Renan_wiki - Recent changes [en]

Talk:Main Page

Admin — Mon, 27 Apr 2026 23:52:56 GMT

← Older revision		Revision as of 23:52, 27 April 2026
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	== Cloud infrastructure, architecture, and beyond ==		== Cloud infrastructure, architecture, and beyond ==

	Cloud infrastructure is the collection of hardware and software components that make cloud computing possible. At its foundation are physical resources like servers, storage arrays, and networking equipment housed in data centers, but what distinguishes cloud infrastructure from traditional IT is the virtualization and abstraction layers built on top. Hypervisors carve physical machines into virtual ones, software-defined networking decouples traffic management from hardware, and orchestration tools coordinate the whole system so resources can be provisioned, scaled, and torn down on demand. The result is that compute, storage, and networking become consumable services rather than fixed assets you have to plan years ahead for.		Cloud infrastructure is the collection of hardware and software components that make cloud computing possible. At its foundation are physical resources like servers, storage arrays, and networking equipment housed in data centers, but what distinguishes cloud infrastructure from traditional IT is the virtualization and abstraction layers built on top. Hypervisors carve physical machines into virtual ones, software defined networking decouples traffic management from hardware, and orchestration tools coordinate the whole system so resources can be provisioned, scaled, and torn down on demand. The result is that compute, storage, and networking become consumable services rather than fixed assets you have to plan years ahead for.

	This shapes architecture choices in significant ways. When you no longer pay for idle capacity, designs tend to favor elasticity, statelessness, and loose coupling so workloads can scale horizontally and recover from failure without manual intervention. Architects make deliberate decisions between monoliths and microservices, between containers and serverless functions, between managed databases and self-hosted ones, with each choice trading control for operational simplicity. Decisions about regions, availability zones, and data residency become first-class concerns rather than afterthoughts, especially for applications with latency requirements or regulatory exposure.		This shapes architecture choices in significant ways. When you no longer pay for idle capacity, designs tend to favor elasticity, statelessness, and loose coupling so workloads can scale horizontally and recover from failure without manual intervention. Architects make deliberate decisions between monoliths and microservices, between containers and serverless functions, between managed databases and self-hosted ones, with each choice trading control for operational simplicity. Decisions about regions, availability zones, and data residency become first class concerns rather than afterthoughts, especially for applications with latency requirements or regulatory exposure.

	Deployment practices follow from those architectural commitments. Infrastructure as Code becomes the norm, with tools like Terraform or CloudFormation defining environments declaratively so they can be versioned, reviewed, and rebuilt reliably. CI/CD pipelines automate the path from commit to production, and immutable infrastructure patterns replace the older habit of patching long-lived servers in place. Rollbacks, blue-green deployments, and canary releases become routine because the underlying platform supports spinning up parallel environments cheaply. The discipline this requires is real, but it pays off in faster iteration and fewer surprises in production.		Deployment practices follow from those architectural commitments. Infrastructure as Code becomes the norm, with tools like Terraform or CloudFormation defining environments declaratively so they can be versioned, reviewed, and rebuilt reliably. CI/CD pipelines automate the path from commit to production, and immutable infrastructure patterns replace the older habit of patching long lived servers in place. Rollbacks, blue green deployments, and canary releases become routine because the underlying platform supports spinning up parallel environments cheaply. The discipline this requires is real, but it pays off in faster iteration and fewer surprises in production.

	The provider landscape is dominated by AWS, Microsoft Azure, and Google Cloud, each with distinct strengths. AWS has the broadest service catalog and the deepest market share, Azure tends to win in environments already invested in Microsoft tooling and enterprise agreements, and GCP often appeals to teams doing heavy data analytics or machine learning work. Beyond the big three, providers like Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, and a growing ecosystem of specialized players covers things like edge computing and developer-focused platforms. Choosing among them is rarely a pure technical exercise. Existing skills, contractual relationships, compliance requirements, and the long shadow of vendor lock-in all weigh on the decision, which is why so many organizations end up running multi-cloud or hybrid setups even when the added complexity is real.		The provider landscape is dominated by AWS, Microsoft Azure, and Google Cloud, each with distinct strengths. AWS has the broadest service catalog and the deepest market share, Azure tends to win in environments already invested in Microsoft tooling and enterprise agreements, and GCP often appeals to teams doing heavy data analytics or machine learning work. Beyond the big three, providers like Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, and a growing ecosystem of specialized players covers things like edge computing and developer focused platforms. Choosing among them is rarely a pure technical exercise. Existing skills, contractual relationships, compliance requirements, and the long shadow of vendor lock-in all weigh on the decision, which is why so many organizations end up running multi-cloud or hybrid setups even when the added complexity is real.

