Category: Blogs

Introduction

Is Kubernetes replacing Docker? This question has been a hot topic for discussion lately. Along those lines, the “this vs. that” scenario has been widely employed amongst technologists. But it’s safe to say that there’s certainly some misinterpretation about these technologies. Why?

Because Kubernetes and Docker are primarily different technologies that do have a few differences, yes, but cannot replace each other. But are they great together? Let’s find out.

This article will look at some of the differentiating features between these two powerful technologies and see how they can help businesses when used in tandem.

What is Docker?

Docker is a software development platform that makes it easy for developers to develop and deploy apps within packaged containerized environments. So, no matter the environment or machine, apps run the same way thanks to containers.

What are containers? They are isolated units of software, and each of them holds a group of processes that enable applications to run quickly in every environment. Each of these has its specific jobs, memory, shared resources, etc.

Docker containers can be used to rapidly deploy on any machine without any compatibility issues. Therefore, using Docker paves the way for low maintenance, reduces a ton of effort, and facilitates easy deployment. A major benefit of a Docker container is its ability to let you build scalable, portable apps due to sharing of hardware resources.

What is Kubernetes?

A container orchestration framework, Kubernetes, originally developed by Google, manages containers, including Docker and other technologies.

It further helps to deploy and manage containerized applications in various deployment environments – physical, cloud, virtual, etc. The Kubernetes system automates most container-related activities like creation, configuration, management, maintenance, and more, making it the most sought-after container orchestration tool.

Famous apps like Airbnb, Pinterest, and Spotify run on Kubernetes. Developers can easily control how their applications interact on and outside of Kubernetes and quickly scale them up and down.

Additionally, for organizations that have transitioned to using a microservices-based architecture, using Kubernetes to deploy them can be of tremendous help. Why? Because of its ability to manage, deploy, and scale hundreds or more microservices.

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Introduction

What makes product development so extremely challenging in an organizational context? Synchronization and collaboration are the most important aspects of successful product development. As per recent Gartner research, the IT industry is going to see a 50% increase in collaboration tools and architectures by the end of 2022 vis-à-vis pre pandemic standards.

To facilitate streamlined collaboration for resources in the relevant domains, the product development architecture and processes must provide ways in which it is possible for resources to work together, or separately without issues from one software development team cascading into the other. When it comes to many teams working together to develop and support a large and complex product, a centralized architecture with co-dependent features can slow down a lot of processes – especially those of resolving time-critical issues. This is exactly the challenge that the Micro front-end architecture solves.

You can think of micro frontends as an extension to the microservices architecture to the front end, wherein the application interfaces are separate from each other, managed by different teams, and can be built on different technologies.

What makes Micro Front Ends Different?

If you have services in the back end, and even separate teams that take care of each service, connecting them together in the form of a SPA means that one team cannot work independently from the other. It would mean each team having to be mindful of the other teams’ development activities.

For example, if we have an e-commerce platform with services such as add/remove cart items, listing cart contents, and recommendation system and all are connected to the SPA, it would mean changes to any one of these services means checking the interaction of the other services with it – (Has it caused any errors? Has the user interaction changed?). However, if these three features were to be connected to separate micro front ends, all of them would be separate and independent of each other. Each team involved could handle their microservice separately along with the micro front end. This provides for a much more streamlined and independent framework.

What can Micro Front Ends do for Your Business?

Scale Your Product: Scaling products, especially when it comes to integrating new features or expanding existing features is now incredibly easy with micro frontends. Whenever you need to add something new, you can work exclusively on that service along with its micro frontend, without disturbing anything else in your architecture, Moreover, integrating new services is also much simpler.

Reduced Turnaround Time: With co-dependencies significantly reduced, the scaling of the product we talked about earlier can be done at a much faster rate.

Deploy Independently: Each feature/service that you intend to add/expand on, can now be deployed independently. This could offer a wide array of benefits – separate testing, easy deployment and retraction of pilot features (experimentation), focusing more on the business side of things when it comes to user interaction with features, etc.

Greater Stability: You can provide an optimal performance guarantee to your stakeholders for your application, even when tweaking features and parameters for a particular service or adding new services.

Managing Codebases and Repositories: With the capability of each team handling different features, you can handle documentation, codebases, repositories, etc. for all of your services in neat and accessible storage. This makes technical referencing, code-cleanups, code refactoring, etc. a lot easier for future technical resources.

