective customers. Recently, we visited a company using 17 different tools to monitor infrastructure, applications and services. Each tool has its own portal, its own alert system, and is owned by a different department. There is no way to correlate the data generated from each of these disparate tools. When there is a critical alert, support staff must email back and forth between departments to gather information needed to identify root cause – MTTR can take hours while the business is at a standstill.

Transforming IT with AIOps

Traditional, domain-centric monitoring and IT operations management is no longer adequate in today’s dynamic virtualized environment. These older systems cannot correlate the onslaught of data various IT domains create, and they’re unable to provide the insights IT operations teams need to proactively manage their environments.

But you can rev up digital transformation initiatives with AIOps – Artificial Intelligence for IT Operations. These software systems combine big data and AI or machine learning technology to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation — dramatically simplifying IT operations.

AIOps automatically correlates the millions of data points across the entire stack, applying machine learning so IT can increase end-to-end application assurance and uptime. By correlating, visualizing and predicting issues across hybrid IT stacks, AIOps provides the insights IT teams need to proactively manage and support their digital environments. The improved visibility into the system components and their interdependencies helps organizations accelerate their technology migrations.

The business benefits of AIOps are clear. AIOps optimizes IT by automating 
root cause analysis, enhancing system performance and availability. It can dramatically simplify IT operations, improve efficiencies, and drive down costs. The technology can free up an amazing amount of resources, reducing waste to make operations more efficient. In turn, the organization can align IT and LOB to focus on business transformations that drive higher financial results.

This article was originally published in insideBigData.

Stop IT “Brain Drain” with AIOps

By Enzo Signore, FixStream

Originally Posted on NSIGHTAAS

CIO’s face many challenges today – cybersecurity threats, limited budgets, and business transformation issues, to name a few. But is headcount the biggest worry?  According to a May 2018 Gartner survey, CEOs identified a lack of talent and workforce capability as the biggest inhibitor to digital business progress. There just aren’t enough trained IT professionals to go around, and the competition for available tech talent is fierce.

Hiring for artificial intelligence (AI) positions is especially difficult, as fewer than 10,000 people in the world are qualified to do state-of-the-art AI research and engineering. A recent article in the Silicon Valley Business Journal has highlighted just how significant the current AI talent shortage is. And a study by Ernst & Young  has revealed that over 50 percent of companies working with AI say the lack of qualified workers impacts business operations. “This year, as businesses strategized how to integrate AI into their operations, they were hampered by a shortage of experts with requisite knowledge of the technology,” Ernst & Young chief analytics officer Chris Mazzei said in a press release.

Other IT categories, including business intelligence and data analytics, artificial intelligence, and DevOps/agile processes, also face critical staffing shortages, according to CIO magazine. While recruiting outside talent is one way to fill these IT positions, another approach may be to develop internal workers. Many organizations find that the best way to fill job openings is to train existing IT staff in new job skills and in areas like data science and cloud security.

Get strategic about staff retention

Whether the decision is made to hire outside candidates or develop internal staff, filling IT job openings is just the first step. With so many talented people already employed, employee poaching is at an all-time high, making IT staff retention a big challenge as well. The tight job market forces recruiters to become aggressive, reaching out to workers who may not be considering a job change, but would do so for the right incentive.

After spending so much time and effort to hire/develop your IT staff, how can business operators keep these employees from walking out the door? With so many other suitors, how is it possible to stop the “brain drain” of IT workers?

One way to fight back is to keep current employees engaged with innovative projects that capture their interests and use their skills. These workers should be treated like the valuable assets they are. Their time and talent should not be wasted on menial work that can be better done by system tools. Investing in automation solutions and system upgrades that relieve IT workers of tedious system maintenance and testing duties will enable them to work on more valuable activities.

Modernize the organization to retain IT talent

Savvy CIOs realize that they will need to change their work culture if they want to retain talented employees. Implementing work-saving automation tools and cutting-edge technology can boost IT professionals’ morale and job performance. Freeing up the teams to work on the “fun stuff” — interesting, transformative projects with higher value to the business — will improve staff retention rates and deliver greater “bang for the buck” from investment in IT personnel resources.

There are several ways automation such as AI for IT Operations (AIOps) can change culture.

Enable staff to be more efficient – Many IT employees feel underutilized and bored with ongoing responsibilities like patch management and system maintenance, and have no time to work on innovative projects that benefit the business. Eliminate waste by automating IT inventory discovery. In most IT environments, staff wastes significant time and resources performing manual service management tasks since their CMDB is inaccurate and they do not have visibility into CI relationships. This is especifically challenging when the organization has deployed dynamic environments (virtualized, containers, cloud). To avoid repetitious, work waste, automate the discovery of IT assets.

