Ayehu Named as a Deloitte 2017 Technology Fast 500 EMEA Company

deloitte fast 500 EMEAGrowth attributed to global demand for Ayehu’s IT Automation and Orchestration Platform Powered by Artificial Intelligence

San Jose, CA – December 12, 2017Ayehu, provider of an intelligent automation and orchestration platform powered by Artificial Intelligence, today announced it was included in the Deloitte Technology Fast 500™ EMEA list, a ranking of the 500 fastest-growing technology, media, telecommunications, life sciences and energy tech companies in Europe, the Middle East and Africa (EMEA). Ayehu grew nearly 260 percent during the four-year period.

Ayehu’s chief executive officer, Gabby Nizri, attributes its continued strong growth to the increasing global demand for its IT automation and orchestration platform.

“More organizations are moving toward creating a self-driving enterprise in this digital era. Powered by AI and machine learning, our platform is an essential tool for making the steps toward digital transformation and ensuring future success,” said Nizri.

Ayehu acts as a force multiplier, driving efficiency through a simple and powerful IT automation and orchestration platform powered by AI. The next generation platform is SaaS-ready for hybrid deployments and is powered by machine learning driven decision support, for fully enhanced and optimized automated workflows. IT and security operations can fully automate and mimic the response of an experienced IT or security operators and analysts, including complex tasks across multiple, disparate systems, executing thousands of well-defined instructions without any programming required, helping to resolve virtually any alert, incident or crisis.

About Deloitte Global’s 2017 Technology Fast 500 EMEA program

Deloitte Global’s Technology Fast 500™ EMEA program is an objective industry ranking focused on the technology ecosystem. It recognizes technology companies that have achieved the fastest rates of revenue growth in Europe, the Middle East, and Africa (EMEA) during the past four years. The program is supported by Deloitte Global’s Technology Fast 50 initiatives, which rank high-growth technology companies by location or specifically defined geographic area, and are run by Deloitte Global’s Technology, Media & Telecommunications (TMT) industry group. More information on the program is available at www.deloitte.com/fast500emea.

Now in its seventeenth year, the Technology Fast 500 program in EMEA included over 18 countries, including Belgium, France, Finland, Germany, Italy, the Netherlands, Turkey and the UK. This year’s winners were selected based on percentage fiscal-year revenue growth from 2013 to 2016.

Sponsors of Deloitte Global’s 2017 Technology Fast 500 EMEA program are Euronext, a pan-European exchange that helps tech companies finance growth and innovative projects through the stock market; Oracle NetSuite, provider of cloud-based financials / Enterprise Resource Planning (ERP), HR and omnichannel commerce software that runs the business of companies in more than 100 countries; and Michael Page, recognized by clients and candidates the world over as the leading specialist consultancy in permanent recruitment, temporary staffing and interim management.

About Deloitte

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL (also referred to as “Deloitte Global”) and each of its member firms are legally separate and independent entities. DTTL does not provide services to clients. Please see www.deloitte.com/about to learn more about our global network of member firms.

Deloitte provides audit & assurance, consulting, financial advisory, risk advisory, tax and related services to public and private clients spanning multiple industries. Deloitte serves four out of five Fortune Global 500® companies through a globally connected network of member firms in more than 150 countries and territories bringing world-class capabilities, insights and service to address clients’ most complex business challenges. To learn more about how Deloitte’s approximately 264,000 professionals make an impact that matters, please connect with us on Facebook, LinkedIn or Twitter.

About Ayehu

Named by Gartner as a Cool Vendor, Ayehu’s IT 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 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 Case for Robotic Process Automation in Financial Services

Without question, the financial services industry has experienced tremendous change over the past decade or so. Between ever-changing regulatory challenges to evolving technology to increased competition and more, staying afloat in this field certainly isn’t easy. Robotic process automation (RPA) is helping many institutions meet these challenges head on and emerge even more successful on the other side.

First, it’s important to clarify that despite its name, adopting RPA isn’t technically about unleashing an army of actual robots to perform the rote work of humans. In reality, robotic process automation involves software applications which are designed to handle everything from simple, routine tasks to complex workflows. Furthermore, RPA that incorporates artificial intelligence and machine learning has the capability of adapting and improving over time.

