The future of AIOps

AIOps or Artificial Intelligence based IT operations is the buzzword that’s capturing the CXO’s interest in organizations worldwide. Why? Because data explosion is here, and the traditional tools and processes are unable to completely handle its creation, storage, analysis and management. Likewise, humans are unable to thoroughly analyze this data to obtain any meaningful insights. IT teams also face the challenging task of providing speed, security and reliability in an increasingly mobile and connected world.

Add to this the complex, manual and siloed processes that the legacy IT solutions offer to the organizations. As a result, the productivity for IT remains low due to their inability to find the exact root cause of incidents. Plus, the business leaders don’t have a 360-degree view of all their IT and business services across the organization.

AIOps is the Future for IT Operations

AIOps platforms are the foundation on which the organizations will project their future endeavors. Advanced machine learning and analytics are the building blocks to enhance their IT operations through a proactive approach towards service desk, monitoring and automation. Using effective data collection methods that utilize real time analytic technologies, AIOps provide insights to impact business decisions.

Successful AIOps implementations depend on key parameters Index (KPIs) whose impact can be seen on performance variation, service degradation, revenue, customer satisfaction and brand image.

All these impacts the organization’s services including but not limited to supply chain, online or digital. One way in which AIOps can deliver a predictive and proactive IT is by decreasing the MTBF (Mean time between failure), MTTD (Mean time to detection), MTTR (Mean time to resolution) and MTTI (Mean time to investigate) factors.

The future of AIOps is already on the way in the below mentioned use cases. There is just the surface with scope for many more use cases to be added in the future.

  1. Capacity planning

Enterprise workloads are moving to the cloud with providers such as AWS, Google and Azure setting up various configurations for running them. The complexity involved increases as new configurations are added by the architects involving parameters like disk types, memory, network and storage resources.

AIOps can reduce the guesswork in aligning the correct usage of the network, storage and memory resources with the right configurations of servers and VMs through recommendations.

  1. Optimal resource utilization

Enterprises are leveraging cloud elasticity to improve their application scaling in or scaling out automatically. With AIOps, IT administrators can rely on predictive scaling to take the auto scale cloud to the next level. Based on historical data, the workload will automatically determine the resources required by monitoring itself.

  1. Data store management

AIOps can also be utilized to monitor the network and the storage resources that will impact the applications in the operations. When performance degradation issues are seen, the admin will get notified. By using AI for both network and storage management, mundane tasks such as reconfiguring and recalibration can be automated. Through predictive analytics, storage capacity is automatically adjusted by adding new volumes proactively.

  1. Anomaly detection

Anomaly detection is the most important application of AIOps. This can prevent potential outages and disruptions that can be faced by organizations. As anomalies can occur in any part of the technology stack, pinpointing them in real-time, using advanced analytics and machine learning is crucial. AIOps can accurately detect the actual source which can help IT teams in performing efficient root cause analysis almost in real-time.

  1. Threat detection & analysis

Along with anomaly detection, AIOps will play a critical role in enhancing the security of IT infrastructure. Security systems can use ML algorithms and AI’s self-learning capabilities to help the IT teams detect data breached and violations. By correlating various internal sources like log files, network and event logs, with the external information on malicious IPs and domains, AI can be used to detect anomalies and risk events through analysis. Advanced machine learning algorithms can be used to identify unexpected and potentially unauthorized and malicious activity within the infrastructure.

Although still early in deployment, companies are taking advantage of AI and machine learning to improve tech support and manage infrastructure.  AIOps, the convergence of AI and IT ops, will change the face of infrastructure management.

Advanced Persistent Infrastructure (API) Threats

Infrastructure attacks might rank low in the list of security staff who are more worried about data theft, hacking, cybercrimes, DDoS and many more. While they are focused on them, there is another different type of attack vector that slips under the radar: Advanced Persistent Infrastructure (API).

Advanced Persistent Infrastructure (API) is not to be confused with the other popular word: Application Programming Interface that is a set of protocols, routines, functions and/or commands that programmers use to develop software or facilitate interaction between distinct systems.

Threats cannot be viewed in silos. There is always correlating information that act as precursor for the attacks. Only difference is that we have limited our security perspectives, ignoring patterns that the intruders have used in the past. Intruders usually have limited bandwidth with respect to time, resources and money unless they are part of a large crime organization. They aren’t looking to attack using new servers every time.

This is quite similar to the recycling threats scenario, where hackers exploited the vulnerabilities of an already discovered or publicised threat and manipulated the code to introduce a new variant of the threat. The difference is that here they will reuse existing IPs and domain names across multiple attacks.