Make teamwork a priority – Break down internal silos by mapping applications to infrastructure. Traditional silos caused by IT monitoring tools force the IT team to manually correlate processes across multiple domains. This means long conference calls, manual collection of large amounts of data, and finger pointing when performance issues arise. By mapping applications to infrastructure, its possible to break down these barriers and drive constructive teamwork.

Become predictive – Increase productivity by automating root cause analysis. Instead of repeating the same manual, error-prone and wasteful troubleshooting process that can last 4 hours on average and consume 11 full time employees (in 15 percent of cases, according to the Digital Enterprise Journal), why not predict when the next outage will occur?  This will not only increase the uptime and performance of the business application, but it will free up the IT staff to work on new projects.

By modernizing recruitment/retention practices, and the IT operations process itself, CIO’s can succeed in hiring and keeping valuable IT personnel. Using AIOps is one way to enhance staff productivity and effectiveness so that these workers become a source of innovation.

2019 Predictions for AIOps

Many enterprises have found that Artificial Intelligence for IT operations (AIOps) platforms help them better manage their hybrid IT environment and improve system availability. Next-generation solutions – call it AIOps+ — now offer advanced capabilities such as automated pattern discovery and prediction, automated it infrastructure entity discovery and application mapping, and data and event correlation across the IT stacks. Based on these advanced features, we predict more firms will adopt AIOps+ in the coming year.

#1 – Enterprises will experiment with AIOps tools but will deploy AIOps+ solutions

While standalone AIOps tools can deliver useful capabilities such as anomaly detection and noise reduction across both legacy and digital environments, organizations may discover the promise of AIOps is difficult to achieve without understanding the business application context. Enter AIOps+ that works across the IT environment, ingesting and correlating massive amounts of data from a variety of sources, from business transactions to applications to it infrastructure. The full-stack data correlation delivered by AIOps+ will increase the accuracy of the machine learning predictions by enabling the ML algorithms to work on real-time, application specific events.

#2 – AIOps+ will help organizations succeed with digital transformations

While traditional IT environments can accept MTTR in the range of hours, modern organizations that are increasing their reliance on digital processes, will not survive unless they can depend on hybrid IT environments with significantly higher uptime performance. Imagine an on-line reservation system, a patient onboarding application, or an eCommerce site – what would be the business impact if they were down for hours or day? AIOps+ solutions provide the advanced real-time/predictive analytics needed for IT teams to make sense of vast sets of event data and drive faster IT incident response. By extracting meaningful insights from business transaction metrics, application flows and incident data, IT can quickly determine the root cause of an issue and even predict when the next outage will occur. Industry analyst Gartner sees an increasing role for artificial intelligence systems  in the next few years as IT departments struggle to support their sprawling digital environments with limited staff.

#3 – MSPs will start deploying AIOps+ to increase their revenues and efficiency

Given the pressing need for 24/7 system availability and reliability, AIOps+ is becoming the future of the agile, digital enterprise. Clients depend on their MSPs to meet their service level agreements (SLA’s) and maintain system availability at all time. However, as more mission-critical applications migrate to the cloud, the siloed, fragmented nature of distributed hybrid IT operations can hinder the incident diagnosis/resolution process. Performing root-case analysis and system diagnostics is complicated by several factors such as: where is the problem located and who owns it; is the issue related to an application or infrastructure failure; and how is the problem impacting system performance?  AIOps+ can provide the end-to-end visibility of distributed IT environment and real time data analysis that MSP’s need to automate root cause analysis and quickly resolve service performance issues.

#4 – Enterprises will appoint centralized teams to take responsibility for AIOps+ deployments

Today, very few organizations have a centralized team responsible for IT operations. Since today’s tools are siloed, IT organizations have structured themselves in the same manner with compute, network, applications and storage analysts each focused on their niche, each using a disparate tool. They still are not using cross-functional tools that correlate data across each silo. In isolation, it may not look as if there is an issue however when the data is correlated, issues emerge. With AIOps+ solutions, organizations gain access to powerful new capabilities. Building a centralized team ensures that the organizations gets a holistic view of the entire hybrid IT environment.

#5 – Consolidation in the AIOps market will start to occur, with those offering AIOps+ gaining ground

Many AIOps vendors have emerged in the market – and not all are worth the hype. Today, there are big and small AIOps providers with varying capabilities. As the AIOps market matures, we foresee a supplier shakeout, with those offering limited AIOps capabilities not surviving. Rather, we think successful vendors will be those offering robust AIOps+ solutions with advanced features such full stack correlation, agentless auto-discovery, automated remediation/restoration, data anomaly detection, and seamless integration with ITSM tools.