Main Page

Admin — Mon, 27 Apr 2026 22:26:42 GMT

← Older revision		Revision as of 22:26, 27 April 2026
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	[[File:Tuxedo_cat.jpg\|thumb\|left\|200px\|~~Our~~ Renan_wiki mascot.]]		[[File:Tuxedo_cat.jpg\|thumb\|left\|200px\|The Renan_wiki mascot.]]

			Welcome to the Renan Wiki, This production grade platform demonstrates a dockerized, serverless MediaWiki deployment within the AWS ecosystem, specifically focusing on cloud infrastructure integration and automated security protocols for a networking concentration. The architecture utilizes AWS Fargate for serverless compute, a managed Amazon RDS instance with AES-256 and enforced SSL encryption, and Amazon S3 for durable media storage. Network identity and security are maintained at the edge via an AWS Certificate Manager SSL certificate, while the Application Load Balancer enforces canonical redirection to the renanwiki.org domain and mandates HTTPS for all traffic. The entire stack is isolated within a custom VPC to minimize the attack surface through private subnets and restrictive Security Groups. Browse around at your leisure or create your own page with whatever content you'd like to add. Just keep in mind that embedding files or images requires uploading them first and using the right syntax, and you'll want to enable page protection to preserve your work



	Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, and cloud orchestration. This platform serves as a central knowledge base documenting the transition from physical hardware management to cloud-native, serverless environments. Inside, you'll find detailed documentation on architectural designs, with a particular focus on containerization with Docker and scalable deployments through AWS Fargate. Whether you're looking for specific project logs or broader insights into cloud-native transitions, the site is designed to offer a clear, narrative-driven exploration of complex technical challenges and their solutions. Browse around at your leisure, or create your own page with whatever content you'd like to add. Just keep in mind that embedding files or images requires uploading them first and using the right syntax, and you'll want to enable page protection to preserve your work.

Template:Renan wiki disclaimer

Admin — Mon, 27 Apr 2026 03:00:43 GMT

← Older revision		Revision as of 03:00, 27 April 2026
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	Renan_wiki is served over plain HTTP. Traffic between your browser and this site		(*Renan_wiki is served over plain HTTP. Traffic between your browser and this site
	— including login credentials and page content — is not encrypted and		— including login credentials and page content — is not encrypted and
	can be intercepted on the network. Do not enter passwords you reuse elsewhere or		can be intercepted on the network. Do not enter passwords you reuse elsewhere or
	submit any sensitive, personal, or non-public information.		submit any sensitive, personal, or non-public information.*)

Template:Renan wiki disclaimer

Admin — Mon, 27 Apr 2026 02:58:42 GMT

Created page with "Renan_wiki is served over plain HTTP. Traffic between your browser and this site — including login credentials and page content — is not encrypted and can be intercepted on the network. Do not enter passwords you reuse elsewhere or submit any sensitive, personal, or non-public information."

New page

Renan_wiki is served over plain HTTP. Traffic between your browser and this site
— including login credentials and page content — is not encrypted and
can be intercepted on the network. Do not enter passwords you reuse elsewhere or
submit any sensitive, personal, or non-public information.

Renan wiki disclaimer

Admin — Mon, 27 Apr 2026 02:56:51 GMT

Admin deleted page Renan wiki disclaimer content was: "Renan_wiki is served over plain HTTP. Traffic between your browser and this site — including login credentials and page content — is not encrypted and can be intercepted on the network. Do not enter passwords you reuse elsewhere or submit any sensitive, personal, or non-public information.", and the only contributor was "Admin" (talk)

Main Page

Admin — Mon, 27 Apr 2026 02:34:01 GMT

← Older revision		Revision as of 02:34, 27 April 2026
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	[[File:Tuxedo_cat.jpg\|thumb\|left\|200px\|Our Renan_wiki mascot.]]		[[File:Tuxedo_cat.jpg\|thumb\|left\|200px\|Our Renan_wiki mascot.]]

	Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration~~, and cybersecurity~~. This platform serves as a central knowledge base ~~for~~ documenting ~~technical evolution and~~ the transition from physical hardware management to cloud-native, serverless environments.		Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, and cloud orchestration. This platform serves as a central knowledge base documenting the transition from physical hardware management to cloud-native, serverless environments. Inside, you'll find detailed documentation on architectural designs, with a particular focus on containerization with Docker and scalable deployments through AWS Fargate. Whether you're looking for specific project logs or broader insights into cloud-native transitions, the site is designed to offer a clear, narrative-driven exploration of complex technical challenges and their solutions. Browse around at your leisure, or create your own page with whatever content you'd like to add. Just keep in mind that embedding files or images requires uploading them first and using the right syntax, and you'll want to enable page protection to preserve your work.
	Inside, you ~~will~~ find detailed documentation on architectural designs, ~~specifically focusing~~ on containerization with Docker and ~~the deployment of~~ scalable ~~solutions~~ through AWS Fargate~~. Beyond infrastructure, this wiki explores critical defense strategies, ranging from access control models to deep dives into modern vulnerability analysis~~. Whether you ~~are~~ looking for specific project logs or ~~strategic~~ insights into cloud-native transitions, ~~this~~ site is designed to ~~provide~~ a clear, narrative-driven exploration of complex ~~technological~~ challenges and their solutions. Browse around at your leisure, or ~~go ahead and~~ create your own page with whatever content you'd like to add. Just keep in mind that embedding files or images requires uploading them first and using the right syntax, and you'll want to enable page protection to preserve your work.

Main Page

Admin — Mon, 27 Apr 2026 02:11:19 GMT

Admin changed protection settings for Main Page [Edit=Allow only administrators] (indefinite) [Move=Allow only administrators] (indefinite)

← Older revision		Revision as of 02:11, 27 April 2026
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	Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration, and cybersecurity. This platform serves as a central knowledge base for documenting technical evolution and the transition from physical hardware management to cloud-native, serverless environments.		Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration, and cybersecurity. This platform serves as a central knowledge base for documenting technical evolution and the transition from physical hardware management to cloud-native, serverless environments.
	Inside, you will find detailed documentation on architectural designs, specifically focusing on containerization with Docker and the deployment of scalable solutions through AWS Fargate. Beyond infrastructure, this wiki explores critical defense strategies, ranging from access control models to deep dives into modern vulnerability analysis. Whether you are looking for specific project logs or strategic insights into cloud-native transitions, this site is designed to provide a clear, narrative-driven exploration of complex technological challenges and their solutions.		Inside, you will find detailed documentation on architectural designs, specifically focusing on containerization with Docker and the deployment of scalable solutions through AWS Fargate. Beyond infrastructure, this wiki explores critical defense strategies, ranging from access control models to deep dives into modern vulnerability analysis. Whether you are looking for specific project logs or strategic insights into cloud-native transitions, this site is designed to provide a clear, narrative-driven exploration of complex technological challenges and their solutions. Browse around at your leisure, or go ahead and create your own page with whatever content you'd like to add. Just keep in mind that embedding files or images requires uploading them first and using the right syntax, and you'll want to enable page protection to preserve your work.

Talk:Main Page

Admin — Mon, 27 Apr 2026 01:56:36 GMT

← Older revision		Revision as of 01:56, 27 April 2026
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	== Cloud infrastructure, architecture, and beyond ==		== Cloud infrastructure, architecture, and beyond ==

	Cloud infrastructure is the ~~foundation~~ of ~~everything, the physical~~ and ~~virtual resources~~ that make cloud computing possible. At ~~the hardware level, this means data centers full of~~ servers, storage arrays, and networking equipment ~~distributed across regions~~ and ~~availability zones for redundancy~~. ~~On top of that~~ hardware ~~sits a virtualization layer~~, ~~typically hypervisors or container runtimes, which abstracts~~ the ~~physical~~ resources ~~into pools that~~ can be ~~allocated~~ on demand. ~~Supporting services like load balancers~~, ~~firewalls, identity management~~, and ~~monitoring round out the picture, giving users programmable building blocks~~ rather than ~~raw machines~~.		Cloud infrastructure is the collection of hardware and software components that make cloud computing possible. At its foundation are physical resources like servers, storage arrays, and networking equipment housed in data centers, but what distinguishes cloud infrastructure from traditional IT is the virtualization and abstraction layers built on top. Hypervisors carve physical machines into virtual ones, software-defined networking decouples traffic management from hardware, and orchestration tools coordinate the whole system so resources can be provisioned, scaled, and torn down on demand. The result is that compute, storage, and networking become consumable services rather than fixed assets you have to plan years ahead for.

