#@GoogleCloud

[nando161mando]

"No Tech for Apartheid’s protest is as much about what the public doesn’t know about Project Nimbus as what it does. The contract is for Google and Amazon to provide AI and cloud computing services to the Israeli government and military, according to the Israeli finance ministry, which announced the deal in 2021.

Nimbus reportedly involves Google establishing a secure instance of Google Cloud on Israeli soil, which would allow the Israeli government to perform large-scale data analysis, AI training, database hosting, and other forms of powerful computing using Google’s technology, with little oversight by the company.

Google documents, first reported by the Intercept in 2022, suggest that the Google services on offer to Israel via its Cloud have capabilities such as AI-enabled facial detection, automated image categorization, and object tracking."

[avaaddamschat]

[govindhtech]

UNC5537: Extortion and Data Theft of Snowflake Customers

Targeting Snowflake Customer Instances for Extortion and Data Theft, UNC5537 Overview. Mandiant has discovered a threat campaign that targets Snowflake client database instances with the goal of extortion and data theft. This campaign has been discovered through Google incident response engagements and threat intelligence collections. The multi-Cloud data warehousing software Snowflake can store and analyze massive amounts of structured and unstructured data.

Mandiant is tracking UNC5537, a financially motivated threat actor that stole several Snowflake customer details. UNC5537 is using stolen customer credentials to methodically compromise Snowflake client instances, post victim data for sale on cybercrime forums, and attempt to blackmail many of the victims.

Snowflake instance According to Mandiant’s analysis, there is no proof that a breach in Snowflake’s enterprise environment led to unauthorized access to consumer accounts. Rather, Mandiant was able to link all of the campaign-related incidents to hacked client credentials.

Threat intelligence about database records that were later found to have come from a victim’s Snowflake instance was obtained by Mandiant in April 2024. After informing the victim, Mandiant was hired by the victim to look into a possible data theft affecting their Snowflake instance. Mandiant discovered during this investigation that a threat actor had gained access to the company’s Snowflake instance by using credentials that had previously been obtained through info stealer malware.

Using these credentials that were taken, the threat actor gained access to the customer’s Snowflake instance and eventually stole important information. The account did not have multi-factor authentication (MFA) activated at the time of the intrusion.

Following further intelligence that revealed a wider campaign aimed at more Snowflake customer instances, Mandiant notified Snowflake and potential victims via their Victim Notification Programme on May 22, 2024.

Snowflakes Mandiant and Snowflake have notified about 165 possibly vulnerable organizations thus far. To guarantee the security of their accounts and data, these customers have been in direct contact with Snowflake’s Customer Support. Together with collaborating with pertinent law enforcement organizations, Mandiant and Snowflake have been undertaking a cooperative investigation into this continuing threat campaign. Snowflake released comprehensive detection and hardening guidelines for Snowflake clients on May 30, 2024.

Campaign Synopsis According to Google Cloud current investigations, UNC5537 used stolen customer credentials to gain access to Snowflake client instances for several different organizations. The main source of these credentials was many info stealer malware campaigns that compromised systems controlled by people other than Snowflake.

As a result, a sizable amount of customer data was exported from the corresponding Snowflake customer instances, giving the threat actor access to the impacted customer accounts. Subsequently, the threat actor started personally extorting several of the victims and is aggressively trying to sell the stolen consumer data on forums frequented by cybercriminals.

Mandiant Mandiant discovered that most of the login credentials utilized by UNC5537 came from infostealer infections that occurred in the past, some of which were from 2020. Three main causes have contributed to the multiple successful compromises that UNC5537’s threat campaign has produced:

Since multi-factor authentication was not enabled on the affected accounts, successful authentication just needed a working login and password. The credentials found in the output of the infostealer virus were not cycled or updated, and in certain cases, they remained valid years after they were stolen. There were no network allow lists set up on the affected Snowflake client instances to restrict access to reliable sources. Infostealer Mandiant found that the first infostealer malware penetration happened on contractor computers that were also used for personal purposes, such as downloading pirated software and playing games. This observation was made during multiple investigations related to Snowflake.

Customers that hire contractors to help them with Snowflake may use unmonitored laptops or personal computers, which worsen this initial entry vector. These devices pose a serious concern because they are frequently used to access the systems of several different organizations. A single contractor’s laptop can enable threat actors to access numerous organizations if it is infected with infostealer malware, frequently with administrator- and IT-level access.

Identifying The native web-based user interface (SnowFlake UI, also known as SnowSight) and/or command-line interface (CLI) tool (SnowSQL) on Windows Server 2022 were frequently used to get initial access to Snowflake customer instances. Using an attacker-named utility called “rapeflake,” which Mandiant records as FROSTBITE, Mandiant discovered more access.

