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How to get a higher return on your Intelligent Automation investment

maximizing your intelligent automation ROI

Despite the fact that intelligent automation offers a multitude of benefits to organizations of all sizes and industries, there are still many key decision makers that fail to recognize the value this technology can have for their own enterprises. In order to demonstrate how important automation is for the future of business, IT managers must find a way to maximize ROI and demonstrate the quantifiable benefits to the powers that be. Here are five simple strategies for getting those numbers headed in a positive direction.

Define Needs, Benefits and Expectations

You can’t focus on improving anything – whether it’s efficiency through intelligent automation or the actual ROI it delivers – unless everyone understands what to expect. Time should be taken to identify and define the specific needs of the organization, and then specify how automation can solve those problems and meet those needs. Once this information is gathered, you can then more accurately measure all of the specific areas where automation is producing a solid return and how. A few key places to start include effort reduction, mean-time-to-resolution (MTTR), lowered rate of error, compliance and system up-time. Improving each of these areas will directly boost your return on investment.

Understand the Process and Where Automation Fits

The driving purpose behind intelligent automation is to use technology to replicate repetitive, manual tasks. To improve automation ROI, one must dig much deeper than this basic concept to understand the entire process at hand and identify exactly how automation can be integrated for optimal results. Important questions to ask in this analysis include:

  • What factors should trigger an automated process?
  • What must occur before and after the automated process?
  • What variables and inputs will be necessary to achieve the best outcome?

Most importantly, how does automation fit with the big picture – the larger business process as a whole? While individual tasks could certainly be automated, automating the entire process or workflow may actually produce a greater value for the business.

Recognize the Context and Customize Accordingly

Calculating accurate ROI involves understanding the specific context in which the automated process in question is running and customizing that process for optimal results. For instance, the automated response to a critical incident, such a systems outage, during peak business hours should be markedly different than the response to a similar outage that occurs in the middle of the night. These contextual considerations should be built into the automation process and they should also be considered whenever measuring results. By customizing the process, the intelligent automation platform can execute different actions based on each scenario, thereby producing a greater return overall.

Test Thoroughly Prior to Release

Testing an automated process manually or in a development system can certainly be time consuming, but it’s absolutely critical to achieving maximum ROI. Before an automated process is deployed in a live environment, it must be adequately measured to ensure that it is not only producing the desired results, but is doing so consistently. Once the automated process is released, ongoing testing is still strongly recommended, as this helps to ensure that the triggers, inputs, actions and outputs are all running as smoothly and efficiently as possible. Routine audits can also help to identify areas that could be improved upon for even greater benefit.

Ongoing Evaluation and Improvement

Intelligent automation may feel like a “set it and forget it” solution, and theoretically it is to a certain degree, but the organizations that reap the greatest rewards from this technology do so by taking a continuous process improvement approach. Regular evaluation of how automated process are working and analysis of where they may be expanded to produce even better results is a must if you are looking to maximize ROI. IT professionals should be asking whether additional tasks could be automated, or whether existing automated processes could be integrated with one another or built upon for greater efficiency.

Individually, each of these five tips can have an impact on your overall return. When combined, however, they can help to both improve short-term goals as well as drive long-term strategies to produce the desired results of reducing human effort, improving operational efficiency, boosting service levels, reducing errors and downtime, remaining compliant and much more. The end product is a consistently favorable return on investment, which can help to win over those who are not yet on the intelligent automation bandwagon.

Want to see some real-world numbers that can be generated by intelligent automation? Check out our latest case study below.

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How to Predict and Remediate IT Incidents Before They Affect Business Outcomes [Webinar Recap]

Author: Guy Nadivi

The ability to proactively predict  and remediate IT incidents BEFORE they occur, rather than react to them after they’ve already happened, is one of the key value propositions of a new IT operations category called AIOps, which stands for Artificial Intelligence for IT Operations.

Leveraging the AI part of AIOps to mitigate problems before they become problems is a game changer for IT. So we’ve partnered with Loom Systems, who like ourselves are a Gartner Cool Vendor in their category, to demonstrate how two best-of-breed providers can integrate their respective platforms to create an enterprise-grade AIOps solution. In doing so, we believe the result is an early glimpse at the self-healing data center of tomorrow, and we think you’ll be intrigued to experience how you can peek over the horizon to see  and automatically remediate incidents before they impact end-users.

