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aita-alternia · 8 months

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aita for Eating a bee and blaming it on my coworker?

i [12 indigo] am an apicultural engineedler for [a Large company name redacted]. we Provide a live software service so realtime support and updates are very Important. recently, a concentrated Effort has been made to port our old and Exceedingly convoluted network onto a new beehouse mainframework to comply with silicomb 2.0 standards and drag our Very tangled Very old codebase into the present decasweep. it has been a lot of effort over almost a full sweep, but the new mainframe is beautiful and well worth the time and will make it much easier to debug and re-bug the network going forward.

due to our service being live, our small team of developunishers were required to supervise the migration of our bees between mainframe overday, which we turned into a little Shindig since if all went well there wouldn't be much to do once Everything was underway. one of my coworkers [14 violet] who I will call aparna for this story brought faygo for us to celebrate with [she is Not a practicing juggalo but she still talks about growing up in the church All The Time. it is frankly Quite grating. we do not need to hear again about how you chose your paint aparna you do not actually paint anymore i fail to see how it is presently Relevant. and she Always seems to talk about it louder when she notices im listening]

anyway it was getting close to migration time and Most of my coworkers were there. we opened bottles of soda and began to prep the signal drones. [not like Her Imperious Condescension's drones, these are apicultural beenary signallers that serve signposts for the queen for the interframe migration. basically Her Smaller Majesty the Hive Queen Who Makes Our Code Work needs to know where to go to get to the new mainframe but we can't move her there directly since she's too vicious to be handled directly. instead we move the drones who we can manually override and she follows them into the new beehome.] this step of the process is Usually pretty smooth. the Most difficult part is usually when the queen moves and the Entire hive follows her; the multithreading can be somewhat difficult to manage and if the beestreams begin to cross over too much, they can jam the entrances to the new beehome, causing the formation to collapse and potentially bringing down the network. that's why we have to supervise the migration closely.

however. a Mistake was made. and it was made early.

at some point during setup one of the signal drones was knocked loose of its designated position. i do not know how this happened [but it's probably aparna's fault. she is always making these kinds of very Small mistakes. never anything Severe but little things. annoying things. many of them.] this is usually easy to correct except that it went unnoticed and, drawn by some instinct of insects Everywhere, found its way into my soda.

which i then drank.

i could tell the bee was in there right away, but my instinctive self defense reaction was to swallow and crush whatever was buzzing in my mouth with my Powerful esophageal muscles. so that is what I did. the signal drone died Swiftly in my throat. i was safe from the Threat of its sting - and we were down an essential component for the migration

i Panicked. i turned my head and frantically coughed up the signal drone, passing it off as the soda going down the wrong pipe. this dislodged the signal drone into my hand. i knew that if i were caught it would Not go well for me. if i got in Trouble at this job my lusus might start trying to push me toward the cavalreapers again. i could not let that happen.

then i noticed that someone's soda was open on the table next to me.

i invite you to guess what i did next. i also invite you to guess whose drink it happened to be.

it took some time for the absence of the signal drone to be noticed, but eventually aparna took a drink of her faygo and spat it out along with the body of the drone. it was Very clear what had happened and she took the blame for the subsequent Disaster of having to emergency patch the signal formation, as well as the debugging required to fix the resulting path collisions during the Full migration.

aparna will be fine. our boss likes her Very much overall and is Extremely unlikely to get rid of her [i would likely have come forward by now if i had done this to Any other coworker, but aparna is in no danger and Also she deserves it for being careless and Also it was probably her who knocked the drone out of formation to begin with], whereas i would Very likely have been fired had they known it was actually my fault. however i am concerned that aparna may be on to me. she has been glaring at me even More than usual for the past few days. i have glared back as i will Not be Cowed by a juggalo - and a lapsed one at that. she'll have to do better than an annoyance if she wants anything out of me.

so. am i the Asshole?

#OK^^^^^^Y THIS IS SO MUCH #THIS IS MY F^VORITE SUBMISSION EVER IM PRINTING IT OUT ^ND FR^MING IT ON MY W^LL #LITER^LLY I DONT C^RE IF THIS IS OBJECTIVELY ^ BULGE MOVE . WE ^LL DO CR^ZY THINGS IN THE N^ME OF PITCH FLIRTING #<- I ME^N WH^T WHO S^ID TH^T #am i the asshole

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sallingwinkler85 · 8 months

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Syspro Erp Software Program Erp Enterprise System Erp Solutions

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factmrlokesh · 9 days

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Fleet Maintenance Software Market Projected to Reach US$ 30.9 Billion by 2032, Growing at a CAGR of 9.2%

Over the projected period of 2022 to 2032, the fleet maintenance software market is expected to develop at an amazing CAGR of 9.2%. The market share of fleet maintenance software is expected to grow from US$ 11.6 billion in 2021 to around US$ 30.9 billion by 2032.

On a digital model, fleet maintenance software facilitates the owner's tracking and repair of the fleet. Fleet maintenance software adoption is essential in today's logistics and transport industry due to the growing complexity of maintaining a record of preventative maintenance services, repairs, work orders, inventory management, gas station, personnel deployment, availability of vendors, and other crucial details.

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In the rapidly evolving field of fleet management, effectiveness, security, and conformity are critical elements. Software for fleet maintenance has become a potent instrument for streamlining processes, enhancing car performance, and guaranteeing legal compliance. This article explores the ever-changing fleet maintenance software market, highlighting major trends, evolution, and the game-changing effects it has on fleet management.

Competitive Landscape:

It is possible to develop fleet management software internally or obtain it from a third-party service provider; the cost and level of complexity of these programs vary greatly. Basic functionality is added, and fleet management software is connected to fleet maintenance software.

The trend of adopting fleet maintenance software started in the 1970s on what were then mainframe computers. By the 1980s, however, personal computers, or PCs, were the primary focus of the leading players in the fleet maintenance software market.

AI, or artificial intelligence, is another cutting-edge technology that is being extensively used with a wide range of solutions and improving customer experiences for various operations and enterprises. AI integration with solutions to boost efficiency and deliver quick insights has become a lucrative business strategy for certain new major companies in the fleet maintenance software market. This is increasingly being acknowledged as a positive acceptance in a number of fleet management market share domains, such as manufacturing, construction, logistics, and transportation.

The Development of Software for Fleet Maintenance:

The days of maintaining records by hand and creating maintenance schedules on paper are long gone. Fleet management software, which offers real-time insights into vehicle health, maintenance schedules, and compliance needs, has completely changed the way fleets are handled. In order to enable preventive maintenance and maximize fleet performance, what started out as simple software for tracking maintenance activities has developed into sophisticated platforms that interface with telematics systems, predictive analytics, and IoT sensors.

Growth catalysts and market dynamics:

The market for fleet maintenance software is expanding quickly due to a number of factors. Fleet maintenance software is becoming more and more popular in sectors including construction, public utilities, transportation, and logistics as a result of the growing complexity of fleet operations and the desire to cut costs. Furthermore, fleet managers are in greater need of software solutions that help them efficiently track and manage maintenance tasks, vehicle inspections, and emissions compliance due to the increased focus on safety, sustainability, and regulatory compliance.

Important Market Trends:

There are several trends influencing how the fleet maintenance software market develops. Predictive maintenance skills that foresee equipment problems and improve maintenance schedules are made possible by the integration of AI and machine learning algorithms into maintenance software, which is one noteworthy trend. This proactive strategy lowers maintenance costs, increases asset longevity, and minimizes downtime. Furthermore, fleet managers can now access maintenance data and insights from any location with the growing popularity of cloud-based solutions and mobile applications, which makes remote monitoring and decision-making easier.

Key Companies Profiled:

Geotab

Automotive Rentals Inc.

Omnitracs

Teletrac Navman

Trimble

Verizon Connect

Wheels Inc.

Mix Telematics

Chevin Fleet Solution

Donlen Corporation among others.