The evolution of the Apache Struts vulnerability is a good example of how threat actors use advanced persistent infrastructure as an attack vector. In 2014, there were initial reports of exploits against the Struts vulnerability. In early 2017, new exploits were discovered in a Struts 2 vulnerability. Security analysts noticed the two exploits followed a very distinct pattern.

A couple of interesting observations were made:

Tactics May Change but IPs Don’t. Unless they are a member of a big crime organization, most hackers don’t have the resource to buy new IP addresses and domains every time. Hence, when an IP address comes online we should know exactly what it is tied to and its history.

Hackers act on the slow response. The reality is that when a new zero-day exploit is reported, organizations are slow to move on patching these things. Capitalizing on the slow response, the hackers act quickly to make use of the exploit. What they do is simply retool their favorite form of malware, and then use the infrastructure access they have in place, like IPs and domains, to launch the new attacks.

How to recognize infrastructure breach?

  • Organizations must recognize how these IP addresses and domains are reused that allow them to predict what threat may be coming.
  • Look at the activity history. That will give an idea about what to look out for.
  • Whenever a new version or variant of a known malware is identified, monitor old IPs and domains that directly correlate for new activity.

According to data submitted by companies to research analysts, looking back at historical report data in their vulnerabilities, they found that the IP addresses used with the original attacks can still be used with the new threats.

Perimeter security is not just enough to prevent the infrastructure breach. By understanding how hackers reuse infrastructure, companies have a better idea of the areas of the network to target when investigating a new threat, especially when it is a reiteration of an old malware.

GAVS’ Managed Security Services gives your IT enterprise the ability to simplify security management, thereby minimizing risks, protecting critical information, and effectively reducing the cost and complexity of your security infrastructure. With an end-to-end suite of fully managed services, the security services give a consolidated view of your security environment. Effective management, cost-effectiveness and seamless monitoring are the major drivers fueling the demand for these services.

Contact GAVS’ security experts at https://www.gavstech.com/reaching-us/ to better understand the Advanced Persistent Infrastructure threats and steps to mitigate them.

5G Technology and Network Security

5G is the next generation telecommunication standard that is expected to be officially deployed in 2020, but South Korea has already demonstrated it in the 2018 Winter Olympics. It is the fifth generation wireless broadband technology based on the IEEE 802.11ac standard. The premise of 5G is to blur the differences between wireless and wired networking to facilitate the growing mobility of network users.

5G will provide broadband access everywhere, entertain higher user mobility and enable connectivity of massive number of devices such as Internet of Things (IoT) devices in a reliable and affordable way. Technology enablers such as cloud computing, Network Function Virtualization (NFV) and Software Defined Networking (SDN) are maturing in their use of 5G.

But in a 5G business environment, the rise of new business, new architecture, and innovative technologies will present new challenges to security and privacy protection where security is a necessary enabler for continuity of the business.

Security challenge ahead of 5G

  • New business models – Compared to traditional communication network which is limited to improving individual communication, 5G network is about serving vertical industries from which a diverse set of services will emerge.

The security demands are also going to vary among the services. Consider the mobile IoT devices that need lightweight security while high speed mobile services demand efficient mobile security. Therefore, there is a need for more stringent authentication methods to prevent unauthorized access to IoT devices. For example, biometric identification could be part of the authentication in smart homes.

  • IT driven Network Architecture – New IT technologies like virtualization, Software Defined Network (SDN) and Network Functions Virtualization (NFV) are projected as a way to make 5G networks agile and efficient but less costly.

Implementing 5G network and infrastructure security will be different as isolation of the virtual network elements (NEs) in the cloud-based infrastructure should also be considered. Based on the network virtualization technology, a network could be built on different virtual network slices, with each slice handling a particular service requirement. 5G security design may need to consider issues like how to isolate, deploy, and manage virtual network slices securely.

  • Heterogenous access – Given the various technologies by which networks can be accessed (directly, Wi-Fi, LTE, via a gateway ) security designers need to build security architecture that’s suitable for different access technologies.
  • Privacy Protection – With the advances of mobile Internet, more and more vertical industries, including health care, smart home, and smart transport, will resort to 5G networks. The data that is being sent over the network include personal information that can be obtained to hack into the personal lives of the users. As a differentiator, networks may need to sense what type of service a user is using. The service type sensing may involve user privacy. Add all this together and privacy protection in 5G is more challenging.

Are you geared up for 5G technology and security?