#6 – Traditional siloed ITOM/ITOA budgets will freeze and be reallocated to AIOps+

To keep up with the demands of digital business, organizations need to rethink their approach to managing silo hybrid IT environments and system maintenance. As the pain of operational volume, value, variety and velocity of big data analytics grows, organizations need an effective alternative to disparate application monitoring tools and siloed solutions. We predict forward-thinking organizations will reallocate budgets to AIOps+ solutions to better manage, plan, and troubleshoot issues across the entire IT infrastructure monitoring in real-time.

#7 – An ecosystem of solutions (built by SI/VAR/MSPs) will emerge to enrich existing AIOps+ platforms

The best AIOps solutions can seamlessly integrate with other IT assets, ERP applications, and multiple data sources. For example, FixStream’s new release integrates with ServiceNow and Cherwell ITSM/CMDB platforms, New Relic APM, SolarWinds and ManageEngine monitoring tools, etc. delivering functions such as auto-ticketing and change management, and creating an integrated solution greater than the sum of its parts. Taking it a step forward, we see a community of value-added resellers (VARs), system integrators (SI’s) and MSP’s emerging to create customized solutions for AIOps+ platforms that enhance its capabilities, perhaps to meet the needs of a specific industry or to incorporate advanced security features.

Conclusion

In 2019, we think more IT organizations will recognize how AIOps+ solutions can detect, predict and resolve business issues across an enterprise’s entire hybrid IT environment. For example, the latest AIOps+ offering from FixStream enables customers to detect patterns with 90%+ probability and reduce MTTR to just minutes, so IT operations can achieve appropriate service levels and meet customer expectations.

For more information on how FixStream AIOps+ can help you modernize IT ops this year, view our video.

What’s the Real Cost of Data Center Downtime?

We all know that IT downtime is expensive and damaging to organizations and their productivity. Yet, despite ongoing investments in technology, system outages still bedevil many enterprises, including cloud-based environments. In 2018, for example, cloud outages at companies such as Microsoft, Amazon Web Services, and Visa reminded us that even well-maintained IT environments are vulnerable to system disruptions. An extreme example is the 2017 Delta Airlines 5-hour outage that caused the cancellation of 280 flights and cost the company $150 million dollars.

With numerous IT assets spread across on-premise and cloud environments, downtime today can cause a lot more harm than mere customer inconvenience. System outages can directly impact productivity, throughput, profitability and customer attrition. You only need to experience one system outage to realize how much harm it can cause to a company’s reputation and standing in the marketplace. But rather than considering IT downtime as an inevitable cost of doing business, senior IT managers can proactively take steps to minimize their occurrences and impact. And quantifying the cost of system outages can justify spending to remediate them.

How Much do System Outages Really Cost?

Catastrophic airline outages aside, just how costly is downtime to the typical enterprise? There are direct costs for system diagnosis and repair, as well as indirect costs such as the loss of organizational productivity and damage to corporate reputation. Costs may also include damage to (or loss of) mission-critical data and other assets, legal and regulatory impact, and repair costs for core business processes and systems. Add in the lost revenue related to business disruptions and missed sales opportunities, and you can see how even one hour of downtime can cost several hundred thousand or million dollars.

To tally up estimated costs, analyst firms have surveyed clients who experience system downtime and can quantify its impact. Cost estimates will vary by industry, size of the organization, and region. For example, according to Statista, in 2017/2018 the average cost of server downtime was approximately $300,000-400,000 per hour, while 44% of survey responders reporting costs of $1M/per hour or more. And those costs, and associated business impact, would be higher if you experience an unplanned outage during peak traffic time.

The more complex, virtualized and interconnected system environments become, the longer it takes to diagnose and resolve unplanned outages. The siloed, disparate nature of most IT hybrid system infrastructures have caused Mean-Time-To-Recovery (MTTR) rates to escalate along with costs. In fact, ITIC’s Reliability and Hourly Cost of Downtime Trends Survey confirmed that 81% of organizations report the cost of unplanned downtime typically exceeds $300,000/hour, with monetary costs exceeding millions of dollars per minute in extreme cases.

The ITIC study also shows that downtime costs vary between industries and enterprise size. For example, large enterprises with over 1,000 employees could see the costs associated with a single of hour of downtime to exceed $5 Million in nine specific industries, including Banking/Finance; Government; Healthcare; Manufacturing; Media & Communications; Retail; Transportation and Utilities.