Mandiant believes FROSTBITE is used to conduct reconnaissance against target Snowflake instances, despite the fact that Mandiant has not yet retrieved a complete sample of FROSTBITE. Mandiant saw the use of FROSTBITE in both Java and.NET versions. The Snowflake.NET driver communicates with the.NET version. The Snowflake JDBC driver is interfaced with by the Java version.

SQL recon actions by FROSTBITE have been discovered, including a listing of users, current roles, IP addresses, session IDs, and names of organizations. Mandiant also saw UNC5537 connect to many Snowflake instances and conduct queries using DBeaver Ultimate, a publicly accessible database management tool.

Finish the mission Mandiant saw UNC5537 staging and exfiltrating data by continuously running identical SQL statements on many client Snowflake systems. The following instructions for data staging and exfiltration were noted.

Generate (TEMP|TEMPORARY) STAGE UNC5537 used the CREATE STAGE command to generate temporary stages for data staging. The data files that are loaded and unloaded into database tables are stored in tables called stages. When a stage is created and designated as temporary, it is removed after the conclusion of the creator’s active Snowflake session.

UNC5537 Credit Since May 2024, Mandiant has been monitoring UNC5537, a threat actor with financial motivations, as a separate cluster. UNC5537 often extorts people for financial benefit, having targeted hundreds of organizations globally. Under numerous aliases, UNC5537 participates in cybercrime forums and Telegram channels. Mandiant has recognized individuals who are linked to other monitored groups. Mandiant interacts with one member in Turkey and rates the composition of UNC5537 as having a moderate degree of confidence among its members who are located in North America.

In order to gain access to victim Snowflake instances, Attacker Infrastructure UNC5537 mostly leveraged Mullvad or Private Internet Access (PIA) VPN IP addresses. Mandiant saw that VPS servers from Moldovan supplier ALEXHOST SRL (AS200019) were used for data exfiltration. It was discovered that UNC5537 was storing stolen victim data on other foreign VPS providers in addition to the cloud storage provider MEGA.

Prospects and Significance The campaign launched by UNC5537 against Snowflake client instances is not the product of a highly advanced or unique method, instrument, or process. The extensive reach of this campaign is a result of both the expanding infostealer market and the passing up of chances to further secure credentials:

UNC5537 most likely obtained credentials for Snowflake victim instances by gaining access to several infostealer log sources. There’s also a thriving black market for infostealerry, with huge lists of credentials that have been stolen available for purchase and distribution both inside and outside the dark web.

Infostealers Multi-factor authentication was not necessary for the impacted customer instances, and in many cases, the credentials had not been changed in up to four years. Additionally, access to trusted locations was not restricted using network allow lists.

This ad draws attention to the ramifications of a large number of credentials floating throughout the infostealer market and can be a sign of a targeted attack by threat actors on related SaaS services. Mandiant predicts that UNC5337 will carry on with similar intrusion pattern, soon focusing on more SaaS systems.

This campaign’s wide-ranging effects highlight the pressing necessity for credential monitoring, the ubiquitous application of MFA and secure authentication, traffic restriction to approved sites for royal jewels, and alerts regarding unusual access attempts. See Snowflake’s Hardening Guide for additional suggestions on how to fortify Snowflake environments.

Read more on Govindhtech.com

[pulsaris]

A Canonical lançou nesta última semana a nova versão do Ubuntu LTS. A versão 24.04 (Noble Numbat) traz inúmeras novidades destacando-se delas o suporte avançado para os mais recentes processadores Intel, AMD e Qualcomm.

A nova versão já é suportada pela Pulsaris e será muito em breve suportada oficialmente pela ESET também.

Os clientes que pretenda efectuar a migração deverão entrar em contacto connosco através dos canais de comunicação habituais.

[connectinfo1999]

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Google Cloud Professional Cloud Architect Certification. Become a GCP Cloud Architect, Latest GCP Exam and Case Studies.

Google Cloud Platform is one of the fastest-growing cloud service platforms offered today that lets you run your applications and data workflows at a 'Google-sized' scale.

Google Cloud Certified Professional Cloud Architect certification is one of the most highly desired IT certifications out today. It is also one of the most challenging exams offered by any cloud vendor today. Passing this exam will take many hours of study, hands-on experience, and an understanding of a very wide range of GCP topics.

Luckily, we're here to help you out! This course is designed to be your best single resource to prepare for and pass the exam to become a certified Google Cloud Architect.

Why should do a Google Cloud Certification?