Let’s start with the obvious question many of you might have on your mind – what is AIOps? It is after all, a term that kind of snuck up on all of us.

The term AIOps, like a lot of buzzwords in our industry, was originated by Gartner. In this case, a Sr. Director Analyst named Colin Fletcher coined it in 2016, and its earliest published appearance (as best I can tell) was in early 2017.

Interestingly though, Colin told me he originally meant the term to refer to Algorithmic IT Operations.

Since then it’s evolved to refer to Artificial Intelligence for IT Operations.

Now we all know how it is in IT marketing. New buzzwords are used to refresh a category and create excitement. So is AIOps basically just a recycling of the term “IT monitoring”? Are IT monitoring and AIOps basically the same? Twins, so to speak, but with different names?

Here’s the definition for IT Monitoring, courtesy of an internet publication many of you are probably aware of called TechTarget:

  “IT monitoring is the process to gather metrics about the operations of an IT environment’s hardware and software to ensure everything functions as expected to support applications and services.   Basic monitoring is performed through device operation checks, while more advanced monitoring gives granular views on operational statuses, including average response times, number of application instances, error and request rates, CPU usage and application availability.”    

The operative words there are “gather metrics” – “through device operation checks”.

This reflects one of the primary characteristics of IT Monitoring – namely that it’s passive in nature.

And here’s Colin Fletcher’s original definition for AIOps:

“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.”

Unlike IT Monitoring, AIOps is proactive and far more sophisticated. So AIOps is a LOT MORE than just IT Monitoring.

At this point you may be asking yourself, “OK, but how can this benefit me?”

As we all know, in today’s Digital Era, most businesses are digital or undergoing a digital transformation, which means that IT systems are replacing many traditional physical business processes, and that in turn means more work for IT Operations.

In fact, IT Operations engineers have become responsible for the customers’ digital experience. When your organization’s systems are misbehaving, underperforming, or worse not working at all, your customers’ satisfaction is affected, which often leads to customer churn.

It’s that simple.

End users often use applications or websites and love how simple and intuitive they can be. In IT though, we all know that building something to look nice and simple, can actually be quite difficult. That’s because there are usually many technologies under the hood that need to work together seamlessly in order for these digital experiences to run smoothly.

As if that wasn’t enough, let’s add some more complexity:

With Cloud Computing on the one hand, and Microservices architectures on the other, things become even more complex, for the following reasons:

  1. Cloud computing means abstraction – that can lead to struggles understanding what the impact of a performance issue on a host will do to other components of your applications.
  2. These environments change dynamically, making it harder to stay on top of everything.
  3. Microservices often require disparate data sources, each generating its own logs and metrics, making tracing and correlation an inherent part of root cause analysis (RCA).

So, the increased complexity of digital businesses architectures, coupled with the explosion of different data types, and the elevated expectations consumers have these days for seamless end user experiences, makes the life of IT Operations teams quite challenging.

Enter AIOps.

AIOps is a set of tools that enable achievement of optimum availability and performance by leveraging machine learning technologies against massive data stores with wide variance. The big idea here is to use machines to deal with machines.

Here are some examples of the challenges customers often look to address by implementing AIOps:

  • Outage prevention – organizations in the process of cloud migration or architecture change, often look for modern technologies like AIOps to help them prevent outages before the business is affected. This is a marked difference from 2 years ago when the market was just focused on noise reduction. Artificial intelligence and machine learning have raised expectations of how much more is possible.
  • Capturing different data feeds – this means it’s not just about alerts anymore. There’s a huge need to consolidate logs, metrics, and events together, and to make sense out of them as a whole.
  • Consolidation of tools – this one is mainly about the workflow of the users. They’d like AIOps to make their daily lives easier and consolidate everything into one system.

A monitoring architecture for modern enterprises that can do all of the above would be a real-life example of a self-healing architecture.

Everything starts with observability. Many enterprises use one or more infrastructure monitoring tools. Application Performance Management (APM) monitors do a great job in monitoring performance, but are very limited for the application stack and log management, rendering them a bit unhelpful for triage and forensic investigations.

