Encouraging Employees for innovating your Business

Innovation in the business doesn’t come from the company and its policies. It is employees who bring in innovation. It not only requires a different mindset to do things differently but is also mandatory to possess the required skillset. Innovating ideas is vital for the long-term success of the company. Candidates possessing innovative ideas and experience contribute to a successful company.

Let us look at the traits of such employees.

1.   Neither constant yes-masters nor constant nay-sayers

An employee who cannot challenge the status quo is not well-suited for the innovating team. An employee who can’t say no when required doesn’t fit into the innovation team quite well.

While the employees who constantly say no impede the innovation. They have a negative attitude which can stifle innovative ideas

2.   Independent and long-race runners

Innovation takes time to bear fruits. It’s not an over-the-night task. Working on new ideas, products, and processes takes time. It involves multiple iterations, failures, experiments, etc. Innovators are like marathon runners who are persistent as well as independent. To work on original and creative ideas, innovation require independent thinkers who can take initiative.  

3.   Creative thinkers with excellent communication skills

One of the most vital ingredients of innovation is creativity. The candidate must be a creative thinker and rigorous implementer to take innovation to a fruitful end. For any innovation to succeed, it must be communicated well to every stakeholder. So, excellent communication is significantly important.

4.   Cross-sector experience holder

It is one of the crucial traits which allow creative thinkers to think beyond the conservational approach to the problem. Working in the same sector for a long time brings in rigidity to look above the predefined ways. It is detrimental to innovation.

Other characteristics are:

• Adaptability
• More curiosity and less judgemental
• Problem-solver & Problem-finder
• Experimenters
• Action takers
• Futuristic

What companies must do to show they value innovative candidates?

Demonstrate:

Demonstrate the capabilities of the companies and how the company is willing to innovate. Most companies do that but the picture changes after candidates are hired. So, demonstrate how your company welcomes innovation in your daily business cycle.

Pay:

Pay has become another measure to check the innovation. Low salaries don’t attract top talents in any industry. So, you must be ready to pay appropriately for the talent. Rather than just looking at the salary you are paying, try looking in terms of ROI.

Though ROI calculation is not a comprehensive parameter, it gives you a short-term view. Innovators often impact your business culture and have the potential to change several business practices. Such impacts are beyond ROI calculation.

Respect:

You may judge these out-of-the-box thinkers as eccentric. But this eccentricity makes them good at what they do. So, be respectful of their eccentricity and give them space to innovate for you.

Listen:

Good ideas are wasted if there is no one to listen to them. People who are good at innovation games require listening ears to appreciate their point of view and get feedback about their solution/product. It instills confidence in them and will attract them.

Welcome the change:

Be open-minded to see a change in company culture. Don’t be offended when someone challenges your legacy. Be open to listening to why and how an innovative solution is better for your company. If you feel offended by this, it will send in the wrong signal of inflexibility to the innovators.

Conclusion

There is no fixed set of traits an innovator must possess. For hiring someone as an innovator, soft skills are equally important as hard skills. As a company, some of the above-mentioned pointers can attract innovators to your company. Hiring innovators is essential as any innovation in the industry is brought in by the employees, not by the companies.

Share your thoughts with us on this at contact.us@virtuetechinc.com

Transforming Businesses with AIOps

Digital transformation is continuously pushing businesses towards automation. Enterprises are now using artificial intelligence for IT operations (AIOps) to enhance their businesses, improve risk management, deliver services efficiently, and get insightful reports for better analysis.

Artificial intelligence in AIOps helps businesses in identifying actual issues using predictive analysis. Hence, it plays a significant role in making businesses more efficient. It also helps in troubleshooting critical incidents that need to be resolved, getting to the root cause of the problem, and offering accurate suggestions to correct them while reducing the meantime to resolution (MTTR).

What is AIOps?

IT leaders are resorting to AIOps as a solution to automate mundane tasks and authorize their IT team to deploy better services and extract actionable insights.

In simple words, AIOps is incorporating machine learning and data analytics into IT operations to monitor, achieve, and troubleshoot network management goals.

