Artificial Intelligence to Make DevOps More Effective

Artificial Intelligence to Make DevOps More Effective
Artificial Intelligence (AI) has found its way into numerous industrial processes. Companies implement AI not just to accelerate production, but also to increase precision and efficiency. Nevertheless, AI used to be a buzzword only a few decades ago, when the developments were not as far reaching as they have become now; it needed particular minds to both develop and operate it. However, now, our modern IT infrastructure has become endowed with talented thinkers that can turn impossibility into reality.

With an increasing emphasis on DevOps, organizations are focusing on efficiency and better reliability. The multi-leveled and interwoven IT strategies require equally sharp eyes and a keen mind to notice and trace critical events that trigger a specific function – this is where real-time and centralized log analytics plays a vital role. AI helps to troubleshoot the main issues quickly and efficiently, while also predicting future problems.

AI has gone from being a buzzing luxury to becoming a necessity of industries today; AI is redefining the entire system of proceedings itself. It is being combined with human knowledge to create breakthroughs and opportunities that would have been impossible without its intervention. Even in IT, where the environment has increasingly become agile and dynamic due to DevOps, the complex methodologies are being simplified through AI implementation. Apart from procedural ease, AI enables IT professionals in gaining insights into the problems that are otherwise so hard to trace.

The immensely complicated DevOps process often falls outside the reach of the human mind. The operations involved need precision, pace and, big data streaming, which are possible only with AI intervention. Thus, AI has become a powerful and essential tool for efficiently analyzing and taking over decision-making processes for better results. AI fills the gaps between human capability and big data through applications of operational intelligence. Additionally, AI speeds up troubleshooting and real-time decision-making.

AI’s Cognitive Insights
One of the most groundbreaking pieces of AI technology is applied in IT operations, namely Cognitive Insights (CI), which utilizes machine-learning algorithms to match human domain knowledge with log data, open source repositories, discussion forums, and social threads. Through this informational repertoire, CI forms relevant insights that contain solutions to a wide range of critical issues faced by DevOps teams on a daily basis. DevOps engineers face numerous challenges, which can be effectively attenuated by integrating AI into log analysis and other concerning operations. There are several applications of Cognitive Insights, which include:

Frequent attacks such as Distributed Denial of Service (DDoS) have become all the more prevalent. Threats which used to be limited to high-profile public websites and multinational organizations are now targeting small-scale servers, SMBs, and mid-sized enterprises. Having a centralized logging architecture to identify and pinpoint potential threats from numerous entries is essential for warding off such attacks. For this purpose, the application of anti-DDoS mitigation through Cognitive Insights has been highly effective. Leading organizations such as Dyn and British Airways had sustained potential damage from DDoS attacks in the past and subsequently installed a full-fledged ELK-based anti-DDoS mitigation strategy to restrict hackers and secure their operations against future attacks.

IT operations
Cognitive Insight can compile logs at a centralized point, with each entry carefully monitored and registered. It also provides the luxury of viewing the process flow clearly and executing queries of records from various applications; this thereby increases overall efficiency. With AI Cognitive Insight it is becoming straightforward to pinpoint the small, yet potentially harmful, issues in vast streams of log data. The core of this program is based on ELK stack and makes it easier to have a clear view of DevOps processes through the help of data simplification and assortment.

Besides these cases, AI integration in DevOps can yield several other useful outcomes including:

• AI-driven log analytics systems efficiently solve issues of identifying and resolving critical issues, which subsequently amplifies management and overall operational pace
• Improved customer success due to better results
• Monitoring and customer support becomes even easier
• Risk reduction and resource optimization
• Maximize efficiency by making logging data easily accessible

In other words, Cognitive Insights and other such Artificial Intelligent integrations can be of great help in data log management and troubleshooting. They can quickly pinpoint the issues from thousands of log entries which are often time consuming and erroneous when a human mind handles them.

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How Big Data Is Changing the Financial Industry

How Big Data is changing the Financial Industry
Big Data is the talk of the town these days; not only has it ushered in the next generation of technology, but it has also modified the way businesses and financial institutions are performing their day to day activities.

Financial institutions are always on the lookout to enhance their day to day operations while keeping their competitiveness intact. Let’s have a quick look at analyzing the top 5 financial trends which are quickly taking over the financial industry and paving the path for modernizations.

Strengthening Financial Models: Data is prevalent in every industry. Financial institutions such as banks, lending institutions, trading firms, etc., produce tons of data on a regular basis. To manage such voluminous data, there is an imminent need to bring into operation a data handling language which is equipped to handle, manipulate and analyze massive volumes of information – this is where the role of Big Data comes into the picture. Financial institutions often work on different business and financial models, especially with respect to approving loans, trading stocks, etc. To make efficient working models past data trends need to be taken into consideration. The better the data relativity, the stronger the model and lesser would the risks involved. All such strategies can be derived from the use of Big Data, which in turn becomes an effective method to drive data-driven models through different financial services.