Total Cost of System Downtime by Industry

(summary Ponemon Institute study)

  • Financial Services $994,000
  • Healthcare $918,000
  • eCommerce $909,000
  • Industrial $761,000
  • Retail $758,000
  • Hospitality $514,000
  • Public Sector $476,000

Take a look at the following charts (Ponemon Institute study). The first chart shows reveals the relatively consistent breakdown of cost categories associated with business disruption. The second chart illustrates that the average shutdown duration hasn’t changed in the last 6 years.

Why System Outages Happen

A 2018 study by Information Technology Intelligence Consulting points to human error and security issues topping the list of causes for unplanned downtime, with network interruptions another contributing factor, and outdated processes can lengthen the time it takes to resolve outages. Pinpointing the root cause of system outages is complicated by manual, time-consuming correlation of massive amounts of siloed operational data. Proactive planning, automation, and better resources can help minimize human error and hardware/software failures. For example, automated real-time correlation of data between business, application, and infrastructure components can help predict potential system issue so they can be resolved before impacting the business.

Proactively Manage Assets to Minimize System Downtime

To prevent downtime, you must be able to effectively monitor and maintain your assets in real time, and arm your IT staff with tools to help make sense of IT complexity. Artificial Intelligent systems for IT Operations (AIOps) can transforms IT Ops by significantly reducing human errors and the tedious repetition of cumbersome manual processes. By providing real-time full-stack data correlation and visualization of the entire system environment IT staff can gain actionable insights to optimize system performance and meet customer expectations. Viewing and understanding application dependencies can also help employees forecast the potential impact of system changes before they are implemented. This allows you to carefully plan transitions and migrations so they don’t affect the performance of business-critical applications.

AIOps can reduce system downtime by increasing application assurance and uptime. To see how FixStream AIOps can help you improve system availability and reliability, download our free eBook.

BT and FixStream: Mapping the Way to Rapid Issue Resolution

Problem: The Challenge of Diagnosing System Issues in a Virtual Landscape

By Sameer Padhye

In traditional IT environments, various services were managed in siloes. As organizations adopted different technologies and migrated to the cloud and microservices, system environments became more complex, interconnected and difficult to diagnose. IT teams end up drowning in data and distracted by system noise. Faced with massive amounts of system alerts and incidents to diagnose, IT Operations staff don’t have the insights needed to proactively manage and resolve system issues within their environments.

The situation is complicated by the fact that most hybrid IT environments have multiple technology components – i.e. network, storage, compute, application services etc. – provided by a variety of vendors. For example, typical business transactions may use an average of 80 different types of technology. These components are monitored and managed in silos by different teams and tools, making it difficult to uncover the point(s) of failure within the network. Having a distributed, fragmented landscape of various system technologies and suppliers makes it difficult to quickly find and resolve incidents.

The truth is that today’s virtualized dynamic hybrid IT environments can’t be adequately managed with yesterday’s domain-centric monitoring systems. As applications and services shift to the cloud, you need automated resources to monitor and keep track of your network to ensure all is running smoothly. Using manual monitoring approaches no longer makes sense.

Why is that? One reason is that traditional tools and processes deliver a limited awareness of system components and their interdependencies across the hybrid IT infrastructure.

With no end-to-end visibility within an application environment, how can a performance issue with a specific application be quickly uncovered and resolved using manual approaches?

Another shortcoming of manual monitoring is that issues are often diagnosed sequentially (i.e. is the failure within the firewall, the storage? How about the database?), dramatically lengthening the time it takes to discover and repair the faulty component.

Incident Triage Requires Real-time Visibility across Entire Infrastructure

To make sense of distributed systems’ alarms and rapidly pinpoint any faults, IT teams need a solution that delivers consolidated management data and an up-to-date visual end-to-end overview of the complete network solution.

One such solution is Service Intelligence, a new managed service from BT based on big data and machine learning technologies provided by FixStream. Using FixStream’s AIOps solution, Service Intelligence monitors the health of each network site and component. Bringing numerous sources of information together, the service delivers a real-time 360-degree view of system availability and performance status across the entire data-center infrastructure and the wide area network connecting the sites.

Faster Fault Discovery, Faster Problem Resolution

The Service Intelligence solution aggregates the data from all the management tools from any device or location and displays the topology and application maps on a context-aware, intuitive, visually rich dashboard. Service Intelligence uses the geographical/network site’s topology and application maps to overlay diagnostic data across the entire infrastructure. Just as Google Maps visualizes traffic jams or accidents in the navigation panel, FixStream builds application maps and alerts to its users when there is an outage so operations staff can quickly triage and resolve the issues.