These monitoring tools are usually focused on specific data feeds or IT layers, and they emit alerts when things go wrong. However, these can lead to confusing alert storms.

This is another reason why organizations are beginning to leverage AIOps to work for them and make sense out of it all. Think of AIOps as a robot that turns monotonous data into information you cannot ignore. In our case, turning logs into predictions or early stage detection of an outage.

Now that you know something is about to break, can you prevent it from happening? That’s exactly the idea of self-healing. When working with an intelligent automation platform like Ayehu, you can build simple (or complex) remediation workflows, that can take the alert from Loom Systems and automatically remediate the incident BEFORE it becomes something more calamitous.

In your monitoring architecture, you want the Automation tool to seamlessly interact with both the AIOps solution and your ITSM platform, to open a ticket and update it as you’re taking remedial action.

When configured properly, this architecture can resolve issues before they affect the business, while also documenting what happened for future reference.

Gartner concurs with this approach.

In a paper published earlier this year (ID G00384249 – April 24, 2019), they wrote that:

  “AI technologies play an important role in I andO, providing benefits such as reduced mean time to response (MTTR), faster root cause analysis (RCA) and increased I andO productivity. AI technologies enable I andO teams to minimize low-value repetitive tasks and engage in higher-productivity/value-oriented actions.”    

No ambiguity there.

A little further down in the same paper, Gartner gave the following recommended actions, representing their most current advice to infrastructure and operations leaders regarding AIOps and automation:

  Embark on a journey toward driving intelligent automation. This involves managing and driving AI capabilities that are embedded by infrastructure vendors, in addition to reusing artificial intelligence for operations (AIOps) capabilities to drive end-to-end (from digital product to infrastructure) automation.”    

With AIOps + Automation, it’s possible to predict and prevent network outages or other major disruptions by proactively detecting the conditions leading up to them and automatically remediating them BEFORE disaster strikes. Given how costly a service interruption can be to an enterprise, avoiding issues before they happen will be a critical function in the self-healing data center of tomorrow.

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Ayehu Announces Availability of NG Intelligent IT Automation Platform Version 1.5

Latest AI-Powered Platform Enhances Productivity and Flexibility with New Activity Designer and GitHub Community Repository

San Jose, CA –- October 16, 2019 Ayehu, a leader in intelligent automation, has announced the availability of its Next Generation (NG) IT Automation and Orchestration Platform, Version 1.5. The new release provides IT and security operations teams with new features that give users more control and flexibility, driving increased productivity.

“As corporations are facing enormous digital challenges, CIOs are being required to do more with less,” said Yaron Levy, Co-Founder and Chief Technology Officer, Ayehu. “The NG platform automates the increasing influx of system alerts and incidents and can also potentially take care of all Level 1 help desk requests. Our latest version gives users more options to access, create and customize the workflows they need to automate. This accelerates results and maximizes the value of automation.”

Ayehu’s scalable NG platform delivers automated workflows that help enterprises save significant time on manual and repetitive tasks and maintain greater control over IT infrastructure.

By acting as a centralized hub that intelligently automates IT service management, cyber security, monitoring and messaging, and virtual support agent workflows, the AI-powered platform reduces mean-time-to-resolution by up to 90%. And as the backbone for intelligent virtual support agents and chatbots, Ayehu helps IT leaders embrace the future of work. The easily adoptable solution communicates and resolves tickets, issues and requests automatically. This greatly reduces, and in some cases even eliminates the L1 and L2 support demands.

The latest version includes the following productivity and flexibility enhancements:

  • Activity Designer – A new feature designed to give users the option to build their own activities as an extension of the library of more than 500 no-code, pre-built activities provided by Ayehu. Customers can now independently develop or modify existing activities in Python, C# or .net to extract further value through customization that meets specific needs.
  • GitHub Community Repository – A new community hub that contains more than 100 of Ayehu’s workflow templates, as well as source code for built-in activities. Customers can use this in conjunction with the Activity Designer to create custom activities based on existing pre-built workflows. The GitHub Community Repository also provides free access to useful peer-developed workflow templates and activities in Ayehu NG Workflow and Activities which have already been created and contributed to the community. 
  • Activity Designer Training – Two new Ayehu Automation Academy courses, Activity Designer Essentials and Advanced Activity Designer, train and certify developers in creating new activities using the Activity Designer. Certified Activity Designers can enhance their organization’s automation capabilities or develop new income opportunities for themselves by delivering high-quality activities for third parties. The Academy has already certified nearly 1,000 IT automation engineers since its inception earlier this year.

