Qubetics presale offers 1079.25% ROI, making it the best crypto to buy now. Don’t miss out on CRO's Google Cloud boost and IMX's seamless Web3 upgrade.

Qubetics Presale: Best Crypto to Buy Now with CRO & IMX Updates

As 2024 draws to a close, Google Cloud Security’s Cybersecurity Forecast 2025 offers a grounded outlook on the cybersecurity challenges and trends expected in

Google’s Cybersecurity Forecast 2025 (Key Insights and Trends for the Year Ahead) - SOCRadar® Cyber Intelligence Inc.

Google’s head of cloud security response has announced a new critical move to make security less cloudy and more transparent. Here’s what we know.

Google Cloud Goes Transparent With New Critical Security Announcement

Google Cloud will be assigning CVE identifiers to serious cloud vulnerabilities, even ones that don’t require patching.

Google Cloud to Assign CVEs to Critical Vulnerabilities - SecurityWeek

And as the MVB Program continues with support from Google Cloud, the BNB Chain ecosystem is only going to get bigger and better.

Google Cloud Backs BNB Chain’s Builder Program - Altcoin Buzz

Google Cloud partners with BNB Chain and ZetaChain, marking a dual investment in blockchain innovation, development, and security.

Google Cloud Dives Deeper into Blockchain with New BNB Chain and ZetaChain Partnership

12, 2024 (GLOBE NEWSWIRE) -- Recursion (NASDAQ: RXRX), a leading clinical stage TechBio company decoding biology to industrialize drug discovery, announced today the release of OpenPhenom-S/16, a publicly available foundation model in Google Cloud’s Vertex AI Model Garden.

Recursion Announces the Release of OpenPhenom-S/16 in Google Cloud’s Model Garden

Google Cloud is now collaborating with ZetaChain as a network validator, aiming to accelerate the growth of Web3 technology and Universal Apps within the ZetaChain ecosystem. ZetaChain is a Web3 project focused on creating a Universal Blockchain, enabling seamless connections across any blockchain.

Google Cloud becomes a validator on ZetaChain to boost Web3 growth | CryptoTvplus - The Leading Blockchain Media Firm

NTT Data, a global digital business and IT services company, announced on Monday an expansion of its strategic partnership with Google Cloud. The collaboration aims to accelerate cloud-based data analytics and generative AI solutions across the Asia-Pacific (APAC) region, with the ambitious target o

NTT Data Expands Google Cloud Partnership | siliconindia

HANOVER, Md.–(BUSINESS WIRE)–TEKsystems Global Services, a global provider of technology and business solutions, announced its strategic partnership agreement with Google Cloud to help customers achieve greater agility and scalability through IP-driven services.

TEKsystems Global Services Announces Strategic Partnership with Google Cloud | citybiz

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Google Cloud x Gemini: Accomplish More in the Cloud with Generative AI

Generative AI is a type of machine learning and artificial intelligence (AI) that is garnering a lot of attention right now, and we want to help keep you a step ahead by sharing the latest training available from Google Cloud. In this blog, we have compiled resources to help you learn about generative AI, how it can impact your business, and how to use it. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. We have brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost. This includes two learning paths that each feature comprehensive content: one is for the non-technical audience (introductory) ‘Introduction to Generative AI learning path’, and the other is for technical practitioners (more advanced) ‘Generative AI for Developers learning path’. Prefer less of a time commitment? Opt for individual courses and labs with the topics that suit your specific interest. Powered by Google Cloud technology, generative AI is reimagining the way that organizations do business by leveraging data. The use cases are far-ranging, from having smarter conversations with and creating rich experiences for customers, to enhancing business processes, to helping developers write code, and more. Google Cloud has been working for decades to bring AI technology solutions to organizations, and our tools make it easier to build experiences across our cloud portfolio. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI. Plus, labs give you direct access to Generative AI Studio and Vertex AI (Google Cloud’s machine learning platform) to get hands-on, technical experience. Get started with our training list below. No-cost foundational courses: no technical experience needed Don’t have a lot of time but want to learn the basics? Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. If getting started has you hungry to learn more, continue your no-cost learning to earn the Generative AI Fundamentals skill badge. It includes the course above, plus two other courses: ‘Introduction to Large Language Models’ and ‘Introduction to Responsible AI’. In total, this takes about two hours to complete and you’ll earn a digital skill badge to share on your resume and social channels to validate your foundational understanding of Google Cloud generative AI technology. Dig in deeper with our generative AI learning paths For a more comprehensive learning experience, choose from our two new gen AI learning paths — a mix of courses, labs and skill badges. Please note: we plan to add new trainings to this list, so keep checking back for more. Introduction to Generative AI - this path includes no-cost video courses. Content is non-technical, introductory, and designed for the tech-adjacent audience: roles like sales, HR, marketing and operations. Here is a look at the content: Introduction to Generative AI - course
Introduction to Large Language Models - course
Introduction to Responsible AI - course
Generative AI Fundamentals - earn a skill badge
Responsible AI: Applying AI Principals with Google Cloud - course Generative AI for Developers - this path includes a combination of technical hands-on labs and courses and requires Google Cloud credits to complete. It is designed for technical developers who work with gen AI, and includes the introductory training as a prerequisite. Content includes: Responsible AI for Developers - course
Introduction to Image Generation - course
Attention Mechanism - course
Encoder-Decoder Architecture - course
Transformer Models and BERT Model - course
Create Image Captioning Models - course
Introduction to Generative AI Studio - course
Generative AI Explorer: Vertex AI - earn a skill badge
Explore and Evaluate Models Using Model Garden - lab
Prompt Design Using PaLM - lab Gain technical experience with labs We currently offer these generative AI labs for anyone looking to get some hands-on experience by working directly in Google Cloud: Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes
Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes
Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes
Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes
Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes
Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes
Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Text embeddings with DeepLearning.AI and Andrew Ng We have brand new content built in collaboration with DeepLearning.AI, taught by Andrew Ng, founder of DeepLearning.AI and a globally recognized leader on the topic. Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” to learn various tasks like classification, outlier detection, text clustering, and semantic search. You’ll also learn to integrate them into LLM applications. Check out the video below to hear about these exciting opportunities found within text embeddings and generative AI. https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true New for technical practitioners: Intro to AI and ML Learn the big picture of how Google supports the data-to-AI journey and how generative AI is embedded in the AI development platform in our new course, Introduction to AI and Machine Learning on Google Cloud, designed mainly for technical practitioners — AI developers, data scientists, and ML engineers. The course covers the technologies, products and tools used to build an ML model, an ML pipeline, and a gen AI project based on the goals of data and AI practitioners. Made up of four primary modules that include labs and quizzes, this introductory course takes about six hours to complete and requires 12 credits. Stay on the cloud fast track with Innovators Plus Generative AI is  constantly evolving, and we’re developing new training materials to help you keep your career knowledge and skills up to date. An Innovators Plus subscription gives you access not only to generative AI content, but the full Google Cloud Skills Boost catalog of on-demand training for a whole year. You get $1,500 in developer benefits for only $299, including up to $1,000 in Google Cloud credits. Considering getting certified? You’ll also get an exam voucher, plus special access to Google Cloud experts and execs, live learning events, and more to round out your knowledge. Check out the details and sign up here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. Originally published here. Contributed by: Google Cloud Generative AI is a type of machine learning and artificial intelligence (AI) that is garnering a lot of attention right now, and we want to help keep you a step ahead by sharing the latest training available from Google Cloud. In this blog, we have compiled resources to help you learn about generative AI, how it can impact your business, and how to use it. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here We have brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost . This includes two learning paths that each feature comprehensive content: one is for the non-technical audience (introductory) ‘ Introduction to Generative AI learning path ’, and the other is for technical practitioners (more advanced) ‘ Generative AI for Developers learning path ’. Prefer less of a time commitment? Opt for individual courses and labs with the topics that suit your specific interest. brand-new generative AI training options, and are constantly adding to our training catalog on Google Cloud Skills Boost Introduction to Generative AI learning path Introduction to Generative AI learning path Generative AI for Developers learning path Generative AI for Developers learning path Powered by Google Cloud technology, generative AI is reimagining the way that organizations do business by leveraging data. The use cases are far-ranging , from having smarter conversations with and creating rich experiences for customers, to enhancing business processes, to helping developers write code, and more. use cases are far-ranging use cases are far-ranging Google Cloud has been working for decades to bring AI technology solutions to organizations, and our tools make it easier to build experiences across our cloud portfolio. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI . Plus, labs give you direct access to Generative AI Studio and Vertex AI (Google Cloud’s machine learning platform) to get hands-on, technical experience. Get started with our training list below. Whether you’re executive-level, an IT decision maker, in a non-technical role, or a technical practitioner, we have videos, courses and labs to help you learn about the power of generative AI No-cost foundational courses: no technical experience needed Don’t have a lot of time but want to learn the basics? Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. Our no-cost Introduction to Generative AI course is a great place to start. It takes about 45 minutes to finish. Introduction to Generative AI Introduction to Generative AI If getting started has you hungry to learn more, continue your no-cost learning to earn the Generative AI Fundamentals skill badge . It includes the course above, plus two other courses: ‘Introduction to Large Language Models’ and ‘Introduction to Responsible AI’. In total, this takes about two hours to complete and you’ll earn a digital skill badge to share on your resume and social channels to validate your foundational understanding of Google Cloud generative AI technology. continue your no-cost learning Generative AI Fundamentals skill badge Generative AI Fundamentals skill badge two hours to complete Dig in deeper with our generative AI learning paths For a more comprehensive learning experience, choose from our two new gen AI learning paths — a mix of courses, labs and skill badges. Please note: we plan to add new trainings to this list, so keep checking back for more. Introduction to Generative AI - this path includes no-cost video courses . Content is non-technical, introductory, and designed for the tech-adjacent audience: roles like sales, HR, marketing and operations. Here is a look at the content: Introduction to Generative AI Introduction to Generative AI Introduction to Generative AI this path includes no-cost video courses Introduction to Generative AI - course Introduction to Large Language Models - course Introduction to Responsible AI - course Generative AI Fundamentals - earn a skill badge Responsible AI: Applying AI Principals with Google Cloud - course Introduction to Generative AI - course Introduction to Large Language Models - course Introduction to Responsible AI - course Generative AI Fundamentals - earn a skill badge Responsible AI: Applying AI Principals with Google Cloud - course Generative AI for Developers - this path includes a combination of technical hands-on labs and courses and requires Google Cloud credits to complete. It is designed for technical developers who work with gen AI, and includes the introductory training as a prerequisite. Content includes: Generative AI for Developers Generative AI for Developers Generative AI for Developers Responsible AI for Developers - course Introduction to Image Generation - course Attention Mechanism - course Encoder-Decoder Architecture - course Transformer Models and BERT Model - course Create Image Captioning Models - course Introduction to Generative AI Studio - course Generative AI Explorer: Vertex AI - earn a skill badge Explore and Evaluate Models Using Model Garden - lab Prompt Design Using PaLM - lab Responsible AI for Developers - course Introduction to Image Generation - course Attention Mechanism - course Encoder-Decoder Architecture - course Transformer Models and BERT Model - course Create Image Captioning Models - course Introduction to Generative AI Studio - course Generative AI Explorer: Vertex AI - earn a skill badge Explore and Evaluate Models Using Model Garden - lab Prompt Design Using PaLM - lab Gain technical experience with labs We currently offer these generative AI labs for anyone looking to get some hands-on experience by working directly in Google Cloud: Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Get Started with Generative AI Studio (requires one credit) - introductory, 60 minutes Get Started with Generative AI Studio Get Started with Generative AI Studio Generative AI with Vertex AI: Getting Started (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Getting Started Generative AI with Vertex AI: Getting Started Generative AI with Vertex AI: Prompt Design (requires one credit) - introductory, 90 minutes Generative AI with Vertex AI: Prompt Design Generative AI with Vertex AI: Prompt Design Vertex AI PaLM API: Qwik Start (requires one credit) - introductory, 60 minutes Vertex AI PaLM API: Qwik Start Vertex AI PaLM API: Qwik Start Integrate Search in Applications Using Gen AI App Builder (requires five credits) - introductory, 90 minutes Integrate Search in Applications Using Gen AI App Builder Integrate Search in Applications Using Gen AI App Builder Prompt Design using PaLM (requires one credit)  - intermediate, 90 minutes Prompt Design using PaLM Prompt Design using PaLM Explore and Evaluate Models using Model Garden (requires five credits) - intermediate, 60 minutes Explore and Evaluate Models using Model Garden Explore and Evaluate Models using Model Garden Text embeddings with DeepLearning.AI and Andrew Ng We have brand new content built in collaboration with DeepLearning.AI , taught by Andrew Ng, founder of DeepLearning.AI and a globally recognized leader on the topic. Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” to learn various tasks like classification, outlier detection, text clustering, and semantic search. You’ll also learn to integrate them into LLM applications. Check out the video below to hear about these exciting opportunities found within text embeddings and generative AI. DeepLearning.AI DeepLearning.AI DeepLearning.AI DeepLearning.AI Enroll for no-cost in “Understanding and Applying Text Embeddings with Vertex AI” “Understanding and Applying Text Embeddings with Vertex AI” “Understanding and Applying Text Embeddings with Vertex AI” https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true https://youtu.be/9SYpG_tFT38?si=BqFxnCisV2z5Xs2h&embedable=true New for technical practitioners: Intro to AI and ML Learn the big picture of how Google supports the data-to-AI journey and how generative AI is embedded in the AI development platform in our new course, Introduction to AI and Machine Learning on Google Cloud , designed mainly for technical practitioners — AI developers, data scientists, and ML engineers. The course covers the technologies, products and tools used to build an ML model, an ML pipeline, and a gen AI project based on the goals of data and AI practitioners. Made up of four primary modules that include labs and quizzes, this introductory course takes about six hours to complete and requires 12 credits. Introduction to AI and Machine Learning on Google Cloud Introduction to AI and Machine Learning on Google Cloud this introductory course takes about six hours to complete and requires 12 credits. Stay on the cloud fast track with Innovators Plus Generative AI is  constantly evolving, and we’re developing new training materials to help you keep your career knowledge and skills up to date. An Innovators Plus subscription gives you access not only to generative AI content, but the full Google Cloud Skills Boost catalog of on-demand training for a whole year. You get $1,500 in developer benefits for only $299, including up to $1,000 in Google Cloud credits. Considering getting certified? You’ll also get an exam voucher, plus special access to Google Cloud experts and execs, live learning events, and more to round out your knowledge. Check out the details and sign up here . sign up here sign up here New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here Originally published here . here Contributed by: Google Cloud

Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level

Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform

For decades, threat intelligence solutions have had two main challenges: They lack a comprehensive view of the threat landscape, and to get value from intelligence, organizations have to spend excess time, energy, and money trying to collect and operationalize the data. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. Recently, at the RSA Conference in San Francisco, we announced Google Threat Intelligence, a new offering that combines the unmatched depth of our Mandiant frontline expertise, the global reach of the VirusTotal community, and the breadth of visibility only Google can deliver based on billions of signals across devices and emails. Google Threat Intelligence includes Gemini in Threat Intelligence, our AI-powered agent that provides conversational search across our vast repository of threat intelligence, enabling customers to gain insights and protect themselves from threats faster than ever before. “While there is no shortage of threat intelligence available, the challenge for most is to contextualize and operationalize intelligence relevant to their specific organization,” said Dave Gruber, principal analyst, Enterprise Strategy Group. “Unarguably, Google provides two of the most important pillars of threat intelligence in the industry today with VirusTotal and Mandiant. Integrating both into a single offering, enhanced with AI and Google threat insights, offers security teams a new means to operationalize actionable threat intelligence to better protect their organizations.” Unmatched visibility into threats Google Threat Intelligence provides unparalleled visibility into the global threat landscape. We offer deep insights from Mandiant’s leading incident response and threat research team, and combine them with our massive user and device footprint and VirusTotal’s broad crowdsourced malware database. Google threat insights: Google protects 4 billion devices and 1.5 billion email accounts, and blocks 100 million phishing attempts per day. This provides us with a vast sensor array and a unique perspective on internet and email-borne threats that allow us to connect the dots back to attack campaigns.
Frontline intelligence: Mandiant's eIite incident responders, security consultants, and frontline intelligence operations analysts dissect attacker tactics and techniques, using their experience to help customers defend against sophisticated and relentless threat actors across the globe in over 1,100 investigations annually, resulting in a corpus of over 15 years of frontline intelligence.
Human-curated threat intelligence: Mandiant’s global threat experts meticulously monitor threat actor groups for activity and changes in their behavior to contextualize ongoing investigations and provide the insights you need to respond.
Crowdsourced threat intelligence: VirusTotal's global community of over 1 million users continuously contributes potential threat indicators, including files and URLs, to offer real-time insight into emerging attacks.
Open-source threat intelligence: We use open-source threat intelligence to enrich our knowledge base with current discoveries from the security community. This comprehensive view allows Google Threat Intelligence to help protect your organization in a variety of ways, including external threat monitoring, attack surface management, digital risk protection, Indicators of Compromise (IOC) analysis, and expertise. AI-driven operationalization Traditional approaches to operationalizing threat intelligence are labor-intensive and can slow down your ability to respond to evolving threats, potentially taking days or weeks to respond. https://youtu.be/QGUri8v4THc?embedable=true By combining our comprehensive view of the threat landscape with Gemini, we have supercharged the threat research processes, augmented defense capabilities, and reduced the time it takes to identify and protect against novel threats. Customers now have the ability to condense large data sets in seconds, quickly analyze suspicious files, and simplify challenging manual threat intelligence tasks. How Gemini helps simplify and assist with threat intelligence Gemini 1.5 Pro is a valuable part of Google Threat Intelligence, and we’ve integrated it so that it can more efficiently and effectively assist security professionals in combating malware. Gemini 1.5 Pro offers the world’s longest context window, with support for up to 1 million tokens. It can dramatically simplify the technical and labor-intensive process of reverse engineering malware — one of the most advanced malware-analysis techniques available to cybersecurity professionals. In fact, it was able to process the entire decompiled code of the malware file for WannaCry in a single pass, taking 34 seconds to deliver its analysis and identify the killswitch. We also offer a Gemini-driven entity extraction tool to automate data fusion and enrichment. It can automatically crawl the web for relevant open source intelligence (OSINT), and classify online industry threat reporting. It then converts this information to knowledge collections, with corresponding hunting and response packs pulled from motivations, targets, tactics, techniques, and procedures (TTPs), actors, toolkits, and Indicators of Compromise (IoCs). Google Threat Intelligence can distill more than a decade of threat reports to produce comprehensive, custom summaries in seconds. Make Google part of your security team Google Threat Intelligence is just one way we can help you in your threat intelligence journey. Whether you need cyber threat intelligence training for your staff, assistance with prioritizing complex threats, or even a dedicated threat analyst embedded in your team, our experts can act as an extension of your own team. Google Threat Intelligence is part of Google Cloud Security’s comprehensive security portfolio, which includes Google Security Operations, Mandiant Consulting, Security Command Center Enterprise, and Chrome Enterprise. With our offerings, organizations can address security challenges with the same capabilities Google uses to keep more people and organizations safe online than anyone else in the world. To learn more about Google Threat Intelligence and the rest of Google Cloud Security’s comprehensive portfolio, come meet us in person at our RSA Conference booth (N5644), and catch us at our keynotes, presentations, and meetups. You can also register for our upcoming Google Threat Intelligence use-cases webinar series, and read our expert analysis and in-depth research at the Google Cloud Threat Intelligence blog. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. Originally published here. Contributed by: Google Cloud For decades, threat intelligence solutions have had two main challenges: They lack a comprehensive view of the threat landscape, and to get value from intelligence, organizations have to spend excess time, energy, and money trying to collect and operationalize the data. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here Recently, at the RSA Conference in San Francisco, we announced Google Threat Intelligence, a new offering that combines the unmatched depth of our Mandiant frontline expertise, the global reach of the VirusTotal community, and the breadth of visibility only Google can deliver based on billions of signals across devices and emails. Google Threat Intelligence includes Gemini in Threat Intelligence, our AI-powered agent that provides conversational search across our vast repository of threat intelligence, enabling customers to gain insights and protect themselves from threats faster than ever before. “While there is no shortage of threat intelligence available, the challenge for most is to contextualize and operationalize intelligence relevant to their specific organization,” said Dave Gruber, principal analyst, Enterprise Strategy Group. “Unarguably, Google provides two of the most important pillars of threat intelligence in the industry today with VirusTotal and Mandiant. Integrating both into a single offering, enhanced with AI and Google threat insights, offers security teams a new means to operationalize actionable threat intelligence to better protect their organizations.” “While there is no shortage of threat intelligence available, the challenge for most is to contextualize and operationalize intelligence relevant to their specific organization,” said Dave Gruber, principal analyst, Enterprise Strategy Group. “Unarguably, Google provides two of the most important pillars of threat intelligence in the industry today with VirusTotal and Mandiant. Integrating both into a single offering, enhanced with AI and Google threat insights, offers security teams a new means to operationalize actionable threat intelligence to better protect their organizations.” Unmatched visibility into threats Google Threat Intelligence provides unparalleled visibility into the global threat landscape. We offer deep insights from Mandiant’s leading incident response and threat research team, and combine them with our massive user and device footprint and VirusTotal’s broad crowdsourced malware database. Google threat insights: Google protects 4 billion devices and 1.5 billion email accounts, and blocks 100 million phishing attempts per day. This provides us with a vast sensor array and a unique perspective on internet and email-borne threats that allow us to connect the dots back to attack campaigns. Frontline intelligence: Mandiant's eIite incident responders, security consultants, and frontline intelligence operations analysts dissect attacker tactics and techniques, using their experience to help customers defend against sophisticated and relentless threat actors across the globe in over 1,100 investigations annually, resulting in a corpus of over 15 years of frontline intelligence. Human-curated threat intelligence: Mandiant’s global threat experts meticulously monitor threat actor groups for activity and changes in their behavior to contextualize ongoing investigations and provide the insights you need to respond. Crowdsourced threat intelligence: VirusTotal's global community of over 1 million users continuously contributes potential threat indicators, including files and URLs, to offer real-time insight into emerging attacks. Open-source threat intelligence: We use open-source threat intelligence to enrich our knowledge base with current discoveries from the security community. Google threat insights: Google protects 4 billion devices and 1.5 billion email accounts, and blocks 100 million phishing attempts per day. This provides us with a vast sensor array and a unique perspective on internet and email-borne threats that allow us to connect the dots back to attack campaigns. Google threat insights: Frontline intelligence: Mandiant's eIite incident responders, security consultants, and frontline intelligence operations analysts dissect attacker tactics and techniques, using their experience to help customers defend against sophisticated and relentless threat actors across the globe in over 1,100 investigations annually, resulting in a corpus of over 15 years of frontline intelligence. Frontline intelligence: Human-curated threat intelligence: Mandiant’s global threat experts meticulously monitor threat actor groups for activity and changes in their behavior to contextualize ongoing investigations and provide the insights you need to respond. Human-curated threat intelligence: Crowdsourced threat intelligence: VirusTotal's global community of over 1 million users continuously contributes potential threat indicators, including files and URLs, to offer real-time insight into emerging attacks. Crowdsourced threat intelligence: Open-source threat intelligence : We use open-source threat intelligence to enrich our knowledge base with current discoveries from the security community. Open-source threat intelligence This comprehensive view allows Google Threat Intelligence to help protect your organization in a variety of ways, including external threat monitoring, attack surface management, digital risk protection, Indicators of Compromise (IOC) analysis, and expertise. AI-driven operationalization Traditional approaches to operationalizing threat intelligence are labor-intensive and can slow down your ability to respond to evolving threats, potentially taking days or weeks to respond. https://youtu.be/QGUri8v4THc?embedable=true https://youtu.be/QGUri8v4THc?embedable=true By combining our comprehensive view of the threat landscape with Gemini, we have supercharged the threat research processes, augmented defense capabilities, and reduced the time it takes to identify and protect against novel threats. Customers now have the ability to condense large data sets in seconds, quickly analyze suspicious files, and simplify challenging manual threat intelligence tasks. How Gemini helps simplify and assist with threat intelligence How Gemini helps simplify and assist with threat intelligence Gemini 1.5 Pro is a valuable part of Google Threat Intelligence, and we’ve integrated it so that it can more efficiently and effectively assist security professionals in combating malware. Gemini 1.5 Pro offers the world’s longest context window, with support for up to 1 million tokens . It can dramatically simplify the technical and labor-intensive process of reverse engineering malware — one of the most advanced malware-analysis techniques available to cybersecurity professionals. In fact, it was able to process the entire decompiled code of the malware file for WannaCry in a single pass , taking 34 seconds to deliver its analysis and identify the killswitch. 1 million tokens 1 million tokens WannaCry in a single pass WannaCry in a single pass We also offer a Gemini-driven entity extraction tool to automate data fusion and enrichment. It can automatically crawl the web for relevant open source intelligence (OSINT), and classify online industry threat reporting. It then converts this information to knowledge collections, with corresponding hunting and response packs pulled from motivations, targets, tactics, techniques, and procedures (TTPs), actors, toolkits, and Indicators of Compromise (IoCs). Google Threat Intelligence can distill more than a decade of threat reports to produce comprehensive, custom summaries in seconds. Make Google part of your security team Make Google part of your security team Google Threat Intelligence is just one way we can help you in your threat intelligence journey. Whether you need cyber threat intelligence training for your staff, assistance with prioritizing complex threats, or even a dedicated threat analyst embedded in your team, our experts can act as an extension of your own team. Google Threat Intelligence is part of Google Cloud Security’s comprehensive security portfolio, which includes Google Security Operations , Mandiant Consulting , Security Command Center Enterprise , and Chrome Enterprise . With our offerings, organizations can address security challenges with the same capabilities Google uses to keep more people and organizations safe online than anyone else in the world. Google Security Operations Google Security Operations Mandiant Consulting Mandiant Consulting Security Command Center Enterprise Security Command Center Enterprise Chrome Enterprise Chrome Enterprise To learn more about Google Threat Intelligence and the rest of Google Cloud Security’s comprehensive portfolio, come meet us in person at our RSA Conference booth (N5644), and catch us at our keynotes, presentations, and meetups . You can also register for our upcoming Google Threat Intelligence use-cases webinar series , and read our expert analysis and in-depth research at the Google Cloud Threat Intelligence blog . Google Threat Intelligence Google Threat Intelligence RSA Conference booth RSA Conference booth keynotes, presentations, and meetups keynotes, presentations, and meetups Google Threat Intelligence use-cases webinar series Google Threat Intelligence use-cases webinar series Threat Intelligence blog Threat Intelligence blog New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here. New Google Cloud customers from HackerNoon receive $300 plus an additional $50 in free credits to test, deploy, and explore Google Cloud for 90 days. Get started using the link here . here Originally published here . here Contributed by: Google Cloud