Here are few results from Google's 2020 Survey:

89% of Google Cloud certified individuals are more confident about their cloud skills

GCP Cloud Architect was the highest paying certification of 2020 (2) and 2019 (3)

More than 1 in 4 of Google Cloud certified individuals took on more responsibility or leadership roles at work

Why should you aim for Google Cloud - GCP Cloud Architect Certification?

Google Cloud Professional Cloud Architect certification helps you gain an understanding of cloud architecture and Google Cloud Platform.

As a Cloud Architect, you will learn to design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

The Google Cloud Certified - Professional Cloud Architect exam assesses your ability to:

Design and architect a GCP solution architecture

Manage and provision the GCP solution infrastructure

Design for security and compliance

Analyze and optimize technical and business processes

Manage implementations of Google Cloud architecture

Ensure solution and operations reliability

Are you ready to get started on this amazing journey to becoming a Google Cloud Architect?

So let's get started!

Who this course is for:

You want to start your Cloud Journey with Google Cloud Platform

You want to become a Google Cloud Certified Professional Cloud Architect

[innovativeacademy-blog]

Quiz Time

Visit: https://innovativeacademy.in Call us: +91 8447712333

[inextures]

Interactive and Conversational Search with Google Cloud and Elasticsearch

These days, where we have such a lot of online information, it’s truly essential to find what you really want rapidly and precisely. That is the very thing that this blog post is about. We will discuss a better approach for looking and searching online, utilizing something many refer to as interactive and conversational search.

This method makes searching more like having a chat, and it uses some cool tools from Google Cloud and Elasticsearch. We’ll take a gander at how these better approaches for looking are unique in relation to the old ones, and how Google Cloud’s most recent tech improves looking through even. We’re likewise going to look at Elasticsearch, which is a search engine web index, and perceive how it cooperates with Google Cloud to make your searches fast and simple.

What is Interactive and Conversational Search?

A flow method for looking for information that goes beyond the usual practice of inputting keywords into a search engine is interactive and conversational search. All things being equal, it empowers clients to communicate with the search system in a more normal and conversational manner, using text or voice.

This technology utilizes progress in artificial intelligence, especially in natural language processing and machine learning, to comprehend, interpret, and answer client inquiries in a way like that of a human. The objective is to further develop the search experience by making it more automatic, productive, and easy to understand.

Users can get clarification on pressing issues or make demands in natural language, and the system is intended to comprehend the context and intent behind these searches, resulting in more accurate and relevant replies.

This technology is particularly helpful in applications requiring fast and exact information retrieval, such as customer service bots, personal digital assistants, and sophisticated data analysis tools.

Google Cloud – Powering Advanced Search Capabilities

What is Google Cloud?

Google Cloud is a Google cloud computing service that provides a variety of server and computation choices for web applications. It offers computing, storage, and Application Development Services that are provided on Google hardware, allowing developers and organizations to develop, test, and roll out applications on Google’s highly scalable and dependable infrastructure.

Let’s discuss various aspects of Google Cloud

The AI and Machine Learning Edge of Google Cloud

At its core, Google Cloud uses the force of power of artificial intelligence (AI) and machine learning (ML)  to offer extraordinary abilities in information handling and analytics. These technologies are significant in understanding and interpreting the vast amount of data generated day to day. Google Cloud’s sAI and ML services are intended to be available and adaptable, making them reasonable for organizations, all things considered.

The strength of Google Cloud lies in its complex calculations and neural networks, which are continually learning and evolving. This consistent improvement considers more precise expectations and insights, essential for making a proficient and intelligent search experience.

Enhancing Search Functionalities with Google Cloud

Google Cloud significantly enhances search functionalities in several ways, most notably through natural language processing (NLP). NLP is a branch of AI that focuses on the interaction between computers and human language. It enables machines to understand, interpret, and respond to human language in a useful and meaningful way.

One of the key applications of NLP in search is understanding the context and intent behind user queries. Traditional search engines might struggle with complex or conversational queries, but with Google Cloud’s NLP capabilities, search engines can interpret these queries more effectively. This means users can ask questions in natural, conversational language and receive more accurate and relevant results.

For example, if a user searches for “best strategies for online marketing in 2023,” Google Cloud’s NLP tools can analyze the query to understand the specific intent – in this case, looking for recent and effective online marketing strategies. The search engine can then prioritize content that is not only relevant to online marketing but also current and strategy-focused.

Real-World Applications and Future Potential

The applications of Google Cloud’s search capabilities are vast and varied. From powering sophisticated recommendation engines in e-commerce platforms to enabling efficient document search in large corporate databases, the potential is limitless. The real power lies in its adaptability and how businesses can leverage these tools to meet their specific needs.