Opportunities and Difficulties in the Market:

The Fleet Maintenance Software Market is experiencing expansion, but it is also facing obstacles such opposition to changing from conventional fleet management procedures, interoperability problems, and data security concerns. But these difficulties also offer chances for uniqueness in the market and creativity. Software vendors can address these issues and seize new market opportunities by utilizing cutting-edge technologies like blockchain for safe data management, creating open APIs for smooth system integration, and offering user-friendly interfaces and training courses.

Prospects for the Future:

The market for fleet maintenance software seems to have a bright future. Advanced fleet maintenance software is predicted to become more and more in demand as fleet operations continue to be digitalized, electric and autonomous vehicles become more common, and sustainability and regulatory compliance become more important. Additionally, software providers have a chance to provide cutting-edge solutions that leverage the strength of big data analytics, IoT, and AI to deliver actionable insights and promote ongoing fleet operations improvement as fleets grow more networked and data-driven.

Key Segments:

By Fleet Type :

Passenger Car

Commercial Fleets

By Component :

Solution

Services

By Region :

North America

Latin America

Europe

Asia Pacific

Middle East and Africa (MEA)

To sum up, the market for fleet maintenance software is essential to facilitating fleet management's effectiveness, safety, and compliance. Fleet maintenance software gives fleet managers the real-time visibility they need to make informed decisions, reduce downtime, and maximize asset utilization. It also provides information on vehicle health, maintenance requirements, and regulatory compliance requirements. Fleet Maintenance Software Market participants can spur innovation and influence fleet management in the digital era by embracing market trends, tackling obstacles, and utilizing emerging technology.

#marketinsights #markettrends #researchreport

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roamnook · 15 days

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Google Cloud enables digital transformations with cutting-edge solutions in industries like Retail, Finance, and Healthcare. Harness AI, multicloud capabilities, and global infrastructure to tackle your toughest challenges. Explore now.

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Bringing New, Polarizing, and Informative Facts to the Table

Google Cloud

Google Cloud is a leading provider of cloud computing services that can help businesses solve their toughest challenges. With a focus on digital transformation, Google Cloud offers a wide range of solutions to accelerate business growth and drive innovation.

Key Benefits of Google Cloud:

Why Google Cloud - Top reasons businesses choose Google Cloud

AI and ML - Enterprise-ready AI capabilities

Multicloud - Run your applications wherever you need them

Global infrastructure - Build on the same infrastructure as Google

Data Cloud - Make smarter decisions with unified data

Open cloud - Scale with open, flexible technology

Security - Protect your users, data, and apps

Productivity and collaboration - Connect your teams with AI-powered apps

Reports and Insights:

Executive insights - Curated C-suite perspectives

Analyst reports - What industry analysts say about Google Cloud

Whitepapers - Browse and download popular whitepapers

Customer stories - Explore case studies and videos

Solutions

Google Cloud offers industry-specific solutions to reduce costs, increase operational agility, and capture new market opportunities. Whether you're in the retail, consumer packaged goods, financial services, healthcare and life sciences, media and entertainment, telecommunications, gaming, manufacturing, supply chain and logistics, government, or education industry, Google Cloud has tailored solutions for your digital transformation needs.

Not seeing what you're looking for?

See all industry solutions

Application Modernization:

CAMP Program - Improve your software delivery capabilities

Modernize Traditional Applications - Analyze and migrate traditional workloads to the cloud

Migrate from PaaS: Cloud Foundry, Openshift - Tools for moving existing containers to Google's managed container services

Migrate from Mainframe - Tools and guidance for migrating mainframe apps to the cloud

Modernize Software Delivery - Best practices for software supply chain and CI/CD

DevOps Best Practices - Processes and resources for implementing DevOps

SRE Principles - Tools and resources for adopting Site Reliability Engineering

Day 2 Operations for GKE - Tools and guidance for effective GKE management and monitoring

FinOps and Optimization of GKE - Best practices for running cost-effective applications on GKE

Run Applications at the Edge - Guidance for localized and low-latency apps on Google's edge solution

Architect for Multicloud - Manage workloads across multiple clouds with a consistent platform

Go Serverless - Fully managed environment for developing, deploying, and scaling apps

Artificial Intelligence:

Contact Center AI - AI model for speaking with customers and assisting human agents

Document AI - Automated document processing and data capture

Product Discovery - Google-quality search and product recommendations for retailers

APIs and Applications:

New Business Channels Using APIs - Attract and empower an ecosystem of developers and partners

Unlocking Legacy Applications Using APIs - Cloud services for extending and modernizing legacy apps

Open Banking APIx - Simplify and accelerate secure delivery of open banking compliant APIs

Databases:

Database Migration - Guides and tools to simplify your database migration life cycle

Database Modernization - Upgrades to modernize your operational database infrastructure

Databases for Games - Build global, live games with Google Cloud databases

Google Cloud Databases - Database services to migrate, manage, and modernize data

Migrate Oracle workloads to Google Cloud - Rehost, replatform, rewrite your Oracle workloads

Open Source Databases - Fully managed open source databases with enterprise-grade support

SQL Server on Google Cloud - Options for running SQL Server virtual machines on Google Cloud

Data Cloud:

Databases Solutions - Migrate and manage enterprise data with fully managed data services

Smart Analytics Solutions - Generate instant insights from data at any scale

AI Solutions - Add intelligence and efficiency to your business with AI and machine learning

Data Cloud for ISVs - Innovate, optimize, and amplify your SaaS applications using Google's data and machine learning solutions

Data Cloud Alliance - Ensure global businesses have seamless access and insights into the data required for digital transformation

Digital Transformation

Google Cloud helps businesses accelerate their recovery and ensure a better future through solutions that enable hybrid and multi-cloud environments, generate intelligent insights, and keep workers connected. Whether you want to reimagine your operations, optimize costs, or adapt to the challenges presented by COVID-19, Google Cloud has solutions for you.

Areas of Focus:

Digital Innovation - Reimagine your operations and unlock new opportunities

Operational Efficiency - Prioritize investments and optimize costs

COVID-19 Solutions - Get work done more safely and securely

COVID-19 Solutions for the Healthcare Industry - How Google is helping healthcare meet extraordinary challenges

Infrastructure Modernization - Migrate quickly with solutions for SAP, VMware, Windows, Oracle, and other workloads

Application Migration - Discovery and analysis tools for moving to the cloud

SAP on Google Cloud - Certifications for running SAP applications and SAP HANA

High Performance Computing - Compute, storage, and networking options to support any workload

Windows on Google Cloud - Tools and partners for running Windows workloads

Data Center Migration - Solutions for migrating VMs, apps, databases, and more

Active Assist - Automatic cloud resource optimization and increased security

Virtual Desktops - Remote work solutions for desktops and applications (VDI & DaaS)

Rapid Migration Program (RaMP) - End-to-end migration program to simplify your path to the cloud

Backup and Disaster Recovery - Ensure business continuity needs are met

Red Hat on Google Cloud - Enterprise-grade platform for traditional on-prem and custom applications

Productivity and Collaboration

Google Workspace offers a suite of collaboration and productivity tools designed for enterprises. Whether you need collaboration tools, secure video meetings, cloud identity management, browser and device management, or enterprise search solutions, Google Workspace has you covered.

Productivity and Collaboration Solutions:

Google Workspace - Collaboration and productivity tools for enterprises

Google Workspace Essentials - Secure video meetings and modern collaboration for teams

Cloud Identity - Unified platform for IT admins to manage user devices and apps

Chrome Enterprise - ChromeOS, Chrome Browser, and Chrome devices built for business

Cloud Search - Enterprise search for quickly finding company information

Security

Google Cloud provides advanced security solutions to detect, investigate, and respond to online threats. With security analytics and operations, web app and API protection, risk and compliance automation, software supply chain security, and more, Google Cloud helps protect your business from cyber threats.