Actionable Threat Intelligence at Google Scale: Meet Google Threat Intelligence Powered by Gemini

Axion Processors: Google's First Arm-based CPUs

Building an API with Go, PostgreSQL, Google Cloud and CockroachDB

Flare has launched its Blockchain Machine Images on Google Cloud Marketplace, enabling developers to deploy nodes across more than 20 blockchain networks with unprecedented speed and efficiency. The integration, announced on October 25, 2024, addresses a persistent challenge in blockchain development - the time-consuming process of node deployment and maintenance. Through this solution, developers can now launch full blockchain nodes within minutes, a process that traditionally required hours or days of setup and synchronization. "This integration removes barriers for builders, making node deployment accessible to anyone with just a few clicks," states Josh Edwards, Flare's VP of Engineering. The move positions Flare at the forefront of blockchain infrastructure development, expanding beyond the standard Bitcoin and Ethereum offerings common in the market. The platform's capabilities extend across multiple dimensions: Instant Deployment: Developers can launch nodes for Flare, Bitcoin, Ethereum, and other networks through a streamlined interface


Cost Reduction: The solution eliminates the need for extensive infrastructure investment


Maintenance Automation: Updates and patches can be implemented with single-click operations


Unlimited RPC Calls: The system supports unrestricted blockchain data access for intensive workloads For enterprises considering blockchain adoption, this development reduces the technical barriers to entry. Companies can now initiate blockchain pilots without investing in specialized infrastructure or technical expertise. The platform's integration with Google Cloud's infrastructure provides the security and scalability requirements that enterprise users demand. Dai Vu, Managing Director of Marketplace & ISV GTM Programs at Google Cloud, emphasizes the significance: "This integration enables customers to manage blockchains on Google Cloud's global infrastructure, supporting their digital transformation initiatives." The launch builds upon Flare's existing relationship with Google Cloud, complementing their API Portal that facilitates blockchain transactions and state access. This expansion demonstrates Flare's commitment to creating a comprehensive blockchain data infrastructure. Market implications suggest this development could accelerate blockchain adoption across industries. Financial technology companies can now integrate blockchain data into their applications with reduced technical overhead. The platform's support for data indexing and historical data access opens possibilities for advanced analytics and machine learning applications in the blockchain space. The broader impact extends to the blockchain ecosystem as a whole. By simplifying node deployment across multiple networks, Flare's solution could foster increased decentralization and network resilience. The ability to rapidly deploy nodes may lead to more robust and distributed blockchain networks. Looking ahead, Flare plans to expand support to additional blockchain networks, potentially establishing a new standard for blockchain infrastructure deployment. The company's focus on data-intensive use cases, including machine learning and real-world asset tokenization, positions this development as a stepping stone toward more sophisticated blockchain applications. This integration represents a convergence of enterprise-grade cloud infrastructure with blockchain technology, potentially catalyzing the next wave of blockchain innovation and adoption. As organizations continue to explore blockchain applications, solutions that simplify technical implementation while maintaining security and scalability will prove crucial for mainstream adoption. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Flare has launched its Blockchain Machine Images on Google Cloud Marketplace, enabling developers to deploy nodes across more than 20 blockchain networks with unprecedented speed and efficiency. Flare The integration, announced on October 25, 2024, addresses a persistent challenge in blockchain development - the time-consuming process of node deployment and maintenance. Through this solution, developers can now launch full blockchain nodes within minutes, a process that traditionally required hours or days of setup and synchronization. "This integration removes barriers for builders, making node deployment accessible to anyone with just a few clicks," states Josh Edwards, Flare's VP of Engineering. The move positions Flare at the forefront of blockchain infrastructure development, expanding beyond the standard Bitcoin and Ethereum offerings common in the market. The platform's capabilities extend across multiple dimensions: Instant Deployment: Developers can launch nodes for Flare, Bitcoin, Ethereum, and other networks through a streamlined interface Cost Reduction: The solution eliminates the need for extensive infrastructure investment Maintenance Automation: Updates and patches can be implemented with single-click operations Unlimited RPC Calls: The system supports unrestricted blockchain data access for intensive workloads Instant Deployment: Developers can launch nodes for Flare, Bitcoin, Ethereum, and other networks through a streamlined interface Instant Deployment: Developers can launch nodes for Flare, Bitcoin, Ethereum, and other networks through a streamlined interface Cost Reduction: The solution eliminates the need for extensive infrastructure investment Cost Reduction: The solution eliminates the need for extensive infrastructure investment Maintenance Automation: Updates and patches can be implemented with single-click operations Maintenance Automation: Updates and patches can be implemented with single-click operations Unlimited RPC Calls: The system supports unrestricted blockchain data access for intensive workloads Unlimited RPC Calls: The system supports unrestricted blockchain data access for intensive workloads For enterprises considering blockchain adoption, this development reduces the technical barriers to entry. Companies can now initiate blockchain pilots without investing in specialized infrastructure or technical expertise. The platform's integration with Google Cloud's infrastructure provides the security and scalability requirements that enterprise users demand. Dai Vu, Managing Director of Marketplace & ISV GTM Programs at Google Cloud, emphasizes the significance: "This integration enables customers to manage blockchains on Google Cloud's global infrastructure, supporting their digital transformation initiatives." The launch builds upon Flare's existing relationship with Google Cloud, complementing their API Portal that facilitates blockchain transactions and state access. This expansion demonstrates Flare's commitment to creating a comprehensive blockchain data infrastructure. Market implications suggest this development could accelerate blockchain adoption across industries. Financial technology companies can now integrate blockchain data into their applications with reduced technical overhead. The platform's support for data indexing and historical data access opens possibilities for advanced analytics and machine learning applications in the blockchain space. The broader impact extends to the blockchain ecosystem as a whole. By simplifying node deployment across multiple networks, Flare's solution could foster increased decentralization and network resilience. The ability to rapidly deploy nodes may lead to more robust and distributed blockchain networks. Looking ahead, Flare plans to expand support to additional blockchain networks, potentially establishing a new standard for blockchain infrastructure deployment. The company's focus on data-intensive use cases, including machine learning and real-world asset tokenization, positions this development as a stepping stone toward more sophisticated blockchain applications. This integration represents a convergence of enterprise-grade cloud infrastructure with blockchain technology, potentially catalyzing the next wave of blockchain innovation and adoption. As organizations continue to explore blockchain applications, solutions that simplify technical implementation while maintaining security and scalability will prove crucial for mainstream adoption. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

Flare Revolutionizes Blockchain Node Deployment with Google Cloud Marketplace Integration

Flare revolusioneer Blockchain Node-ontplooiing met Google Cloud Marketplace-integrasie

Flare revoluciona la implementación de nodos blockchain con la integración de Google Cloud Marketplace

Flare Merevolusi Penerapan Node Blockchain dengan Integrasi Google Cloud Marketplace

Flare が Google Cloud Marketplace との統合によりブロックチェーン ノードの展開を革新

Flare Google Cloud Marketplace интеграциясымен блокчейн түйінін орналастыруда төңкеріс жасайды

Flare Google Cloud Marketplace интеграциясы менен блокчейн түйүнүнүн жайылышын революция кылды

Flare Merevolusikan Penerapan Nod Blockchain dengan Penyepaduan Pasaran Awan Google

फ्लेयरले गुगल क्लाउड मार्केटप्लेस एकीकरणको साथ ब्लकचेन नोड परिनियोजनलाई क्रान्ति गर्दछ

Flare Google Cloud Marketplace Integration සමඟ Blockchain Node Deployment විප්ලවීය කරයි

கூகுள் கிளவுட் மார்க்கெட்ப்ளேஸ் ஒருங்கிணைப்புடன் பிளாக்செயின் நோட் வரிசைப்படுத்தலை ஃப்ளேர் புரட்சிகரமாக்குகிறது

“Flare” “Google Cloud Marketplace Integration” bilen “Blockchain” düwünleriniň ýerleşdirilmegini rewolýusiýa edýär

Flare cách mạng hóa việc triển khai nút Blockchain với tích hợp Google Cloud Marketplace