Enhanced Data Processing and Storage: Technology will never stop growing. Since the aforementioned has become an inseparable part of every organization’s life cycle, the data generated by daily operations gives way to the need of the hour storage and data processing. If one talks about the use of Big Data, the name is a clear giveaway in itself; it encompasses the use of the language, which means storing data in the Cloud or on other shared servers becomes a cinch. Thus distribution and processing come as a byproduct of storage capabilities. Cloud management, data storage, and data processing have become the words to reckon with, as more and more organizations are considering opportunities within the technical world.

Machine Learning Generates Better Returns: Financial Institutions deal with customer data on a day to day basis. Not only is such information critical, but very valuable, since it gives insights into the daily functioning of the bank. Considering the sensitivity of the data, there is a pressing need to evaluate the stored data, and protect it from fraudulent activities, while ensuring the risk is reduced drastically. Machine Learning has become an integral part of modern fraud prevention systems, which help to enhance risk management and prevent fraudsters from entering into protected domains.

Blockchain Technology: When customer data is at the fore, and financial transactions are at risk, Anti-Money Laundering (AML) practices become a topic of deliberation. Many people are beginning to give considerable importance to Blockchain technology within the financial industry forum. Blockchain possesses the ability to decentralize databases, and further link separate transaction information through code. This way, it can secure the transactions and offer an extra layer of security to the organizations dealing with sensitive data.

Customer Segmentation: Banks are always under pressure to convert their business models from business-centric to customer-centric models; this means that there is a lot of pressure to understand customer needs and place them before business needs to maximize the efficacy of banking. To facilitate the shift banks need to perform customer segmentation to be able to provide better financial solutions to their customers. Big Data helps perform such tasks with simplicity, thereby enhancing groups and data analysis.

There is no denying the fact that Big Data has increasingly taken over various industries in a short matter of time. The higher the opportunities being exploited, the better the results being displayed by banks and other financial institutions. The idea is to expand efficiency, provide better solutions, and become more customers centric. All the while decreasing the tangent of fraud and risks within the financial domain.

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How Cloud Migration will help Boost Security and Compliance

How Cloud Migration will help Boost Security and Compliance
Although the adoption of cloud services is becoming increasingly popular in the past few years, many organizations are still skeptical of migrating to the cloud due to security concerns. This outlook tends to emerge from a lack of exposure to the emerging potentialities of the modern cloud. However, the case has become precisely opposite—firms, no matter how small or large, can benefit immensely from cloud migration when regarding stronger security and compliances.

Cloud providers reassure organizations of seamless and hassle-free cloud migration and ongoing maintenance; they make the security and protection of third party data their priority because their reputation highly depends on the kinds of services they provide. Once this goodwill suffers a blow, their company sustains a considerable loss, which is certainly not favored.

The cloud providers render security with the help of following measures:

Safekeeping the Data
Cloud providers are not just any organizations; they have grown considerably and have become among the wealthiest companies in the world. Security concerns come to them not as a challenge, but rather as an opportunity. These companies have a highly skilled team of professional IT engineers that are capable of tackling any security danger that may occur. Take for instance the most prominent cloud provider—Amazon. Amazon’s security parameters are well above the average reach of hackers. Amazon and other cloud providers take protecting infrastructure and customer data as their top priority. They apply a significant portion of their budget to meet and often go beyond security expectations. Companies such as Amazon go through a series of exercises that ensure the protection of physical infrastructure and systems.

Shared Responsibility Model
A model that is implemented at the organizational level is the Shared Responsibility Model in which a cloud infrastructure provider is responsible for maintaining the physical security of its data center, including building access, network and server hardware, as well as monitoring the hypervisor in charge of the virtual machines. On the other hand, the customer is responsible for securing operating systems, applications, and data running on cloud accounts. This co-operation is established when both sides are happy and comply willingly. The benefit is mutual, thus, this model is generally upheld. With its implementation, the cloud providers render best practices for controlling access and limiting network exposures which result in a secured infrastructure.

Supply of Personalized Tools
Typically, cloud providers supply tools that complement cloud-based security management tools to help the organization defend their virtual environments. Take, for instance, Amazon Web Services (AWS) CloudTrail; it provides visibility into the actions being taken by both legitimate users and bad actors operating in the cloud environment and acts as an active vigilante for the entire operation. Other security tools such as firewalls, file integrity monitoring solutions, and centralized logging also remain functional and works together in conjuncture with cloud tools. Thus, it all adds further layers of security that are purposefully built for strengthening and monitoring the environment.

Besides security measures, cloud computing is also highly compliant with the modern day needs of an organization. They focus on cost-effectiveness and the ease of use while keeping in mind the procurement of untainted security measures.

