Latest news with #EC2
India Today
30-07-2025
- Business
- India Today
Amazon Web Services adds 6 free tech training courses for learners
Amazon Web Services (AWS) has launched six free online courses for 2025. The objective is simple: to help students and professionals learn new skills in areas like cloud computing, data, and artificial intelligence (AI).These courses are open to anyone and can be accessed online. No prior experience is needed, just a willingness to learn.1. Machine Learning Plan Covers basics of machine learning, including model training, data workflows, and AI security. Prepares learners for the AWS Certified Machine Learning -- Specialty Getting Started with DevOps on AWSA short 60-minute course that introduces DevOps culture, tools, and best practices for beginners.3. AWS Cloud Quest: Cloud PractitionerA beginner-friendly, game-based course where learners build cloud solutions using AWS tools like EC2, S3, and VPC. Earn a digital badge upon completion.4. Machine Learning Terminology and ProcessA one-hour course that explains basic ML concepts in simple language—ideal for those starting with AI.5. Data Analytics Learning PlanFocuses on building secure and scalable data analytics systems. Helps learners turn raw data into real-world insights.6. DevOps Engineer Learning PlanOffers lessons in version control, infrastructure automation, and software deployment. Designed for those aiming for or transitioning into DevOps six courses aim to give learners a chance to build practical knowledge at no content is designed to support both students looking for their first job and working professionals hoping to shift today's job market, where technology is changing fast, many are looking for ways to stay free courses by AWS may help people take the first step toward that goal, by learning at their own pace, from home, without paying for expensive classes.- Ends
Time of India
30-07-2025
- Business
- Time of India
Amazon is offering free tech courses for students and professionals: Here are 6 you can start now
If you're a student thinking ahead or a professional pivoting into cloud, AI, or analytics, 's newest learning lineup might just make your upskilling plans a lot smoother, and cheaper. Tired of too many ads? go ad free now In 2025, Amazon Web Services (AWS) has rolled out six free tech courses and learning plans that blend foundational theory with hands-on experience, all accessible online. Here's a closer look at what's on offer: AWS Cloud Quest: Cloud Practitioner This gamified course is a beginner-friendly gateway into cloud computing. Build real-world cloud solutions in a simulated environment, earn a digital badge, and get familiar with AWS services like EC2, VPC, and S3. Great for students kickstarting a tech career or professionals making their first cloud move. Best for: Absolute beginners and career explorers. Machine Learning Learning Plan A comprehensive path designed for data scientists and developers looking to integrate AI into their work. This plan covers essentials like model training, data science workflows, and security in ML. You'll even work on Amazon SageMaker-based object detection models. Bonus: It preps you for the AWS Certified Machine Learning – Specialty exam. Recommended for: ML/AI aspirants aiming for serious credentials Data Analytics Learning Plan For those fascinated by what numbers reveal, this course offers a deep dive into building secure, scalable analytics solutions. It's tailored for developers, data engineers, and analysts aiming to translate raw data into real-world insights. This free course is perfect for students in data-focused degrees and early-career analysts DevOps Engineer Learning Plan This is your toolkit if you're eyeing a DevOps role or want to understand CI/CD pipelines better. Tired of too many ads? go ad free now The modules cover version control, infrastructure as code, automation, and cloud-based deployment strategies. This course is ideal for developers and operations professionals who are transitioning into DevOps roles. Getting Started with DevOps on AWS Short on time? This 60-minute course introduces the basics of DevOps culture, practices, and tools. Learn how AWS helps teams deploy secure applications faster, improve time-to-market, and keep risks in check. Curious techies with just an hour to spare Machine Learning Terminology and Process Confused by ML jargon? This one-hour course simplifies the machine learning process and breaks down commonly used techniques. It's ideal for those who want to understand how machine learning projects come together — minus the math headache. This course is worth exploring if you're a developer dipping your toes into AI. Whether you're hunting for your first job or switching lanes mid-career, these free resources could be the bridge between ambition and expertise. You don't need prior experience. Just curiosity, commitment, and maybe a decent Wi-Fi connection. TOI Education is on WhatsApp now. Follow us .