“Intelligent automation is a necessary force multiplier for CIOs and IT leaders who want to create successful self-driving organizations, achieve operational efficiency and improve employee experience with IT,” added Gabby Nizri, co-founder and CEO, Ayehu. “It is our mission to provide the technology, tools and resources that help them turn understaffed, strapped IT and security departments into happier, more efficient and productive teams.”

To learn more about the Ayehu Next Generation Automation and Orchestration Platform Version 1.5 visit: https://ayehu.com/ayehu-it-automation-orchestration-platform-powered-by-ai/

About Ayehu

Ayehu’s AI-powered automation and orchestration platform is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by more than 200 major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe. For more information, please visit www.ayehu.com and the company blog.  Follow Ayehu on Twitter and LinkedIn.

The changing role of CIO and intelligent automation’s impact.

With the ever-increasing volume and complexity of data coming in (thanks in large part to trends like the IoT, BYOD and, of course, Big Data), the role of the CIO has also begun to rapidly evolve over the past decade or so. These individuals are now facing pressures to keep infrastructure updated as well as analyze and leverage the data available to them for the benefit of the organization, and all while keeping costs down and internal networks, systems, applications and information secure. This is no easy feat, but thanks to intelligent automation, it is entirely achievable.

Due to the heavy volume of data being shared today, integrating automated workflows and processes has become increasingly necessary in order to analyze and derive value from that data, and in a way that is as cost-effective as possible. If IT departments are to remain relevant, drive efficiency and support a profitable operation, it is imperative that they employ the use of intelligent automation, and with the CIO as the key decision maker, it’s up to him or her to ensure that the right resources are in place.

As recently as just a few short years ago, the general public was becoming aware of the IoT, but today organizations of every size and industry are capturing insight and achieving real, sustainable ROI from this advanced (and ever-evolving) technology. Furthermore, intelligent automation is virtually revolutionizing everything from the SOC and NOC to the service desk and data center. Intuitive technology and artificial intelligence are being utilized to proactively monitor systems and devices, gather and evaluate complex data, remediate incidents and resolve issues – in many cases before any human worker is even made aware.

As a result of all of these changes, more basic requests, like password resets and system refreshes, which used to be handled almost exclusively by L1 support professionals are now being shifted to intelligent automation technology. Self-service chatbots are empowering the end-user like never before while simultaneously alleviating IT personnel of the heavy burden associated with these routine, repetitive (but necessary) tasks.

Of course, this hasn’t necessarily made life perfect for IT professionals. Increased consumerization of IT has resulted in the services of many IT departments being compared and contrasted against that of external service providers. Expectations of faster service and the demand to take on more while also minimizing costs as much as possible continue to rise, subsequently increasing the pressures on top IT personnel. Perhaps no one is feeling the pressures of these demands more than the CIO. Embracing intelligent automation is no longer an option, but a critical requirement.

At the same time, the IT world is witnessing a significant change in responsibilities for the CIO, shifting from the old way of the maintenance and provision of physical infrastructure and devices to more of a data management role with an emphasis on innovating and creating value. Digitalization is now the focus, with CIOs playing a lead role in developing and implementing it throughout the entire enterprise. Paradoxically, these high-level IT professionals are being forced to orient and align themselves more with value creation than the efficiency that once defined them.

Data analytics is now being hailed as one of the primary contributors to driving this value, particularly given the ever-increasing pool of available information. It’s important to point out, however, that CIOs and other top IT managers must take the time necessary to understand what data is available to them, what that data equates to and, most importantly, how they can best leverage that information to improve operations across all functions of the organization. Savvy CIOs will leverage intelligent automation to obtain key insights that will support current and future business goals as well as identify new insight and make data-driven decisions that will give the company competitive advantage.

Finally, the evolving role of the CIO will involve more engagement, inspiration and education of others than ever before. To fulfill these duties, it’s absolutely essential that the CIO develops into a strong visionary and consistent innovator for the organization. Through better data analysis and the more widespread use of intelligent automation, those in this important role will begin to morph into the position of strategic advisor, driving the business onward and upward toward increasing and sustainable success well into the future.