As we look to the future, the integration of AI and ML in search is only set to deepen. With advancements in AI and machine learning, particularly in areas like deep learning and predictive analytics, Google Cloud is well-positioned to lead this charge. The potential for creating even more personalized, intuitive, and intelligent search experiences is immense, paving the way for a new era in digital information access and management.

Elasticsearch – The Backbone of Search Engines

Elasticsearch stands out as a pivotal technology. Originally released in 2010, it has rapidly grown to become a key player in the search engine landscape, renowned for its speed, scalability, and robust set of features.

What is Elasticsearch?

Elasticsearch is an open-source, distributed search and analytics engine, designed for horizontal scalability, reliability, and easy management. It is built on top of Apache Lucene, a high-performance, full-text search engine library. This foundation enables Elasticsearch to not only perform complex searches but also to handle large volumes of data in real time.

Also Read: Explore Elasticsearch and Why It’s Worth Using?

Core Features of Elasticsearch

Full-Text Search: At its core, Elasticsearch excels in full-text search. It breaks down texts into individual terms or phrases and allows for complex query types including fuzzy matching, wildcard searches, and synonym handling. This makes it extremely powerful for searching through large volumes of text-heavy data.

Scalability: One of the most amazing elements of Elasticsearch is its capacity to scale. It can deal with petabytes of structured and unstructured information, and its appropriate nature implies that it can develop with your necessities. Whether you’re a little startup or a huge endeavor, Elasticsearch adjusts to your data requirements without compromising on performance.

Real-Time Data and Analytics: Elasticsearch works progressively. As soon as a document is indexed, it’s searchable. This feature is critical for applications that require immediate insights from their data, like monitoring tools, financial analysis, and e-commerce platforms.

Distributed Architecture: Its distributed architecture ensures that your data is always available and accessible. Elasticsearch automatically replicates data to ensure resilience and high availability, meaning that even in the case of hardware failure, your search system remains operational.

Powerful API and Ecosystem: Elasticsearch comes with a rich set of APIs that allow for seamless integration with numerous languages such as Java, Python, PHP, JavaScript, and more. The Elastic Stack, which includes Kibana for data visualization and Logstash for data processing, complements Elasticsearch to provide a comprehensive search and data analysis solution.

Applications of Elasticsearch

Elasticsearch is used across various industries for different purposes:

E-commerce: For product searches and personalized recommendations.

Logging and Monitoring: For analyzing and visualizing logs in real-time.

Security Information and Event Management (SIEM): For threat hunting and security analytics.

Search Applications: As the underlying engine for custom search applications across websites and enterprise systems.

Integrating Google Cloud with Elasticsearch

Integrating Google Cloud with Elasticsearch represents a significant advancement in search and data analysis. This integration combines Google Cloud’s cutting-edge artificial intelligence and machine learning capabilities with Elasticsearch’s robust, scalable search engine framework.

The result is a powerful synergy that enhances search functionalities, enabling more intuitive, accurate, and real-time responses to complex queries. Businesses can leverage this integration to analyze large datasets, gain actionable insights, and provide users with an unmatched search experience.

Whether it’s processing natural language queries, delivering personalized search results, or offering predictive analytics, the combination of Google Cloud and Elasticsearch paves the way for innovative and efficient data-driven solutions.

Use Cases and Applications

The integration of Google Cloud and Elasticsearch significantly enhances search capabilities across various sectors. In e-commerce, it improves product discovery through natural language queries, enhancing both user experience and sales.

Customer service benefits from AI-powered conversational bots that can handle complex inquiries efficiently. In healthcare, it streamlines access to patient records and medical information, aiding in faster decision-making.

Additionally, for data analytics, this combination simplifies extracting insights from large datasets, making the process more intuitive and efficient. This synergy of Google Cloud’s AI and Elasticsearch’s search functionality marks a leap in creating more user-friendly, intelligent search experiences across diverse industries.

Conclusion

The integration of Google Cloud and Elasticsearch marks a transformative step in search technology. More than a technical feat, it’s a portal to a future where search engines evolve into intelligent partners, adept in processing natural language and delivering precise, efficient results.

This synergy heralds a new wave of innovation across sectors, making our interactions with the digital world more intuitive, responsive, and centered around user needs. As we advance, this blend of Google Cloud’s AI and Elasticsearch’s search prowess promises to redefine not just how we search, but also how we experience the digital landscape. The future of search is conversational, intelligent, and here to revolutionize our digital interactions.