Simply put, RPA is revolutionizing the way that banks, lending institutions and insurers carry out their business practices. In fact, this technology is ideal for the financial services industry because of the staunch regulations and high volume of transactions being performed on a daily basis. From an accounting perspective, for instance, RPA can be applied to everything from recording journal entries to performing account reconciliation. RPA can even be used to manage invoices, audit expense reports and process payments.

The Case for Robotic Process Automation in Financial ServicesPerhaps the area where robotic process automation is most beneficial to financial institutions is in the way of regulatory compliance and risk management. Employing an intelligent automation platform, a financial firm can utilize advanced technology to automatically evaluate account openings and review disclosures to ensure that employees remain compliant at all times. Robotic software can run continuous reviews and reconciliations to identify anomalies and alert management of potential problems.

In terms of risk management, RPA can help spot and verify even the most subtle of changes in exposure as well as determine the cause for such movement. Automation can also be used to assess credit limits and identify the cause when those limits are breached. Intelligent RPA combined with AI and machine learning can take these things a step further by leveraging data to provide recommendations for which course of action should be taken in order to limit risk and remain compliant.

One of the reasons RPA is such a valuable tool in the financial industry is because it is capable of undertaking tasks at an incredibly high rate of speed while also performing those tasks uniformly and without error. This is why it’s widely accepted, both by financial firms as well as regulatory agencies. It is not, however, meant to replace human workers altogether. To the contrary, RPA is designed to augment the skills of human employees, making their jobs easier and freeing them up to focus on those tasks that cannot be automated.

And lastly, despite being in an industry that is perpetually dealing with change, the one thing that seems to always remain constant is the need to reduce operating costs while maximizing efficiency. Robotic process automation is fundamentally designed to help firms achieve these goals by enabling the standardization and centralization of a broad spectrum of business processes. At the same time, RPA increases controls and facilitates consistency in execution. And because automation eliminates much of the tedious, manual tasks, staff can apply their talent to more high-value and meaningful work, which means higher retention rate. In other words, everyone wins.

Given all of these value-added benefits, it’s no surprise that leading financial institutions are already leveraging the power of RPA to help streamline operations and provide competitive advantage. If you are in the financial industry and would like to see for yourself just how automation can improve your firm’s overall performance, we encourage you to take Ayehu for a test drive today.

eBook: 10 time consuming tasks you should automate

Ayehu Expands into Japan with IWI Partnership

AyehuAyehu Expands into Japan with IWI Partnership today announced that it has entered into an agreement with Intelligent Wave Inc. (IWI) in Tokyo, Japan, to offer its Next Generation IT Automation and Orchestration platform as part of its solutions portfolio.  IWI has begun offering the solution to help customers automatically respond to threats and event management with preprogrammed workflows.

“Enterprises world-wide are facing many of the same technology and staffing challenges that can effectively be addressed with the right automation tools,” says Brian Boeggeman, VP of Partnerships and Alliances, Ayehu. “IWI is our first partnership in Japan, which is a key milestone for our operations, and we anticipate that customers will embrace the opportunity to engage with Ayehu’s automation orchestration and platform for immediate and significant result in solving their most important business challenges.”

In this partnership, Ayehu acts as a force multiplier, driving efficiency through a simple and powerful IT automation and orchestration platform powered by AI. The next generation platform helps enterprises save time on manual and repetitive tasks, accelerate mean time to resolution (MTTR) as it centrally manages event information such as malware, unauthorized access, etc. and can identify threat level and critical details. IT and security operations teams can fully- or semi-automate the manual response of an experienced IT or security operator/analyst, including complex tasks across multiple, disparate systems. With more than 140 pre-configured templates, organizations can easily prepare, customize and execute workflows without any programming required. Ayehu’s response time is instant and automatic, helping to resolve virtually any alert, incident or crisis.

IWI will exhibit at CyberTech Tokyo on November 30th, 2017 (http://tokyo.cybertechconference.com)

About Intelligent Wave Inc. (IWI)

Intelligent Wave Inc. (JASDAQ: 4847), a solution provider of financial information systems, delivers an online network based credit card payment system. With a focus on development, implementation and maintenance, IWI provides system solutions that integrate components and technology. IWI provides advanced security integrated solutions covering a wide range. For more details, please visit http://www.iwi.co.jp/ or http://www.iwi-security.jp/.