Are you a CIO that is struggling to adapt to your changing role? Intelligent automation, powered by AI and machine learning, could provide the foundation upon which you can continue to build your career and your legacy.

Experience the power of Next-Gen Intelligent Automation today!

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3 Ways NOT Automating Could Cost Your Business (Big Time)

Industry experts frequently point out the many ways leveraging intelligent automation can benefit an organization. For instance, increased efficiency levels, lower expenditure, scalability and the ability to do more with less all top the list. What we don’t often mention, however, is the flipside. That is, the impact NOT automating could potentially have on a company’s ongoing success and future profitability. In fact, failing to automate can come at a substantial cost in three specific areas. Here’s how.

Human Error

As the IT realm continues to become more complex, the risk of errors by the individuals responsible for handling fundamental tasks and workflows will inevitably increase. These errors can be costly in a number of ways, including impact to both internal departments as well as clients, and potential loss of business. These costs can be further compounded by the amount of time it takes the IT department to correct said errors.

To gain a clearer picture of exactly how much human error can cost your organization, take some time to document all the recent mistakes your IT team has made and then assign a dollar value to each of those errors. You may be surprised at how much those losses can truly add up. What’s more, the larger your organization grows, the more complex your infrastructure will become, which means an even greater risk of IT errors. Intelligent automation dramatically reduces, and in most cases, entirely eliminates human error, ensuring a more efficient and effective operation overall.

Employee Turnover

Recent data estimates that replacing an employee can cost a business up to 33% of that person’s annual salary. To put this into perspective, let’s say you pay your average IT support technician a salary of $45,000 per year. If that employee quits, it could cost you up to $15k just to find someone to find their replacement. That’s an incredible waste of money.

In the IT field, however, turnover is a serious problem, the biggest reason for which is employee burnout. Being on call 24/7 may be par for the course, but those 2am phone calls get old real quick. Furthermore, having staff on-hand to monitor, maintain and update your infrastructure around the clock isn’t practical, nor is it typically feasible.

By introducing intelligent automation into the mix, you’ll alleviate much of the unnecessary burden from your IT team. They’ll be able to focus their efforts on more meaningful work, which will keep them engaged and happy. In turn, they’ll be more likely to recommend you as a good employer to their own networks, which could help you recruit additional talent when it comes time to scale.

Missed Opportunities

Tying in directly with the two points listed above is the third way lack of automation can cost your business: missed opportunities. When employees are bogged down with manual, repetitive and boring tasks, not only will they not have the time or energy to work on other, more meaningful projects, but if they’ve got one foot out the door, they probably won’t care much about your company’s success anyway.

Likewise, when human errors are causing issues with the current way your organization operates, it can stagnate your chances to scale and grow. In other words, your IT team will be so busy putting out fires and trying to recover from costly mistakes, they won’t have the time or energy to dedicate to other value-added and mission-driven activities.

If you want your company to be able to compete in the digital age, you need employees who are ready, willing – and most importantly – able to innovate. Intelligent automation complements human workers by doing much of the heavy lifting while enabling better decision-making and freeing up employees to fully utilize their cognitive abilities. This creates a “best of both worlds” scenario where everyone benefits.

So, can intelligent automation save your company money, make your operations more efficient and provide other valuable benefits? Absolutely. But it’s equally as important to consider what the real costs are of not automating. The question you should be asking isn’t should you automate, but rather can you really afford not to.

Get started with AI-powered intelligent automation today FREE for 30 days. Click here to claim your free trial.

Still holding out on IT automation? Here are 4 signs the time has come.

stop resisting IT automation

IT automation is certainly not a new concept. In fact, it’s been in use to some degree for over a century. Yet, there are still a great number of enterprise-level organizations that are on the fence about whether this advanced technology is really worth investing in. If you are one of these late bloomers and are still unsure of whether or not you should take the plunge and employ intelligent IT automation in your company, here are four signs that will let you know it’s time.

Your IT department is struggling to deliver services in a timely, efficient manner.