We are back with another Company of the Week feature! Every week, we share an awesome tech brand from our tech company database, making their evergreen mark on the internet. This unique HackerNoon database ranks S&P 500 companies and top startups of the year alike. This week, we are proud to present Google Cloud! Alphabet’s Google Cloud offers customers computing resources to power their artificial intelligence and machine learning workloads, capitalizing on the company’s years of experience running and managing large (dare we say, humongous!) servers. Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon! Google Cloud <> HackerNoon Tech Community Google Cloud recently utilized HackerNoon for its content marketing needs, highlighting some exciting courses and features to HackerNoon readers plus an offer to utilize up to $350 in free credits to test, deploy, and explore Google Cloud for 90 days. You can check out some of their recent posts below: Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level
Axion Processors: Google's First Arm-based CPUs
Actionable Threat Intelligence at Google Scale: Meet Google Threat Intelligence Powered by Gemini
Google Cloud x Gemini: Accomplish More in the Cloud with Generative AI
Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform Learn How You Can Book a Spot on HackerNoon’s Billboard Meet Google Cloud: #FunFacts We thought it would be interesting if we asked Gemini to tell us some fun little facts about Google Cloud. Here’s what it said: Did you know that Google Cloud powers the search engine giant's own services like Google Search, YouTube, and Gmail? That's right, the same technology that helps you find cat videos also runs some of the world's busiest websites! How about this: Google Cloud's enterprise data warehouse, BigQuery, is so powerful that it can process over 110 terabytes of data per second! That's like streaming thousands of high-definition movies simultaneously. 🤯 Google Cloud is helping to protect endangered species! Many organizations use Google Earth Engine, a cloud computing platform, to analyze satellite imagery and track deforestation, wildlife populations, and other environmental factors. It's like having a super-powered microscope for our planet! 🌍🐼 How’s that for interesting 😏 Experience the power of Google Cloud yourself and get $300 + $50 extra free trial credits Share Your Company's Story via HackerNoon That's all this week, folks! Stay Creative, Stay Iconic. The HackerNoon Team We are back with another Company of the Week feature! Every week, we share an awesome tech brand from our tech company database , making their evergreen mark on the internet. This unique HackerNoon database ranks S&P 500 companies and top startups of the year alike. Company of the Week Company of the Week tech company database tech company database This week, we are proud to present Google Cloud ! Alphabet’s Google Cloud offers customers computing resources to power their artificial intelligence and machine learning workloads, capitalizing on the company’s years of experience running and managing large (dare we say, humongous!) servers. Google Cloud Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon! Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon ! Want to be featured on HackerNoon’s Company of the Week? Request Your Tech Company Page on HackerNoon Google Cloud <> HackerNoon Tech Community Google Cloud recently utilized HackerNoon for its content marketing needs, highlighting some exciting courses and features to HackerNoon readers plus an offer to utilize up to $350 in free credits to test, deploy, and explore Google Cloud for 90 days. You can check out some of their recent posts below: exciting courses utilize Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level Axion Processors: Google's First Arm-based CPUs Actionable Threat Intelligence at Google Scale: Meet Google Threat Intelligence Powered by Gemini Google Cloud x Gemini: Accomplish More in the Cloud with Generative AI Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level Learn Generative AI with Google Cloud: New Courses from Introductory to Advanced Level Axion Processors: Google's First Arm-based CPUs Axion Processors: Google's First Arm-based CPUs Actionable Threat Intelligence at Google Scale: Meet Google Threat Intelligence Powered by Gemini Actionable Threat Intelligence at Google Scale: Meet Google Threat Intelligence Powered by Gemini Google Cloud x Gemini: Accomplish More in the Cloud with Generative AI Google Cloud x Gemini: Accomplish More in the Cloud with Generative AI Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Learn How You Can Book a Spot on HackerNoon’s Billboard Meet Google Cloud: #FunFacts We thought it would be interesting if we asked Gemini to tell us some fun little facts about Google Cloud. Here’s what it said: Did you know that Google Cloud powers the search engine giant's own services like Google Search, YouTube, and Gmail? That's right, the same technology that helps you find cat videos also runs some of the world's busiest websites! Did you know that Google Cloud powers the search engine giant's own services like Google Search, YouTube, and Gmail? That's right, the same technology that helps you find cat videos also runs some of the world's busiest websites! Did you know that Google Cloud powers the search engine giant's own services like Google Search, YouTube, and Gmail? How about this: Google Cloud's enterprise data warehouse, BigQuery, is so powerful that it can process over 110 terabytes of data per second! That's like streaming thousands of high-definition movies simultaneously. 🤯 How about this: Google Cloud's enterprise data warehouse, BigQuery, is so powerful that it can process over 110 terabytes of data per second! That's like streaming thousands of high-definition movies simultaneously. 🤯 Google Cloud is helping to protect endangered species! Many organizations use Google Earth Engine, a cloud computing platform, to analyze satellite imagery and track deforestation, wildlife populations, and other environmental factors. It's like having a super-powered microscope for our planet! 🌍🐼 Google Cloud is helping to protect endangered species! Many organizations use Google Earth Engine, a cloud computing platform, to analyze satellite imagery and track deforestation, wildlife populations, and other environmental factors. It's like having a super-powered microscope for our planet! 🌍🐼 Google Cloud is helping to protect endangered species! How’s that for interesting 😏 Experience the power of Google Cloud yourself and get $300 + $50 extra free trial credits Experience the power of Google Cloud yourself and get $300 + $50 extra free trial credits $300 + $50 extra free trial credits Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon Share Your Company's Story via HackerNoon That's all this week, folks! Stay Creative, Stay Iconic. The HackerNoon Team

Meet Google Cloud: HackerNoon Company of the Week

Google ক্লাউডের সাথে দেখা করুন: সপ্তাহের হ্যাকারনুন কোম্পানি

Lernen Sie Google Cloud kennen: HackerNoon-Unternehmen der Woche

Conozca Google Cloud: la empresa de la semana de HackerNoon

Découvrez Google Cloud : Entreprise de la semaine selon HackerNoon

गूगल क्लाउड से मिलिए: हैकरनून कंपनी ऑफ द वीक

Google Cloud のご紹介: HackerNoon の今週の企業

Google Cloud를 만나보세요: HackerNoon 주간 회사

Conheça o Google Cloud: HackerNoon Empresa da Semana

Встречайте Google Cloud: компания недели HackerNoon

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Gặp gỡ Google Cloud: Công ty của tuần HackerNoon

了解 Google Cloud：HackerNoon 本周公司

This tutorial shows you how to deploy and automate a Docker container using Pulumi in Google Cloud Platform's Cloud Run with minimum permissions. Here's the GitHub Repository for reference: https://github.com/superjose/deploy-to-cloud-run-go Get the CLIs: . Create a Google Cloud Account Install Google Cloud CLI Install Pulumi CLI - We need it to build the Docker container. Install Docker Bootstrap the project: Create a directory: pulumi mkdir pulumi Run to initialize a pulumi project with Go (It can be your language of choice pulumi new go Navigate to the directory. pulumi cd pulumi Navigate to and create a new project. cloud.google.com Take note of the (Usually the project's name). project-id Generate the necessary permissions using gcloud CLI Login with the Google Auth CLI: gcloud auth login (Optional) Set the project in google cloud CLI (Can be changed anytime). This saves you from passing into every command. --project [PROJECT-ID] gcloud If your machine has multiple GCP projects, skip this step and pass the flag into every command. --project gcloud Create a service account (The account that Pulumi will connect to): gcloud iam service-accounts create pulumi-gcp --description="Pulumi GCP" Download the credentials for the service accounts and store them locally (Remember to replace with your GCP Project Id): [PROJECT-ID] gcloud iam service-accounts keys create ~/keys/gcp/pulumi-service-account-key-file.json --iam-account=pulumi-gcp@[PROJECT-ID].iam.gserviceaccount.com Set Pulumi's gcp credentials config path:
(This will connect the service account with Pulumi) pulumi config set gcp:credentials ~/keys/gcp/pulumi-service-account-key-file.json Set the GCP Project by doing: pulumi config set gcp:project [PROJECT-ID] Create a file (Inside the dir) and add the required permissions in : roles.gcp.yml pulumi includedPermissions # https://cloud.google.com/iam/docs/creating-custom-roles#creating
# Yaml to define the Pulumi GCP Roles that need to be created with gcloud CLI
title: Pulumi GCP Roles
description: |
  This policy ensures that all GCP roles are created using Pulumi.
stage: GA
# https://cloud.google.com/iam/docs/permissions-reference
includedPermissions:
  - serviceusage.services.list
  - serviceusage.services.enable
  - serviceusage.services.disable
  - serviceusage.services.get
  - serviceusage.services.use
    # Permissions for GCR
  - storage.objects.create
  - storage.objects.delete # Optional: only include if you need to delete images
  - storage.objects.get
  # Permissions for Google Artifact Registry
  - artifactregistry.repositories.create
  - artifactregistry.repositories.delete
  - artifactregistry.repositories.get
  - artifactregistry.repositories.list
  - artifactregistry.repositories.update
  - artifactregistry.repositories.downloadArtifacts
  - artifactregistry.repositories.uploadArtifacts
  - artifactregistry.repositories.deleteArtifacts
  # Permissions
  # Permissions
  - run.services.create
  - run.services.get
  - run.services.list
  - run.services.update
  - run.services.delete
  - run.services.getIamPolicy
  - run.services.setIamPolicy
  - iam.serviceAccounts.actAs
# NOTE: This should be removed the first time you're creating a role.
# This etag is to update the current active role (As GCP lets you manage multiple roles)
# I'm commenting it out so I can always replace the role
# etag: BwYS74Xx5y4= Create the with the file above:
(We assume we're running this code from the directory) pulumi_admin_role pulumi gcloud iam roles create pulumi_admin_role --project=[PROJECT-ID] --file='./roles.gcp.yml' In case you need to make edits, change the file and use: gcloud iam roles update pulumi_admin_role --project=[PROJECT-ID] --file='./roles.gcp.yml' We're also adding the role (I haven't found a better way) (Otherwise we'd get 403 errors when refreshing and updating in Pulumi)<sup>1</sup> serviceAccountAdmin gcloud projects add-iam-policy-binding [PROJECT-ID] --role roles/iam.serviceAccountAdmin   --member serviceAccount:pulumi-gcp@[PROJECT-ID].iam.gserviceaccount.com (The following will add the new role to the service account) gcloud projects add-iam-policy-binding [PROJECT-ID] --role projects/[PROJECT-ID]/roles/pulumi_admin_role   --member serviceAccount:pulumi-gcp@[PROJECT-ID].iam.gserviceaccount.com Our in the directory:
(Check the code for comments!) main.go pulumi We enable the required services (Artifact Registry, and Cloud Run). Artifact Registry is used to host the docker container image. Cloud Runner will launch the Docker image from Artifact Registry. We build the docker image locally (We specify the platform in case you're using an ARM chip like M1, M2, Snapdragon SQ, X Elite, etc.) We create a chain of "DependsOn" to notify Pulumi:
5.1 Services need to be enabled first
5.2 We create the Artifact Repository
5.3 We build the docker image and push it to Artifact Registry.
5.4 We pull the Docker Image from Artifact Registry and run it.
5.5 We add IAM permissions so it can be accessed from anywhere. package main