Why artificial intelligence will change cybersecurity as we know it

AI and Intelligent Automation Network Guest Post

Guest post originally published in AI & Intelligent Automation Network.

Artificial intelligence (AI) and machine learning are becoming embedded in businesses across the globe, and cybersecurity is quickly emerging as a key area of focus for enterprises striving to enhance the security of sensitive data.

Despite this growing adoption, however, many are still struggling with misconceptions and confusions surrounding the different types of solutions available on the market today.

To set these misconceptions to rest once and for all, one must recognize certain key considerations around AI and understand how it is disrupting the information and network security realm.

It’s equally important to recognize the difference between traditional automation and intelligent automation and its impact on cybersecurity. With this knowledge in hand, business leaders can then begin to capitalize on the opportunities and long-term potential of AI and automation in the intelligent enterprise.

The role of AI in cybersecurity 

Perhaps the ultimate turning point in terms of organizations recognizing the critical importance of adequate network security was the Target breach of 2013. The utter magnitude of that breach opened the eyes of many and placed the topic of cybersecurity front and center on the list of business priorities.

Since that time, there has been a steady influx of attacks that have evolved and increased in both complexity and frequency, subsequently increasing the need for fast, accurate incident response and remediation.

The challenge many organizations face, however, is how? Hiring additional staff isn’t always feasible, whether it’s due to budgetary restraints or simply a lack of qualified personnel.

Additionally, given the sophistication and relentlessness of today’s cyber-attacks, many organizations are finding that human ability is no match. That’s where automation and orchestration technology has become a true game changer.

Combined with artificial intelligence and machine learning capability, automated cybersecurity is meeting attackers head on and essentially fighting fire with fire.

In the context of cybersecurity, AI is able to perceive its own environment well enough that it can independently identify threats and take the appropriate action, all without the need for human intervention. AI is particularly powerful from an incident response perspective because it is adept at recognizing patterns and anomalies far better than any human agent ever could.

Essentially, it’s like having an army of intelligent robots standing at the ready, 24/7/365 to detect and respond to threats. Few, if any, human workforces can accomplish such a feat, especially with such tremendous accuracy.

Machine learning is bringing that power to the next level because it can “learn” and improve on its own, based on factors such as the outcome of previous actions taken. Together with artificial intelligence, machine learning can effectively be used to predict future outcomes based on past events. This can help humans make more data-driven and therefore more accurate business decisions. And when the monumental task of incident management can be shifted from human to machine, businesses are better able to allocate resources toward the most valuable human-led tasks.

Simply put, as the amount of data continues to grow and the global threat landscape continues to advance, both in number and sophistication of attackers, organizations can no longer rely on antiquated tools and manual activities.

Automated cybersecurity incident response powered by AI and machine learning will enable business leaders to stay a step ahead of the threats.

Traditional vs. intelligent automation

IT automation is certainly not a new concept, but the technologies behind it have progressed significantly in recent years. As a result of these advancements, businesses are benefiting in a number of tangible ways, including that of enhanced network security.

But what’s the difference between the traditional automation tools of the past and today’s sophisticated platforms that are powered by intelligent technology?

While both technologies function with similar end-goals in mind—that is, streamlining and automating manual tasks and workflows—intelligent automation is designed to take things a step further by augmenting human intelligence. Not only is this a more cost-effective and scalable approach, but it can be implemented without having to sacrifice process quality and reliability.

Ultimately, the key differentiator between traditional and intelligent automation is the ability to make decisions.

Basic automation tools are capable of gathering and organizing data into reports that human agents can then use to forecast and plan. With machine learning, that data can be analyzed by artificial intelligence at a rate of speed and accuracy far greater than humans are capable of. The result is more valuable information that can facilitate improved business decisions.

The future of AI in cybersecurity

The opportunities that AI-powered automation presents to the enterprise are many, particularly in terms of enhanced network security.

For instance, intelligent automation is capable of quickly detecting and identifying not only known but also entirely new classes of threats. Over time, these agentless systems will continue to learn, adapt and improve on their own, becoming even more effective at managing incidents and analyzing the changing behaviors of attackers.

Additionally, deep learning algorithms will be able to sift through enormous amounts of data in real-time to uncover valuable insights into the growing threat landscape, enabling rapid and effective improvements to existing incident remediation processes.