Challenges with AIOps

To have a competitive edge, a business must focus on seamless user experience and meeting ever-growing customers’ demands. IT comes to aid businesses but it also brings along some challenges.

In a traditional IT environment, every component work in silos. Technology is divided among engineers, administrators, and business personnel. They work in silos without being aware of the infrastructure. AIOps can help in atomizing business processes and predicting failures. Some of the challenges that can be addressed by AIOps are:

Root Cause Identification:

Early detection of the root cause of an issue helps businesses in reducing the vulnerability of the systems. Organizations spend a large sum of money on infrastructure so that they can monitor events, and check logs, errors, and anomalies on a centralized AIOps platform. It makes it easy to compare all the metrics, find out issues, and automate remedial steps.

Resolution of problem:

AIOps is the best way to restructure silo-based environment to IT infrastructure with comprehensive monitoring. AIOps-based automation is vital for the resolution of problems occurring in real-time. It resolves them as soon as they occur and prevent/reduces the impact on the end-user.

Providing space for innovation:

AIOps Strategy and framework can automate the most mundane tasks. With automation, one can get a complete idea of what had happened and what helped to fix an issue. It frees up the time for the team to focus on innovative solutions searching to reduce IT costs and increase customer retention.

How can AIOps help your enterprise?

Enterprises must understand the concept and capabilities of AIOps before their implementation. It can be applied and enhanced from time to time. Let us see how enterprises are using AIOps.

Instant Alerts: 

Businesses are using AIOps to deploy smart alert notifications that let IT teams understand event history, resolve incidents, and meet service-level needs for problem resolution.

Root Cause Analysis:

It helps businesses in ensuring more uptime and steadiness of the services. Root cause analysis is a quick diagnosis of problems that helps in predicting the cause and effect of operational issues.

Threat Detection:

AIOps uses machine learning algorithms to identify threats using pattern recognition. It allows IT teams to extract signals from noise and recognize events that show unusual behaviour.

Incident Visualisation:

AIOps highlight incidents to organizations that can cause problems and need immediate attention. Relevant performance metrics help teams in quick resolution of the issue.

Does your business mandatorily need an AIOps solution?

AIOps is gaining popularity due to the shift towards modern IT strategy. It is a question of utmost importance for businesses if they need an AIOps solution or not. Here are some questions that will aid you in the evaluation of the right AIOps tool:

• What problem does an AIOps solution resolve?
• What are the salient features of the AIOps platform? Are those helpful in achieving your desired goal?
• What benefits will you reap when you implement AIOps into your business?
• How is this tool different from the AIOps monitoring tool?

Answers to these questions will help to find out whether you need an AIOps solution or not. If you conclude to use one of the AIOps solutions available, compare them with other available tools, use free trials, and then make the right decision. Reach out to us at contact.us@virtuetechinc.com if you are planning to implement AIOps into your business.

Enterprise Integration: Adding value to a business

Back in the era of on-premise applications and simple computing architecture, communication between systems was considerably easy. But with the onset of applications on the cloud, cloud computing, complex databases, and ever-changing customer demand, businesses require a system with seamless information exchange. 

Such systems not only save the information but also send and process messages, data, and requests. It implies that a system must analyze and organize data so that it is easily accessible and understandable across the organization.

What is Enterprise Integration?

It is an amalgamation of all the business processes, applications, data, and devices that work together as a single system. It makes organisations robust and adaptable to dynamic customer needs. With an increase in disparate applications & need for simultaneous processing in a complex environment, many CIOs see enterprise integration as an opportunity to become more responsive and agile.

Why businesses must adopt enterprise integration?

As businesses embrace digital trends, business transformation is accelerating. Companies must achieve previously unattainable levels of data control. Enterprise integration bridges the gap between computer programs and aids in data management via simple interfaces.