import (
	"errors"
	"log"
	"os"

	"github.com/joho/godotenv"
	"github.com/pulumi/pulumi-docker/sdk/v3/go/docker"
	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/artifactregistry"
	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/cloudrun"
	"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/projects"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

// This is the name you created in Google Cloud Platform (GCP).
const gcpProjectId = "deploy-to-cloud-run-go"

// The Docker Image Name
const dockerImageName = "my-app-docker"
const artifactRegistryServiceName = "artifact-registry-api"
const artifactRegistryRepoName = "my-app-artifact-repo"
const artifactRegistryRepoLocation = "us-east1"
const cloudRunAdminServiceName = "cloud-run-admin-service"
const cloudRunServiceName = "cloud-run-service"

// For more info: https://cloud.google.com/run/docs/locations
const cloudRunLocation = "us-east1"

// The tag for the Docker image
const imageTag = "latest"

// This is a url like: us-east1-docker.pkg.dev
// It is used to push the Docker image to Google Container Registry
// For more info: https://cloud.google.com/container-registry/docs/pushing-and-pulling
// The format is: <region>-docker.pkg.dev
var dockerGCPServer = cloudRunLocation + "-docker.pkg.dev"

// The full path to the Docker image
// It is used to deploy the Docker image to Google Cloud Run
// The format is: <region>-docker.pkg.dev/<project-id>/<repo-name>/<image-name>:<tag>
// For more info: https://cloud.google.com/run/docs/deploying
// Example: us-east1-docker.pkg.dev/deploy-to-cloud-run-go/my-app--artifact-repo/my-app-docker:latest
var dockerImageWithPath = dockerGCPServer + "/" + gcpProjectId + "/" + artifactRegistryRepoName + "/" + dockerImageName + ":" + imageTag

func main() {

	// Load the .env file
	err := godotenv.Load()

	if err != nil {
		log.Fatal("Error loading .env file")
	}

	pulumi.Run(func(ctx *pulumi.Context) error {

		enabledServices, serviceResultErr := enableServices(ctx)

		if serviceResultErr != nil {
			return serviceResultErr
		}

		artifactRegistryRepo, createArtifactErr := createArtifactRegistryNewRepository(ctx, &enabledServices)
		if createArtifactErr != nil {
			return createArtifactErr
		}

		dockerImage, buildAndPushErr := buildAndPushToContainerRegistry(ctx, &enabledServices, artifactRegistryRepo)

		if buildAndPushErr != nil {
			return buildAndPushErr
		}

		deployContainerErr := deployContainerToCloudRun(ctx, &enabledServices, dockerImage)

		if deployContainerErr != nil {
			return deployContainerErr
		}

		return nil
	})
}

type EnabledServices struct {
	CloudRunService         *projects.Service `pulumi:"cloudRunService"`
	ArtifactRegistryService *projects.Service `pulumi:"artifactRegistryService"`
}

func enableServices(ctx *pulumi.Context) (EnabledServices, error) {

	cloudRunService, cloudRunAdminErr := projects.NewService(ctx, cloudRunAdminServiceName, &projects.ServiceArgs{
		Service: pulumi.String("run.googleapis.com"),
		Project: pulumi.String(gcpProjectId),
	})

	if cloudRunAdminErr != nil {
		return EnabledServices{}, cloudRunAdminErr
	}

	artifactRegistryService, err := projects.NewService(ctx, artifactRegistryServiceName, &projects.ServiceArgs{
		Service: pulumi.String("artifactregistry.googleapis.com"),
	})

	if err != nil {
		return EnabledServices{}, err
	}
	return EnabledServices{
		CloudRunService:         cloudRunService,
		ArtifactRegistryService: artifactRegistryService,
	}, nil
}

func createArtifactRegistryNewRepository(ctx *pulumi.Context, enabledServices *EnabledServices) (*artifactregistry.Repository, error) {

	if enabledServices == nil || enabledServices.ArtifactRegistryService == nil {
		return nil, errors.New("enabledServices cannot be nil")
	}

	dependingResources := []pulumi.Resource{
		enabledServices.ArtifactRegistryService,
	}

	repo, err := artifactregistry.NewRepository(ctx, artifactRegistryRepoName, &artifactregistry.RepositoryArgs{
		Location:     pulumi.String(artifactRegistryRepoLocation),
		RepositoryId: pulumi.String(artifactRegistryRepoName),
		Format:       pulumi.String("DOCKER"),
		Description:  pulumi.String("The repository that will hold social-log Docker images."),
	}, pulumi.DependsOn(dependingResources))

	if err != nil {
		return nil, err
	}

	return repo, nil
}

func buildAndPushToContainerRegistry(ctx *pulumi.Context, enabledServices *EnabledServices, artifactRegistryRepo *artifactregistry.Repository) (*docker.Image, error) {

	if enabledServices == nil || enabledServices.ArtifactRegistryService == nil {
		return nil, errors.New("enabledServices cannot be nil")
	}

	if artifactRegistryRepo == nil {
		return nil, errors.New("artifactRegistryRepo cannot be nil")
	}

	// Lookup GOOGLE_CREDENTIALS environment variable which should hold the path to the JSON key file
	jsonKeyPath, present := os.LookupEnv("GOOGLE_CREDENTIALS_FILE_PATH")
	if !present {
		return nil, errors.New("GOOGLE_CREDENTIALS_FILE_PATH environment variable is not set")
	}

	// Read the JSON key file
	jsonKey, err := os.ReadFile(jsonKeyPath)
	if err != nil {
		return nil, err
	}

	dependingSources := []pulumi.Resource{
		enabledServices.ArtifactRegistryService,
		artifactRegistryRepo,
	}

	// Build and push Docker image to Google Container Registry using the JSON key
	image, err := docker.NewImage(ctx, dockerImageName, &docker.ImageArgs{
		Build: &docker.DockerBuildArgs{
			Context: pulumi.String("../"), // Adjust the context according to your project structure