When a ticket gets opened to IT, how long does it take to achieve satisfactory resolution? In today’s fast-paced business environment, regardless of what industry you are in, agility and efficiency are absolutely critical to ongoing success and future growth. If the demands of your workforce are becoming too much for your skilled IT personnel to handle, the time to leverage technology has come. Not only will IT automation alleviate the burden of many of the day-to-day repetitive tasks, but it will also free up your talented technicians to apply their valuable skills in a more resourceful and profitable manner.

You have way too many staff members on hand just to handle those peak cycles.

Optimized resource allocation is the key to running a lean, profitable operation. If you have far too many IT employees on the payroll just so you can ensure smooth workflow during peak cycles, you are undoubtedly wasting money the rest of the year. Conversely, if your current IT department becomes completely overwhelmed during those peak cycles, your capacity is too low and you’re likely to see higher employee turnover rates. IT automation provides the ability to scale up or down as needed without having to make any changes to your human workforce.

Your employees are wasting an incredible amount of time and effort on repetitive tasks.

Even if you feel that your operation is being managed at the appropriate capacity and the turnaround time of your IT department is acceptable, if your IT team is spending the majority of their day completing manual tasks and processes, you’re wasting money and missing out on opportunity. You’re also facing a much higher risk of costly human error. Why not let artificial intelligence handle these simple, routine tasks? That way you’ll be paying an appropriate salary to workers who are able to better utilize their valuable skillset and the work will be completed faster and more accurately.

Your legacy systems and applications are operating independently.

Of course it doesn’t make sense to invest in an entire system overhaul, but what kind of operation are you running if every application you’ve got in place is functioning in its own silo. The problem many organizations face is the fact that legacy systems which offer useful benefits individually don’t have the capability of working together. This leads to tremendous inefficiency. The beauty of most modern IT automation and orchestration platforms is that they are designed to integrate existing systems, platforms and applications to create a more cohesive and streamlined infrastructure. This allows the organization to avail itself of all the benefits of each legacy system as they work in tandem, complementing and enhancing each other’s capabilities.

If you can relate to any of the four challenges listed above, the time to consider adopting intelligent IT automation is now. Get started today with your free 30 day trial and see for yourself what you’ve been missing out on.

eBook: 10 time consuming tasks you should automate

4 Tech Trends to Watch for in 2020

4 Tech Trends to Watch for in 2020Technology has been evolving since the dawn of time. As we prepare to enter another new decade, we can expect to see even more accelerated change on the tech front. With so much happening so remarkably quickly, it can be difficult to know which trends to track. To narrow things down, we’ve rounded up the top four adaptations that we believe will bring the greatest innovation and growth in 2020 and beyond. Take a look below.

Intelligent Automation

Not surprisingly, intelligent automation topped our list of technologies that will drive progress and success over the next several years. Thanks to the growing proliferation of cloud computing, big data and increasingly “smart” robotics, the future is a place where automation will no longer be an option, but rather a necessity. Leveraging these highly advanced technologies will enable organizations in every industry to streamline operations, maximize efficiency and uptime, dramatically lower costs and remain competitive.

Intuitive AI

While artificial intelligence plays a role in the big-picture automation trend, its capabilities and ongoing advancements warrant a separate mention on this list. The computers of tomorrow will be able to learn and evolve much the same way we do, which means that in addition to increased computing power, AI will be able to carry out tasks that were once reserved for humans and at a lightning speed. Underlying technologies, like machine learning, facial recognition and natural language processing will enable AI to continue to learn and grow smarter without the need for human intervention.

Voice Command

We’ve already begun seeing rapid and advancing developments in voice technology, thanks to the increasing adoption of voice assistants, like Siri and Alexa. Over the coming months and years, expect to see voice technology continue to develop and improve, particularly in the way of its ability to interpret and understand the context of the spoken word. This is where NLP will really begin to have a significant impact on our day to day lives.

Analytics

Enterprises across the globe are already leveraging analytics as a key driver of growth and innovation. Not only can analytics confirm whether you are successful in your industry, but they can help predict which direction the market will likely head in over the coming months and years. Data processing, facilitated by AI and machine learning, will continue to be used to turn massive amounts of information into actionable insights, as well as identifying issues and recommending next steps.

Without question, we are entering an exciting era in technological advancement. The most exciting part is that you don’t have to wait until next year to experience the power of these amazing tech trends. Download your free 30 day trial of Ayehu today and put the power of intelligent automation, powered by AI and machine learning, to work for you! Click here to get started.