Security Solutions:

Security Analytics and Operations - Solution for analyzing petabytes of security telemetry

Web App and API Protection - Threat and fraud protection for web applications and APIs

Security and Resilience Framework - Solutions for each phase of the security and resilience life cycle

Risk and compliance as code (RCaC) - Solution to modernize your governance, risk, and compliance function with automation

Software Supply Chain Security - Solution for improving end-to-end software supply chain security

Security Foundation - Recommended products to help achieve a strong security posture

Smart Analytics

Google Cloud's smart analytics solutions enable organizations to generate instant insights from data at any scale. With data warehousing, data lake modernization, Spark integration, stream analytics, business intelligence, data science, marketing analytics, geospatial analytics, and access to various datasets, Google Cloud provides the foundation for data-driven decision making.

Smart Analytics Solutions:

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ashu-digiroads-01 · 1 month

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Navigating the Evolution of Data Centers: Tracing the Past, Present, and Future Trends in the Data Center Market

In the digital age, where data is the new currency, the significance of data centers cannot be overstated. These facilities serve as the backbone of the digital infrastructure, enabling the storage, processing, and dissemination of vast amounts of information that power our modern world. Over the years, data centers have undergone a remarkable evolution, driven by technological advancements, changing business needs, and environmental considerations. Let's embark on a journey through the past, present, and future of data centers, exploring key trends and developments shaping the Data Center Market.

The Past: Foundation Stones of Data Centers

The roots of data centers can be traced back to the mid-20th century when early computer systems required dedicated spaces for housing mainframes and other computing equipment. These rudimentary facilities were characterized by large physical footprints, basic cooling systems, and limited scalability. However, with the proliferation of computing technologies and the emergence of the internet, the demand for more sophisticated data infrastructure grew exponentially.

During the late 20th and early 21st centuries, the advent of virtualization, cloud computing, and e-commerce fueled the rapid expansion of data center facilities. Traditional enterprise-owned data centers gave way to colocation facilities and cloud service providers, marking a significant shift in the industry landscape. This period witnessed a focus on improving energy efficiency, reliability, and scalability, laying the groundwork for the data center innovations that would follow.

The Present: Innovations and Optimization

In the present day, data centers have evolved into highly efficient, scalable, and resilient facilities, catering to the diverse needs of businesses across industries. Key trends shaping the current Data Center Market include:

Hyperconvergence: The convergence of computing, storage, and networking resources within a single integrated system has gained traction, offering simplified management, scalability, and cost savings.

Edge Computing: With the proliferation of IoT devices and the need for real-time processing, edge computing has emerged as a critical trend. Edge data centers bring computing closer to the source of data generation, reducing latency and improving performance for applications like autonomous vehicles, smart cities, and industrial automation.

Renewable Energy Adoption: In response to growing concerns about environmental sustainability, data center operators are increasingly investing in renewable energy sources such as solar and wind power. This shift towards green data centers not only reduces carbon emissions but also helps mitigate long-term operational costs.

AI and Automation: Artificial intelligence (AI) and machine learning are being leveraged to optimize data center operations, predict equipment failures, and enhance energy efficiency. Automation tools enable proactive maintenance, capacity planning, and resource allocation, streamlining workflows and reducing human intervention.

The Future: Anticipating Trends and Challenges

Looking ahead, the Data Center Market is poised for further evolution, driven by emerging technologies and evolving business requirements. Some key trends and challenges that are likely to shape the future of data centers include:

5G and IoT Expansion: The rollout of 5G networks and the proliferation of IoT devices will fuel the demand for edge computing infrastructure, necessitating the deployment of smaller, more distributed data centers at the network edge.

Hybrid and Multi-Cloud Adoption: Organizations are increasingly embracing hybrid and multi-cloud strategies to leverage the flexibility and scalability offered by public cloud providers while maintaining control over sensitive data and workloads. This trend will drive the need for interconnected data center ecosystems that seamlessly integrate with cloud platforms.

Data Sovereignty and Compliance: As data privacy regulations become more stringent globally, organizations must navigate complex compliance requirements related to data residency and sovereignty. Data center providers will need to offer solutions that ensure compliance with regulations such as GDPR, CCPA, and HIPAA, while also providing robust security measures to protect sensitive data.

Sustainability and Energy Efficiency: The quest for sustainability will continue to drive innovation in data center design and operations. From adopting advanced cooling technologies to implementing energy-efficient hardware and renewable energy sources, data center operators will prioritize environmentally responsible practices to minimize their carbon footprint.

Conclusion

The evolution of data centers has been marked by a relentless pursuit of efficiency, scalability, and reliability. From humble beginnings as basic computer rooms to the sophisticated, interconnected facilities of today, data centers have become indispensable assets in the digital economy. As we chart a course towards the future, the Data Center Market will continue to innovate and adapt to meet the evolving needs of businesses and society at large, ensuring that data remains accessible, secure, and sustainable in the years to come.

#data center market

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standardprinters12 · 4 months

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Different Types Of Computers! – Standard Print Infotech

Computers and laptops have become a crucial part of every individual’s life because all of us are highly dependent on them. The Computer On Rent In Mumbai is offering everyone excellent quality and a wide range of computers at economical prices. Today, in this article, we are going to shed some light on different types of computers.

Different Types Of Computers

Personal Computers (PCs): These are the most common type of computers used by individuals. Personal computers include desktops, laptops, and workstations. They are designed for general computing tasks, such as browsing, word processing, and entertainment.

Desktop Computers: These are standalone computers designed to be placed on a desk. They consist of a separate monitor, keyboard, and mouse connected to a central processing unit (CPU) that houses the main components.

Laptops: Laptops are portable computers with an integrated screen, keyboard, and touchpad or pointing device. They are suitable for users who need mobility and can be used in various environments.

Workstations: Workstations are high-performance computers designed for specialized tasks such as graphics design, video editing, and scientific applications. They typically have advanced processors and graphics capabilities.

Servers: Servers are computers designed to manage network resources and provide services to other computers in a network. They can handle tasks such as file storage, email, and web hosting. Servers are often located in data centers.

Mainframes: Mainframes are powerful computers that can handle large-scale processing and manage extensive databases. They are commonly used in enterprise-level applications, including financial transactions and large-scale data processing.

Supercomputers: Supercomputers are the most powerful computers, capable of performing complex calculations and simulations at extremely high speeds. They are used for scientific research, weather forecasting, and other computationally intensive tasks.

Embedded Computers: Embedded computers are integrated into other devices and systems, performing specific functions within those devices. Examples include the computer systems in cars, household appliances, and industrial machinery.

Smartphones and Tablets: Smartphones and tablets are portable computing devices that combine the features of a computer with communication capabilities. They are designed for mobile use and often run on operating systems like iOS or Android.

If you or anyone you might know is looking for a Laptop On Rent in Mumbai, then you don’t have to worry about anything at all because Standard Print Infotech is the destination for you.

About Standard Print Infotech

Standard Print Infotech is one of the leading names for offering a wide range of computer accessories. The team of professionals working with them never compromises with the standards and always ensures that everything is done according to the needs of the client.

Credit:- https://penzu.com/p/0c5c073d52e0436f

#Computer On Rent In Mumbai #Laptop On Rent in Mumbai

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jcmarchi · 4 months

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Ioan Iacob, Founder & CEO at FLOWX.ai – Interview Series

New Post has been published on https://thedigitalinsider.com/ioan-iacob-founder-ceo-at-flowx-ai-interview-series/

Ioan Iacob, Founder & CEO at FLOWX.ai – Interview Series

Ioan Jacob, is the founder and CEO of FLOWX.AI, a revolutionary AI Application Modernization Platform for enterprise mission-critical applications. It is a modern event-driven platform built on a microservices architecture. It uses the most popular industry standards for process modeling, business rule management and integrates as easily with legacy systems as with the latest APIs and RPAs.