It is the key to improving internal processes and business activities. It also aids in the development, implementation, and distribution of critical applications. Enterprise integration, in particular, allows you to easily do the following:

• Enterprise integration reduces the complexity of data and makes it more accessible to everyone.
• It makes software upgrades simple and quick, and it allows systems to communicate and share data in real-time.
• Sharing critical information, simplifying processes, and capitalizing on opportunities all help businesses improve operational scalability and expand their reach and revenue.

Types of integration

There are the following types of integration that connects critical systems and applications across businesses:

1.    Application Integration

Application integration combines individual applications designed for a specific purpose so that they can work in tandem with other applications of the same type. It optimizes data and workflow across multiple software applications to modernize infrastructure and support agile operations. Data can be shared in real-time through seamlessly interconnected processes, resulting in improved insights, visibility, and productivity across the organization.

Application integration also aids in the integration of existing on-premises systems with rapidly evolving cloud-based enterprise applications. It enables businesses to operate more effectively and efficiently by orchestrating a variety of functions across their entire infrastructure.

2.    Data Integration

Data integration is the process of discovering, retrieving, and compiling information or data from disparate sources to provide users with a single structured and unified view, as the name implies. It makes data more freely available and easier to consume for both the system and the users, allowing analytic tools to produce effective, actionable business insights.

In most cases, integration begins with ingestion and includes steps such as cleansing, ETL mapping, and transformation. When done correctly, data integration can improve data quality, free up resources, and lower IT costs while also fostering innovation without requiring changes to existing applications or data structures.

3.    Process Integration

Previously, integrating business processes was only available to large corporations that could afford it. However, today’s businesses of all sizes must streamline processes such as marketing, sales, customer service, supply chain management, and so on.

Businesses could use process integration, also known as Business Process Integration (BPI), to efficiently connect systems, workflows, and processes to transform operations and drive efficiency. It also automates management, operational, and support processes, giving businesses a competitive advantage. This allows business leaders to spend less time and energy worrying about integration issues and more time and energy driving new business.

Roadmap to implement enterprise integration

The steps to implement enterprise integration are as follows:

• Evaluating the need for implementation & your organization goal
• Creating a strategic plan to implement
• Measuring the effectiveness of the strategy
• Observing the results & improving upon minimum errors & inefficiencies.

Conclusion:

Every growing organisation must think of enterprise integration. It takes collaboration among your functional and business units to another level. Let us know how you think it can help your business at contact.us@virtuetechinc.com.

Automation of cloud infrastructure with Terraform

The accelerated acceptance of cloud services has increased the migration of on-premise and physical infrastructure to cloud datacenters. It brings advantages like reduced IT costs, scalability, business continuity, data security, data recovery, and efficiency.

Today, cloud service providers give the provision of automating infrastructure too. It led to the development of the concept of infrastructure as code. Infrastructure as a code is just another implementation of DevOps. Other applications like CI/CD, configuration management, test automation, containerization, & Orchestration have shortened the life cycle of software development. Therefore, DevOps has become a necessity for thriving in the market.  

Why use infrastructure as Code?

Infrastructure management looks over the performance of the infrastructure elements required for the software to provide business value. It includes managing physical equipment like endpoints, and servers as well as virtual elements like network and app configurations.

DevOps engineers are typically in charge of IT infrastructure. They must keep it adaptable, scalable, secure, and controllable. To accomplish these objectives, DevOps engineers containerize applications. These applications are deployed and managed by using tools such as Docker.

Containerization enables the running of an application in a manageable cluster without the need for manual configuration of the application and following documentation step by step. Engineers can instead use a Dockerfile to record changes and move code from one environment to another.

A containerized application can run on a physical server, a virtual machine, or a cloud service. A cloud service is the most convenient option because it has far more advantages than disadvantages.

Once the application was deployed on the cloud, DevOps engineers started working on the environment. Cloud providers offer capabilities of generating instances in some seconds. Not only, just instances but also different required infrastructure like VPN, private and public subnets, gateways, and many other components.

Infrastructure as code is a package of files that describes the customization you have done in the cloud characteristics’. After configuring files, you just need to run a few commands to get everything up and running.