Time Business News
27-07-2025
- Time Business News
Beyond Lift-and-Shift: Building Cloud-Native Architectures That Scale
It's easy to assume that once your workloads are in the cloud, the hard part is over. In most cases, it's not. Yes, you've moved things off physical servers. You're no longer managing hardware. Maybe you're even using some managed services. But the actual software? That's probably the same tightly wound legacy system it's always been. A lift-and-shift approach—while useful in the short term—doesn't address how your systems work. It just changes where they run. Let's be honest. If your application couldn't scale properly before, running it on EC2 or a managed VM won't magically fix that. You've avoided some infrastructure pain, but the underlying design still drags. That's why 'modernizing' through migration alone rarely holds up. Moving to the cloud should be more than a logistical upgrade. It needs to be an architectural shift. Otherwise, you're just relocating tech debt. This is where cloud-native architecture becomes more than a term you hear at conferences. It's the practical path to building systems that work with the cloud instead of simply sitting on it. It means building for elasticity, not just uptime. Designing for failure, not assuming things won't break. And most of all, it means creating modular systems that evolve quickly, recover gracefully, and scale as needed—without a war room every time traffic spikes. In this post, we'll look at what true cloud-native maturity looks like, how to tell if you're on the right path, and why cloud-native architecture is quickly becoming a baseline—not a bonus. It's common to hear the word modernization tossed around in cloud conversations. In many cases, what people mean is replatforming—maybe they've moved a few databases to managed services or containerized a legacy application to make deployments smoother. These are improvements, no doubt, but they only scratch the surface. The trouble is, these changes don't touch the core structure of how applications are built. You can wrap a monolith in a container, move it to a virtual machine in the cloud, and still end up with the same limitations you had on-prem. If scaling requires a full redeployment or rolling back a release involves days of QA, you're not really modernized. You're just hosting old code in a newer environment. This is the shortfall many organizations don't see until much later. They invest time and resources in migration, but remain constrained by fragile codebases, tightly coupled services, and long deployment cycles. These challenges don't go away until the architecture is reimagined with a cloud-native development service that enables modular design, scalability, and faster innovation by default. A shift to cloud-native architecture doesn't happen overnight. It's a layered process, with technical and cultural milestones along the way. Think of it less as a switch and more as a staircase—each step building on the last. Stage 1: Lift-and-Shift This is where most journeys begin. Applications are moved from on-premise environments to cloud infrastructure, typically with minimal modification. It's fast and cost-effective, but largely operational. There's little or no impact on scalability, resilience, or speed of change. Stage 2: Replatforming and Container Adoption As teams get more comfortable in the cloud, they begin exploring managed services. Databases are migrated to platform-native options, and legacy applications might be containerized to simplify deployment. Containerization at this stage helps reduce environment inconsistencies and enables more predictable builds and releases. But containers alone don't modernize the application. They package what's already there. Without rearchitecting, the code inside the container remains as inflexible as before. Stage 3: Service Decomposition This is where momentum shifts. Organizations begin breaking apart large applications into independently deployable services. Embracing microservices architecture allows teams to isolate features, accelerate updates, and reduce interdependencies. Of course, microservices bring their own complexity—distributed tracing, service discovery, and contract management to name a few. But when managed well, they provide a foundation for resilience, agility, and controlled scalability. Stage 4: Fully Cloud-Native Operations At this level, systems are designed to scale automatically, recover from failure without human intervention, and deliver changes through automated pipelines. Infrastructure is provisioned via code, monitored continuously, and updated in response to real-world metrics. This is the hallmark of mature cloud-native architecture—systems that respond to change as a constant, not a disruption. Organizations that