What initially attracted you to computer science?

I’ve always been captivated by the concept of leverage—the idea of force multiplication. Computer science, to me, represents the ultimate tool in amplifying the most valuable capability of people: the human mind.

It offers an incredibly rapid path from idea to realization—a trait that has propelled the exponential surge in innovation over the last 50 years. This power of rapid transformation and impact is what initially drew me to computer science.

Now, with FLOWX.AI, we’re redefining how mission-critical software can be built—which means we have an opportunity to boost the growth curve itself. Our world runs on enterprise software – banking, utilities, agriculture, defense – enterprise software undergirds our civilization. And there’s so much leverage to bringing the best technology to the enterprise, because that impacts so many lives downstream, and this is why we think we can be so helpful to the world. Today we’re spending trillions of dollars to build, run and maintain that layer of technology.

So, think about it: what if we could make building enterprise software orders of magnitude more efficient?

This would enhance vital services like banking, utilities, or defense—making them more interconnected, user-friendly, and more efficient for people to use. And, maybe even more importantly, with the resources freed up we could considerably accelerate the pace of innovation.

Imagine, for example, a world where government agencies can quickly develop and deploy advanced AI systems to streamline public services, improve healthcare delivery, and address pressing social issues. By optimizing enterprise software development, we can unlock a new era of technological progress and societal advancement.

We’re not just part of the tech revolution; we’re redefining its boundaries of what’s possible.

You previously Co-Founded Qualitance, a platform that designed technology and products for Fortune 500 companies and startups. What was one of the more interesting projects that you worked on, and what did you learn from this experience?

We were involved in a range of digital transformation projects at Qualitance with both Fortune 500 companies and startups.

This experience brought us to a crucial realization. Despite the rapid evolution in consumer digital products and substantial investments by large corporations, there was a massive gap in building and taking digital solutions to market, especially in mission-critical and core business areas like banking.

This challenge was (and still is) especially pronounced in the financial sector, but is equally prevalent across all enterprise sectors.

We understood the need for digital transformation platforms to provide capabilities on three key dimensions that are today challenging the enterprise:

Integration – it needs to be able to integrate seamlessly with existing complex technology landscapes – from heritage mainframe architectures to modern systems

Rapid modern digital product development – being able to respond to market needs and regulatory requirements in almost real-time. There is tremendous competition and the IT and business teams need to build modern digital products that provide excellent user experience quickly and cost effectively,

Robustness – reliability, scalability, security: because enterprises handle mission critical workloads, these are non-negotiable requirements.

These observations are at the core of building FLOWX.AI. Our focus is on empowering large enterprises to quickly and efficiently develop and modernize digital platforms, while integrating seamlessly capabilities of any existing or new systems.

When did you first realize that the current methods of software development are broken and not scalable?

Complexity in the enterprise world has increased exponentially, and so have costs and the time it takes to get products to market.

This is what I’ve experienced working alongside many talented teams in the enterprise world for more than a decade. I have seen how being able to develop robust and good software remains incredibly expensive—despite the access to amazing talent and the proliferation of technologies designed to solve the problem.

Before FLOWX.AI, the only options for developing digital in the enterprise were either inflexible vertical solutions or massive custom development projects trying to blend together multiple technology platforms.

As a result, teams in the enterprise world are constrained by lack of flexibility to build what they need and are limited by proprietary programming languages and legacy systems. This, coupled with the increase in complexity, is holding the most talented teams back. These teams get sucked into tedious and low-return work that barely, marginally moves the needle. Spiraling IT costs along with diminishing returns is one of the toughest challenges enterprises face. This was particularly evident within large financial services organizations.

I can’t emphasize enough how frustrating this is for everyone in the space. It’s depressing for engineers who have to do tedious and unexciting work. It’s keeping business leaders back because they can’t provide their customers with the intuitive, scalable, and connected services they need. So this is what we responded to. We had been working side by side with these people. In fact, we had been these people throughout our careers. So we really understood them and we wanted to fix this problem, to give them back the control of their technology, of their business.

What was the genesis story behind FLOWX.AI?

We had been working on the platform that ultimately became FLOWX.AI for over a decade. We had this massive feeling that we’re sitting on something incredibly powerful, but we couldn’t quite put our finger on it.

Then, during a meeting with Revolut’s team in London, it hit us. When we learned that Revolut’s business was built on top of Barclays core banking system, we realized that we had on our hands a platform that could enable any bank to develop robust and beautiful mission-critical systems at a speed that was orders of magnitude higher.

Then, our first customer, the largest bank in Southeastern Europe, adopted our technology and started using it as their default digital development platform for a large part of their business— building digital platforms that were facing both customers and employees—from the entire in-branch onboarding for both retail and corporate banking to asset management platforms. Witnessing the speed at which they were able to develop confirmed we were indeed on the verge of a new revolution. With the same team and existing systems, they were able to develop in several weeks what used to take a year or more with FLOWX.AI.

Our innovation is the FlowX AI Core, enabled by a scalable, robust, and open architecture. Our AI Core is the first-ever enterprise AI that can cohesively model technology, business processes and business rules, and user experience. We have been big believers for a long time now in the power of AI to augment and accelerate human potential, and we have brought it to fruition within the core of our platform.

What are some of the current problems with how enterprises are currently viewing code generation?

The challenge with automated code generation is the perception that it is—or that it should be—universally applicable, especially in handling complex systems. While effective for simpler applications, it often falls short in more sophisticated environments. This isn’t just a limitation of the technology itself but stems from the intricacies in creating detailed specifications that such systems require. Automated tools, unlike human engineers, lack the nuanced understanding necessary to bridge and fill in specification gaps, adjust complex logic, and manage deep integration and decision-making processes.

Moreover, there’s a risk in underestimating the value of human input and expertise. Although automation can speed up certain development processes, it hasn’t yet evolved to fully grasp and manage the complexities of advanced systems.

At FLOWX.AI, we have taken a slightly different path. Our approach leverages AI to enhance, not replace, human expertise. We focus on using AI to augment human capabilities, ensuring that the development of complex systems is not just accelerated but also precisely tailored to specific business requirements. This strategy aims to strike a balance, harnessing the speed and efficiency of AI with a “human-in-the-loop” approach, retaining the critical insights and adaptability of human oversight.

Why is replacing coding with no-code or low-code tools not the solution?

The limitations of no-code tools stem from their inherent simplicity which, while user-friendly, fail to meet the specific and complex needs of large-scale enterprises. Low-code also lacks the full power and control of the widespread programming languages—and further, it creates a resourcing constraint, having to find or upskill resources. And what businesses need is the freedom and flexibility to build and innovate. This is why we brought together generative AI with no-code visual design on an open BYOC architecture which can be extended with any programming language.

However, the focus of digital product development goes beyond coding. It encompasses the creation of efficient processes, intuitive products, and seamless user experiences. This holistic approach is vital in addressing the multifaceted challenges of enterprise solution development.

FLOWX.AI was built to meet the end-to-end needs of building digital twins for enterprise businesses. We don’t just focus on coding; we leverage the power of AI to assist in accelerating building complex, bespoke enterprise solutions that consider all aspects of the digital product development lifecycle.

Could you share your views on the benefits of creating a hybrid of low-code and coding?

Creating a hybrid of low-code and coding is very powerful because it offers a unique blend of efficiency, flexibility, and customization. It provides speed, while still enabling complete control over what people build.

This is part of what we offer. Our approach integrates AI, no-code, and coding techniques to build comprehensive digital solutions. I can break this down into four main areas:

AI-Generated Baseline: Today, the FlowX AI can generate around 60% to 80% of the development process. This AI layer speeds up the creation of fundamental components—process, code, user experience—significantly, reducing initial development time.

No-Code Visual Development: With visual design interfaces, we allow for quick assembly and modification of applications, enabling rapid prototyping and accelerated iterative development loops. This usually takes completion to 90-95%.