Originally published by: Interactive and Conversational Search with Google Cloud and Elasticsearch

[capitalnumbers]

Serverless Architecture for Scalable, Cost-Effective Web Apps

Serverless architecture helps businesses build web apps faster, cheaper, and without worrying about server maintenance. Cloud providers like AWS and Google Cloud take care of all the backend work, so developers can focus on writing code.

In this setup, apps scale automatically based on demand, and companies only pay for the actual usage, not idle time. This means less cost, better security, and quicker updates.

Popular tools include AWS Lambda, API Gateway, and Google Cloud Functions. These tools support tasks like running code, storing data, or building APIs - all without managing servers.

Use cases include mobile and web backends, real-time data processing, and scheduled jobs. Best practices include keeping code small, monitoring performance, and securing environments.

Overall, serverless makes building apps easier and more efficient. It’s ideal for growing businesses that want to stay fast, flexible, and budget-friendly.

[simple-logic]

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Comment Below👇

💻 Explore insights on the latest in #technology on our Blog Page 👉 https://simplelogic-it.com/blogs/

🚀 Ready for your next career move? Check out our #careers page for exciting opportunities 👉 https://simplelogic-it.com/careers/

[technocourses]

Google Cloud Architect Certification Training: Become a GCP Leader in 2025

In today’s cloud-powered economy, organizations are looking for experts who can design scalable, reliable, and secure cloud solutions. If you aspire to take on cloud leadership roles, the Google Cloud Architect Certification Training is your gateway to becoming an elite cloud professional.

The Professional Cloud Architect certification is Google Cloud’s flagship credential — recognized globally and highly valued by employers. This blog walks you through the training path, skills you’ll master, and how to prepare effectively in 2025.

🌐 What Is a Google Cloud Architect?

A Google Cloud Architect designs cloud infrastructure, chooses optimal cloud solutions, and oversees implementation strategies on GCP. Their responsibilities include:

Designing cloud architecture for enterprise applications

Ensuring scalability, high availability, and security

Making key design decisions on networking, storage, compute

Leading cloud adoption strategies and migrations

Collaborating with devs, ops, and stakeholders

🎯 Why Choose the Google Cloud Architect Certification?

Here’s why this credential is a top-tier choice in cloud computing:

Recognized as one of the highest-paying cloud certifications

Backed by Google’s robust infrastructure (used by Spotify, Twitter, and Etsy)

Opens doors to roles like Cloud Architect, Solutions Engineer, Cloud Consultant

Offers deep coverage of real-world infrastructure scenarios

Validates expertise in designing, managing, and securing GCP environments

🧠 What You'll Learn in the Architect Certification Training

A structured training program will equip you with end-to-end cloud architecture expertise. Core modules typically include:

1. GCP Fundamentals

GCP core services (Compute, Storage, Networking)

Understanding GCP billing and resource hierarchy

IAM and project-level security

2. Designing GCP Architecture

Designing scalable systems

Choosing compute options (GKE, App Engine, Compute Engine)

Storage design (Cloud Storage, Spanner, Bigtable)

3. Networking & Security

Designing VPCs and subnets

Managing firewalls, load balancing, and hybrid connectivity

Identity management and secure cloud design

4. Deployment & Automation

Infrastructure as Code (IaC) with Terraform and Deployment Manager

CI/CD pipelines and DevOps on GCP

Monitoring with Cloud Operations Suite (formerly Stackdriver)

5. Disaster Recovery & Business Continuity

High availability and failover strategies

Backup and restore architecture

Designing for reliability using SRE principles

🏆 Certification Exam Overview

Google Cloud Certified – Professional Cloud Architect

Duration: 2 hours

Format: Multiple choice and multiple select

Cost: $200 USD

Delivery: Online or in-person at a test center

Prerequisite: No formal prerequisite, but 1+ years of GCP experience recommended

📌 Pro Tip: The exam is scenario-based, testing your ability to apply architectural thinking under real-world constraints.

📚 Recommended Training Resources

To pass the exam and gain real-world confidence, here are the top learning paths: Platform Course Name Highlights Coursera (by Google)Preparing for Google Cloud Architect Exam Real-world scenarios, quizzes, and case studies NetCom LearningGoogle Cloud Architect Certification Training Instructor-led with exam-focused labs Google Cloud Skills BoostArchitect Learning Path Google’s official training platform QwiklabsArchitecting with Google Cloud: Design and Process Hands-on labs with full GCP access

💼 What Roles Can You Land?