	~~Cloud~~ architecture ~~is how those building blocks get assembled into working systems~~. ~~Traditional monolithic~~ designs ~~run an entire application as a single unit~~, ~~which is simple but harder to scale~~ and ~~maintain. Microservices break applications into smaller independent components that communicate over APIs, allowing teams to~~ scale and ~~deploy pieces individually. Serverless takes this further by letting developers run code in response to events~~ without ~~managing any underlying servers at all~~. ~~Most real-world systems mix these patterns~~, ~~layering compute~~, ~~storage~~, ~~networking, and security services to balance performance~~, ~~cost~~, and ~~resilience~~, ~~and increasingly relying on infrastructure as code to make the whole stack reproducible~~.		This shapes architecture choices in significant ways. When you no longer pay for idle capacity, designs tend to favor elasticity, statelessness, and loose coupling so workloads can scale horizontally and recover from failure without manual intervention. Architects make deliberate decisions between monoliths and microservices, between containers and serverless functions, between managed databases and self-hosted ones, with each choice trading control for operational simplicity. Decisions about regions, availability zones, and data residency become first-class concerns rather than afterthoughts, especially for applications with latency requirements or regulatory exposure.

	Deployment ~~models describe where~~ those ~~architectures actually live~~. ~~Public cloud runs workloads on shared infrastructure operated by a third party and is usually~~ the ~~cheapest and most scalable option. Private cloud uses dedicated infrastructure~~, ~~either on-premise~~ or ~~hosted elsewhere~~, and ~~tends to be chosen for sensitive data or strict compliance needs~~. ~~Hybrid cloud combines~~ the ~~two~~, ~~keeping critical workloads private while bursting into~~ the ~~public cloud for elasticity, and multi-cloud spreads workloads across more than one provider to avoid lock~~-in ~~or take advantage of specific strengths~~. ~~Edge~~ deployments ~~push compute closer to where data~~ is ~~generated, which matters for things like IoT,~~ real~~-time analytics~~, and ~~anything where latency is the bottleneck~~.		Deployment practices follow from those architectural commitments. Infrastructure as Code becomes the norm, with tools like Terraform or CloudFormation defining environments declaratively so they can be versioned, reviewed, and rebuilt reliably. CI/CD pipelines automate the path from commit to production, and immutable infrastructure patterns replace the older habit of patching long-lived servers in place. Rollbacks, blue-green deployments, and canary releases become routine because the underlying platform supports spinning up parallel environments cheaply. The discipline this requires is real, but it pays off in faster iteration and fewer surprises in production.

	The provider landscape is dominated by ~~three hyperscalers~~. ~~Amazon Web Services is the largest by market share and~~ has the broadest catalog ~~of services~~, ~~which makes it the default choice for many enterprises. Microsoft~~ Azure ~~has grown quickly thanks~~ to ~~its tight integration with~~ Microsoft's enterprise ~~software ecosystem~~ and ~~a strong hybrid cloud story that resonates with organizations already running Windows Server and Active Directory. Google Cloud Platform tends~~ to ~~lead in~~ data analytics, machine learning~~, and Kubernetes-native tooling, and fits naturally for teams already invested in Google's data stack~~. Beyond the big three, Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, ~~while~~ platforms ~~like DigitalOcean~~, ~~Linode~~, and ~~Vultr offer simpler~~, ~~developer~~-~~friendly alternatives for smaller workloads~~.		The provider landscape is dominated by AWS, Microsoft Azure, and Google Cloud, each with distinct strengths. AWS has the broadest service catalog and the deepest market share, Azure tends to win in environments already invested in Microsoft tooling and enterprise agreements, and GCP often appeals to teams doing heavy data analytics or machine learning work. Beyond the big three, providers like Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, and a growing ecosystem of specialized players covers things like edge computing and developer-focused platforms. Choosing among them is rarely a pure technical exercise. Existing skills, contractual relationships, compliance requirements, and the long shadow of vendor lock-in all weigh on the decision, which is why so many organizations end up running multi-cloud or hybrid setups even when the added complexity is real.

Main Page

Admin — Mon, 27 Apr 2026 01:18:42 GMT

Admin protected Main Page [Edit=Allow only autoconfirmed users] (indefinite) [Move=Allow only autoconfirmed users] (indefinite)

← Older revision		Revision as of 01:18, 27 April 2026
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			[[File:Tuxedo_cat.jpg\|thumb\|left\|200px\|Our Renan_wiki mascot.]]

	Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration, and cybersecurity. This platform serves as a central knowledge base for documenting technical evolution and the transition from physical hardware management to cloud-native, serverless environments.		Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration, and cybersecurity. This platform serves as a central knowledge base for documenting technical evolution and the transition from physical hardware management to cloud-native, serverless environments.

File:Tuxedo cat.jpg

Admin — Mon, 27 Apr 2026 00:27:21 GMT

Admin uploaded File:Tuxedo cat.jpg

New page

File:Tuxedo cat.jpg

Admin — Mon, 27 Apr 2026 00:20:10 GMT

Admin deleted page File:Tuxedo cat.jpg content was: "", and the only contributor was "Admin" (talk)

File:Tuxedo cat.jpg

Admin — Mon, 27 Apr 2026 00:04:09 GMT

Admin uploaded File:Tuxedo cat.jpg

New page

Talk:Main Page

Admin — Sun, 26 Apr 2026 22:48:27 GMT

← Older revision		Revision as of 22:48, 26 April 2026
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	== Cloud infrastructure ==		== Cloud infrastructure, architecture, and beyond ==

	Cloud ~~architecture refers to how~~ computing ~~resources~~, ~~services~~, and ~~applications are organized~~ and ~~connected to deliver functionality over~~ a ~~network~~.Cloud architecture ~~refers to~~ how ~~computing resources, services, and applications are organized and connected to deliver functionality over a network~~. ~~The most common architectural patterns include~~ monolithic designs~~, where everything runs~~ as a single unit, ~~microservices, where~~ applications ~~are broken~~ into smaller independent components that communicate ~~through~~ APIs, and ~~serverless, where the provider handles all the underlying infrastructure and~~ developers ~~focus only on~~ code ~~execution~~. ~~Modern architectures often blend~~ these ~~approaches~~, layering compute, storage, networking, and security services to balance performance, cost, and resilience.		Cloud infrastructure is the foundation of everything, the physical and virtual resources that make cloud computing possible. At the hardware level, this means data centers full of servers, storage arrays, and networking equipment distributed across regions and availability zones for redundancy. On top of that hardware sits a virtualization layer, typically hypervisors or container runtimes, which abstracts the physical resources into pools that can be allocated on demand. Supporting services like load balancers, firewalls, identity management, and monitoring round out the picture, giving users programmable building blocks rather than raw machines.
	Deployment models describe where ~~and how~~ those architectures actually ~~run~~. Public cloud ~~places~~ workloads on shared infrastructure ~~managed~~ by a third party~~, which~~ is ~~typically~~ the most ~~cost-effective and~~ scalable option. Private cloud ~~keeps everything on~~ dedicated infrastructure, either on-premise or hosted, and ~~is often~~ chosen for sensitive data or strict compliance ~~requirements~~. Hybrid cloud combines ~~both~~, ~~letting organizations keep~~ critical workloads private while ~~leveraging~~ the public cloud for elasticity, and multi-cloud spreads workloads across more than one provider to avoid lock-in or take advantage of specific strengths. ~~Increasingly, edge~~ deployments push compute closer to where data is generated, ~~reducing latency~~ for things like IoT ~~and~~ real-time analytics.
	The provider landscape is dominated by three hyperscalers. Amazon Web Services ~~remains~~ the largest by market share and ~~offers~~ the broadest catalog of services, ~~making~~ it the default choice for many enterprises. Microsoft Azure has grown ~~rapidly~~ thanks to its tight integration with Microsoft's enterprise software ecosystem and strong hybrid cloud story. Google Cloud Platform tends to lead in data analytics, machine learning, and Kubernetes-native tooling, and ~~is a natural fit~~ for ~~organizations~~ already invested in Google's data stack. Beyond the big three, ~~providers like~~ Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, while platforms like DigitalOcean, Linode, and Vultr offer simpler, developer-friendly alternatives for smaller workloads.		Cloud architecture is how those building blocks get assembled into working systems. Traditional monolithic designs run an entire application as a single unit, which is simple but harder to scale and maintain. Microservices break applications into smaller independent components that communicate over APIs, allowing teams to scale and deploy pieces individually. Serverless takes this further by letting developers run code in response to events without managing any underlying servers at all. Most real-world systems mix these patterns, layering compute, storage, networking, and security services to balance performance, cost, and resilience, and increasingly relying on infrastructure as code to make the whole stack reproducible.