Most probably not yet. However, major network organizations are already on their way for deploying 5G by 2020. In principle, 5G technology is secure, but the main issue in terms of privacy and security is at the application level where the apps are dealing with data collection and transferring your data.

The arrival of 5G will enable many sectors, including automotive and healthcare, to leverage the Internet of Things to deliver product and service innovations. As 5G systems are going to be service-oriented, it is not sufficient for the legacy systems to be upgraded to accommodate the 5G security constraints. This requires a complete overhaul of the security architecture with emphasis on privacy, data/network security from the angle of services. It has to be implemented at the design level of the security architecture.

GAVS Technologies offer advisory services with respect to network security and infrastructure changes needed to be future ready for 5G technologies as part of your business strategies. The inclusion of multiple cloud based IT environments and edge computing makes for a decentralized network that allow operators to deliver services closer to the customers, thus reducing network congestion and improving the performance of applications.

GAVS will help businesses to answer questions like

  • Whether 5G security and privacy solutions will cover the service layer in addition to the access layer
  • Whether to extend the role of end-to-end protection mechanisms from those of earlier generations
  • Whether to aim for extended protection of identity and location privacy against active attackers

There will be a fast growing need for secure infrastructure, including stringent identity management and data protection as well as a vast array of system level protections in place to defend against distributed denial of service (DDoS) and other network or cyberattacks.

GAVS’ is positioned to address the security requirements of its clients with a wide range of solutions to protect every aspect of their businesses as 5G technology becomes available. Know the feasibility of 5G adoption for your organization with a chat with our security experts here: https://www.gavstech.com/reaching-us/

Digital Transformation Trends in Healthcare

The first phase of Digital transformation (DX 1.0) involved identifying new technologies, trends, drivers and processes that pushed organizations out of their status quo and helped grow their business.

Digital transformation (DX2.0) involved in organizations addressing the new challenges and opportunities that the 2.0 version presented. The trends, drivers and technologies that drove the first iteration evolved, forcing organizations to adapt to these new tools and upgrade themselves to stay in the race.

The premise of this 2nd wave in healthcare industry is to move towards a patient-centric approach rather than just treating the condition. Providing more value in terms of patient care over volume. The best example is the CES that happened in January 2019, that provided a platform for healthcare companies, experts to project the future of digital transformation in healthcare.

CES 2019 – A Showcase for Digital Transformation

The annual CES (Consumer Electronics Show) 2019 January edition was an eclectic mix of technologies, innovations and interactive sessions that showcased the capabilities and futuristic innovations in the Healthcare, ICT, Sports and of course Electronics domain. It was all about digital transformation using Smart IT, AI, IoT and 5G technologies that connects everything.

As part of the knowledge sharing initiative, the Healthcare summit spanning 6 days from Jan 6 to Jan 11 was an opener for all the health tech companies to arm patients and consumers with information. It was a platform for medical personnel to take healthcare to the next level.

Of interest is the healthcare revolution happening in the wearable tech and IoT, Health apps, patient engagement through technology and AI in healthcare. Broadly driving this transformation is the relatively stable economic growth, increased transparency, affordable medical plans, and government policies cutting the red tape.

DX2.0 is an opportunity for retail in the healthcare sector to leverage technologies like AI, machine learning, IoT, Blockchain, advanced performance and analytics for wearables, and healthcare apps. Digital health is allowing more evidence-based discoveries and providing new treatment options.

Healthcare Trends dominating Digital Transformation

As digital health grows at an increasing pace, the legacy network and IT architecture need to keep pace with it. The innovative solutions for making healthcare affordable, diagnosing, treatment, and its advancements need a supportive environment from CXOs, governments and revolutionary leaders.

Here are the top areas where healthcare digital transformation is occurring:

Artificial Intelligence

It’s changing the modern healthcare outlook. A combination of varied technologies like machine learning and natural language processing helps unlock relevant patient medical data to improve patient decision making process.

Some practical applications of AI include:

  • Voice assistants: HIPAA-compliant voice and chatbot applications will allow clinicians and care givers to focus on more healthcare related tasks instead of non-core routine activities like scheduling etc. Leading companies like Amazon, Apple, Microsoft are focusing on developing VAs for healthcare use cases like elderly care, pain management etc.
  • AI driven research: Through its fast data processing capability, it can help in identifying patterns and paths in the vast amount generated by both individuals and institutions thus aid in research. AI can help in identifying clinical trial subjects and studies that help in advancing medical research in a precise manner.