Reduced Business Expenditure
From its advent, cloud computing engineers have strived to seek the betterment of the existing platform services. The financial aspect in organizations is of great importance to the engineers too. Therefore, a traceable shift can be seen in cloud computing as far as reducing cost is concerned. Cloud computing is much more affordable than a traditional data center as it works on a pay-as-you-go model. The building, maintenance and retrieval of data in conventional terms is costly and messy as opposed to cloud computing. Cloud computing uses real-time extraction that takes seconds to locate the data, while any modifications can be done without any harm to the existing data. The labor-force employed and time consumed in cloud computing is a lot less than traditional data centers which result in a more cost-efficient solution for the business.

Greater flexibility
Cloud computing enables organizations to become more agile and flexible through a variety of benefits. The cloud allows businesses to expand their infrastructure without any evident disturbance elastically. Organizations can instantaneously start using systems and applications on newly acquired cloud space without having to worry about the organizational insecurity. Instead, the human resource can work on their business strategies. Even for the IT professionals, who manage these clouds, their efforts can be oriented to other more strategic initiatives instead of a web of data complexity.

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Understand How Artificial Intelligence and Machine Learning Can Enhance Your Business

Understand How Artificial Intelligence and Machine Learning Can Enhance Your Business

Automation is the key to success; every company is expanding on this domain’s expertise, as organizations take on a more global approach. Given the problems of decision making, learning, and the need for adaptability when understanding data, data scientists introduced the concept of Machine Learning within the realm of Artificial Intelligence. These practices have been able to bring about a radical change in modern business efficiency.

Artificial Intelligence is commonly a platform which performs tasks intelligently, without incurring the need for human intervention. On the other hand, Machine Learning is an exclusive part of the Artificial Intelligence world, which encapsulates the know-how and the logic behind making the concept of Artificial Intelligence a real success story. Through the use of Machine Learning, machines can be taught to work more sensibly, thereby allowing them to recognize different patterns and understand new circumstances with ease.

Machine Learning has come to be used extensively, especially when it comes to providing analytical solutions to the world of consumers and technology. Through large systems of data, Machine Learning has been able to drive solutions, which help create a more data-driven approach towards solving problems.

How Artificial Intelligence is Changing Enterprise Applications

Corporate enterprises are showing a growing interest in the field of Artificial Intelligence and Machine Learning. From IBM’s Watson to Google’s DeepMind to AWS’s multiple Artificial Intelligence services, there is a lot of activity happening in the market these days.

Other features of Machine Learning include the likes of Deep Learning, computer vision and natural language processing (NLP). With all these innovations languages in place, computers can enhance their functionalities, including pattern recognition, forecasts, and analytical decision-making.

By incorporating Artificial Intelligence and Machine Learning techniques in day to day functions, large enterprises can automate everyday tasks and enhance their overall efficiency in the long run.

Here are some ways in which Machine Learning techniques are helping enterprises enhance their efficiency:

Improving Fraud Detection: Fraud detection has become the need of the hour, as more and more companies are investing heavily in these new capabilities. With more companies falling prey to fraudulent practices, there is an imminent need to be ahead in the game of fraud detection. With Artificial Intelligence and Machine Learning in place, companies and organizations can extensively direct their resources towards enriching their fraud prevention activities, to help isolate potential fraud activities.

Loss Prediction and Profit Maximization: When it comes to deriving insights from heaps of data, there is nothing better than Machine Learning to prevent loss prediction and maximize profits. The stronger the techniques, the more foolproof the loss prediction methodologies would become in the long run.

Personalized Banking: In this era of digitization, everything is automated. For this reason, banks often seek to deliver customized, top notch, personalized experiences to their customers to keep loyalty intact. By leveraging their data, banks can aim to unearth customer needs and fulfill them with the utmost precision and dedication.

Robotic Financial Advisors: Portfolio management has become the talk of the town these days, especially since robotic financial advisors have stepped into the game. Clients can benefit immensely by this advancement, since the right opportunities are mapped with their portfolio needs and demands. Robotic applications are easy to merge with services such as Alexa and Cortana, allowing banks to provide exceptional service to their customers. Through this integration, financial institutions can hope to acquire new customers and also offer more individualized services to existing customers.

Next-Era Digital Traveling: Through the use of recommendation engines, travelers can experience the new recommendations for their travel aspirations. Organizations can play a role by allowing customers to converse with chatbots, which are created through the use of Artificial Intelligence and Machine Learning. As predicted by Gartner, by the year 2020, 25% of all customer service operations will rely on virtual assistant technology to make their business ends meet.

Detailed Maintenance: Through the help of predictive maintenance, industries like aviation, transportation, and manufacturing are expecting to be able to provide the best customer service in the market. Through the use of predictive models, such industries can accurately forecast prices and predict their losses, thereby, reducing any redundancies in the future.