The long-term goal of automation powered by AI is to achieve an even greater level of flexibility along with enhanced thinking capability that matches the human mind as closely as possible. The result will be a genius-level platform that is faster, more accurate, more consistent and far more effective at achieving maximum cybersecurity than any human team could ever accomplish.

Such a system, just like the human cognition it’s designed to simulate, will be capable of learning new processes, adapting according to its changing environment, arriving at its own conclusions and making its own intelligent decisions.

Perhaps the most interesting fact of all is that this type of system is not some far off distant vision of the future, but a present reality and one that is already driving the intelligent enterprise of today with the promise of keeping it a step ahead of the threat landscape of tomorrow.

To read the guest post in its entirety, please click here.

Two Key Ways Intelligent Automation is Changing the Face of Cybersecurity

Two Key Ways Intelligent Automation is Changing the Face of CybersecurityArtificial intelligence and machine learning technologies are being integrated into many aspects of our everyday lives. If you use Siri or Amazon Echo, you’ve already been touched by AI to some degree. One area where this so-called “smart” technology has become particularly valuable is in the realm of cybersecurity. But despite the buzz, it’s important to understand the real capabilities of intelligent automation in security.

Better Detection

Many are surprised to learn that artificial intelligence in cybersecurity isn’t a new concept. In fact, machine learning has been used to detect unwanted traffic for many years, including in such common tools as spam filters. So why all the hype today? Because that technology has continued to evolve and improve. Where it really shines today, specifically in terms of network security, is in its ability to pinpoint attacks that are outside the norm.

In other words, intelligent automation can detect a pattern or anomaly and recognize that something is suspicious entirely on its own. Not only is this incredibly effective, but it’s something human agents simply cannot do. That’s where an AI powered cybersecurity platform becomes what we like to call a force multiplier.

Volume Control

Another way intelligent automation is revolutionizing the way organizations handle their cybersecurity is in the sheer volume of threats. With the relentless onslaught of increasingly sophisticated attacks operating around the clock, even the most competent and diligent security team cannot keep up. AI technology, on the other hand, can handle an immense amount of data, continuously monitoring, instantly analyzing and immediately reacting to address potential incidents.

Again, like its intuitive ability to read patterns and detect anomalies, machine learning in cybersecurity can also become a force multiplier by augmenting human capability. This is particularly true in instances for which human decision making is still necessary. AI technology can monitor and assess enormous amounts of raw data looking for problems and pass them on to human analysts for closer examination. Furthermore, the interaction with humans allows the intelligent automation platform to continuously refine and improve its search algorithms (hence, the “learning” in machine learning).

When it boils down to it, the hype about AI and machine learning in security is turning out to be all that it’s cracked up to be. With the right platform, intelligent automation can bring your cybersecurity strategy to an entirely new level, providing enhanced protection and keeping your organization a few steps ahead of potential attacks.

To see this innovative technology in action, simply click here and request a free product demo.

How to Get Critical Systems Back Online in Minutes

What is Intelligent Process Automation (and Why Should You Care)?

What is Intelligent Process Automation (and Why Should You Care)?There’s been quite a bit of buzz lately surrounding the topic of intelligent process automation, with viewpoints ranging from ‘farfetched’ and ‘too good to be true’ to excitement that the future is essentially happening right before our eyes. But for many business leaders, the topic is completely off their radar, whether it’s due to lack of technical prowess or simply because they’re too busy to learn more. As such, we thought it might be helpful to summarize exactly what intelligent automation is and, more importantly, why it should be something every busy professional considers.

Intelligent Process Automation Defined

In simplest of terms, IPA is a set of innovative technologies that bring together robotic process automation (RPA) with machine learning. Like conventional automation tools, IPA is designed to assist human workers by taking over repetitive, routine and manual tasks. Where IPA differs from automation tools of the past, however, is in its capability to not only mimic human activities, but actually learn from them and improve over time, without the need for human intervention.

Thanks to cognitive technology and deep learning algorithms, automated rule-based workflows can be further enhanced with decision-making capabilities. As a result, forward-thinking organizations that have already adopted intelligent process automation technology are realizing greater efficiency levels, improved staff performance, less risk, better response times and ultimately more positive customer experiences.