Bring-Your-Own-Code (BYOC) for Customization: The remaining bits, which require specific and detailed customizations, are handled through traditional coding BYOC in any programming language. This allows for the creation of highly tailored solutions, ensuring that the final product meets the exact needs and specifications of the customer.

AI-Assisted Development and Optimization: our AI helps enterprise teams maintain consistency over time as they modify and update functionality and experience, but also suggests improvements—from technology to process and user experience—and monitors and identifies problems in real-time.

The key advantage of this hybrid approach can be seen especially when it comes to making changes and maintaining the software. Teams developing on FlowX.ai can add in just a few weeks new functionality that would typically take years to add to an existing system. That is because we provide features that help users easily make modifications and because our platform encapsulates most of the complexity, handling non-functional requirements such as scalability and security. As a result, any code that needs to be created or modified lies in more isolated components, providing for more control and testability. This setup makes it easier to change, track and audit changes, but also to test things – leading to a massive reduction in effort and maintenance.

Ultimately, combining AI, no-code, and traditional coding, balances speed and ease of use with the ability to create highly customized and complex enterprise solutions because it blends the speed of gen AI with the accessibility of visual design and the full power and control of programming languages.

More importantly, this approach frees up engineers from a lot of tedious tasks and ongoing maintenance, so innovation doesn’t stall.

How will AI augment engineers versus replacing them?

Our belief is AI can not and will not replace engineers, it will augment their capabilities. The fundamental human element in engineering involves sophisticated thinking and problem-solving, areas where human intellect and creativity are irreplaceable. AI is adept at handling about 80% of tasks, particularly those that are repetitive or considered low-value. AI excels at efficiently processing routine work with speed and accuracy, ultimately enabling them to focus on higher-level problems and innovative solutions.

This is a net-positive for engineers. The key moving forward is to figure out how to create a synergistic relationship where each complements the other, leading to a more productive and innovative engineering environment. This approach underscores a future where AI and human intelligence work in tandem, each playing to their strengths to achieve greater outcomes in the field of engineering and beyond.

Can you discuss the innovative application modernization platform that FLOWX.AI has developed?

FLOWX.AI is the first ever unified platform for end-to-end enterprise digital development, with an open architecture that makes it easy to develop and extend further – with any programming language.

At the core of the platform there is an intelligent orchestration layer that can integrate fast any – literally any type – of existing system, through the intelligent integration layer. On top of the orchestration layer teams can develop modern digital products again very fast – through our AI-powered omnichannel user experience layer,

As I mentioned previously, FLOWX.AI brings together AI-assisted development, low-code / no-code as well as full coding capabilities. This combination provides enterprises with a flexible, scalable and robust platform they can use to build and take applications to market.

We built FLOWX.AI in response to lack of innovation in application development. Traditional methods are often too rigid and cost prohibitive. No-code solutions, while promising in theory, have frequently fallen short in meeting the specific and complex demands of modern enterprises. Vertical point solutions are inflexible and hard to customize and develop further – they’re not designed for continuous development.

Our customers are achieving remarkable results. For instance, many of our customers can integrate around 20 systems in just 4-6 weeks and develop, build, and launch complex digital solutions like digital mortgages within 8 to 12 weeks.

Why is this solution able to scale so well?

FLOWX.AI is built on a state-of-the-art, elastically-scalable, event-driven architecture, which relies on microservices and containerization. The use of microservices architecture further enhances scalability by allowing for the independent scaling and updating of different parts of the application without disrupting the entire system.

This fully cloud-native framework ensures agility, resilience, and scalability, crucial for handling the dynamic demands of enterprise-level digital product development. It is also an infrastructure-agnostic architecture, which can be deployed in any cloud / multi-cloud / hybrid cloud setup or on-prem.

It also provides high availability and fault tolerant deployment setups, which are vital for maintaining uninterrupted service in mission-critical applications.

The combination of microservices and containerization in an open architecture positions FLOWX.AI as an ideal platform for enterprises looking to innovate rapidly while maintaining high standards of reliability and security. This architecture not only supports the current technological needs of enterprises but also positions them to effortlessly adapt to future advancements and challenges in the digital landscape.

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maintec · 9 months

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mainframe managed service providers offer a range of benefits to organizations that rely on mainframe computing infrastructure. These benefits can help improve operational efficiency, reduce costs, enhance security, and enable organizations to focus on their core business objectives.

#managed mainframe services #mainframe managed service providers #mainframe maintenance service providers in us #mainframe services

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govindhtech · 5 months

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Mainframe Apps Revolutionized Through Generative AI Magic

Using generative AI to modernize mainframe apps

If you take a closer look at any well-designed mobile application or business interface, you will probably discover mainframes operating underneath the integration and service layers of any significant enterprise’s application architecture.

As part of a hybrid infrastructure, these fundamental systems are used by critical applications and systems of record. The business’s ability to maintain its operational integrity might be severely jeopardized by any disruption to its current operations. So much so that many businesses are reluctant to alter them significantly.

But change is unavoidable, since technological debt is mounting up. Businesses must upgrade these apps in order to achieve company agility, meet consumer demand, and stay competitive. Leaders should look for innovative methods to speed up digital transformation in their hybrid strategy rather than putting it off.

COBOL is not to responsible for modernization delays

The shortage of skills is perhaps the largest barrier to mainframe modernization. Many of the mainframe and application specialists who throughout the years have built and extended business COBOL codebases are probably retired or have moved on.

Even more concerning, it will be difficult to get talent from this next generation since graduates of computer science programs that emphasize Java and other modern languages would not automatically think of themselves as mainframe application developers. They may not find the task as exciting or agile as cloud native programming or mobile app design. In many respects, this is a really unfair bias.

Long before object orientation, much alone cloud computing or service orientation, existed, COBOL was developed. It shouldn’t be a difficult language for less experienced developers to learn and comprehend since it has a small collection of instructions. Furthermore, there is no reason why agile development and more frequent, smaller releases inside an automated pipeline akin to DevOps wouldn’t be advantageous for mainframe programs.

Change management is particularly challenging when one has to figure out what various teams have done with COBOL throughout the years. An limitless number of components and logical loops have been added by developers to a procedural system that has to be updated and tested as a whole, not as individual parts or loosely connected services.

Interdependencies and possible points of failure are too complicated and many for even experienced developers to go through when code and applications are weaved together on the mainframe in this way. Because of this, developing COBOL apps might seem more difficult than necessary, leading many businesses to search for solutions outside of the mainframe before they should.

Overcoming generative AI’s constraints

Due to the increasing availability of consumer-grade visual AI picture generators and large language models (LLMs) like ChatGPT, generative artificial intelligence, or GenAI, has been the subject of several hypes recently.

Even though there are a lot of exciting new possibilities in this field, there is a persistent “hallucination factor” with LLMs when used in crucial business processes. Artificial intelligence (AI) systems that have been trained on online material often provide results that are somewhat correct but nonetheless persuasive and credible.

For example, ChatGPT recently used fictitious case law precedents in a federal court;

The indolent attorney who utilized it may face consequences. Putting your faith in an AI chatbot to write business application code raises comparable concerns. While a generic LLM may make fair general ideas for how to develop an app or simply churn out a standard registration form or build an asteroids-style game, the functional integrity of a business application relies greatly on the machine learning data the AI model was trained with.

Thankfully, production-focused AI research was underway long before ChatGPT made its debut. As the creator and pioneer of the mainframe, IBM has been developing deep learning and inference models under the watsonx brand. They have also developed observational GenAI models that have been trained and adjusted on COBOL-to-Java transition.

Their most recent IBM Watsonx Code Assistant for Z solution speeds up the modernization of mainframe applications by combining generative AI with rules-based workflows. Development teams may now rely on a very useful and enterprise-focused application of automation and GenAI to help with auto-refactoring, application discovery, and COBOL-to-Java conversion.