Easy Hiring of Developers/SMEs: It becomes a lot easier to hire resources and save on their training time. They can be directly integrated into the team working on the technologies and services they are experts at, without having to train them for inter-dependent considerations.

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Introduction

Customer Experience (CX) is what drives success for software products especially SaaS solutions. The way your product is perceived in the market by its end users is what determines its success or failure. As per Gartner, over 70% of product development leaders are struggling to keep up with CX standards that increase customer satisfaction and ensure organizational success. A deep understanding of the paradigm and subject matter expertise can help product development organizations build software that is business-friendly and help improve Customer Experience in the long run.

When developing a customer-facing software solution, the end-users’ overall experience is of paramount importance to business retention and next stages of software development. Customers and buyers today are increasingly aware of the many options available to them. People want unified, smooth, continuous interactions with minimum navigations, which puts technology at the core of these experiences. From a brand perspective, technology can provide deep insights into what customers expect from their interactions. For most organizations, a customer-centric IT strategy must go far beyond simply setting up a workflow solution. Read this blog to understand the various ingredients that make up a good Customer Experience.

Product Ecosystem – Each Touch Point Must Be Balanced

Various organizations don’t stop building solutions when done with one use case. An ecosystem of solutions is what drives value for your company as a whole. With all your touchpoints in the ecosystem, CX-driven development must be balanced and not lose focus when new touchpoints are being integrated into your ecosystem. Think Google with its various touchpoints – Google Books, Google Movies, Google Play, Google Pay, etc. The end-user experience for all of these applications is largely the same and is made possible by a solid foundation that ensures compatibility and uniformity in experience – no matter how unique the situation and different from the other.

A lot of organizations struggle with this uniformity across all touchpoints in their ecosystem. This happens because unique solutions leverage different technologies, and demand varying user flows. Uniformity becomes a challenge if you have a narrowed-down technology resource pool that has to do everything together and keep up with market demands. The solution to this problem can be working with technology partners that can help an organization minimize the difference between the demand for varying user flows and the uniformity in the Customer Experience. While an organization focuses on Customer Experience requirements and uniformity, the implementation of discrete UI/UX and development requirements can be delegated to your technology partner. This also enables you to not slow down when touchpoints are being constantly integrated into your ecosystem.

Product Architectures

Does your product architecture support your Customer Experience requirements? Your organization needs to be absolutely certain that the CX parameters and standards you decide on are supported by your architecture. If your architecture is monolithic, and the CX standards that you have decided on require dynamic changes at regular intervals of time – say quarterly or yearly – your business might suffer because of the difficulties involved in integrating dynamic changes on a monolithic architecture. The above example, however, is simplified to highlight the very precise issue. Architecture decision is not as black and white as dynamic or static, it all depends on your product offerings.

Product architectures have evolved over time and are accommodating intermediary layers between the ones we are already used to. Reference Architectures are one of the ways to go about figuring out template solutions to your business requirements. You can reach out to a technology consultant or innovations service provider that can help you with reference architectures to build your product on. So, what are some examples of these architectures?

1. Microservices Architecture
Microservices are something that can give you a lot of dynamic freedom in your product features. Microservices ensure that all feature integrations are independent of each other. This means that disconnecting one feature does not mean issues cascading into the rest, and each microservice can be addressed independently. This enables a product developer to freely and quickly work on each feature depending on iterative requirements, and deploy or retract them as and when required.

In contrast, the static monolithic architecture, or even dynamic but connected services architecture leads your product features to be dependent on so many parameters that changes and resolutions take much longer than they should.

2. Back End for Front End (BFF)
Back End for Front End (BFF) architecture puts an intermediary layer between your front end and back end. What’s the point of this? BFF mitigates the need for you to build new code restructuring your architecture when new clients are added. For example, if you currently have mobile and desktop clients that have communication frameworks set up with your servers, adding a tablet client will require you to deploy a new communication framework between the tablet’s front end and your backend (server).

However, if you have an intermediary layer between the front and back end (BFF), the BFF can take care of this communication framework, instead of the need for a new service at the backend. Each time, you will only have to set up this framework in the BFF and not restructure your architecture with new services at the backend. Your product development will probably require an architecture that is vastly different from any of the architectures mentioned here, and they will determine your Customer Experience with regards to turnaround times, service latencies, and a lot more. Figuring out a suitable architecture for your product is a very important step in your Software Development Life Cycle (SDLC) that is coherent with your Customer Experience.