Automating infrastructure management processes will help you reap the following benefits:

• Time-saving on repetitive tasks
• Speeding up of application deployment
• Reduction in human error
• Increased project scalability
• Easy knowledge transfer to other teams.
• Develop documentation faster.

Introduction to Terraform

Terraform is an open-source infrastructure as code developed by HashiCorp. It empowers users to define the infrastructure using high-level configuration language known as HashiCorp Configuration Language or JSON. It supports all major cloud computing services such as AWS, Azure, and Google cloud platforms.

Installing Terraform is easily done in Linux and Mac OS while Windows face some challenges in installing. Hence, it is recommended to use a UNIX system running in a docker container.

For a better experience, use Terraform with Terragrunt. Terragrunt is a wrapper that allows you to store infrastructure configurations.

With these pros, terraform is one of the most convenient choices to automate cloud infrastructure management.

Cons of managing infrastructure with Terraform

 Implementation of terraform had led us to discover its limitations which are as follows:

1. Tedious to manage complex configuration change: When terraform is used by multiple teams, changing project infrastructure takes more time than doing it manually. Any change in configuration has to be committed, tested, and implemented.
2. Complexity in permission management: DevOps engineer requires a super account with elevated access rights to work on terraform. It would be difficult to divide infrastructure into several parts and separate access rights to DevOps engineers.
3. Late Deployment of product-specific features: A latency has been observed in delivering product-specific features when terraform developers work for AWS CloudFormation, AWS Cloud development Kit, etc.

Conclusion

Automating cloud infrastructure management can reduce the time and effort required by DevOps engineers to configure the infrastructure of cloud-based projects. With tools like Terraform, you can configure infrastructure in one go and then can reuse it on other projects. Feel free to reach out to us at contact.us@virtuetechinc.com in case of any suggestions and queries.

Composable Data Analytics

There has been a quantum leap in digital transformation. The rate of advancement is measured by feeding and scaling AI. Other factors that will be crucial in digital transformation are composable data and analytics.

Before moving forward, let us know what is composable data.

Composable Data can store and spread different resources to different machines or devices. A set of information or software applications is only provided when the end-user requests. Applications of composable data can be seen in supply chain management where it ensures seamless communication between employees and managers, optimised route selection, and delivery tracking. Another application can be found in the healthcare industry where composable data will increase the computation speed of IoMT (Internet of Medical Things)

In this manner, composable data makes it easier to assemble AI from across many tools for BI, data management, and analytics. It allows companies to integrate the usage of microservices and containerization together to create a service.

Why Businesses should focus on Composable Data Analytics?

It will help in finding new ways of packaging data as a part of a service or product. It could be built using no-code platforms available on the cloud. Laying out the building foundation for composable data and analytics is essential to promote easy access and sharing across distributed data environments. It is a set of tools put together to form a solution. Metadata and graph databases make this practical and feasible. It is a tough job but emerging technologies are making it possible.

Impact on Big Data

The need of combining a wide variety of data into application to improve situational awareness and decision-making is increasing. The pandemic had made a lot of historic data obsolete and opened doors for analysing a broader spectrum of new data. There are also many small use cases where a tiny amount of data is present to work with. Hence, new investigating technologies like federated learning and content analytics are required to organize new types of data such as speech, video, and text.

It is the way to digital transformation and scalable AI. Organizations must pay attention to new privacy and AI models. Although, it has been observed that businesses are grappling with scaling AI prototypes and pilots into production.

Implication on Business Value

  Gartner’s research showed that 72% of data and analytics leaders are heavily involved in the digital transformational efforts of the organizations. These data leaders now face various emerging trends due to composable which are as follows:

1.    XOps:

The progression of DevOps to support artificial intelligence and machine learning gave birth to XOps. The X in XOps stands for MLOps, FinOps, and ModelOps. It increased the flexibility and agility in coordinating infrastructure, data sources, and business needs in new ways.