Three approaches to modernizing mainframe applications

Organizations should elevate mainframe programs to the level of top features in the continuous delivery pipeline so that they are as flexible and adaptable to change as any other distributed or object-oriented application.

Through three phases,

IBM Watsonx Code Assistant for Z assists developers in integrating COBOL code into the application modernization lifecycle:

1.Finding Developers: must determine which areas need care before updating. The method begins by listing every program on the mainframe and creating architecture flow diagrams that include all of the data inputs and outputs for each application. The visual flow model makes it simpler for developers and architects to detect dependencies and evident dead ends within the code base.

2.Refactoring: The main goal of this phase is to disassemble monoliths into more palatable forms. IBM Watsonx Code Assistant for Z searches through extensive program code bases to determine the system’s intended business logic. The method refactors the COBOL code into modular business service components by eliminating the connection between instructions and data, such as discrete operations.

3.Transformation: This is where an LLM optimized for corporate COBOL-to-Java translation may work its magic. The GenAI approach converts Java classes from COBOL program components, enabling real object orientation and concern separation to support agile, concurrent development by many teams. The AI then provides look-ahead ideas, much like a co-pilot feature you might find in other development tools, so developers can concentrate on improving Java code in an IDE.

The Intellyx perspective

As most vendor promises regarding AI are really automation under a different name, they tend to be wary about them.

Gaining proficiency in the syntax and structures of languages like COBOL and Java appears to be more in line with GenAI’s interests than studying every detail of the English language and conjecturing about the veracity of words and paragraphs.

The world’s most resource-constrained firms may save money and effort on modernization with the help of generative AI models created specifically for businesses, such as IBM Watsonx Code Assistant for Z. Recursive AI models such as IBM Watsonx Code Assistant for Z find perfect training grounds in applications on well-known platforms with thousands of lines of code.

GenAI can assist teams overcome modernization obstacles and enhance the skills of even more recent mainframe developers to create major advances in agility and resilience on top of their most important core business applications, even in circumstances with limited resources.

Read more on Govindhtech.com

#MainframeApps #GenerativeAI #COBOL #ChatGPT #LLM #AImodel #IBMWatsonx #Java #technews #technology #govindhtech

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aryacollegeofengineering · 5 months

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How Much Do You Really Know About Different Types of Cloud Computing

How many types of cloud computing

It can be shared that resources, software, and information are provided to computers and other devices on demand, like the electricity grid.

Best Private Engineering College in Rajasthan have many courses for Cloud computing It is a paradigm shift following the shift from mainframe to client-server in the early 1980s and Details are abstracted from the users, who no longer need expertise in, or control over, the technology infrastructure "in the cloud" that supports them.

It is Internet-based computing where virtual shared servers provide software, infrastructure, platform, devices, and other resources and hosting to customers on a pay-as-you-use basis and All information that a digitized system has to offer is provided as a service in the cloud computing model also users can access these services available on the "Internet cloud" without having any previous know-how on managing the resources involved

ARCHITECTURE:- It involves multiple cloud components communicating with each other over application programming interfaces, usually web services

CLOUD COMPUTING SAMPLE ARCHITECTURE: - UNIX philosophy of having multiple programs each doing one thing well and working together over universal interfaces Complexity is controlled and the most significant components of cloud computing architecture are known as the front end and the back end.

Types Of Cloud Computing

PUBLIC CLOUD: It allows systems and services to be easily accessible to the general public and Public cloud may be less secure because of its openness, e.g., e-mail also Public clouds are made available to the general public by a service provider who hosts the cloud infrastructure so Generally, public cloud providers like Amazon AWS, Microsoft and Google own and operate the infrastructure and offer access over the Internet also with this model, customers have no visibility or control over where the infrastructure is located.

PRIVATE CLOUD: It allows systems and services to be accessible within an organization and It offers increased security because of its private nature also Private cloud is cloud infrastructure dedicated to a particular organization so Private clouds allow businesses to host applications in the cloud while addressing concerns regarding data security and control, which is often lacking in a public cloud environment also It is not shared with other organizations, whether managed internally or by a third party, and it can be hosted internally or externally

HYBRID CLOUD: It is a mixture of public and private clouds. However, the critical activities are performed using a private cloud while the non-critical activities are performed using a public cloud Hybrid Clouds are a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together offering the advantages of multiple deployment models and In a hybrid cloud, you can leverage third-party cloud providers in either a full or partial manner; increasing the flexibility of computing so Augmenting a traditional private cloud with the resources of a public cloud can be used to manage any unexpected surges in workload

COMMUNITY CLOUD: Systems and services to be accessible by a group of organizations.

COMPONENTS SaaS (software as a service): SaaS refers to software that’s made available as a web-based service.

Utility computing: It allows access to storage and virtual servers on demand.

Cloud-based web services: It allows you to offer services online, such as credit card processing services, employee payroll processing, or viewing an interactive map.

MSP (managed service providers): It delivers applications to IT instead of end-users.

IaaS (infrastructure as a service): It refers to computer infrastructure (e.g., virtualization) that’s delivered as a service

ADVANTAGES OF CLOUD COMPUTING

Flexibility: High rate of flexibility.

Low Cost: With this companies can save big by employing cloud computing as it eliminates the cost of hardware and software.

Speed & Scales: Buying and configuring hardware and software are time-consuming.

Easier Management of Data and Information: All data are centralized, and data are more organized, making it easy to manage.

Device Diversity: Our applications and data anywhere in the world, on any system

Increased Storage Capacity: It is another benefit of cloud computing, as it can store more data as compared to a personal computer.

Easy to Learn and Understand: It is used for cloud applications like Gmail, and Google Docs, so anything related to the same is most likely to be understood by the users.

Automatic Updating: Time and effort to update multiples server.

Customize Setting: It allows you to customize your business applications

CONCLUSION

Top Engineering College in Jaipur says While cloud computing is really great and you’re probably already using it, either for business or for personal means Cloud computing is a cheap way for companies to have all the resources they need in one place, also It’s a much better way to spread your resources, and it becomes easier to access things from longer distances also it is very useful for companies.

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#best btech college in jaipur #best engineering college in jaipur #best btech college in rajasthan #best private engineering college in jaipur #top engineering college in jaipur #best engineering college in rajasthan

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factmrlokesh · 1 month

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Fleet Maintenance Software Market Set for Remarkable Growth, Expected to Surpass US$ 30.9 Billion by 2032 at 9.2% CAGR

𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝗮 𝗦𝗮𝗺𝗽𝗹𝗲 𝗖𝗼𝗽𝘆 𝗢𝗳 𝗥𝗲𝗽𝗼𝗿𝘁:

𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲:

The Development of Software for Fleet Maintenance:

Growth catalysts and market dynamics:

Important Market Trends:

𝗞𝗲𝘆 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗣𝗿𝗼𝗳𝗶𝗹𝗲𝗱:

Geotab

Automotive Rentals Inc.

Omnitracs

Teletrac Navman

Trimble

Verizon Connect

Wheels Inc.

Mix Telematics

Chevin Fleet Solution

Donlen Corporation among others.

Opportunities and Difficulties in the Market:

𝗥𝗲𝗮𝗱 𝗠𝗼𝗿𝗲:

Prospects for the Future:

Key Segments:

By Fleet Type :

Passenger Car

Commercial Fleets

By Component :

Solution

Services

By Region :

North America

Latin America

Europe

Asia Pacific

Middle East and Africa (MEA)

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shristisahu · 5 months

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Mastering Cloud Evolution: Strategies for Unleashing Business Agility

Originally Published on: QuantzigCloud Migration Strategies for Maximized Cost Savings

Revolutionizing Operational Excellence Through Tech Platform Engineering and Connected Propositions

In the ever-evolving realm of technology, the imperative adoption of cloud migration strategies takes center stage for businesses striving to achieve unparalleled agility and scalability. At the forefront is the Tech Platform Engineering approach, orchestrating meticulous cloud migration processes tailored to businesses of diverse sizes and intricacies. Anchored in intricate planning, this approach encompasses migration strategies that thoroughly evaluate the existing environment against cloud server prerequisites. A pivotal element is Application Performance Management (APM), ensuring seamless visibility and optimal performance across public, private, hybrid, or multicloud environments.