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Introduction

According to Gartner’s recent research, remote workers will comprise 32% of product development teams globally. More than 50% of the total product development workforce will work in a hybrid work environment. As tech startups are struggling to retain talent in an environment where large corporations are providing extremely competitive compensations and benefits, remote working comes as a ray of hope for these startups where remote working is an extremely desirable work benefit for many product development employees. The term ‘remote product development’ is getting increasingly popular these days owing to the major adoption of the model by many young start-ups and tech enterprises.

Bringing together a product development team is essential if you have a product idea and want to turn it into a full-fledged product that meets all your expectations (quality, budget, performance, time, etc.). Remote product development is the ideal solution for companies with talent dispersed throughout the globe. Read this blog to learn how you can leverage remote product development to your advantage, and how to start building a remote product development team.

What is Remote Product Development?

Remote product development is the process of having your product developed somewhere other than your company’s physical location. You outsource your new product development to product development professionals in scattered geographies and not limited to the vicinity of your office but those who are a part of your organization. Outsourced product development on the other hand is when you outsource your product development to technology professionals for some other organization and in this model either you or the outsourced vendor could be responsible for the technology development.

It could be the office of a company to which you have outsourced your product’s development or a video conference with everyone on the team working from different locations. Tech startups can now have their products developed by the best minds on the planet, even if they are thousands of miles apart.

Why Should You Build Remote Product Development Teams?

While remote product development teams had not gained a lot of momentum before the pandemic, a lot of organizations were forced to work from home. During this time, a lot of benefits came into the spotlight for remote working and encapsulate the idea of why remote working is beneficial and has become a standard for many tech companies today. Let us take a look at why remote product development is gaining momentum among the leaders of tech organizations.

Access to Extended Capabilities and Talents: As tech companies look to assemble teams, it could be frustrating to limit yourself to your vicinity to look for the niche talent you require. If this is the case, you have to spend time training these resources and spend more money. However, with remote product development, location stops being a barrier for you to be able the right talent for your product development requirements. Moreover, outsourced product development and the flexibility it provides with extended team’s engagement models as well as the capacity to provide you with experienced and talented resources to immediately start working on your product is unparalleled.

Diverse Perspectives: Having access to remote resources also allows you to leverage the opinions and perspectives of different geographies with different practices. This can help you optimize your product for the market. Being limited to a particular region will limit your product development practices established only in that region. However, remote resources can contribute to the optimization of your product so it can be end-user friendly for various geographical locations.

Reducing Time to Market: Leveraging remote product development teams reduces turnaround time for a lot of parameters such as onboarding resources and executing tasks. Needless to say, this will have a direct impact on the time it takes to launch your product in the market.

Access to the Latest Tools and Technologies: With remote product development, you can leverage outsourced product development and extended team capabilities. These service providers help tech startups leverage the latest technology for product success. With remote teams, you can ensure that you have the expertise that can help you leverage the latest tools and technologies.

Controlled Costs: Perhaps the most important aspect of onboarding resources is the expenses involved. When working with outsourced development and extended team service providers, you will have a clear idea of what compensation it is that you have to provide the resources as you can leverage flexible engagement models with your provider. You do not have to worry anymore about details such as negotiating salaries, providing relocation and accommodation benefits, etc. Instead, you can focus on more value-driving benefits that help in the retention of these resources and improve productivity.

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Introduction

Going forward in 2022, it is going to get even more difficult to hire IT talent than what the situation currently is. This is not only because of a talent crunch. There are a few other factors at play here including demand & supply, skillsets availability, experience vs payout, notice period, digital adoption across industries, maintaining cybersecurity in remote/hybrid models. Furthermore, tech startups face competition from established tech giants. Technical resources choose established firms that are providing higher compensation and benefits. For newer startups looking to build an initial tech team, this poses a major challenge.

Some other reasons which increase the difficulty in IT hiring include

• Managing health and safety protocols in the pandemic.
• Integrating the right technology for hybrid/remote communication.
• Providing technical resources with the desired career progression.

How do we go about addressing these challenges?