Internet of Medical Things (IoMT)

The number of medical devices that control/monitor the health status of the individuals daily is increasing to help detect any abnormalities the moment they occur. The data compiled by these devices will help the mHealth technologies to provide actionable insights, promote preventive care, value-based and patient centric care leading to an enhanced patient satisfaction.

IoMT is not limited to wearables. The future of medical supply chain management using RFIDs for tagging and packaging of medicines to ensure quality by the manufacturers and making the system more transparent and efficient.

Telemedicine

Patients can’t afford delays in scheduling doctor’s appointments for treatment. Telemedicine offers a viable solution to this problem by offering them remote consultations through the effective use of video conferencing, wearable devices and easy availability of smartphones. This not only saves time and resources but makes healthcare delivery more effective and productive.

Big Data & Predictive Analytics

Medical data produced at both individual and organizational level have valuable insights regarding the patient healthcare. The convergence of big data, cloud computing, IoT and analytics tools can process this huge volume of data within a short duration, which is impossible for humans.

These can be effectively used to predict potential spread of diseases in real time, lower the risk estimates in treatment plans, better precision medicine and research through improved patient profiling.

Artificial and Virtual Reality (AR/VR)

Medical education and surgical training are the immediate applications of AR/VR. Improved body imaging, visualization and mapping using sensors allows patients have precise diagnosis and helps in minimal invasive medical procedures and surgeries. This results in better doctor patient relationship, less stress and an enhanced patient experience. Pain management and physical therapy are other areas where research is being focused on.

Bio-printing

Using AI, 3D printing technologies, VR technologies, bio printing of various body parts like legs, arms, ears help the physically challenged patients lead a normal life style.

All these need a complete overhaul in the business models of healthcare industry with the focus on identifying gaps in the digital transformation process and propose a plan of action for all the stakeholders involved. This allows them to set realistic expectations from the professionals.

To get business leaders to be proactive about digital transformation in healthcare, they need a big push with tangible examples from other companies that experimented with DX2.0. Only then will they come aboard with this concept and support this change wholeheartedly. Having a clear-cut vision of the digital transformation in the healthcare domain by the leaders will make this endeavor be a success.

GAVS congratulates CustomersFirst Now – Leader – Journey Mapping Software – Aragon Research

Congrats CustomersFirst Now | CX Consulting | Customer Journey Mapping, for winning the 2018 Innovation Award for Customer Journey Mapping by Aragon Research. We are proud to be part of the journey in creating this best in class journey mapping software CFNInsight | Enabling customers’ success through cutting-edge technology innovation. 

 

What chatbots will do for your enterprise?

Gen X, Y or any other fancy term describing the current demographics is tuned to using voice, text and natural language to complete their work. That’s why a new generation of enterprise chatbots is needed at work.

Read over the textbook definition of a chatbot and you’ll understand it’s a computer program designed to hold conversations with humans over the internet. They can understand written and spoken text and interpret its meaning as well. The bot can then look up relevant information and deliver it to the user.

While chatbots reduces time and efforts, it’s not easy to create a chatbot that customers will trust. Businesses will have to consider the overall

  • Security
  • Team complexity
  • Brand image
  • Scalability/availability
  • Identity and access management
  • Other parameters to fully integrate chatbots in their organizational structure

If correctly implemented enterprise chatbots can perform pre-defined roles and tasks to improve the business processes and activities.

Shortlisting the right chatbot

Automating repetitive and mundane work will increase the productivity, creativity, and efficiency of the organization. Evolution of chatbots will create more business opportunities for enterprises and new companies. Both SMBs and enterprises can improve their customer satisfaction with customized chatbots that help in offloading employee workload or support the various teams in the organization.

Enterprises first need to identify the type of chatbots needed for their organization to kick start their digital transformation. Depending on their requirements, there are two types of chatbots.

  • Standalone applications
  • Built within the messengers

Usually chatbots associated with messengers have an edge over standalone apps. They can be downloaded and used instantly. They are even easy to build and upgrade, faster compared to apps and websites and also cost effective. You also don’t have to worry about memory space.

AI based or machine learning chatbots learn over time from past questions and answers, and evolve their response accordingly.

What’s in it for enterprises?

 There are some universal benefits that businesses in any industry or vertical can benefit from.

Streamlining your IT processes

A variety of business processes across your departments can be streamlined using chatbots. Your employees’ mundane, repetitive but essential tasks can be taken up by the chatbots, giving more time for revenue generating activities. For instance, they can be tasked with follow ups with clients or answering the FAQs by customers.