Service Intelligence correlates alarms and consolidates data from multiple sources, providing a single pane of glass display of current infrastructure status. The display highlights trouble spots via a “rooftop view” that pinpoints where the fault is located on a topology or application map. It correlates alarms from multiple sources to rapidly pinpoint any faults on a topology or application map. With this information, Support teams can quickly repair the exact issue, improve performance or remedy an outage.

Predictive Diagnostics Can Stop System Failures Before They Happen

Over time, the machine learning capabilities within Service Intelligence solution begins to recognize patterns, leading to predictive capabilities for potential failures. Staff can identify the business-impacting problem that needs to be prioritized and address it preemptively, rather than waiting to repair system components when they actually fail. By proactively resolving potential issues, teams can avoid potential damage to the business.

Service Intelligence Delivers a Better Customer Experience

The improved diagnostics and problem resolution capabilities of Service Intelligence are driven by FixStream, the next generation of IT operations analytics. Customers benefit with:

  • Greater speed and accuracy of system issue diagnostics and resolution across multi-vendor, multi-technology system landscape.
  • Less downtime due to rapid incident diagnosis and speedy resolution.
  • Reduced costs associated with fault management,
  • End users are able to complete business transactions seamlessly, reducing revenue lost from system downtime. The result is higher customer satisfaction and increased revenue.

The FixStream/BT – United to Deliver Network Availability across the Globe

BT uses FixStream AIOps technology to provide customers with real-time, end-to-end visibility and incident management of your entire ICT estate on a global basis. FixStream’s cloud and visualization platform can prevent outages and identify blind spots in today’s world, one that increasingly depends less on hardware and more on virtualized networks and software.

Large global organizations have mission-critical applications can’t afford to fail. With the Service Intelligence solution, customers now have the tools they need to automate incident management across their organization.

Predict and Resolve Issues across Hybrid IT with AIOps

Virtual Systems require a new approach to IT Management

The need for business agility and 24×7 availability has driven IT systems to rapidly evolve, becoming more virtual, shared and dynamic. While this new virtualized, distributed approach to IT is optimal for digital business applications, it makes it harder to diagnose and resolve performance issues. When you have system components acting independently across siloes, Operations teams can struggle to monitor and analyze end-to-end system performance.

Without a clear view of the entire interconnected system environment and its various elements, your Operations team could be “flying blind”.  Just as air traffic controllers need the data provided by radar to safely navigate and direct various airplanes simultaneously, your IT team needs new tools that help them effectively identify, monitor and manage hybrid IT systems.

Improve the View with Auto Discovery and Application Mapping

Application performance can degrade for a multitude of reasons, along an entire path. Knowing the path traversed by each application is therefore critical to uncover outages. This requires a real-time, accurate auto-discovery process and application mapping.

Artificial Intelligence for IT Operations (AIOps) can help organizations achieve dynamic, real-time, accurate visibility across their hybrid IT environments. Using multi-layer correlation and predictive analytics across business KPI’s, application and infrastructure entities, AIOps can automate the discovery and mapping of critical business processes to application process flows, hosts, backend databases and infrastructure entities such as switches, routers and storage arrays. IT Leaders can visualize operations at a glance and application dependency details at every device level for operational or change management.

By automatically discovering and mapping your complex, multi-tier enterprise applications, you can always maintain an accurate and complete inventory of system components and application dependencies. For instance, Broadcom used AIOps to drastically increase the accuracy of their system components inventory. And, the information can be used to show the potential impact of system changes, ensuring that your transitions and migration plans don’t affect the performance of business-critical applications. Data center migrations can be completed up to 75% more quickly. (Watch this video illustrating the results achieved by Maxim Integrated)

Connecting the dots between business, application and infrastructure issues

IT teams face a daily deluge of data and alerts, making it difficult to discern which incidents need to be dealt with first. Operational data is typically siloed and decentralized, existing in disparate domains and stacks. IT team members often have to manually correlate and analyze thousands or millions of data points to resolve an issue.

Manual correlation is time-consuming and prone to error, and data – often repetitive and even irrelevant — quickly gets out-of-date. Analyzing and interpreting all that data into valuable, actionable insights can be a daunting, never-ending task.

Automated data correlation between business, application, and infrastructure would help, but often isn’t possible with outdated tools. If IT teams can’t analyze the data and isolate the problems quickly, organizations suffer system outages that last longer than necessary. This leads to dissatisfied customers, lost revenues, and unmet business needs.