Since the pandemic, there have been changes to the approach to building tech teams. Alternatives to in-house hiring such as outsourcing have increased. The pandemic has raised challenges in building local teams. Many firms responded to these challenges by outsourcing IT requirements not only the resources but also their product development. This uncovered more benefits in building teams such as:

• Tapping into relevant talent from locations that were earlier inaccessible or not thought of,
• Reducing costs involved in setting up infrastructure for new hires,
• Quicker fulfilment of engineering positions,
• Business continuity and adherence to product roadmap as well as pre-defined timelines & milestones,
• An increase in outsourcing has allowed tech startups to view the value of technology partners as co-innovators rather than skillset providers

Here are some of the other instances of increased outsourcing since the pandemic.

Increase in Digital Adoption

Global IT expenditure is forecasted to grow by more than 5% in 2022 which is almost twice than the pre-Covid forecast average. Digital Adoption for businesses and startups saw a rampant increase in the last 2 years. This is because companies had to start adopting communication technologies. Furthermore, even simple business operations such as employee timesheets, activity trackers, team updates became digitized. Since companies adopted digitization as a necessity, they also started realizing its value.

More efficient and modern practices in the business operation side of things are likely to continue for several years. An increasing number of custom software development companies like Pratiti are helping customers build custom solutions vis-à-vis their requirements.

Reducing Infrastructure Cost through Digitization

As a result of Covid-19, businesses are focusing more on saving money and getting more work done at a lower cost, resulting in the outsourcing of functions like payroll services. For businesses, IT outsourcing is the ideal option. Companies can eliminate office space expenditures and all associated costs by engaging IT service providers and other offshore software developers.

In-house resources possess the expertise to develop new products. But to ensure that these products are sustainable and monetizable in the market, there needs to exist a new product development roadmap. This includes validating the feasibility of new product ideas through processes such as proof of concept.

Testing new product ideas for feasibility is extremely important before launching the full-fledged product.

This new product development roadmap can be outsourced to organizations that have the expertise and capabilities to validate a product definition and build the corresponding proof of concept, minimum viable product (MVP), or prototype. This ensures a higher chance of success for new products, as well as knowing what to do if you identify why your product is not yet feasible for the market.

Product Support is as important as Product Development

Once a product is deployed, it becomes important to integrate a support ecosystem for it to sustain itself in the market. If your limited in-house team focuses on all of these parameters, it becomes difficult to focus on overall product innovation and organizational growth. Product Support functions include setting up automated QA practices, a cloud solution to help with performance analysis among other benefits, and helping companies reduce Total Cost of Ownership (TCO) and boost revenues by right-sizing the team, right-shoring the resources, and right-shaping products. Setting up this ecosystem is unexplored trenches for many companies in their early to mid-stages.

IT hiring for these fields becomes difficult because you do not know how to set up product support departments and what resources to look for. For example – are you looking for pure quality assurance engineers (QA) or are you looking to hire SDETs (Software Development Engineers in Test)? Different kinds of products will require different kinds of resources, with niche skillsets. With these added layers of complexity, it is best to leverage the expertise of product support services providers who can set up an efficient ecosystem for you.

The landscape involved in business operations and hiring resources has changed dramatically in the last few months and has set precedent for the evolution of these parameters for several years to come. If you are looking for a technology partner to integrate these evolutions into your business, reach out to an expert custom software solution and outsourced product development partner like Pratiti Technologies to accelerate your digital transformation journey today.

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Introduction

Electronic Health Records are quickly replacing manual data entry in leading healthcare organizations. As per a recent study by Deloitte, 90% of physicians are looking to continually update their organization’s electronic health record systems. This is the situation because healthcare organizations are becoming increasingly aware of the digitization of health records and want to keep their systems up to date to keep leveraging its benefits. In 2022, up to 95% of healthcare organizations are already leveraging EHR systems in the US alone. If you’re looking for EHR solutions and want to start by learning what benefits it can offer your healthcare organization, we have collated a few benefits that our customers have benefited from with our custom EHR solutions. A few of these benefits are as under:

Centralized Records

EHRs go beyond just storing the information. EHRs are necessary to keep all necessary information about a patient in a centralized and integrated format for easy access to any relevant information. This includes allergies, ailment history, drugs prescription history, etc. Further solutions can be integrated that can fetch all necessary information from the EHR to intimate the healthcare provider about what the patient requires in the event of an incident. If this was done manually or the digital solution was too basic containing only storage functionalities, it would be much more time-consuming and in some moderately likely cases, unprecedented.