IPA in Action

As an example of intelligent process automation in action, let’s consider a financial services firm in which a customer support agent must pull information from a dozen different systems in order to provide basic level, day to day service. With IPA employed, software robots can interpret text communications, make decisions that don’t require pre-programming, offer suggestions to clients and provide real-time tracking and visibility into the workflow between systems and human agents.

Business Value of Intelligent Process Automation

With IPA a significant portion of the manual work is instantly taken off the plate of customer support agents. This frees them up to focus their efforts and abilities toward more mission-critical business projects. Customers still receive the same high level of support and the organization benefits from an engaged team that is free to be creative and innovative in achieving business goals.

While the greatest benefits of IPA come as a result of complete, enterprise-wide implementation, business leaders can unlock ROI quickly even just by automating just one or two manual tasks that routinely bog down employees.

In addition to intuitive automation, IPA can also bring value in the way of improved decision-making capabilities. Through sophisticated machine learning algorithms, intelligent process automation platforms can deliver data-driven recommendations to key decision makers to help optimize workflows and improve performance. Business leaders can then apply this insight to future planning and forecasting for better results.

Getting Started with IPA

The best news of all is that with the right partner, implementing IPA doesn’t have to be a complex, highly technical project. Ayehu’s Next Generation intelligent process automation and orchestration platform features an easy to use workflow designer, enabling rapid adoption and time-to-value, with an extensive pre-built library of activities and end-to-end workflows. No coding or programming required.

Experience it for yourself. Click here to take Ayehu for a test drive today!

eBook: 10 time consuming tasks you should automate

How AI Can Bring Your Cybersecurity to the Next Level

How AI Can Bring Your Cybersecurity to the Next LevelArtificial intelligence and machine learning are starting become buzzwords in just about every industry. Cybersecurity is no exception. In fact, even governments across the globe are jumping on the bandwagon in an effort to enhance the security of their sensitive data. Yet, despite the growing adoption, many of security agents are struggling with misconceptions and confusions surrounding the different types of solutions available on the market today. If you are among them, here’s what you need to know about how AI is disrupting the information and network security realm.

The first point to consider is the difference between traditional automation and intelligent automation powered by machine learning. While both function toward the same end-goal of streamlining and automating manual cybersecurity tasks, such as incident detection and remediation, intelligent automation takes things a step further by augmenting human intelligence, which is both costly and unscalable. Most importantly, this is done without sacrificing reliability and quality of the processes being automated.

The real difference comes into play in the area of decision making – something all cybersecurity leaders are responsible for. With traditional automation, lots of data is gathered and can be turned into reports which can then be used to help human agents forecast and plan for the future. With machine learning, that data is analyzed by artificial intelligence at a rate far faster than any human could possibly compute. The result is more accurate, precise and valuable information for making better business decisions. When you can leverage data more effectively, you can better protect your organization moving forward.

Expanding on this, automation powered by AI is capable of quickly detecting and identifying entirely new classes of threats. Over time, these agentless systems continuously learn, adapt and improve, becoming even more effective at detecting incidents, analyzing attacker behaviors and even managing more obscure threat events. At the same time, deep learning algorithms sift through mountains of data in real-time to uncover and provide valuable insights into threats and enable rapid, highly effective improvements to cybersecurity remediation processes.

The long-term goal of AI powered automation is to achieve even greater flexibility and enhanced thinking capacity that is as close to the human mind as possible. The result will be a genius system that is faster, more consistent and far more effective at maximizing cybersecurity than human agents ever could be. Such a platform, just like the human cognition its designed to mimic, will be capable of adapting and learning new tasks and processes, arriving at its own conclusions and making its own intelligent decisions.

What could your organization achieve with this level of cybersecurity protection? Believe it or not, this is not a far off goal or figment of the future. Automation powered by machine learning is here now, and you can see it in action today by clicking here.

Bring your company’s protection to the next level with the next generation of IT automation.

eBook: 5 Reasons You Should Automate Cyber Security Incident Response

How Machine Learning is Set to Revolutionize Data Centers

How Machine Learning is Set to Revolutionize Data CentersArtificial intelligence is disrupting and transforming nearly every industry, with simple tasks to complex workflows being shifted from human to machine. The IT realm is no exception, with machine learning algorithms being leveraged to help data centers improve efficiency, productivity and overall performance. Even tech powerhouse Google is using its own DeepMind technology to manage the consumption of power at its server farms, resulting in a 40 percent reduction of electricity usage.