Adding AIOps can deliver measurable value in key ITSM areas, such as ticket and event suppression and mean time to ticket resolution (MTTR). With AIOps, IT Operations can quickly identify and resolve system issues in minutes, not hours. As a result, your IT teams can become more productive, as they focus on projects that deliver business value versus chasing down noisy alerts. For instance, the City of Las Vegas uses AIOps to predict outages across any of their Oracle ERP applications, helping preserve their revenue flow.

Automated Anomaly Detection and Prediction Increases System Availability

Traditional tools are limited in their abilities because they provide domain-centric views without correlating events, thus impacting the visibility and the management of a hybrid cloud environment. During an IT incident, distributed applications make it difficult to track down where the problems are occurring.

Using machine learning techniques, AIOps correlates data about distributed applications and underlying infrastructure, making predictive analysis and efficient root cause analysis possible. The AIOps platform can learn and identify normal patterns of behavior for various system components and metrics. If the algorithms then detect anomalies, they can trigger alerts and actions by automation tools to identify and even fix basic problems. Over time, AIOps can use data patterns to predict potential incidents so they can be resolved before impacting system operations.

Achieve Proactive IT Management with AIOps

Traditional business models have been disrupted by digital transformation and new technology such as mobile and cloud. As enterprises launch more and more applications to support the user experience throughout the customer lifecycle, IT departments will struggle with infrastructure management and problem resolution.

AIOps solutions are expected to solve these challenges in a very elegant and effective way, revolutionizing IT Operations and accelerating digital transformation initiatives. Therefore, industry analysts are now predicting that the AIOps market will reach $11B by 2025.

FixStream AIOps brings together big data, machine learning and artificial intelligence techniques to transform IT operations. For instance, FixStream can predict outages with over 90% accuracy across very complex IT environments, reducing the noise by 40%. By providing a consolidated business-centric view of hybrid IT environments, FixStream AIOps solution helps IT teams proactively manage, plan, and troubleshoot revenue-impacting business-critical processes in real time.

For more information on how FixStream’s AIOps Platform can transform your IT operations, download our free book AIOps for Dummies.

How Integrating AIOps with ITSM will Modernize IT

By Enzo Signore

Introduction – The Importance of a Single Accurate View of IT Infrastructure

As organizations transform digitally, the systems and processes required to manage their dynamic, hybrid IT infrastructures often can’t keep pace. So, it’s natural for IT executives to want new solutions that help them understand and anticipate how different IT components will interact while delivering critical business applications. Not only is this understanding useful for effective system diagnostics, it’s critical for forecasting the impact of infrastructure changes.

Having an accurate and up-to-date view of what IT assets you have, where they are located, how they are configured, and the relationships existing between them are all vital functions for system management and business scaling. But building and maintaining a single accurate source of this information is problematic. In response, many IT departments have created a Configuration Management Database (CMDB), a database that contains all relevant information about IT assets installed across the IT environment, as well as data describing the relationship between specific items and how they interconnect.

Done right, the CMDB can provide a trusted source for information and a total up-to-date view of your IT configuration items, their attributes, and relationships. Done wrong, and the CMDB can end up with incorrect or redundant data, leading to ineffective decision making, inaccurate configurations, and duplication of effort. As with any database project, the analogy “garbage in, garbage out” is appropriate here and a main factor in CMDB projects failing. If the CMDB isn’t populated with accurate and timely information, and if that data isn’t kept clean, the CMDB project won’t deliver its potential value, wasting time and money. But without the right tools, this is a difficult task. No wonder that, by 2019, up to 90% of organizations are forecast to get their CMDB implementation wrong, according to Gartner.

The FixStream/Cherwell Software Partnership – Turning Information into Insight

In response, FixStream, a pioneer of Artificial Intelligence for IT Operations (AIOps), is working with Cherwell Software, a global leader in enterprise service management and CMDB software. Together, the two companies will deliver a next-generation integrated IT Operations solution that combines machine learning with workflow automation to help find, predict and resolve ITSM issues better and faster.

The joint solution, demonstrated at Cherwell Global Conference in Colorado Springs (Sept. 18-20), integrates FixStream’s AIOps solution with Cherwell’s workflow automation software to automate the discovery of entities across data-centers. Once the entities are identified, the FixStream solution will facilitate the ingestion of accurate inventory information into Cherwell’s CMDB, so the data stored there is correct and updated as needed.

How does the solution work? After creating an accurate and real-time inventory of the physical, logical, and virtual entity across the IT stack via an agent-less auto-discovery process, the FixStream software will automatically update the Cherwell CMDB. FixStream will also correlate business transactions with applications and infrastructure, visualizing operational issues in the context of the business applications. It will then apply machine learning to detect patterns, enabling IT teams to predict and prevent outages with over 80% probability across the entire system stack.