succeed with cloud-native architecture tend to follow a few common design philosophies—practical, not theoretical. Modularity First Applications are built from loosely coupled components that serve discrete purposes. This not only simplifies testing and release management but also makes it easier to scale selectively. One high-demand service doesn't burden the entire system. Infrastructure as Code Instead of manual setup, environments are defined in templates and managed through automation tools. This allows for faster provisioning, safer rollbacks, and consistency across dev, staging, and production. Observability and Alerting In cloud-native systems, monitoring can't be an afterthought. Logs, metrics, and traces must be integrated from the start, with clear thresholds for alerting. Real-time visibility is critical to troubleshooting, performance tuning, and maintaining uptime. Elastic Scalability Designing for scalability means planning for fluctuations—both expected and unpredictable. Systems should be able to expand horizontally based on demand, then contract when usage drops. This elasticity not only supports growth but keeps costs in check. There's often a tendency to conflate containerization with modernization. It's easy to understand why—containers offer portability, speed, and isolation. But if what you're running inside those containers is still a legacy monolith, you're not gaining much. Containers are an enabler. They simplify DevOps workflows and support automation. But they won't solve application design issues on their own. True modernization demands a shift in how software is structured, how services interact, and how failures are handled. When used thoughtfully, microservices offer more than just architectural clarity—they give teams autonomy. A single product feature can be updated without impacting unrelated areas of the application. Services can be scaled independently based on load, improving both performance and efficiency. But this only works when the groundwork has been laid: strong CI/CD pipelines, contract testing, centralized logging, and a culture that values ownership and communication. Without that, microservices can become just as tangled as the monoliths they replaced—only harder to debug. Scaling is about more than capacity—it's about predictability. If you have to pause deployments during high traffic, or if failure in one component brings down the entire system, your application isn't built for scale. In a well-designed cloud-native architecture, scalability is proactive, not reactive. Load balancers, auto-scaling groups, and event-driven architectures work together to ensure performance during spikes and efficiency during lulls. Systems adjust on their own—without developers scrambling to provision new resources at 2 a.m. That kind of confidence only comes when resilience is built in from the beginning, not bolted on later. Cloud migration may be the first step, but it isn't the destination. For businesses to thrive in fast-changing markets, they need systems that are flexible, observable, and built to adapt. That means going beyond hosting applications in the cloud—it means designing them for the cloud. A well-executed cloud-native architecture doesn't just reduce downtime or accelerate releases. It changes how teams think, how software is delivered, and how quickly organizations can respond to new opportunities. Yes, the shift takes time. But the payoff is more than technical—it's strategic. And in today's digital economy, that difference can define whether a company leads or lags. TIME BUSINESS NEWS
Web Release
24-06-2025
- Web Release
Tenable Research Finds Rampant Cloud Misconfigurations Exposing Critical Data and Secrets
Tenable®, the exposure management company, today released its 2025 Cloud Security Risk Report, which revealed that 9% of publicly accessible cloud storage contains sensitive data. Ninety-seven percent of such data is restricted or confidential, creating easy and prime targets for threat actors. Cloud environments face dramatically increased risk due to exposed sensitive data, misconfigurations, underlying vulnerabilities and poorly stored secrets – such as passwords, API keys and credentials. The 2025 Cloud Security Risk Report provides a deep dive into the most prominent cloud security issues impacting data, identity, workload and AI resources and offers practical mitigation strategies to help organizations proactively reduce risk and close critical gaps. Key Findings From The Report Include: ? Secrets Found in Diverse Cloud Resources, Putting Organizations at Risk: Over half of organizations (54%) store at least one secret directly in Amazon Web Services (AWS) Elastic Container Service (ECS) task definitions — creating a direct attack path. Similar issues were found among