How is AIOps Really Used in IT?

How is AIOps Really Used in IT?

Digital transformation has simultaneously simplified and added a layer of complexity to the modern world of IT operations. Managing multiple environments across a number of locations invoked the need to introduce several disparate tools and platforms, leaving IT siloed and, oftentimes, overwhelmed. This has perpetuated the need for artificial intelligence for IT operations, or AIOps for short. For those not yet leveraging AIOps, or who are still in the beginning stages, here are three real-world, value-added use cases to consider.

Threat Detection – AIOps is the perfect complement to a security management strategy because its machine learning algorithms are capable of mining massive amounts of data for scripts, botnets and other threats or anomalies that could potentially harm a network. This is especially true for threats that are complex and sophisticated, which is why it’s such a valuable addition.

Intelligent Alerting – Today’s ITOps teams are being inundated with alerts of which only a small portion are actually critical. AIOps can manage these alerts autonomously, evaluating, identifying core issues, prioritizing and either escalating or remediating them without the need for human intervention. Imagine trimming that overflowing inbox of alerts down to just one or two that truly matter.

Capacity Optimization – Through the use of AI-based statistical analysis, IT operations teams can optimize application workloads and availability across the entire infrastructure. This technology is capable of proactively monitoring bandwidth, utilization, CPU, memory and much more, with the goal of maximizing application uptime. AIOps can also be used for predictive capacity planning.

Of course, this is really just the beginning. As environments become increasingly complex and technology options continue to grow, IT operations teams will find themselves under even more pressure to deliver maximum business value with minimal downtime. AIOps emerges as the ideal solution, facilitating infrastructure monitoring and management that is much faster and far more efficient. It’s no surprise, that IT leaders and other key decision-makers are starting to take notice.

Today, AIOps is all about threat management, streamlined alerting and maximizing uptime. Tomorrow, IT automation powered by artificial intelligence, machine learning and natural language processing technology is positioned to forge entirely new pathways for innovation and growth. In other words, the journey has just begun and the future is beaming with possibility.

Want to get in on the ground floor? Grab your free 30-day trial of Ayehu NG and put the power of AIOps to work for your organization.

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Bridging the NOC and SOC for an Integrated IT Powerhouse

The similarities between the role of the Network Operation Center (NOC) and Security Operation Center (SOC) often lead to the mistaken idea that one can easily handle the other’s duties. Furthermore, once a company’s security information and event management system is in place, it can seem pointless to spend money on a SOC. So why can’t the NOC just handle both functions? Why should each work separately but in conjunction with one another? Let’s take a look a few reasons below.

First, their roles are subtly but fundamentally different. While it’s certainly true that both groups are responsible for identifying, investigating, prioritizing and escalating/resolving issues, the types of issues and the impact they have are considerably different. Specifically, the NOC is responsible for handling incidents that affect performance or availability while the SOC handles those incidents that affect the security of information assets. The goal of each is to manage risk, however, the way they accomplish this goal is markedly different.

The NOC’s job is to meet service level agreements (SLAs) and manage incidents in a way that reduces downtime – in other words, a focus on availability and performance. The SOC is measured on their ability to protect intellectual property and sensitive customer data – a focus on security. While both of these things are critically important to the success of an organization, having one handle the other’s duties can spell disaster, mainly because their approaches are so different.

Another reason the NOC and SOC should not be combined is because the skillset required for members of each group is vastly different. A NOC analyst must be proficient in network, application and systems engineering, while SOC analysts require security engineering skills. Furthermore, the very nature of the adversaries that each group battles differs, with the SOC focusing on “intelligent adversaries” and the NOC dealing with naturally occurring system events. These completely different directions result in contrasting solutions which can be extremely difficult for each group to adapt to.

A new set of problems arise, however, when the two teams become siloed, with each group focused on only half of the equation. The resulting gap, particularly in terms of data that is not being shared, perpetuates an even broader gap in the necessary knowledge to maximize the effectiveness of each team. Efforts by the SOC that fail to take into account operational requirements or efficiencies cause bottlenecks that can result in a disruption in network performance. Likewise, fingers can be pointed at the NOC for implementing network designs that leave critical resources exposed and vulnerable.