Armed with this deep insight, enterprises will be able to prioritize and proactively resolve issues and vulnerabilities across their IT infrastructure before they cause business outages and lost revenue. IT staff will be able to identify and visualize in seconds the sequence of correlated events across datacenters, as well as automate the root cause analysis of critical business processes, increasing Configuration Management Databases (CMDB) accuracy.

How will this integrated solution improve IT Operations? The ability for IT organizations to understand how applications, servers, middleware, databases, networking devices, and storage devices interact to deliver business services is critical for anticipating the impact of infrastructure changes. By improving the accuracy and currency of the database’s data, the FixStream-Cherwell joint solution will improve the diagnostic analysis capabilities of the CMDB itself. Using real-time insights and powerful analytics to more quickly and accurately identify issues across the IT infrastructure will allow customers to better monitor and maintain critical business processes and avoid expensive downtime.

Conclusion

The integration of FixStream and Cherwell technology will create an integrated next-generation IT Operations solution that will provide insight into the IT infrastructure’s topology and vulnerabilities. The integration solution is designed to help IT teams to prioritize incidents’ resolution by forecasting their potential impact on business operations with the goal of avoiding damaging business outages and lost revenue.

For more information about the FixStream and Cherwell integration, read our press release here.

Conquering the CIO Talent Challenge

Introduction

CIO’s face many challenges today – cybersecurity threats, limited budgets, and business transformation hassles, to name a few. But would you believe the biggest worry is headcount? Yes, according to a May 2018 Gartner survey, CEOs said a lack of talent and workforce capability is the biggest inhibitor of digital business progress. There just aren’t enough trained IT professionals to go around, and the competition for available tech talent is fierce.

Current reports show IT employees nearly at the top of the hiring list. According to Indeed’s Employer Outlook 2018 survey, 75 percent of those surveyed plan to hire more IT workers this year. With an estimated one million computer programming jobs in the US expected to go unfilled by 2020, CIO’s need to get creative with their hiring and retention strategies.

Recruiting Opportunity – Learn from the experts

Professional recruiters and consultants have valuable recommendations on how to win the talent war when vying for high-demand IT workers. They include:

  • Look for Characteristics – In lieu of specific domain experience, look for candidates that have these characteristics – mathematical aptitude, curiosity, creativity, perseverance, rapid learning, passion for problem solving, and interest in your specific business.
  • Think outside the box – According to Gartner, CIO’s who think beyond traditional recruitment processes will have more success tapping into IT talent pools. Relationships with universities, partners and crowdsourcing sites can uncover appropriate candidates. Also train non-IT professionals for IT roles. As IT and business priorities integrate, hiring people with business skills makes sense.
  • Match the job description to the actual requirements – It’s vital that the job description accurately defines what the position entails. Not only will this help speed up the hiring process by weeding out mismatched candidates, it will ensure that the new hire understands what is expected.
  • Recruit millennials where they congregate –  With millennials forecasted to be 35% of the global workforce by 2020, IT recruiters need to target them on sites that they visit, like Snapchat and Instagram.

Modernize Your Organization to Retain IT Talent

CIOs realize that they need to change their culture if they are to retain talented employees. Implementing work-saving automation tools and cutting-edge technology can boost IT professionals’ morale and job performance. Let’s take a close look on how automation like AI for IT Operations (AIOps) changes culture.

  • Enable Staff to be More Efficient – Many IT employees feel underutilized and bored with ongoing responsibilities like patch management and system maintenance, with no time to work on innovative projects that benefit the business. Eliminate waste by automating IT inventory discovery. In typical IT environments, staff wastes significant time and resources in performing manual service management tasks since their CMDB is inaccurate and they do not have visibility into the CI relationships. This is specifically challenging when the organization has deployed dynamic environments (virtualized, containers, cloud). To avoid repeated, wasted work, automate the discovery of IT assets.
  • Make Teamwork a Priority – Break down internal silos by mapping application to infrastructure. Traditional silos caused by IT monitoring tools force the IT team to manual correlation processes across multiple domains. This means long conference calls, manual collection of large amount of data, and finger pointing when performance issues arise. By mapping applications to infrastructure you break down these barriers and drive constructive teamwork.
  • Become Predictive – Increase productivity by automating root cause analysis. Instead of repeating the same manual, error-prone and wasteful troubleshooting process that can last 4 hours on average and consume 11 full time employees in 15% of the cases (Digital Enterprise Journal), why not predict when the next outage will occur?  This will not only increase the uptime and performance of the business application, but it will free up the IT staff to work on new projects.