Act as personal assistants

Chatbots are a great help for the time constrained employees to manage, schedule, or cancel their meetings, setting alarms and other tasks. Context sensitive digital assistants help in organizing their daily routine by understanding the context, behaviors and patterns and suggesting recommendations.

24/7 customer support

Customer expectation is high with them demanding instant and quick resolution for their concerns and problems. Enterprise chatbot solutions offer a cost effective 24/7 customer services for you. Advancements in AI, machine learning and natural language processing (NLP) can allow them to understand the context, usage of slangs, and human conversation to a large extent. On a cautionary note, chatbots should easily handover the conversation to humans to avoid any unnecessary customer conflicts.

Generate business insights

The data deluge faced by the enterprises is costing them through lost insights and business opportunities. Vast data generated across the organization by employees, customers and business processes cannot be completely analyzed, and it leaves data gaps. Leveraging chatbots for processing and analyzing the stored data can result in identifying potential problem areas and take preemptive actions to mitigate the risks.

Reduce Opex & Capex costs

Enterprise chatbots are one-time investments, where you pay only for the chatbot, train it and its forever yours. No monthly payrolls, or sick leaves. You have a 24/7 virtual employee managing your routine and repetitive tasks.

Increase efficiency and productivity

The end result of all the above points is increased productivity. By training your employees about the services and products, a chatbot solution helps your employees to tackle the generic queries from customers. Thus, ending the time-consuming customer facing tasks and helping in the sales funnel.

In conclusion, chatbots are changing the working dynamics of enterprises. The best way to ensure a satisfied customer experience is to build bots that act without being supervised and offer the best solutions to their problems. With new advancements like AI, NLP and Machine Learning, it’s safe to say that chatbots are the future of enterprises.

 

 

 

 

 

 

 

 

AIOps – IT Infrastructure Services for the Digital Age

AIOps – IT Infrastructure Services for the Digital Age

Authors:

Ashwin Venkatesan, Practice Director, Information Technology Services, Everest Group & Bharath ReddySenior Analyst, Information Technology Services, Everest Group

The IT infrastructure services landscape is undergoing a significant shift, driven by digitalization. As focus shifts from cost efficiency to digital enablement, organizations need to re-imagine the IT infrastructure services model to deliver the necessary back-end agility, flexibility, and fluidity. Automation, analytics, and Artificial Intelligence (AI) – comprising the “codifying elements” for driving AIOps – help drive this desired level of adaptability within IT infrastructure services. Automation, analytics, and AI – which together comprise the “codifying elements” for driving AIOps– help drive the desired level of adaptiveness within IT infrastructure services. Intelligent automation, leveraging analytics and ML, embeds powerful, real-time business and user context and autonomy into IT infrastructure services. Intelligent automation has made inroads in enterprises in the last two to three years, backed by a rapid proliferation and maturation of solutions in the market.

Benefits of codification of IT infrastructure services

Progressive leverage of analytics and AI, to drive an AIOps strategy, enables the introduction of a broader and more complex set of operational use cases into IT infrastructure services automation. As adoption levels scale and processes become orchestrated, the benefits potentially expand beyond cost savings to offer exponential value around user experience enrichment, services agility and availability, and operations resilience. Intelligent automation helps maximize value from IT infrastructure services by:

  1. Improving the end-user experience through contextual and personalized support
  2. Driving faster resolution of known/identified incidents leveraging existing knowledge, intelligent diagnosis, and reusable, automated workflows
  3. Avoiding potential incidents and improving business systems performance through contextual learning (i.e., based on relationships among systems), proactive health monitoring and anomaly detection, and preemptive healing

Although the benefits of intelligent automation are manifold, enterprises are yet to realize commensurate advantage from investments in infrastructure services codification. Siloed adoption, lack of well-defined change management processes, and poor governance are some of the key barriers to achieving the expected value.  The design should involve an optimal level of human effort/intervention targeted primarily at training, governing, and enhancing the system, rather than executing routine, voluminous tasks.  A phased adoption of automation, analytics, and AI within IT infrastructure services has the potential to offer exponential business value. However, to realize the full potential of codification, enterprises need to embrace a lean operating model, underpinned by a technology-agnostic platform. The platform should embed the codifying elements within a tightly integrated infrastructure services ecosystem with end-to-end workflow orchestration and resolution.

The market today has a wide choice of AIOps solutions, but the onus is on enterprises to select the right set of tools / technologies that align with their overall codification strategy.

Click here to read  the complete whitepaper by Everest Group