AI and machine learning technology presents a tremendous opportunity for IT operations teams to automate and streamline critical functions, manage infrastructure and react swiftly and effectively to problems without the need for human intervention. Many well-known, global enterprises are now turning to automation to do everything from previewing incidents and working on operations parameters to overseeing the process of pinpointing and addressing root causes. Automation powered by AI is particularly valuable to the data center because it’s scalable and helps to ensure maximum operability.

One problem data centers of all sizes and in all industries face on a daily basis is the increasing number of events that are occurring. Many are experiencing millions upon millions each day. There is simply no human team that can handle that kind of volume. The answer is automation, but it goes beyond that. At this volume, relying on alerts and escalations won’t cut it. Data center leaders need intuitive machines that can make decisions about how events should be addressed.

What’s more, as data centers achieve scales and speeds well beyond what we’re accustomed to currently, it’s going to reach a point where graphs and reports of alerts aren’t going to be useful to humans. They simply won’t be capable of interpreting them with enough speed and efficiency to maintain the 100% availability they’re striving to deliver. IT leaders will need AI-based automation to be able to analyze and take the appropriate action as needed.

Lastly, automation and orchestration tools that are powered by machine learning will enable data center leaders to effectively predict when problems with the infrastructure may potentially arise. By leveraging available data, future issues can be forecast and circumvented proactively, further reducing the risk of downtime and improving service levels across the board. All of this is made possible through the use of intelligent automation.

See it in action with a live demo today and start preparing your data center for a brighter, more profitable future!

5 Ways to level up your service desk using it process automation

3 Biggest Cybersecurity Challenges on the Horizon

3 Biggest Cybersecurity Challenges on the HorizonWhether you’re already knee-deep in the industry or you’re simply kicking around the idea of becoming a cybersecurity professional, staying abreast of the current and future trends is essential. In particular, it’s important to have a good idea of what challenges those in the security realm are facing and expect to face in the near future. Let’s take a look at three specific areas where tomorrow’s security agents will need to focus their efforts.

Complexity

Not only are the threats of tomorrow becoming more and more sophisticated (and therefore difficult to combat), but the IT environment itself is becoming equally complex. Marrying disparate systems to create a more cohesive infrastructure and finding a way to seamlessly link legacy applications with newer ones is a challenge in and of itself. The more complex the network, the more points of entry for attackers and the greater the vulnerability.

Cybersecurity professionals must leverage technology that is capable of keeping up with the evolving threats their organizations face. Incorporating machine learning and artificial intelligence into the mix can help keep IT teams a step ahead in the fight to protect information.

Adversaries

In addition to the external forces that wish to do organizations harm, cybersecurity teams must also account for the insider threats that threaten the sanctity of confidential data. Employees at every level are routinely putting their employers at risk, most often without even realizing what they’re doing. This is why the job of IT must also involve ongoing communication, education and training to ensure that everyone recognizes the importance of cybersecurity and their role in keeping information safe.

Meanwhile, hackers are using technology to increase the frequency of their attacks. They are persistent to the point of relentlessness. To address this, adopting appropriate technological measures that can “fight fire with fire” is key. This ensures constant protection that human workers simply cannot deliver.

Staffing Shortage

It’s hard to believe that this is still a topic of discussion, but it remains a significant concern, especially from a cybersecurity perspective. Some organizations don’t have access to enough qualified IT professionals or struggle to retain them while others simply don’t have the resources to keep an entire team on the payroll.

Once again, technology is there to save the day. Automated incident response can augment human IT teams, plugging the holes left by staffing shortages and serving as a virtual army of protection. What’s more, because automated incident management is available around the clock, the organization remains safe from attacks no matter when they occur.

Is your organization adequately prepared to deal with the three biggest challenges to come? To see how Ayehu’s Next Generation automation and orchestration platform can resolve all of these issues for you, request a product demo.

How to Get Critical Systems Back Online in Minutes

The Data Center Dream Team: Your Staff and Automation

The Data Center Dream Team: Your Staff and Automation

This article was originally published in Data Center Knowledge.