Conclusions:

By modernizing recruitment/retention practices, and the IT operations process itself, CIO’s can succeed in hiring and keeping valuable IT personnel. Using AIOps is one way to enhance staff productivity and effectiveness so they become a source of innovation.

Seeing the Unseen with AIOps

This article was originally published in Dataversity.

Today, businesses are implementing new applications and adopting new technologies to become more agile, efficient, and responsive. As part of those efforts, they are employing more cloud-based solutions, software-centric and microservices architectures, virtualization and containers.

In addition, hybrid IT is now table stakes in most enterprise organizations. The dynamic and increasingly complex nature of hybrid IT creates new challenges and makes it difficult to operate efficiently. For example, Gartner predicts that by 2020, more than 50 percent of global organizations will be running containerized applications in production, up from less than 20 percent today. The upside of containers is that they offer portability and greater scalability. However, containers move around a lot, they appear and disappear in the blink of any eye. That in itself multiplies the number of moving pieces exponentially.

IT currently has many disparate tools that collect data. Big data is no longer enough – IT operations needs to gain deep insights into their distributed multi-vendor, multi-domain and multi-technology IT infrastructure in order to meet their challenging business objectives and data correlation is critical.

We need new tools that collect and correlate information about the application itself and about the underlying infrastructure. That should include data about application server performance, events, logs, transactions, and more. The compute, network, and storage resources involved in application delivery also need to be figured into the equation. Only with this full complement – and correlation – of data can organizations understand what is happening with their applications. That is important to ensure applications perform as expected to yield the desired business results.

AIOps Sees Everything…and then some

Artificial Intelligence for IT Operations (AIOps) changes IT Operations by correlating, visualizing and predicting business affecting issues across hybrid IT stacks. It allows IT operations unprecedented visibility into the relationships between every entity in your IT ecosystem.

Let’s take a look at what machine learning for AIOps can do for you.

Application and Infrastructure Inventory – With the complexity of running multifaceted, multi-tier enterprise applications, do you really know what you have in terms of infrastructure and application assets? AIOps with machine learning technology map all the relationship between all of the entities in your IT ecosystem. Before you continue to invest in your stack, you have to know exactly what is in your stack and how it works together. You need to see an accurate and complete inventory of application dependencies so that you know the potential impact of changes and plan transitions and migrations that will not affect the application performance monitoring of business critical applications.

Optimum End User Performance – With AIOps, monitor performance from an end-user’s perspective from transaction through each aspect of the datacenter ensures high performing applications for each individual transaction—with no blind spots—including front end, application performance, infrastructure, containers, and cloud. High-performing customer-facing applications help increase revenues, customer satisfaction, and business agility.

Quickly Identify Root Cause – AIOps maps the flow from applications to infrastructure, including application flows, and virtual and physical compute, network, and storage locations. With these maps, you reduce the complexity and can rapidly drill down, see anomalies, and rectify the situation quickly.

Predict Problems Before they Happen – Increase uptime and performance with AIOps predictive analytics. AIOps correlate data and uncover patterns, which allow your organization to discern what problems are likely to appear downstream from trouble spots. Predictive analytics enable companies like yours to address potential problems before they impact applications and business operations.

Get More Out of Your Cloud Investment – AIOps provides intelligence on application performance so businesses can better allocate resources. The data correlation capabilities reveal what specific resources each application requires. This mitigates the risk of overinvesting and helps you purchase only those cloud resources your applications require.

Traditional, domain-centric monitoring and IT operations management tools are now inadequate because they can’t correlate the onslaught of data various IT domains create. What’s more, they’re unable to provide the insights IT operations teams need to proactively manage their environments – and that just doesn’t work.

IT organizations need a new class of technology to modernize the IT operations process. This technology needs to be able to correlate millions of data points across all IT domains. It should have the smarts to apply machine learning to detect patterns and it should present that information so organizations can easily see what’s happening and gain insights. This technology is AIOps.

About the Author

Enzo Signore, Chief Marketing Officer, Fixstream is passionate about building and growing businesses. He brings a wealth of industry and marketing experience, having led the go to market strategy of early stage companies and established leaders like Cisco and Avaya. Most recently Enzo was the CMO at 8×8, a public SaaS communications company and 5-times Gartner Magic Quadrant leader. Prior, Enzo was responsible for marketing at Avaya, a $4B communications company and for marketing and sales at JDS Uniphase, the leader in optical and test & measurement solutions. Earlier Enzo lead the DSL and Cable business at Cisco, and helped two early stage companies (Retix and ISOCOR) grown from Series A to successful IPO’s. Enzo loves to travel, play sports and is an avid Torino soccer fan.

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