Tech Platform Engineering and Connected Propositions play an increasingly indispensable role in adapting to the dynamic landscape of public cloud platforms such as Google, Azure, and AWS. The focus on applications and data migration, coupled with addressing security concerns and ensuring data backup and recovery, lays a robust foundation for a triumphant cloud migration process. Establishing a pre-migration performance baseline facilitates more effective measurement of post-move success.

This article delves into the transformative influence of Tech Platform Engineering, shedding light on how it strategically deploys cloud migration strategies to optimize business operations. The exploration encompasses a deep dive into the cloud migration process, incorporating the Six R’s of migration – rehosting, replatforming, repurchasing, refactoring, retiring, and retaining – and their profound impact on tech platform optimization. Join us in this enlightening journey to understand how Tech Platform Engineering shapes our digital realm, empowering businesses to adapt and thrive in an interconnected world.

#CloudExcellenceOdyssey

Importance of Platform Engineering & Connected Propositions: Navigating Cloud Migration

At the heart of platform engineering lies the ability to establish agile and scalable infrastructures, indispensable in today's cloud-centric milieu. As businesses immerse themselves in interconnected ecosystems, cloud migration strategies such as rehosting, replatforming, and refactoring assume a pivotal role. From the straightforward 'lift-and-shift' approach to the more intricate re-architecting, these strategies empower businesses to optimize their applications for cloud environments on Google, Azure, or AWS.

In this swiftly evolving tech landscape, possessing a clear cloud migration roadmap is imperative. Businesses must navigate the spectrum of complexity, ranging from virtualized architectures to service-oriented and monolithic mainframe systems. By embracing suitable cloud migration strategies, companies can traverse from low to high complexity environments, leveraging cloud-native features for enhanced performance and agility.

Insights from Stephen Orban underscore the significance of portfolio discovery and planning in the migration process. The '5 R’s' approach – Rehosting, Replatforming, Repurchasing, Refactoring, and Retiring – provides a structured method for effective application migration management. This approach aids in identifying applications suitable for rehosting or 'lift-and-shift,' those requiring replatforming or optimization, and those primed for repurchasing on a new SaaS platform like Salesforce.com or Workday. While refactoring is intricate, it empowers businesses to fully exploit cloud-native features, transitioning from monolithic architectures to more flexible service-oriented or server-less architectures.

#StrategicCloudNavigation

Challenges in a lack of Cloud Migration Solutions

The absence of effective platform engineering begets significant migration challenges, especially in the transition to cloud environments. Without a well-structured cloud migration process, businesses grapple with issues such as data loss, downtime, and resource management difficulties. These challenges are exacerbated in intricate migrations involving public, private, hybrid, or multicloud environments.

Ensuring a seamless application migration to cloud providers like Google, Azure, or AWS stands out as a critical challenge. This necessitates meticulous planning and testing to circumvent potential downtime and data loss. IT professionals need to instill trust in the migration process by ensuring interoperability between old and new systems while managing resource allocation efficiently.

Moreover, businesses often contend with a lack of visibility into their cloud environment, a vital aspect for maintaining application performance management (APM) post-migration. Establishing a baseline premigration performance and consistently monitoring post-move success are often overlooked yet crucial steps. Leveraging tools like Business iQ allows businesses to track hosting costs, agility, scalability, and other pivotal metrics post-migration.

In conclusion, navigating the challenges of cloud migration mandates a strategic approach encompassing comprehensive planning, testing, and resourcing. The selection of the right APM provider instills confidence in the process, ensuring a seamless transition to the cloud.

#CloudMigrationChallenges

Key Benefits of Implementing Platform Engineering: Cloud Migration

The implementation of platform engineering unfolds a plethora of benefits, particularly in the context of cloud migration strategies. Embracing the Six R’s of Migration – Rehosting, Replatforming, Repurchasing, Refactoring, Retiring, and Retaining – empowers businesses to optimize their cloud migration process, harmonizing operational needs with strategic goals.

One of the primary benefits is the transition to an elastic infrastructure, promising substantial cost savings and heightened agility. By transitioning to cloud environments like Google, Azure, or AWS, businesses witness reduced infrastructure footprints, enhanced disaster recovery, and fortified security measures.

Moreover, platform engineering paves the way for a smoother application migration to the cloud, guaranteeing minimal downtime and data loss. It equips IT professionals to adeptly manage resources, garnering the trust of stakeholders by ensuring a seamless transition. Coupled with the right cloud provider and a well-executed migration strategy, businesses can surmount common challenges associated with cloud migration.

In summary, platform engineering offers an elastic infrastructure, cost savings, improved agility, and heightened security, positioning it as a pivotal component of successful cloud migration strategies.

#CloudMigrationAdvantages

What Do Our Platform Engineering Solution and Connected Propositions Offer?

Our platform engineering solution, meticulously designed for cloud migration, presents a comprehensive and strategic approach to the migration process. We hone in on the Cloud Migration Roadmap, tailoring our approach to the size and complexity of the migration. Our fundamental steps encompass planning, selecting the right migration strategy, comprehending the current environment, and delineating cloud server requirements.

The solution places a strong emphasis on Application Performance Management (APM) to uphold visibility in the cloud environment, be it public, hybrid, private, or multicloud. We extend support for migrations to major cloud providers like Google, Azure, and AWS, ensuring the secure and efficient migration of apps and data. Our solution addresses common security concerns and integrates data backup and recovery strategies.

Implementation of the Six R’s of Migration – Rehosting, Replatforming, Repurchasing, Refactoring, Retiring, and Retaining – allows us to provide a tailored approach to each migration scenario. These strategies span from basic 'lift-and-shift' (rehosting) to more intricate processes such as refactoring for cloud-native features.

Our platform engineering ensures that post-migration, businesses can gauge success through tools like Business iQ. We aid in establishing baseline premigration performance and continuously monitoring post-move success, guaranteeing the realization of benefits such as elastic infrastructure, optimized hosting costs, agility, and scalability.

In conclusion, our platform engineering solution for cloud migration is all-encompassing, addressing every facet of the migration process. It ensures businesses migrate efficiently and securely to the cloud, leveraging the benefits of cloud computing to achieve operational and strategic business goals.

#HolisticCloudMigration

Conclusion: Pioneering Cloud Migration Strategies for the Future

In today’s swiftly evolving technological landscape, platform engineering and connected propositions emerge as linchpins for businesses aiming to optimize their cloud migration strategies. These approaches lay a robust foundation for transitioning to cloud environments, adeptly handling the intricacies of planning, migration, and post-migration management.

Platform engineering, especially in the context of cloud migration, unfurls substantial advantages. It guarantees seamless transitions to cloud environments like Google Cloud, Azure, or AWS, minimizing disruption and maximizing efficiency. On the flip side, connected propositions bring coherence to this process, ensuring alignment of every facet of migration, from security to application performance management, with the overarching goals of the business.

In essence, embracing platform engineering and connected propositions transcends mere technology leverage; it embodies a transformation in the way businesses operate and compete in a cloud-first world. It’s a strategic maneuver that empowers organizations to fully harness the expansive potential of cloud computing, steering innovation, efficiency, and growth.