			ExtraOptions: pulumi.StringArray{
				// This option is needed for devices running on ARM architecture, such as Apple M1/M2/MX CPUs
				pulumi.String("--platform=linux/amd64"),
			},
		},
		ImageName: pulumi.String(dockerImageWithPath),
		Registry: &docker.ImageRegistryArgs{
			Server:   pulumi.String(dockerGCPServer),
			Username: pulumi.String("_json_key"),     // Special username for GCP
			Password: pulumi.String(string(jsonKey)), // Provide the contents of the key file
		},
	}, pulumi.DependsOn(dependingSources))
	if err != nil {
		return nil, err
	}

	return image, nil
}

func deployContainerToCloudRun(ctx *pulumi.Context, enabledServices *EnabledServices, dockerImage *docker.Image) error {

	if enabledServices == nil || enabledServices.CloudRunService == nil {
		return errors.New("enabledServices cannot be nil")
	}

	if dockerImage == nil {
		return errors.New("dockerImage cannot be nil")
	}

	dependingSources := []pulumi.Resource{
		enabledServices.CloudRunService,
		dockerImage,
	}

	appService, err := cloudrun.NewService(ctx, cloudRunServiceName, &cloudrun.ServiceArgs{
		Location: pulumi.String(cloudRunLocation), // Choose the appropriate region for your service
		Template: &cloudrun.ServiceTemplateArgs{
			Spec: &cloudrun.ServiceTemplateSpecArgs{
				Containers: cloudrun.ServiceTemplateSpecContainerArray{
					&cloudrun.ServiceTemplateSpecContainerArgs{
						Image: dockerImage.ImageName,
						Resources: &cloudrun.ServiceTemplateSpecContainerResourcesArgs{
							Limits: pulumi.StringMap{
								"memory": pulumi.String("256Mi"), // Adjust the memory limit as needed
							},
						},
					},
				},
			},
		},
		Traffics: cloudrun.ServiceTrafficArray{
			&cloudrun.ServiceTrafficArgs{
				Percent:        pulumi.Int(100),
				LatestRevision: pulumi.Bool(true),
			},
		},
	}, pulumi.DependsOn(dependingSources))

	if err != nil {
		return err
	}

	_, iamErr := cloudrun.NewIamMember(ctx, "invoker", &cloudrun.IamMemberArgs{
		Service:  appService.Name,
		Location: appService.Location,
		Role:     pulumi.String("roles/run.invoker"),
		Member:   pulumi.String("allUsers"),
	})

	if iamErr != nil {
		return iamErr
	}

	ctx.Export("containerUrl", appService.Statuses.Index(pulumi.Int(0)).Url().ToOutput(ctx.Context()))
	return nil
} Update the in your Dockerfile:
There's a , and in which you need to export your environment variable to ENV known issue here HOME /root # Set the ENV HOME before your ENTRYPOINT.
ENV HOME=/root

# This is specific to your project. 
ENTRYPOINT ["/whatever-is-your-entrypoint"] Create a .env file in the pulumi directory: Set the * to the one you saved on full path 11) GOOGLE_CREDENTIALS_FILE_PATH="/Users/myusername/keys/gcp/pulumi-service-account-key-file.json" Run pulumi up You should be up and running! Extras The go.mod module social-log-go

go 1.21

toolchain go1.22.0

require (
	github.com/pulumi/pulumi-gcp/sdk/v7 v7.11.2
	github.com/pulumi/pulumi/sdk/v3 v3.108.1
)

require (
	dario.cat/mergo v1.0.0 // indirect
	github.com/Masterminds/semver v1.5.0 // indirect
	github.com/Microsoft/go-winio v0.6.1 // indirect
	github.com/ProtonMail/go-crypto v0.0.0-20230828082145-3c4c8a2d2371 // indirect
	github.com/aead/chacha20 v0.0.0-20180709150244-8b13a72661da // indirect
	github.com/agext/levenshtein v1.2.3 // indirect
	github.com/apparentlymart/go-textseg/v13 v13.0.0 // indirect
	github.com/atotto/clipboard v0.1.4 // indirect
	github.com/aymanbagabas/go-osc52/v2 v2.0.1 // indirect
	github.com/blang/semver v3.5.1+incompatible // indirect
	github.com/charmbracelet/bubbles v0.16.1 // indirect
	github.com/charmbracelet/bubbletea v0.24.2 // indirect
	github.com/charmbracelet/lipgloss v0.7.1 // indirect
	github.com/cheggaaa/pb v1.0.29 // indirect
	github.com/cloudflare/circl v1.3.7 // indirect
	github.com/containerd/console v1.0.4-0.20230313162750-1ae8d489ac81 // indirect
	github.com/cyphar/filepath-securejoin v0.2.4 // indirect
	github.com/djherbis/times v1.5.0 // indirect
	github.com/emirpasic/gods v1.18.1 // indirect
	github.com/go-git/gcfg v1.5.1-0.20230307220236-3a3c6141e376 // indirect
	github.com/go-git/go-billy/v5 v5.5.0 // indirect
	github.com/go-git/go-git/v5 v5.11.0 // indirect
	github.com/gogo/protobuf v1.3.2 // indirect
	github.com/golang/glog v1.1.0 // indirect
	github.com/golang/groupcache v0.0.0-20210331224755-41bb18bfe9da // indirect
	github.com/golang/protobuf v1.5.3 // indirect
	github.com/google/uuid v1.3.0 // indirect
	github.com/grpc-ecosystem/grpc-opentracing v0.0.0-20180507213350-8e809c8a8645 // indirect
	github.com/hashicorp/errwrap v1.1.0 // indirect
	github.com/hashicorp/go-multierror v1.1.1 // indirect
	github.com/hashicorp/hcl/v2 v2.17.0 // indirect
	github.com/inconshreveable/mousetrap v1.1.0 // indirect
	github.com/jbenet/go-context v0.0.0-20150711004518-d14ea06fba99 // indirect
	github.com/joho/godotenv v1.5.1 // indirect
	github.com/kevinburke/ssh_config v1.2.0 // indirect
	github.com/lucasb-eyer/go-colorful v1.2.0 // indirect
	github.com/mattn/go-isatty v0.0.19 // indirect
	github.com/mattn/go-localereader v0.0.1 // indirect
	github.com/mattn/go-runewidth v0.0.15 // indirect
	github.com/mitchellh/go-ps v1.0.0 // indirect
	github.com/mitchellh/go-wordwrap v1.0.1 // indirect
	github.com/muesli/ansi v0.0.0-20230316100256-276c6243b2f6 // indirect
	github.com/muesli/cancelreader v0.2.2 // indirect
	github.com/muesli/reflow v0.3.0 // indirect
	github.com/muesli/termenv v0.15.2 // indirect
	github.com/opentracing/basictracer-go v1.1.0 // indirect
	github.com/opentracing/opentracing-go v1.2.0 // indirect
	github.com/pgavlin/fx v0.1.6 // indirect
	github.com/pjbgf/sha1cd v0.3.0 // indirect
	github.com/pkg/errors v0.9.1 // indirect
	github.com/pkg/term v1.1.0 // indirect
	github.com/pulumi/appdash v0.0.0-20231130102222-75f619a67231 // indirect
	github.com/pulumi/esc v0.6.2 // indirect
	github.com/pulumi/pulumi-docker/sdk/v3 v3.6.1 // indirect
	github.com/rivo/uniseg v0.4.4 // indirect
	github.com/rogpeppe/go-internal v1.11.0 // indirect
	github.com/sabhiram/go-gitignore v0.0.0-20210923224102-525f6e181f06 // indirect
	github.com/santhosh-tekuri/jsonschema/v5 v5.0.0 // indirect
	github.com/sergi/go-diff v1.3.1 // indirect
	github.com/skeema/knownhosts v1.2.1 // indirect
	github.com/spf13/cobra v1.7.0 // indirect
	github.com/spf13/pflag v1.0.5 // indirect
	github.com/texttheater/golang-levenshtein v1.0.1 // indirect
	github.com/tweekmonster/luser v0.0.0-20161003172636-3fa38070dbd7 // indirect
	github.com/uber/jaeger-client-go v2.30.0+incompatible // indirect
	github.com/uber/jaeger-lib v2.4.1+incompatible // indirect
	github.com/xanzy/ssh-agent v0.3.3 // indirect
	github.com/zclconf/go-cty v1.13.2 // indirect
	go.uber.org/atomic v1.9.0 // indirect
	golang.org/x/crypto v0.17.0 // indirect
	golang.org/x/exp v0.0.0-20231110203233-9a3e6036ecaa // indirect
	golang.org/x/mod v0.14.0 // indirect
	golang.org/x/net v0.19.0 // indirect
	golang.org/x/sync v0.5.0 // indirect
	golang.org/x/sys v0.15.0 // indirect
	golang.org/x/term v0.15.0 // indirect
	golang.org/x/text v0.14.0 // indirect
	golang.org/x/tools v0.15.0 // indirect
	google.golang.org/genproto/googleapis/rpc v0.0.0-20230706204954-ccb25ca9f130 // indirect
	google.golang.org/grpc v1.57.1 // indirect
	google.golang.org/protobuf v1.31.0 // indirect
	gopkg.in/warnings.v0 v0.1.2 // indirect
	gopkg.in/yaml.v3 v3.0.1 // indirect
	lukechampine.com/frand v1.4.2 // indirect
) If you include this Run , and this will fetch all the packages for you go.mod go tidy Footnotes I fought against permissions for 5 days. The predefined GCP role brought in the additional permissions needed. 1* serviceAccountAdmin