Appointment Scheduling Automation

An EHR can be connected to a database containing the contact information of the patient as well as their assigned healthcare provider in order to enable automated scheduling and notifications through phone communication for their appointment. This negates the need for manual follow-ups. This is especially useful in the case of patients with chronic conditions that require care at regular intervals. Without an EHR containing centralized information about patient information including history and contact, this process would have been time-consuming and error-prone.

Faster Compliance with formalities

A custom EHR system that captures and relays information in accordance with regulatory requirements of both government and healthcare provider itself can allow the healthcare organization to focus on the patients more, and less on the formalities required such as compliance forms. This is especially necessary in cases that require immediate medical attention, but regulatory requirements delay the time by which the patient can start receiving care and treatment.

Predictive Analytics

Through the digital storage of data through EHRs, it becomes possible to leverage data analytics and machine learning for use cases around predictive analytics. An automated solution can intimate the healthcare provider or the patient about the risks of the patient’s healthcare conditions on the basis of updated data on the EHR. This can help prevent emergency situations and the development of chronic disease. There are several predictive analytics’ use cases that are becoming increasingly popular leading to saving lives of hundreds of patients due to their high level of accuracy in prediction.

Preventing Errors

In the healthcare setting, it can be catastrophic to make mistakes and mix up data which can happen through manual processes. To avoid this, a custom EHR solution with input constraints and data filters can stop error-prone processes from the initial steps themselves. This is important because to deal with volumes of data, there needs to be data filtering and correction at every step of the way – starting from the entry process itself. This solution could include the prevention of data into the system that is mismatched in the type of data, identifying discrepancies in terms of nature of condition and nature of treatment entered, and much more. This is possible through the use of custom EHR that is needed by the organization.

Today, we are witnessing a great transition towards better healthcare by digitizing and adopting powerful health software development systems, custom healthcare solutions and apps aimed to simplify the most common operations. The EHR/EMR systems, Healthcare apps, IoT based remote monitoring of patients reduces paperwork, improve storage issues, care coordination and increase the overall quality of services provided to the patients/end users through a streamlined workflow.

In order to be able to drive maximum value, and avoid preventable mistakes, leverage the expertise of a technology partner that thoroughly understands the requirements of your healthcare organization and the nature of care you provide. Be it lifestyle improvement, or general medical consulting, or trauma response, every healthcare organization’s EHR will differ in terms of the data required to be processed and the intimations to be conveyed to the healthcare providers or patients. In order to build a custom solution on the foundation of strong and functioning technology implementation, contact Pratiti Technologies to build your EHR today.

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Introduction

Shifting to the Cloud

The pandemic threw light into potential areas of digital disruption in the healthcare sector, but for most decision-makers in the industry – the question of where and how to start remains at large.

The best answer to this dilemma is to explore the world of cloud computing. The pandemic has resulted in several healthcare leaders emphasizing increased leverage of SaaS solutions for running the show.

In fact, Accenture’s survey found that nearly 66% of healthcare executives are expected to transition their core technology infrastructure into the cloud in 2022 alone.

As the pace of digitization soars in the healthcare sector, cloud computing is poised to be the clear forerunner in enabling healthcare organizations to achieve digital excellence.

To that end, here are five reasons why we believe the future of healthcare is in the cloud.

Elimination of Legacy Bottlenecks

Building the next generation of assisted patient services, where patient data from their EMR guide doctors and caregivers, requires a paradigm shift in how technology is perceived in the sector.

Applications built on top of legacy systems can no longer be relied upon for making critical decisions as they have a higher risk of failure and are susceptible to erroneous data management.

Healthcare providers will need to spend considerable time and money on resolving legacy system conflicts and dependencies. Moving to modern SaaS-based operations solutions can easily rectify this challenge.

The cloud infrastructure offers unparalleled scalability, data management, and integration capabilities. This allows healthcare organizations to build a connected network of systems that handle multiple facets of their business.

Doctors can access patients’ EMR data securely, inspect their past behavior, health records, and much more from anywhere, thanks to cloud integration.