The best solution is to respect the subtle yet fundamental differences between these two groups and leverage a quality automation product to link the two, allowing them to collaborate for optimum results. The ideal system is one where the NOC has access to the SIEM, so they can work in close collaboration with the SOC and each can complement – rather than impede – the other’s duties. The SOC identifies and analyzes issues, then recommends fixes to the NOC, who analyzes the impact those fixes will have on the organization and then modifies and implements accordingly.

So, what’s the best way to achieve this cross-functional collaboration and optimization? The most important goal is to eliminate operational and/or technical silos. By leveraging a cross-silo intelligent automation platform, security incidents can be detected and resolved while events simultaneously trigger automatic changes both to security as well as network device configurations. This essentially closes the loop on cyberattack mitigation while effectively bridging the distance between security and ops teams.

As the IT environment introduces increasingly complex applications and workflows across a spectrum of systems and devices, and oftentimes in a variety of different locations, the demand for a more streamlined, holistic approach also continues to grow. The time has come to rethink the way the NOC and SOC work together. With an orchestrated approach, powered by intelligent automation, organizations will be able to close the gap between the two departments to more effectively address today’s multifaceted threats, regardless of where they happen to occur within the network.

Ayehu NG is an intelligent IT Automation and Orchestration platform built for the digital era. As an agentless platform, Ayehu is easily deployed, allowing organizations to rapidly automate tasks and processes, including interoperability across disparate solutions and systems, all in one, unified platform.

If you’re ready to bridge the gap between your NOC and SOC to create an integrated IT powerhouse, click here to start your free trial.

Solving your “what if” scenarios with intelligent automation

When it comes to convincing businesses that intelligent automation is the way of the future, the biggest objection to overcome is the age-old question, “what if….” Many IT professionals and other key decision makers within an organization carry the fear that automated tasks which are put in place to solve a problem may actually end up causing more harm than good.

What could go wrong? What if the whole thing blows up in our faces and we end up with an even bigger mess on our hands? The answer is simple: when automation is designed and tested properly, everything should work out just as it is planned, and the results will be well worth the effort.

Creating and Designing Your Workflow

The first step in setting up intelligent automation so that it works properly is creating and designing your workflows. You have to have your end result in mind, and then figure out the steps necessary to achieve that end result. Various criteria will need to be identified, so that you know whenever a certain function or task occurs, the next step in the workflow will automatically be triggered. So, to summarize, establish your desired end result, and then develop a list of steps to help you achieve that result. List each criterion in the process and determine what next step each criterion would trigger.

Testing 123…

The next important step, once you’ve created your workflow, is to try it out in a controlled environment. Test each step in the process to verify that the desired result for each is achieved. If something isn’t working properly, re-evaluate to determine why and then work to fix that piece until the entire process is functioning correctly. We recommend starting small and testing a variety of situations and scenarios to really be sure everything is working properly. Continue this process until you are confident that your automated workflow is working precisely as it should.

Implement

Once you’ve tested your automated workflow enough to be confident that it’s functioning as it is meant to function, it’s time to put it into action. It can be a bit nerve wracking to implement a workflow for the first time live, but once you see it in action, you’ll become that much more confident that it will be there to meet your needs whenever necessary.

Call on the Experts

If, at any time during the above outlined process, you feel as though you’re not getting the results you’re looking for, or you need some guidance and support, don’t be afraid to reach out to the experts. Remember, part of choosing the right intelligent automation product is choosing a company that offers plenty of training and support to its customers. Any company will be there for you when you’re in the process of making a purchasing decision, but you want to make sure that you choose someone that will also be there for you after the fact. If you’re feeling overwhelmed or just have a few questions, don’t be afraid to reach out to your software partner for assistance.

The hands-off nature of intelligent automation can make some professionals feel uneasy. They may wonder if the very system that’s being put in place to solve a particular problem within the organization will actually end up causing more harm than good. The truth is when you know the steps to take, and you’re careful to work through each step just as you should, the result will be exactly what you’re hoping for. When automation is created, developed, tested and supported properly, there is no longer the need to ask “what if”, but rather “why did I wait so long to do this?”

What are YOU waiting for? Contact us or better yet – download your free trial today to start leveraging intelligent automation for your organization.

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