2.    Decision Intelligence:

Using data to draw out insightful decisions is not new. With the inclusion of a new variety of data sets and the ability to store these data sets, a better decision can be made as organizations are more situationally aware. Composable data analytics provide numerous techniques to align and tune decision models to make them more understandable and traceable.

3.    Data and Analytics become the core of the businesses:

Data and analytics gained unparalleled attention from the businesses with disruptions brought in by the covid-19 pandemic. Analytics has moved from secondary activity to must-do activity for companies.

4.    Introduction of Graph Databases:

Graph databases were present for a while but were of restricted use due to limited data sources, tools, and workflows. The incorporation of graph databases with BI and analytics tools led to rapid growth in technology. According to Gartner, graph technology will comprise 80% of data analytics by 2025.

5.    Data and analytics with edge computing:

IoT allows enterprises to work with edge computing to unlock potential autonomous and intelligent applications. Embedding analytics, decision intelligence to edge computing will be another emerging trend. Including edge computing increases speed and resilience as there is no need for constant cloud connectivity.

Conclusion

Technical advancements has brought in scope for incorporating composable data and analytics into the existing IT ecosystem of the organisations. We have seen some of the applications in the businesses. Let us know how your organisation can use these at contact.us@virtuetechinc.com.

Discovering 5 Open-Source Technologies for DevOps

DevOps is no longer a technology or methodology; it has become a culture now. Its major components are people, processes, and tools. While people and processes are important for maintaining uniformity, tools are responsible for delivering transformational initiatives. Implementing a paid tool for the DevOps environment may lead to a significant increase in costs. So, to cut down the expenses, let us explore some of the free source platforms.

1.   GitLab

This DevOps platform is an open-source code repository that can plan, develop, secure, and operate software in a single application. It is free for individuals. It provides capabilities for each stage of the  software development lifecycle. It is one of the most futuristic features for implementing DevOps practices. 

It is written in Ruby, GO, and JavaScript.

Capabilities offered by the GitLab are:

• Resource management
• CI/CD
• Package management
• Distributed architecture
• Cloud support

GitLab allows you to host different development applications, versions, and chains. It also gives developers scope to inspect the code and roll it back to the stable version in case of unanticipated problems.

Value stream management, Agile management, and source code management are some of the use cases.

2.   Prometheus

This open-source platform is majorly used for monitoring and alerting. It is managed by the Cloud Native Computing Foundation. Its ecosystem has components such as servers, client libraries, gateways, alert managers, and support tools. It is a default monitoring and alerting solution for Kubernetes container-based orchestration engine. Prometheus collects data about your application and infrastructure. The platform gathers little amount of data about many things to help in the understanding trajectory of your system. 

Features of Prometheus are:

• Multi-dimensional data model
• Flexible query language
• Better visualization tools
• Supports service discovery or static configuration

No commercial flavour is available for Prometheus.

3.   Terraform

It is an infrastructure as code software tool developed as HashiCorp. It helps in mitigating the problems of configuration drift. It is a platform-agnostic declaration coding tool that helps developers to configure infrastructure using high-level configuration language. It is compatible with different cloud providers like AWS, Microsoft Azure, Google Cloud Platform, etc.

Dependency graphs and state management are some of the features of the terraform. It can be part of the pipeline as code. Different strategies can be used to create and deploy applications in various cloud platforms. It provides a consistent CLI flow workflow to manage multiple cloud services.

It converts APIs into configuration files. You can write infrastructure code using these declarative configuration files. You can test run the infrastructure changes. These changes can be applied to various cloud providers after testing.

4.   Ansible

It is an IT automation/configuration tool that provides cross-platform support. It is easy to use, secure, and reliable for safe adoption in an organization. It is the most suitable for deployment and rolling updates in release management activities. The point of differentiation from another configuration tool is it is agentless.  It is written in Python, Ruby, Shell, & PowerShell.