Customization Flexibility

When transitioning to a cloud environment, healthcare organizations have a lot of options to flexibly configure their desired service workflows and application management policies. This allows them to build powerful custom EMR solutions on the cloud and enable multiple departments or even hospital branches to use their digital infrastructure when the business expands.

They can set automated backend workflows to help reconcile information and data management between different departments or even amongst various facilities. All these can be built easily and quickly on a cloud infrastructure.

Lower Cost of Operations

One of the prime reasons behind the rapid adoption rate of the cloud in the healthcare sector is cost savings. By migrating from expensive one-time software licenses to a more streamlined subscription model of costs, healthcare organizations can get access to world-class digital services at a fraction of their capital expenditures or budgets.

Building a Sturdy Communication Backbone

During the pandemic, there was a massive boom in telemedicine and telehealth services. And a good majority of patients are likely to favor telemedicine in the future when the pandemic eventually disappears.

This remote medical care facility allowed hospitals to build new revenue streams without incurring substantial capital expenditures. From a profitability standpoint, hospitals can set up remote conferences or telemedicine facilities wherein their expert panel of doctors can examine and treat patients remotely, even in faraway cities.

Healthcare enterprises can set up an always-available communication backbone by migrating their digital landscape to the cloud. This can facilitate seamless data exchange and storage. Moreover, it can enable the development of new telemedicine and telehealth applications to be accessed from anywhere and easily scalable when demand is high.

Improved Security and Compliance

Medical records and other patient data are perhaps the most sensitive personal credentials any organization will deal with from a customer perspective. So, there absolutely cannot be any compromise on data security measures to prevent any data thefts.

Today, the cloud offers more robust security measures than the commonly used in-house data protection mechanisms. In fact, studies show that 60% of enterprise leaders believe that security is a significant cloud-specific advantage.

In a Nutshell

The healthcare sector is entering an era of the digital-first mode of service, as seen in several other industries. The lessons learned from the rapid adoption of cloud due to the pandemic are a welcome sign of moving to a future where nearly all healthcare innovations will be centered around cloud infrastructure.

This is where healthcare organizations need access to expert guidance and practical advice on how to select and implement the perfect cloud roadmap for their digital systems.

Connect with us to know more.

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Introduction

As per the recent research, by 2025, around 50% of healthcare organizations will implement some kind of artificial intelligence into their operations globally. In the US alone, McKinsey estimates that leveraging these technologies in the pharmaceutical industry will generate $100B annually.
AI and ML are being leveraged for R&D and drug discovery in the industry, and they will continue to gain traction as digital transformation capabilities are accelerating globally.

CVS Pharmacy, for example, uses Machine Learning personalization to increase prescription refill rates and reduce gaps in treatment. Furthermore, a start-up from Toronto, Canada is able to scan more than a hundred thousand media sources in over 65 different languages every single day with their application “BlueDot” that helps them to predict dangerous disease outbreaks. ML has also helped identify protein fragments, allowing vaccine development for Covid-19 at a record pace. Artificial intelligence and machine learning are already finding their ways and usage in healthcare to have a huge impact in battling covid-19 and saving human lives.

The healthcare industry can be classified overall into the following 5 sectors, each of which can benefit greatly from AI/ML.

• Healthcare providers and facilities like hospitals, surgery centers, nursing homes, or doctors and physicians
• Medical equipment like diagnostic equipment, orthopedic devices, medical instruments
• Distributors and wholesalers, like pharmacies, distributors of equipment to healthcare providers
• Health insurance and managed care
• Pharma, life sciences, and biotechnology

Healthcare software development companies are developing solutions in order to enable organizations involved in the manufacture and distribution of drugs to use technologies that allow greater efficiency, better outcomes in the patients, and overall patient safety by trying to predict reactions between certain types of drugs. This blog will discuss a few trendy use cases that integrate some form of these technologies, and what is the future for these use cases.

Combatting Deficit in Drug Availability using Machine Learning

As seen in the recent pandemic, life-saving prescription drugs can fall short on availability and fail to meet the demand. To be able to combat this, custom healthcare software development companies develop solutions that leverage machine learning techniques such as linear regression to predict the shortage of drugs on the basis of the current supply trend.