After completing your certification training, you can explore roles such as:

Cloud Architect – Design enterprise-scale systems

Solutions Architect – Work with clients to build scalable GCP solutions

Cloud Infrastructure Engineer – Focus on building and managing GCP environments

DevOps/CloudOps Engineer – Optimize CI/CD, security, and cloud automation

💰 Average Salary: $145,000–$185,000/year (U.S. based, according to PayScale and Glassdoor)

✅ Benefits of GCP Architect Certification

Recognition: Globally respected cloud credential

Career Growth: Faster promotions and job opportunities

Confidence: Real-world scenario training helps you lead cloud projects

Cloud Mastery: Deep dive into architecture, security, DevOps, and performance optimization

🔍 Real-World Case Studies

Companies across industries use GCP to solve mission-critical challenges:

Spotify: Migrated its data and ML workloads to Google Cloud

Home Depot: Uses GCP for inventory analytics and scalability

Target: Leverages GCP’s security and performance for e-commerce platforms

Your role as a Google Cloud Architect will involve designing similar high-performance architectures for these kinds of organizations.

🛠️ Tips to Succeed in Training

Start with GCP Fundamentals – Know the basics before diving into design principles

Master the case studies – The exam is heavy on scenario-based questions

Use Qwiklabs regularly – Practice builds confidence

Simulate failure scenarios – Learn to design for fault tolerance

Understand trade-offs – Choose between performance, cost, and security

🚀 Take the Next Step

Becoming a certified Google Cloud Architect is a prestigious and rewarding move for any IT professional. The training doesn’t just prepare you for an exam — it molds you into a strategic thinker capable of designing world-class cloud solutions.

📌 Ready to Architect the Future?

👉 Start learning at Google Cloud Training 👉 Join live classes at NetCom Learning 👉 Try hands-on labs at Qwiklabs 👉 Prepare with real GCP projects and mock tests

Would you like me to proceed with blog #4: "Google Cloud Certified Professional Cloud Architect" next?

[siict]

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[digitaleduskill]

How Public Cloud Is Transforming E-commerce

The e-commerce industry is growing at an unprecedented pace, and much of its success is driven by technological innovation. One of the most transformative technologies reshaping how online businesses operate is public cloud computing. From improved scalability and cost-efficiency to faster innovation and better customer experiences, the public cloud offers a powerful foundation for modern e-commerce platforms.

Unlike traditional IT infrastructures, public cloud computing provides a flexible and cost-effective way to store data, host applications, and deliver services over the internet. This allows online retailers—regardless of their size—to compete on a global scale.

Scalability for High Traffic Seasons

E-commerce traffic is unpredictable. From festive sales to flash promotions, online stores must handle huge spikes in traffic without crashing. With traditional servers, scaling for demand can be expensive and time-consuming. But public cloud platforms like AWS, Microsoft Azure, and Google Cloud allow businesses to scale resources automatically based on traffic.

For example, during Black Friday or Diwali sales, an online retailer can scale its application and infrastructure in real-time—only paying for the extra resources when needed. This ensures that customers enjoy smooth shopping experiences even during peak demand.

Reduced Infrastructure Costs

Maintaining physical servers, cooling systems, and security requires a significant financial investment. Public cloud computing eliminates the need for expensive hardware and data centers. Instead, e-commerce businesses pay only for what they use, significantly reducing operational costs.

With cloud service providers offering various pricing models—such as pay-as-you-go or reserved instances—businesses can optimize expenses while maintaining performance.

Faster Deployment and Innovation

In today’s competitive e-commerce landscape, speed is everything. Businesses must quickly launch new products, features, or entire marketplaces. Public cloud platforms offer ready-to-use tools, APIs, and microservices that allow developers to build, test, and deploy applications in hours instead of weeks.

Additionally, features such as continuous integration and deployment (CI/CD) pipelines streamline development workflows, helping businesses innovate faster and respond to customer needs promptly.

Enhanced Data Security and Compliance

Security remains a top concern for e-commerce platforms, especially when handling customer data and payment information. Public cloud computing providers invest heavily in cybersecurity infrastructure and offer advanced features such as:

End-to-end encryption

Multi-factor authentication

Automated backups and disaster recovery

Compliance certifications (PCI-DSS, GDPR, ISO, etc.)

These built-in protections ensure that e-commerce businesses maintain customer trust and meet regulatory standards without having to manage everything in-house.

Personalization Through Data Analytics and AI

Personalized shopping experiences drive higher conversion rates. Public cloud platforms enable e-commerce businesses to collect and analyze massive amounts of user data in real time. Using cloud-based AI and machine learning tools, businesses can:

Recommend products

Predict customer behavior

Optimize pricing strategies

Automate inventory management

Cloud-based analytics platforms like Amazon Redshift, Google BigQuery, and Azure Synapse allow businesses to make data-driven decisions that enhance user engagement and boost sales.