Features of the ansible are:

• Distributed architecture
• Easy integration with Docker, Kerberos, LDAP, & other authentication management systems.
• Supports hybrid, on-premise, and cloud environment

5.   Trivy

Trivy is an open-source yet simple and comprehensive vulnerability/misconfiguration scanner for containers. It detects vulnerabilities in OS platforms (Alpine, CentOS, etc), language-specific packages (Bundler, Composer, etc), Infrastructure as code (Kubernetes, etc). A software vulnerability is a flaw, loophole, or weakness present in software or operating system. Just install trivy and scan the specific target by just giving the image name of the container. It is because of these platforms DevSecOps has become easy to implement. It can be integrated with the pipeline as code that can be used to analyse docker images and publish the reports.

We have discussed some of the open-source DevOps tools present. They are many more tools to explore based on your requirement.

Please share your thoughts on open-source tools and technologies with us at contact.us@virtuetech.com.

Gartner’s Top technology of the year 2022 (Part II)

In the era where data is considered as the new oil, talking about just a handful of new technologies doesn’t do justice. So, here we are with another set of emerging technologies that will be an area of interest for many researchers, businesses, & technology enthusiasts.

In part I, we had talked about 6 of the emerging technologies for the year 2022. Continuing the trend, let find out another set of technologies that will supersede the technology market.

1.   Privacy-enhancing Computation

No matter what, data security will always be the top concern for every company. But as companies are looking to take data security as a priority, users are becoming skeptical in sharing the data. Their concern also involves the amount of data they should share with the company.

Privacy-enhancing computation solves the problem of securing personal data in an untrusted environment. Businesses can consume data without compromising confidentiality. It is a superset of privacy-protection technologies that allow data extraction while meeting data security compliance. Organizations can infer the actionable insights without sharing personal data with third parties. It helps security to expand their borders as well as the level of anonymity.

2.   Composable Applications

The term composable signifies the inter-relationships of the components. Earlier only systems used to be highly composable but now it is true for applications too. Composable applications are created from business-centric modular components.

The prime reason for this is the ever-changing needs of the business and the need for quick innovation delivery. Customers are looking for a more contextualized and personalized application experience. So, to adapt applications dynamically and to respond to rapid business change, companies must turn to composable applications.

Composable applications are made from parts or blocks of applications. They are fine-tuned to deliver functionality better than the sum of individual modules.

3.   Distributed Enterprise

Distributed enterprises depict a digital-first approach. Propelled by the huge growth in remote and hybrid working, the distributed enterprise will improve employee experience, digitalize customers and partner touchpoints, and expand product experiences.

Every industry is looking forward to reorganizing its delivery model to leverage the distributed network. Gartner predicts that 75% of the organizations will make 25% faster revenue growth exploiting the benefits of the distributed enterprise.

4.   Total Experience (TX)

 Implementing the total experience will help IT companies in achieving enhanced customer experience and improved employee productivity. Total Experience unites customer experience (CX), user experience (UX), employee experience (EX), and multi-experience (MX) across multiple interaction points to accelerate growth. It helps companies create a superior interconnected experience for the customers and employees. By incorporating experiences, businesses will obtain better outcomes, revenue, and profits.

5.   Autonomic Systems

Autonomic systems help companies to modify their algorithm to adapt to new conditions without any external software update. These self-managed systems can learn new tasks, provide quick responses, and optimize behaviour in a complex environment.

 It uses multiple technologies and is generally used in the complex security environment and is expected to become common in an environment that includes physical systems such as drones, robots, and smart spaces.

6.   Generative AI

It is one of the most promising developments in AI in recent years. It refers to a program that uses existing content like videos, audio, and pictures to generate new content similar to the original content.

Generative AI uses machine learning algorithms to discover underlying patterns of the content from the data. It uses these patterns to generate new content which is similar and original. It could be used in fields ranging from medical to product creation.

These technology trends give us a holistic view of the emerging technologies in different segments of the businesses ranging from security to experiential learning. Concluding the article, we looked at the recent changes which were accelerated by the pandemic and massive disruption in terms of the need for innovation it brought.

Have you not checked our preceding article? Check it out here.

And do let us know which technologies you find interesting for your organisation at contact.us@virtuetechinc.com.