It is coming. We have been fully warned that a massive shortage of qualified technology professionals is going to quickly become our reality. But thanks to the increasing abundance of available data, along with innovative tools for gathering, processing, deciphering and storing that data, machine learning algorithms can now be used to produce fast, affordable results for businesses of every size and industry.

Automation and machine learning have become force multipliers and game changers for many organizations because it means that they are no longer constrained by data center staff or budget limitations. There are some basic yet unavoidable factors are driving the need for these new technologies, but fortunately technology leaders today have options to solve today’s most pressing challenges.

A Glaring Need

Today’s data center professionals are under increasing pressure to accomplish more with fewer and fewer resources. Increasing amounts of available information make manual data management a full-time endeavor. For those operations with limited staff or smaller budgets, finding extra support can be an uphill battle. Furthermore, customer demand and an increasingly competitive landscape have placed significant burdens on IT leaders.

Automation’s Role

IT automation technology facilitates a shift from human (manual) processes to machine, enabling the agentless execution of critical data center tasks and workflows, including but not limited to:

  • Monitoring – Continuously scan and track the status of data center components with automated notification and escalation in the event of a problem
  • Maintenance – Automatic performance of ongoing functions, such as updates and patches
  • Scheduling – Organize the automatic execution of routine data center processes, including backups, downloads/uploads, replication, application events and more without the need for human effort
  • Provisioning and Configuration – Development, testing and deployment of new applications, including physical, virtual and cloud servers
  • Application Service Delivery – Automatic fulfillment of user requests within just minutes
  • Optimized Workload Delivery – Automatic movement of network traffic for better load balancing and/or on-demand delivery of additional applications
  • Security – Automate the incident response process from start to finish, creating a closed loop to quickly detect and address threats, mitigating damages
  • Compliance – Audit and report on live configurations, compare current and past configurations to identify discrepancies and implement rules-based policies to adhere to regulatory standards – all without the need for human intervention

By adopting automation technology, data center professionals are no longer burdened with the challenge of performing many of their duties without disrupting end-users. Previously, things like system refreshes and updates had to be carried out after hours to avoid a potential service interruption. Now, these workflows can be scheduled and executed automatically, alleviating the need for IT staff members to work odd hours.

Automation + Intelligence

Beyond the basics of data center automation, some of today’s platforms are now incorporating intelligent technologies, like machine learning, into the mix. So, not only can IT teams streamline operations by automating manual processes, but they can now rely on the power of artificial intelligence to achieve continuous process improvement.

Automated platforms powered by sophisticated machine learning algorithms, use available data to dynamically create rule-based recommendations, insights and correlations. This enables better data-driven decision making and facilitates more optimized workflows and processes. As a result, not only does the data center itself run more efficiently, but the enhanced service that occurs as a result drives greater customer and employee satisfaction rates. In other words, everyone benefits.

Considerations for IT Leaders

Given the advantages automation can have for the data center, it can be tempting to automate everything. However, IT leaders are better served to take a more comprehensive approach to data center automation. When planning for automation, be sure to consider the following:

Automate intelligently. That is, don’t just automate processes for the sake of it. Instead, processes and workflows should be evaluated and weighed based on each one’s business value as well as the quantifiable outcomes that could be realized as a result of automation.

Practice in with the new and out with the old. Whenever possible, focus should be placed on automating newer processes and workflows first rather than trying to adapt old processes to automation – unless, of course, significant ROI could be realized by changing the existing workflows.

Start small and work from there. An incremental approach to automation is recommended, as it’s always easier to automate basic functions than it is to tackle large scale projects right off the bat. Start with smaller initiatives that can be built upon.

Test first, then deploy. It’s always advisable to experiment with automation changes in a test or QA environment before going live with them. In the absence of a test environment, look for ways to deploy automation incrementally rather than exposing the entire data center to a complete automation change.

There are many cases for which automation can and should be considered thanks to the rapidly evolving technology landscape. For example, IoT deployments are steadily on the rise and adding to the complexity of the data center, making the role of data management in business even more crucial. And increasingly IT teams need the ability to leverage the power of data to meet enterprise-wide objectives, but may lack the qualified staff and resources needed to produce what is needed.

When applied appropriately and strategically, automation technology has the potential to empower data centers – even those with limited resources – to perform at the highest level and yield greater outcomes than were ever thought possible.

5 Ways to level up your service desk using it process automation