If drug availability is nearing shortage, drug distributors can be intimated. The leadership can make decisions around sourcing the medicines elsewhere, or provide alternatives to the drug. The custom healthcare software solution can be configured to suggest alternative drugs using algorithms that find drugs with the same or similar components.

Tracking Inventory to avoid Drug Diversion and Pharmaceutical Logistics

Similar to availability, there is an ongoing problem of drugs being “diverted” to other non-intended places of use, arising from theft by internal staff members. There are significant risks of illegally sourcing drugs in this manner, aside from the shortage resulting from it, as intimated by CDC. This can be averted by using custom healthcare software solutions that leverage machine learning techniques such as data matching. Drug diversion cannot easily go undetected when such a solution is in place. Furthermore, uality control, material waste reduction, improved production reuse, and predictive maintenance are all possible with AI. Machine learning can assist in forecasting and preventing over- and under-demand, as well as resolving supply chain issues and production line breakdowns.

Predicting Patient Adherence

Based on historical data, the adherence level of a patient can be calculated to predict the likelihood of patients, especially chronic patients, to pick up their prescription drugs. Furthermore, based on such solutions, intervention protocols by the healthcare provider can be set up depending on the risk of ill effects of non-adherence on the patient.

Repurposing Existing Drugs

Artificial Intelligence has great potential to be able to identify drug compounds and their effects on pathogens. Machine learning techniques use supervised learning algorithms, which use historical data to predict future effects. This can be useful in swiftly finding drugs with compounds that can be effective against new threats.

Automated Drug Prescription

If a healthcare provider is able to identify symptoms in a patient and feed those into a system leveraging machine learning techniques, supervised ML algorithms can automatically prescribe the drugs in a prescription signed by the healthcare provider. This can be integrated into telemedicine solutions, where during the consultations the healthcare provider can identify and feed the symptom information into the custom healthcare software solution.

Clinical Trials

By enhancing sample screening processes for clinical trials, AI can affect the future of pharmaceuticals. AI can help ensure trial adoption by swiftly evaluating patients and determining the best prospects for a given trial. Additionally, the technology aids in the removal of samples that may obstruct clinical trials, reducing the need to compensate for those factors with a large trial group.

Global healthcare leaders have gained tangible insights from the pandemic, and how to avert the situations it posed in front of us. This includes averting unforeseen developments in the pharmaceutical industry operations. As per the use cases mentioned above, among a plethora of others, it is important to find avenues to leverage AI/ML techniques for life-saving operations, based on the problems identified during the pandemic and other healthcare crises. If your organization has faced problems similar to the above, leverage the expertise of a custom healthcare software development provider

Pratiti Technologies has been providing custom healthcare solutions using technologies such as IoT, machine learning, cloud, and edge to solve problems such as the above. It is important to delegate discrete technology implementation to a technology partner with tangible and proven industry experience. Contact us today to begin your digital transformation journey.

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Data Analytics Solutions | Healthcare Software Development | Cloud Computing Services Providers | Edge Computing Platform

Introduction

DevOps is a term that is often misunderstood. DevOps is strengthening its foothold in software product development companies across the globe and it is imperative that the digital product companies in the IT industry understand what it means.

While some people think that DevOps is only a collaboration of ‘development’ and ‘operations’, the term really refers to the system and processes that are put into practice to increase team collaboration in any type of business, large or small. There are many myths surrounding DevOps.

As an expert digital product development company and drawing from our DevOps expertise, through this blog we want to debunk a few of the common myths about DevOps such as

• Is DevOps a tool?
• Does it require a team?
• Is it useful only for the cloud?
• Is it only for developers?

and more…

Myth 1: DevOps Requires Agile

DevOps and Agile are not synonyms. Agile development is a methodology of software delivery, incrementally applied in its creation, while DevOps enables faster software delivery. DevOps refers not only to a delivery method but to an entire culture. Adopting DevOps results in multiple benefits for businesses.

DevOps can help complement and augment agile development, but it is in no way not dependent on it and can support various work methodologies such as:

• Waterfall – To accelerate and optimize construction processes and implement automation.
• Agile – To provide greater communication between development and operations.
• Hybrid approach – To improve speed, quality, and compliance.

Complete adoption of the DevOps philosophy is necessary for obtaining optimal results.

Glimpse – DevOps in Healthcare: The Implementation & Key Benefits!