organizations using Google Cloud Platform (GCP) Cloud Run (52%) and Microsoft Azure Logic Apps workflows (31%). Alarmingly, 3.5% of all AWS Elastic Compute Cloud (EC2) instances contain secrets in user data — major risk given how widely EC2 is used. ? Cloud Workload Security Is Improving, But Toxic Combinations Persist: While the number of organizations with a 'toxic cloud trilogy' – a workload that is a publicly exposed, critically vulnerable, and highly privileged – has decreased from 38% to 29%, this dangerous combination still represents a significant and common risk. ? Using Identity Providers (IdPs) Alone Doesn't Eliminate Risk: While 83% of AWS organizations are exercising best practices in using IdP services to manage their cloud identities, overly-permissive defaults, excessive entitlements, and standing permissions still expose them to identity-based threats. 'Despite the security incidents we have witnessed over the past few years, organizations continue to leave critical cloud assets, from sensitive data to secrets, exposed through avoidable misconfigurations,' said Ari Eitan, Director of Cloud Security Research, Tenable. 'The path for attackers is often simple: exploit public access, steal embedded secrets or abuse overprivileged identities. To close these gaps, security teams need full visibility across their environments and the ability to prioritize and automate remediation before threats escalate. The cloud demands continuous, proactive risk management, and not reactive patchwork.' The report reflects findings by the Tenable Cloud Research team based on telemetry from workloads across diverse public cloud and enterprise environments, analyzed from October 2024 through March 2025. To download the report today, please visit:
Yahoo
15-05-2025
- Business
- Yahoo
Virtual Machine Market Size to Surpass USD 35.37 Billion by 2032, Owing to Rising Cloud Adoption and Demand for Scalable IT Infrastructure
The Virtual Machine (VM) market is experiencing significant growth, driven by the increasing adoption of cloud computing, the need for cost-effective computing solutions, and the demand for scalable IT infrastructure. Pune, May 15, 2025 (GLOBE NEWSWIRE) -- Virtual Machine Market Size Analysis: 'The Virtual Machine Market size was USD 10.43 Billion in 2023 and is expected to reach USD 35.37 Billion by 2032, growing at a CAGR of 14.6% over the forecast period of 2024-2032.'Get a Sample Report of Virtual Machine Market@ Major Players Analysis Listed in this Report are: Inc. (Amazon Elastic Compute Cloud (EC2), AWS Lambda) Citrix Systems Inc. (Citrix Hypervisor, Citrix Virtual Apps and Desktops) Hewlett Packard Enterprise LP (HPE Synergy, HPE SimpliVity) Huawei Technologies Co. Ltd. (FusionCompute, Huawei Cloud Stack) International Business Machine Corporation (IBM PowerVM, IBM Cloud Virtual Servers) Microsoft Corporation (Microsoft Hyper-V, Azure Virtual Machines) Oracle Corporation (Oracle VM VirtualBox, Oracle Cloud Infrastructure Compute) VMware Inc. (VMware vSphere, VMware Workstation Pro) Parallels Inc. (Parallels Desktop, Parallels Remote Application Server) Red Hat Inc. (Red Hat Virtualization, Red Hat OpenStack Platform) Cisco Systems (Cisco UCS Manager, Cisco HyperFlex) Intel Corporation (Intel VT-x [Virtualization Technology], Intel Server GPU) Virtual Machine Market Report Scope: Report Attributes Details Market Size in 2023 US$ 10.43 Billion Market Size by 2032 US$ 35.37 Billion CAGR CAGR of 14.6 % From 2024 to 2032 Base Year 2023 Forecast Period 2024-2032 Historical Data 2020-2022 Key Regional Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) Key Growth Drivers Increasing Adoption of Cloud Computing and Virtualization Drives Growth in the Virtual Machine Market Do you have any specific queries or need any customization research on Virtual Machine Market, Make an Enquiry Now@ Cloud-Driven Demand Accelerates Virtual Machine Market Expansion with Focus on Flexibility and Cost Efficiency The Virtual Machine market is rapidly expanding as demand for flexible and efficient computing is increasing. With the rapid expansion of cloud computing, VMs have been increasingly accepted due to their ability to reduce resource wastage and cost. Cloud-based virtual machines are especially popular in hybrid and multi-cloud scenarios, providing businesses with the flexibility to run applications on-premises, in the cloud, or various clouds, and be able to leverage cloud services alongside their on-premises systems. The U.S. Virtual Machine (VM) Market was valued at USD 2.61 billion in 2023 and is projected to reach USD 8.09 billion by 2032, expanding at a CAGR of 13.4% from 2024 to 2032. This increase is fueled especially by the broad implementation of cloud and virtualization and AI related workloads.' VMs are widely used in