With digitization paving the path of the future, there is a bright scope for companies and organizations which are investing heavily in these new age technologies of Machine Learning and Artificial Intelligence. Third party consulting services such as Idexcel are ready to help companies looking to take their first step with industry leading consulting and cloud-advisory services.

As we progress through the years, what should be interesting to note are the changes we will get to see in the various industries, as every sector aims to provide exceptional customer service to their customers in multiple ways.

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True Business Efficiency Combines the Power of Cloud Computing and DevOps Practices

True Business Efficiency Combines the Power of Cloud Computing and DevOps

The use of both DevOps and cloud-computing have become a promising combination for companies these days. The blend of practices and implementations provides increased speed and efficiency, as well as higher agility and better end-user experiences. While the Cloud and DevOps are two independent technologies, they become intertwined, resulting in a workflow more efficient than ever before.

The Driving Force of the Cloud and DevOps

Implementation of Cloud computing techniques has rapidly ushered in the use of the DevOps philosophy. Through this trend, enterprises are increasingly making use of agile software to develop and implement administrative IT operations for their customers to enhance their services in the long run.

Through the concept of DevOps, businesses can break down their functional silos and drive discipline between their IT-related processes. Since the process of development is rather elaborate, more companies have to spend a lot of time, effort, and resources to plan and transform their IT infrastructure thoroughly – all to obtain the maximum benefit out of available resources.

The progression of the Cloud and DevOps has been rather sudden, as compared to other technological advancements in the enterprise market. The development of DevOps is aimed at making the approach more Cloud-centric; this means that most public and private Cloud providers are beginning to support the implementation of DevOps within their platforms. These practices will enhance and aid the continuous creation of development tools. Strong integration leaves little or no space for cost inefficiencies, as there is an efficient mode of centralized governance within the processes.

Through effective governance, there is tighter control on developers, since they have a more streamlined process to follow, which is controlled centrally via Cloud services. This way, in a subtle yet efficient manner, companies can bring their differentiated departments under control. Cloud-based DevOps also lessen the need for leveraging resources, thereby providing a usage-based accounting solution. Through such elaborate measures, companies can track their applications and developers related data.

Would it be right to say that the Cloud is running DevOps? The answer is quite merely ‘no.’ Given the interdependence between the two technologies, there is an imminent need for both the technologies to be present to derive maximum functionality. As per RightScale’s 2015 State of the Cloud Report, over 71% of companies have adopted 66% of DevOps within their Cloud Services.

DevOps Leads the way into the Cloud

The Cloud is ruled by DevOps – this fact has been proven time and again. With the powerful combination of the Cloud and DevOps working together, there is a lot of aggregate value for CTOs, who are working to remove technical challenges from the paths of implementation. To gain maximum efficiency out of the partnership between the Cloud and DevOps enterprises need to strive towards the rapid deployment of DevOps practices continually.

Due to the inherent lack of knowledge and deployment techniques, many large enterprises and developers alike fear the implementation, since the concept of utilization comes across as confusing and sometimes, even impossible. If Cloud computing is paving the path towards the future, chances are enterprises and developers will need to take this bull by the horns and make the most out of it. In other words, if the Cloud has to work, one must adequately know how to deploy and implement DevOps for best results. Companies such as Idexcel focus on providing DevOps consulting services which provide reduced development times and operational costs for businesses of all sizes.

Use the Cloud and DevOps to Your Advantage

Budgets need to be focused and modified to utilize the Cloud’s full potential and meet enterprise goals. DevOps is about using the right techniques to mold the Cloud’s functionality to one’s advantage. The better the implementation, the more efficient a process will be created. With the right approach and the proper knowledge, developers and enterprises can go a long way in advancing towards the right direction, especially when it comes to meeting all chalked out goals in the long run.

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CIO Cloud Summit 2018

CIO cloud summit 2018

Event Details: The CIO Cloud Summit brings together top IT executives to have in-depth conversations about industry pain points and best practices. These individuals are guaranteed to be Senior Level IT decision-makers. The summit helps the attendees build a network of IT executive peers capable of providing you with invaluable business advice with which to grow your career. Each summit creates a focused environment that allows executives to focus on the issues that are most important to their organizations and the team ensures that all aspects of the event are run smoothly and according to schedule, so that attendees are free to focus on matters at hand.

[Know more about the Conference]

About Idexcel: Idexcel is a Professional Services and Technology Solutions provider specializing in Cloud Services, Application Modernization, and Data Analytics. Idexcel is proud that for more than 20 years it has provided services that implement complex technologies that are innovative, agile and successful and have provided our customers with lasting value.

Anand Allolankandy – (Sr. Director Technical Sales & Delivery at Idexcel) will be attending this event. For further queries, please write to