Global Reach and Accessibility

The public cloud gives e-commerce companies a global presence without the need to set up physical infrastructure in every region. Cloud providers operate data centers worldwide, allowing businesses to:

Deploy applications closer to users

Improve website load times

Offer localized content and currency

Comply with data residency regulations

This global reach is particularly valuable for small and mid-sized online retailers aiming to expand into international markets.

Seamless Integration with Third-Party Tools

Modern e-commerce platforms rely on a wide range of tools—from CRM systems and payment gateways to shipping APIs and marketing automation tools. Public cloud computing makes it easy to integrate these services seamlessly through APIs and containerized microservices.

This modular approach simplifies operations, enhances agility, and makes it easier to switch or upgrade services as the business grows.

Sustainable and Eco-Friendly

Many public cloud providers have committed to renewable energy usage and sustainable operations. By migrating to the cloud, e-commerce companies contribute to reducing their carbon footprint. Centralized cloud data centers are more energy-efficient than traditional on-premise systems, making cloud adoption a step toward greener business practices.

Final Thoughts

Public cloud computing is not just a trend—it is a foundational shift in how e-commerce businesses operate, grow, and compete. From scaling effortlessly and cutting costs to enhancing security and offering personalized customer experiences, the cloud empowers online retailers to focus on what they do best: delivering value to their customers.

As cloud technologies continue to evolve, the future of e-commerce will become even more agile, intelligent, and globally accessible. Now is the time for businesses to embrace the power of the public cloud and unlock their full digital potential.

[govindhtech]

New Cloud Translation AI Improvements Support 189 Languages

189 languages are now covered by the latest Cloud Translation AI improvements.

Your next major client doesn’t understand you. 40% of shoppers globally will never consider buying from a non-native website. Since 51.6% of internet users speak a language other than English, you may be losing half your consumers.

Businesses had to make an impossible decision up until this point when it came to handling translation use cases. They have to decide between the following options:

Human interpreters: Excellent, but costly and slow

Simple machine translation is quick but lacks subtleties.

DIY fixes: Unreliable and dangerous

The problem with translation, however, is that you need all three, and conventional translation techniques are unable to keep up. Using the appropriate context and tone to connect with people is more important than simply translating words.

For this reason, developed Translation AI in Vertex AI at Google Cloud. Its can’t wait to highlight the most recent developments and how they can benefit your company.

Translation AI: Unmatched translation quality, but in your way

There are two options available in Google Cloud‘s Translation AI:

A necessary set of tools for translation capability is the Translation API Basic. Google Cloud sophisticated Neural Machine Translation (NMT) model allows you to translate text and identify languages immediately. For chat interactions, short-form content, and situations where consistency and speed are essential, Translation AI Basic is ideal.

Advanced Translation API: Utilize bespoke glossaries to ensure terminology consistency, process full documents, and perform batch translations. For lengthy content, you can utilize Gemini-powered Translation model; for shorter content, you can use Adaptive Translation to capture the distinct tone and voice of your business. By using a glossary, improving its industry-leading translation algorithms, or modifying translation forecasts in real time, you can even personalize translations.

What’s new in Translation AI

Increased accuracy and reach

With 189-language support, which now includes Cantonese, Fijian, and Balinese, you can now reach audiences around the world while still achieving lightning-fast performance, making it ideal for call centers and user content.

Smarter adaptive translation

You can use as little as five samples to change the tone and style of your translations, or as many as 30,000 for maximum accuracy.

Choosing a model according to your use case

Depending on how sophisticated your translation use case is, you can select from a variety of methods when using Cloud Translation Advanced. For instance, you can select Adaptive Translation for real-time modification or use NMT model for translating generic text.

Quality without sacrificing

Although reports and leaderboards provide information about the general performance of the model, they don’t show how well a model meets your particular requirements. With the help of the gen AI assessment service, you can choose your own evaluation standards and get a clear picture of how well AI models and applications fit your use case. Examples of popular tools for assessing translation quality include Google MetricX and the popular COMET, which are currently accessible on the Vertex gen AI review service and have a significant correlation with human evaluation. Choose the translation strategy that best suits your demands by comparing models and prototyping solutions.

Google cloud two main goals while developing Translation AI were to change the way you translate and the way you approach translation. Its deliver on both in four crucial ways, whereas most providers only offer either strong translation or simple implementation.

Vertex AI for quick prototyping

Test translations in 189 languages right away. To determine your ideal fit, compare NMT or most recent translation-optimized Gemini-powered model. Get instant quality metrics to confirm your decisions and see how your unique adaptations work without creating a single line of code.