Myth 2: You Can’t have DevOps without Cloud

When many people think of DevOps they think of the cloud. And, there is a good reason for this. Cloud technology provides the ability to dynamically provision infrastructure resources for developers and testers to rapidly obtain test environments without waiting for a manual request to be fulfilled.

That does not mean the cloud is necessary to adopt DevOps practices, though. If an organization has efficient processes for obtaining resources to deploy and test application changes, it can very well adopt a DevOps approach.

Myth 4: DevOps is a software

The DevOps methodology consists of communication, collaboration, and automation of development (engineering) and operations functions and, as described in Myth 3, is required to be adopted by the entire organization to obtain optimal results. The adoption of DevOps can be greatly facilitated by software.

This doesn’t mean that DevOps is software though. Purchasing the software or tools that facilitate DevOps does not mean that DevOps is software. Harnessing the enablers’ full potential is required for optimized results using this methodology.

DevOps is in a nutshell – a philosophy that allows companies to automate their processes and do more collaborative work to achieve a common goal and deliver the software faster.

Myth 5: DevOps will Make the Traditional IT Roles Redundant

If you use DevOps, you will become database architects, cybersecurity specialists, and cloud engineers overnight is another common myth. Instead, DevOps culture breaks down traditional silos between development (engineering), operations, networking, security, and quality assurance teams to deliver continuous value to all the internal and external stakeholders.

Redress misconceptions about IT roles with transparency across teams through collaboration and communication. Hold managers and senior team members accountable to set the example for their organizations. Leadership involvement plays a critical role in debunking this myth.

Myth 6: DevOps Doesn’t Work for Large, Complex Systems

This myth is totally off the radar. DevOps does not work for large and complex systems is similar to believing the Earth is flat.

The opposite of this is actually true: complex systems often require the discipline and collaboration that DevOps provides. Large systems typically have multiple software or hardware components, each, with its own delivery cycles and timelines. DevOps facilitates better coordination of these delivery cycles and release planning.

Myth 7: It is Exclusive to Native Internet Companies

DevOps term became popular among companies such as Netflix, Flickr, and Etsy, whose operations are based on the internet. These companies are some of the pioneers of what is recognized popularly as the DevOps movement.

However, software technology enterprises and corporations have been applying similar principles to deliver software for years, possibly decades, without even being aware of the DevOps movement.

DevOps and its applications are hence not limited to native internet companies.

Myth 8: DevOps Requires Teams’ Physical Proximity

If you still have this misconception after months of lockdown, you need to burst the bubble immediately.

Lockdown has already proven that DevOps works just as efficiently remotely, even more. A common misconception is that teams must be co-located for DevOps collaboration to work. Some managers still think the staff must be in the same room to work together as a team.

However, remote workers, third-party contractors, and cloud service providers play increasingly significant roles in the delivery lifecycle. With the right tools and frameworks to support communication and collaboration along the DevOps lifecycle, efficient results can be achieved. Collaboration is about continuous improvement.

All team members need to know that from day one.

Must Read – Challenges when scaling DevOps in the Enterprise!

Myth 9: DevOps is Only for Continuous Delivery

DevOps does not mean continuous delivery. The purpose of adopting a DevOps culture is to increase the frequency of deliveries in the organization, from a specific interval to daily deployment, thereby improving responsiveness to market changes.

Although continuous delivery is largely dependent on automation and targeted at agile and lean thinking organizations, DevOps does not rely on a shared culture that promotes collaboration.

Myth 10: Soft Skills Aren’t Necessary

Another common DevOps myth is that soft skills, such as diplomacy, empathy, and oral communications, aren’t necessary. Developers and operations along with other stakeholders must all bury their hatchets to become integral collaborators in software delivery and services.

To overcome this, organizations need to add team communications to onboarding processes. For a larger organization, the HR department can easily offer soft skills training for employees. However, the challenge with such courses is finding time for developers to take them.

While adopting DevOps, it is imperative to leverage a subject matter’s expertise for efficient adoption. Organizations just starting with this methodology need to give it some time to track and monitor the efficiency of the results.

Leveraging the expertise of a software product development company specialized in DevOps still remains one of the easiest, most efficient, and easy the pockets option. We, at Pratiti Technologies, have an expert team, specialized in DevOps that can help you with your software deliveries efficiently and quickly. To know more about our capabilities, please contact us today.

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