#StrategicCloudAdoption

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marketresearchreportsandanalysis · 5 months

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Navigating Cloud Migration: A Comprehensive Approach through Platform Engineering

Originally published by Quantzig: Cloud Migration Strategies for Maximized Cost Savings

Introduction:

Exploring Cloud Migration Strategies for Optimized Business Operations

In the dynamic landscape of technological advancement, cloud migration strategies have become indispensable for businesses seeking agility and scalability. At the forefront of this transformation is the Tech Platform Engineering approach, driving the implementation of meticulous cloud migration processes that cater to diverse business sizes and complexities. Anchored in careful planning, this approach scrutinizes the current environment against cloud server requirements, with a focus on Application Performance Management (APM) to ensure seamless performance in various cloud environments.

Tech Platform Engineering, coupled with Connected Propositions, plays a crucial role in adapting to the evolving landscape of public cloud platforms such as Google, Azure, and AWS. This article delves into the transformative power of Tech Platform Engineering, highlighting how it leverages cloud migration strategies to optimize business operations. We will explore the cloud migration process, including the Six R’s of migration – rehosting, replatforming, repurchasing, refactoring, retiring, and retaining – and their impact on tech platform optimization. Join us on this journey to understand how Tech Platform Engineering shapes our digital existence, enabling businesses to adapt and thrive in an interconnected world.

Importance of Platform Engineering & Connected Propositions:

The essence of platform engineering lies in its ability to create agile and scalable infrastructures, crucial in today’s cloud-centric world. As businesses engage in interconnected ecosystems, cloud migration strategies such as rehosting, replatforming, and refactoring play a significant role. These strategies allow businesses to optimize their applications for cloud environments, be it on Google, Azure, or AWS.

In this rapidly evolving tech landscape, a clear cloud migration roadmap is imperative. Businesses must consider the spectrum of complexity, ranging from virtualized architectures to service-oriented and monolithic mainframe systems. By adopting suitable cloud migration strategies, companies can navigate from low-complexity to high-complexity environments, leveraging cloud-native features for enhanced performance and agility.

Stephen Orban’s insights on cloud migration emphasize the importance of portfolio discovery and planning in the migration process. The ‘5 R’s’ approach – Rehosting, Replatforming, Repurchasing, Refactoring, and Retiring – offers a structured method to manage application migration effectively. This approach helps in identifying which applications to rehost or ‘lift-and-shift’, which to replatform or optimize, and which to repurchase on a new SaaS platform like Salesforce.com or Workday. Refactoring, although complex, enables businesses to fully harness cloud-native features, moving from monolithic architectures to more flexible service-oriented or server-less architectures.

Challenges in the Absence of Cloud Migration Solutions:

The absence of effective platform engineering leads to significant migration challenges, especially when transitioning to cloud environments. Without a well-structured cloud migration process, businesses face issues such as data loss, downtime, and difficulties in resource management. These challenges are exacerbated in complex migrations involving public, private, hybrid, or multicloud environments.

One of the critical challenges is ensuring smooth application migration to cloud providers like Google, Azure, or AWS. This requires careful planning and testing to avoid potential downtime and data loss. IT professionals need to establish trust in the migration process by ensuring interoperability between old and new systems and managing resource allocation efficiently.

Moreover, businesses often struggle with visibility into their cloud environment, which is essential for maintaining application performance management (APM) post-migration. Establishing a baseline pre-migration performance and continuously monitoring post-move success are crucial steps often overlooked. Businesses should utilize tools like Business iQ to keep track of hosting costs, agility, scalability, and other vital metrics post-migration.

In conclusion, navigating the challenges of cloud migration requires a strategic approach that includes comprehensive planning, testing, and resourcing. Selecting the right APM provider can instill confidence in the process, ensuring a successful transition to the cloud.

Key Benefits of Implementing Platform Engineering:

Implementing platform engineering provides a host of benefits, particularly in the context of cloud migration strategies. By adopting the Six R’s of Migration – Rehosting, Replatforming, Repurchasing, Refactoring, Retiring, and Retaining – businesses can optimize their cloud migration process, balancing operational needs with strategic goals.

One of the main benefits is the transition to an elastic infrastructure, which offers significant cost savings and enhanced agility. By moving to cloud environments like Google, Azure, or AWS, businesses can experience decreased infrastructure footprints, improved disaster recovery, and enhanced security measures.

Moreover, platform engineering facilitates a smoother application migration to the cloud, ensuring minimal downtime and data loss. It enables IT professionals to efficiently manage resources and gain the trust of stakeholders by ensuring a smooth transition. With the right cloud provider and a well-executed migration strategy, businesses can overcome the common challenges of cloud migration.

In summary, platform engineering offers elastic infrastructure, cost savings, improved agility, and enhanced security, making it a critical component of successful cloud migration strategies.

What Do Our Platform Engineering Solution and Connected Propositions Offer?

Our platform engineering solution, designed for cloud migration, offers a comprehensive and strategic approach to the migration process. We focus on the Cloud Migration Roadmap, which addresses the size and complexity of the migration. Our basic steps include

Connect with us for tailor-made solutions

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universalinfo · 7 months

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The Evolution of Cloud Computing: A Comprehensive Overview

In today’s fast-paced digital world, cloud computing has emerged as a transformative force that is reshaping the way businesses operate and individuals access technology. The evolution of cloud computing has been a remarkable journey, one that has revolutionized the IT industry and changed the way we think about computing. In this comprehensive overview, we will delve into the fascinating history and key milestones of this computing, from its inception to the present day, and explore the driving forces behind its evolution.

Chapter 1: The Birth of Cloud Computing

To truly understand the evolution of cloud computing, we must start at the beginning. This chapter will take you back to the early days of computing, tracing the roots of cloud computing to mainframes and timesharing systems. We will explore how the need for shared resources and cost-efficient computing solutions laid the foundation for what we now know as the cloud.

Chapter 2: The Rise of Virtualization

Virtualization was a game-changer in the world of computing. This chapter will explain how virtualization technologies paved the way for the cloud by enabling multiple virtual machines to run on a single physical server. The advent of virtualization brought scalability and flexibility to computing resources, setting the stage for computing’s rapid ascent.

Chapter 3: The Emergence of Service Models

In this chapter, we will explore the evolution of cloud service models, from Infrastructure as a Service (IaaS) to Platform as a Service (PaaS) and Software as a Service (SaaS). Each service model brought its own set of benefits, allowing businesses to choose the level of control and management they needed from the cloud.

Chapter 4: Cloud Providers and the Competitive Landscape

The cloud computing landscape has evolved with the rise of major cloud providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). This chapter will discuss how these providers have shaped the industry and fueled the growth of computing services, offering a diverse range of offerings to cater to different business needs.

Chapter 5: Cloud Security and Compliance

As cloud adoption surged, concerns about security and compliance grew in tandem. This chapter will delve into the evolution of cloud security measures and the role of compliance standards in ensuring data protection and regulatory adherence in the cloud.

Chapter 6: The Era of Hybrid and Multi-Cloud

Hybrid and multi-cloud environments have become the new norm. This chapter will explain how businesses are leveraging multiple cloud providers and on-premises infrastructure to optimize their operations, achieve greater flexibility, and reduce risk.

Chapter 7: Cloud-Native Technologies and DevOps

Cloud-native technologies and DevOps practices have redefined application development and deployment. This chapter will explore how containers, microservices, and serverless computing have become integral to modern computing strategies with Corporate Info Management.

Chapter 8: The Future of Cloud Computing

In our final chapter, we’ll gaze into the crystal ball and discuss the future of cloud computing. Topics will include edge computing, quantum computing, and the continued evolution of AI and machine learning in the cloud.

Conclusion:

The evolution of cloud computing is a testament to the relentless innovation and adaptability of the IT industry. From its humble beginnings to its current ubiquity, cloud computing has transformed the way we work, play, and connect. As we look ahead to the future, one thing is clear: the cloud will continue to evolve, bringing even greater possibilities and opportunities for businesses and individuals alike. Stay tuned for the next chapter in this ever-evolving technological journey.

#Corporate Info Management #cloud computing

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theconnectiq · 7 months

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