organizations for simplifying infrastructure management, improving scalability as well as operating efficiency. Increasing adoption of hybrid and multi-cloud solutions, combined with advancements in hypervisor technology, is driving market growth. Segment Analysis By Type, System Virtual Machines Lead 2023 Market with 64% Share, While Process VMs Set to Surge at 15.6% CAGR Through 2032[ In 2023, the System Virtual Machine segment dominated the market, accounting for 64.00% of total revenue. This leadership is due to its wide adoption in data centers, enterprise IT, and cloud. System VMs also allow running multiple OSes on a single physical server, contributing to resource optimization and cost reduction for enterprises. Advances in hypervisor technology and cloud VM products have also increased speed and security, and hence usage. The Process Virtual Machine segment is expected to register the largest CAGR of 15.6% during the forecast period. This expansion is driven by the increasing demand for efficient runtime environments. Process VMs are most commonly used to run software applications, but they are also widely implemented in developed containerized applications, serverless computing, and other cloud computing applications, processes, and IT operations these days. By vertical, BFSI leads the Virtual Machine Market with a 29% Share in 2023; the Government Sector is set for the Fastest Growth Amid Digital Transformation. The BFSI sector contributed the highest revenue share of 29.00% in 2023, as the industry increasingly adopts virtualization to have a scalable and secure IT infrastructure. Banks are improving their data security, high-frequency transaction, and disaster recovery capabilities, using virtual machines. The Government & Public sector is expected to grow at the highest CAGR during the forecast period, as organizations in this sector are among the early adopters of new and emerging technologies, as they can be effectively used to thwart cyber-criminal activities. Virtual Machine Market Segmentation: By Type System Virtual Machine Process Virtual Machine By Organization Size Large Enterprises SMEs By Vertical BFSIs Telecommunications & ITES Government & Public Sector Healthcare & Life Sciences Others North America Leads Virtual Machine Market with 38% Share in 2023; Asia Pacific Emerges as Fastest-Growing Region at 15.7% CAGR. North America held the virtual machine (VM) Market share of around 38% in 2023. This leadership is attributed to the robust adoption of cloud technology, powerful IT infrastructure, as well as the massive implementation of virtualization technologies in enterprises across the region. The dominance of North America is attributed to leading cloud service providers, large-scale investment in data centers, and the rising need for a virtualized environment in BFSI, healthcare, and the government sector. Asia Pacific is the fastest-growing region in the Virtual Machine (VM) market, projected to expand at a CAGR of 15.7% over the forecast period. This fast-growing market is driven by the increasing demand for cloud-based virtualization, growth in the spending towards IT, and the increase in digital businesses in developing economies such as China, India, and Southeast Asia. Virtualization is gaining adoption from governments and organizations in the region to increase operational efficiency, handle mass storage of data, and bolster cybersecurity systems. Recent Developments In November 2024 an HPE VM Essentials virtualization product that can operate across HPE and non-HPE platforms. This solution looks to supply customers with a consume- what-you-need model virtualization solution that can possibly be of interest to those that are tired of the virtualization alternatives. In November 2024, Microsoft unveiled major improvements to its Azure Cloud platform, announcing new virtual machines (VMs) and improved cooling and power delivery technologies to accommodate the increasing requirements of Artificial Intelligence (AI) of Contents – Major Key Points 1. Introduction 2. Executive Summary 3. Research Methodology 4. Market Dynamics Impact Analysis 5. Statistical Insights and Trends Reporting 6. Competitive Landscape 7. Virtual Machine Market Segmentation By Organization Size 8. Virtual Machine Market Segmentation By Vertical 9. Virtual Machine Market Segmentation By Type 10. Regional Analysis 11. Company Profiles 12. Use Cases and Best Practices 13. Conclusion About Us: SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world. Related Reports: Applied AI Service Market Business Software And Services Market Case Management Market Online Survey Software Market Cloud Workflow Market CONTACT: Contact Us: Jagney Dave - Vice President of Client Engagement Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