Automate and Deploy a Docker Container to Google Cloud Run from Scratch Using Pulumi and Go

As a backend developer, I often find myself collaborating closely with my frontend team to ensure the seamless deployment of web applications. Recently, our frontend team brought forth a pressing challenge that was slowing down our development workflow. Problem Statement 🤔 They were responsible for managing a Flutter web application running on a Google Cloud Platform (GCP) virtual machine (VM). While the app itself was impressive, the deployment process left much to be desired. The existing deployment workflow was a multi-step ordeal: Build the Flutter web app. Upload the app to the VM. Unzip the uploaded package. Extract the contents into the appropriate Apache directory. And sometimes, things went awry, causing deployment to drag on for far too long. Initial Attempt with Docker Image Deployment 🐳 Our initial approach was to implement Docker image deployment on the VM using GitHub Actions. While this seemed promising, it quickly became apparent that it came with its own set of complexities and challenges. 🤯 The process of creating Docker images occasionally led to failures, leaving us scratching our heads. 🔒 SSH connections to the VM sometimes failed unexpectedly, causing frustrating delays in the deployment process. ⌛ Timeouts became a common occurrence, further exacerbating the deployment woes. It was clear that our initial attempt was far from the seamless deployment solution we were aiming for. Cloud Run The Saviour ☁️ In our quest to find a more efficient deployment solution and streamline collaboration, we stumbled upon Cloud Run—a game-changer in our deployment journey. Here are some key features we harnessed: Auto Deployment from GitHub 🚀 Seamless integration with GitHub. Cloud Build triggers for automatic builds and deploys. Containerization Made Easy 🐳 Dockerfile for defining environment and dependencies. Automatic container building and deployment. Auto-Scaling for Efficiency ⚖️ Dynamic scaling based on incoming requests. Cost-effective resource allocation. Fetching Code from GitHub 🔄 Real-time collaboration among team members. Automatic deployment of pushed changes. Cost Efficiency 💰 Pay-as-you-go pricing model. No charges for idle time. Robust Monitoring and Logging 📊 Detailed logs and metrics. Integration with monitoring tools like Stackdriver. 😜 Solution - Implementation: Now let's jump into the actual solution which worked for us, adding all the templates that worked for us so you can also utilize the same or modify it according to your needs. In this solution phase we will go through Docker setup for your project Apache and server file setup to smooth running of you application in cloud run And at the end the cloud run setup. Step 1: Setting Up Docker in Repo Add this docker file to you existing repo # Stage 1: Build the application
FROM dart:stable AS build

# Install dependencies for Flutter
RUN apt-get update && apt-get install -y curl git unzip xz-utils zip libglu1-mesa

# Clone the Flutter repository
RUN git clone https://github.com/flutter/flutter.git /usr/local/flutter

# Set the Flutter path
ENV PATH="/usr/local/flutter/bin:/usr/local/flutter/bin/cache/dart-sdk/bin:${PATH}"

# Checkout the specific version of Flutter
RUN flutter channel stable
RUN flutter upgrade
RUN git -C /usr/local/flutter checkout 1f6bdb6

#above after checkout is commit hash which indicates the version of flutter
#to learn more about flutter versioning, please visit https://flutter.dev/docs/development/tools/sdk/releases?tab=linux

# Verify Flutter installation
RUN flutter doctor

# Set working directory
WORKDIR /app

# Copy over your app
COPY pubspec.* /app/
RUN flutter pub get
COPY . /app
RUN flutter pub get --offline
RUN flutter clean
RUN flutter build web --release --no-tree-shake-icons

# Stage 2: Create the runtime environment with Apache
FROM httpd:alpine

# Install gettext for envsubst
RUN apk add --no-cache gettext

# Copy the built app to the Apache server directory
COPY --from=build /app/build/web/ /usr/local/apache2/htdocs/

# Expose port
EXPOSE 8080

# Copy the Apache configuration template and startup script
COPY httpd.conf.template /usr/local/apache2/conf/httpd.conf.template

# Add a shell script to start Apache with the right PORT
COPY start-apache.sh /usr/local/bin/start-apache.sh
RUN chmod +x /usr/local/bin/start-apache.sh

# Start Apache using the startup script
CMD ["start-apache.sh"] Above docker file is multi stage In first stage we download dependency of flutter and generate the build In second stage we setup apache to host this as static site in cloud run Now add a apache configuration file to make port dynamic as cloud run expect an open port configuration for application # this should go in directory with httpd.conf.template

ServerRoot "/usr/local/apache2"

Listen ${PORT}

LoadModule mpm_event_module modules/mod_mpm_event.so
LoadModule authn_file_module modules/mod_authn_file.so
LoadModule authn_core_module modules/mod_authn_core.so
LoadModule authz_host_module modules/mod_authz_host.so
LoadModule authz_groupfile_module modules/mod_authz_groupfile.so
LoadModule authz_user_module modules/mod_authz_user.so
LoadModule authz_core_module modules/mod_authz_core.so
LoadModule access_compat_module modules/mod_access_compat.so
LoadModule auth_basic_module modules/mod_auth_basic.so
LoadModule reqtimeout_module modules/mod_reqtimeout.so
LoadModule filter_module modules/mod_filter.so
LoadModule mime_module modules/mod_mime.so
LoadModule log_config_module modules/mod_log_config.so
LoadModule env_module modules/mod_env.so
LoadModule headers_module modules/mod_headers.so
LoadModule setenvif_module modules/mod_setenvif.so
LoadModule version_module modules/mod_version.so
LoadModule unixd_module modules/mod_unixd.so
LoadModule status_module modules/mod_status.so
LoadModule autoindex_module modules/mod_autoindex.so
LoadModule dir_module modules/mod_dir.so
LoadModule alias_module modules/mod_alias.so
LoadModule proxy_html_module modules/mod_proxy_html.so

<IfModule unixd_module>
User daemon
Group daemon
</IfModule>

ServerAdmin you@example.com

<Directory />
    AllowOverride none
    Require all denied
</Directory>

<Directory "/usr/local/apache2/htdocs">
    Options Indexes FollowSymLinks
    AllowOverride None
    Require all granted
</Directory>

<IfModule dir_module>
    DirectoryIndex index.html
</IfModule>

<Files ".ht*">
    Require all denied
</Files>

ErrorLog /proc/self/fd/2

LogLevel warn

<IfModule log_config_module>
    LogFormat "%h %l %u %t \"%r\" %>s %b \"%{Referer}i\" \"%{User-Agent}i\"" combined
    LogFormat "%h %l %u %t \"%r\" %>s %b" common
    CustomLog /proc/self/fd/1 common
</IfModule>

<IfModule alias_module>
    ScriptAlias /cgi-bin/ "/usr/local/apache2/cgi-bin/"
</IfModule>

<Directory "/usr/local/apache2/cgi-bin">
    AllowOverride None
    Options None
    Require all granted
</Directory>

<IfModule headers_module>
    RequestHeader unset Proxy early
</IfModule>

<IfModule mime_module>
    TypesConfig conf/mime.types
    AddType application/x-compress .Z
    AddType application/x-gzip .gz .tgz
</IfModule>

<IfModule mime_magic_module>
    MIMEMagicFile conf/magic
</IfModule>

Include conf/extra/proxy-html.conf Add the just add server file with start-apache.sh name to add an script to run server smoothly #!/bin/sh
# Substitute environment variables in Apache configuration
envsubst < /usr/local/apache2/conf/httpd.conf.template > /usr/local/apache2/conf/httpd.conf

# For debugging: print the PORT variable and the resulting httpd.conf
echo "PORT: $PORT"
# cat /usr/local/apache2/conf/httpd.conf

# Start Apache in the foreground
exec httpd -DFOREGROUND Above file add port from env using envsubst to and replace actual apache config. Now after adding all these just try by running application locally for testing use below command to verify 1 docker build -t my-flutter-app . -> For building
2 docker run -d -p 8080:8080 -e PORT=8080 my-flutter-app -> To run after builiding If all above works fine push it to github. Step 2: Setting Up Cloud Run Begin by navigating to the Google Cloud Console and creating a new project or selecting an existing one. In the Cloud Console, activate the Cloud Run API for your project. You will be able to see the cloud run here something like in below image. Now create cloud run service Fill the details and select the cloud build as option Select the Repo and Branch and setup docker file in option Now click on save and that’s it. Now build will start and you will be able to see it in cloud build section. At the end after successful build you can check you web application on external ip provided by cloud run 🚗 The Journey This blog captures our journey from a challenging deployment process to a streamlined and efficient solution using Cloud Run. With features like auto deployment, containerization, auto-scaling, and cost efficiency, Cloud Run has become a vital tool in our development arsenal. Say goodbye to deployment woes and embrace Cloud Run for a smoother development experience. ☁️🚀

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