APIs that are ready for production for your current workflows

For high-volume, real-time translations, integrate Translation API (NMT) straight into your apps. When tone and context are crucial, use the same Translation API to switch to Adaptive Translation Gemini-powered model. Both models scale automatically to meet your demands and fit into your current workflows.

Customization without coding

Teach your industry’s unique terminology and phrases to bespoke translation models. All you have to do is submit domain-specific data, and Translation AI will create a unique model that understands your language. With little need for machine learning knowledge, it is ideal for specialist information in technical, legal, or medical domains.

Complete command using Vertex AI

With all-inclusive platform, Vertex AI, you can use Translation AI to own your whole translation workflow. You may choose the models you want, alter how they behave, and track performance in the real world with Vertex AI. Easily integrate with your current CI/CD procedures to get translation at scale that is really enterprise-grade.

Real impact: The Uber story

Uber’s goal is to enable individuals to go anywhere, get anything, and make their own way by utilizing the Google Cloud Translation AI product suite.

Read more on Govindhtech.com

[praveennareshit]

How Long Does It Take to Learn Cloud Computing?

It’s 2025. Most tech roles — from app development to data analytics — mention “cloud” in the job description. Whether you’re a student, a working professional, or someone switching careers, you’ve probably wondered:

“How long will it take me to actually learn cloud computing?”

The short answer? Anywhere between 30 to 90 days — depending on your learning path, goals, and support system.

But before we talk timeframes, let’s understand what cloud computing really is.

☁️ What is Cloud Computing? (In Simple Terms)

In the old days, companies needed large rooms filled with servers to host websites or run software. That meant high costs, physical space, and endless maintenance.

Cloud computing changed everything.

Today, companies rent computing power, storage, and tools from cloud service providers over the internet. This means:

No need to buy hardware

Scale up or down anytime

Pay only for what you use

Every time you use Google Drive, stream Netflix, or upload a file to Dropbox — you’re using the cloud.

🧑💻 Who Uses Cloud Computing?

Everyone — from startups to governments. Industries like banking, healthcare, education, logistics, and media all rely on the cloud for flexibility, speed, and cost-efficiency.

And that’s exactly why cloud professionals are in such high demand.

🌐 The 3 Major Cloud Platforms (You Only Need to Start with One)

Amazon Web Services (AWS)

Microsoft Azure

Google Cloud Platform (GCP)

👉 Most beginners choose one platform to start with. Later, multi-cloud skills come naturally.

���️ So, How Long Does It Really Take to Learn Cloud Computing?

Here’s a breakdown from beginner to job-ready:

Learning StageTime NeededUnderstand cloud basics2–3 weeksLearn one cloud platform (AWS/Azure/GCP)4–6 weeksPractice hands-on projects2–4 weeksPrepare for certifications6–8 weeksBuild resume + apply for jobs2–3 months (total path)

✅ Total: 60–90 days, if you learn consistently with real guidance.

🎓 How NareshIT Helps You Learn Cloud — Without Getting Overwhelmed

We understand that learning cloud from scratch can feel overwhelming. That’s why NareshIT’s cloud programs are designed specifically for beginners, freshers, and working professionals who want structure, mentorship, and results.

🔹 AWS Cloud Training — From Basics to Certification

Duration: 60 Days

Topics: EC2, IAM, Lambda, S3, VPC

Outcome: AWS Cloud Practitioner + Associate Architect

Perks: Live labs, real projects, mock interviews

🔹 Microsoft Azure Course — Admin, DevOps & More

Duration: 45 Days

Topics: VMs, Blob Storage, Azure AD, DevOps with multi cloud in Kphb .

Certifications: AZ-900 & AZ-104

Best For: System Admins, career switchers, IT support

🔹 Google Cloud (GCP) Course — Build with AI & Big Data

Duration: 30 Days

Topics: Compute Engine, IAM, App Engine, BigQuery

Certifications: Associate Cloud Engineer

Best For: Data science, Python learners, analytics-focused roles

📅 New Batches Just Opened at NareshIT 👉 Click here to view our cloud training schedules Choose from online, offline, and fast-track options.

🔍 What Makes NareshIT Different?

🧑🏫 Mentors with real cloud project experience

🧪 Hands-on labs, not just slides

🎓 Certification prep + resume building

💬 Live doubt-clearing sessions

💼 Placement guidance after course completion

Whether you’re studying on weekends or starting full-time, we’ll help you move from theory to hiring room.

🚀 Final Thoughts: The First Step Matters Most

You don’t need a fancy degree to start. You don’t need to be a tech wizard. You just need to begin — with a structured path and the right support.

At NareshIT, we’ve trained over 100,000 learn

[ameliakeli]

CloudFuze Wins 2025 Google Cloud Partner of the Year Award!