			Deployment models describe where those architectures actually live. Public cloud runs workloads on shared infrastructure operated by a third party and is usually the cheapest and most scalable option. Private cloud uses dedicated infrastructure, either on-premise or hosted elsewhere, and tends to be chosen for sensitive data or strict compliance needs. Hybrid cloud combines the two, keeping critical workloads private while bursting into the public cloud for elasticity, and multi-cloud spreads workloads across more than one provider to avoid lock-in or take advantage of specific strengths. Edge deployments push compute closer to where data is generated, which matters for things like IoT, real-time analytics, and anything where latency is the bottleneck.

			The provider landscape is dominated by three hyperscalers. Amazon Web Services is the largest by market share and has the broadest catalog of services, which makes it the default choice for many enterprises. Microsoft Azure has grown quickly thanks to its tight integration with Microsoft's enterprise software ecosystem and a strong hybrid cloud story that resonates with organizations already running Windows Server and Active Directory. Google Cloud Platform tends to lead in data analytics, machine learning, and Kubernetes-native tooling, and fits naturally for teams already invested in Google's data stack. Beyond the big three, Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, while platforms like DigitalOcean, Linode, and Vultr offer simpler, developer-friendly alternatives for smaller workloads.

Talk:Main Page

Admin — Sun, 26 Apr 2026 22:37:34 GMT

Cloud infrastructure: new section

New page

== Cloud infrastructure ==

Cloud architecture refers to how computing resources, services, and applications are organized and connected to deliver functionality over a network.Cloud architecture refers to how computing resources, services, and applications are organized and connected to deliver functionality over a network. The most common architectural patterns include monolithic designs, where everything runs as a single unit, microservices, where applications are broken into smaller independent components that communicate through APIs, and serverless, where the provider handles all the underlying infrastructure and developers focus only on code execution. Modern architectures often blend these approaches, layering compute, storage, networking, and security services to balance performance, cost, and resilience.
Deployment models describe where and how those architectures actually run. Public cloud places workloads on shared infrastructure managed by a third party, which is typically the most cost-effective and scalable option. Private cloud keeps everything on dedicated infrastructure, either on-premise or hosted, and is often chosen for sensitive data or strict compliance requirements. Hybrid cloud combines both, letting organizations keep critical workloads private while leveraging the public cloud for elasticity, and multi-cloud spreads workloads across more than one provider to avoid lock-in or take advantage of specific strengths. Increasingly, edge deployments push compute closer to where data is generated, reducing latency for things like IoT and real-time analytics.
The provider landscape is dominated by three hyperscalers. Amazon Web Services remains the largest by market share and offers the broadest catalog of services, making it the default choice for many enterprises. Microsoft Azure has grown rapidly thanks to its tight integration with Microsoft's enterprise software ecosystem and strong hybrid cloud story. Google Cloud Platform tends to lead in data analytics, machine learning, and Kubernetes-native tooling, and is a natural fit for organizations already invested in Google's data stack. Beyond the big three, providers like Oracle Cloud, IBM Cloud, and Alibaba Cloud serve specific niches, while platforms like DigitalOcean, Linode, and Vultr offer simpler, developer-friendly alternatives for smaller workloads.

User:Zeus

Zeus — Sun, 26 Apr 2026 20:23:40 GMT

User account Zeus was created

Main Page

Admin — Wed, 22 Apr 2026 19:54:18 GMT

← Older revision		Revision as of 19:54, 22 April 2026
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	~~<strong>MediaWiki has been installed~~.~~</strong>~~
			Welcome to the Renan Wiki, a digital space dedicated to the intersection of network engineering, cloud orchestration, and cybersecurity. This platform serves as a central knowledge base for documenting technical evolution and the transition from physical hardware management to cloud-native, serverless environments.
			Inside, you will find detailed documentation on architectural designs, specifically focusing on containerization with Docker and the deployment of scalable solutions through AWS Fargate. Beyond infrastructure, this wiki explores critical defense strategies, ranging from access control models to deep dives into modern vulnerability analysis. Whether you are looking for specific project logs or strategic insights into cloud-native transitions, this site is designed to provide a clear, narrative-driven exploration of complex technological challenges and their solutions.



	Consult the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents User's Guide] for information on using the wiki software.		Consult the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents User's Guide] for information on using the wiki software.

Renan wiki:About

Admin — Wed, 22 Apr 2026 19:50:42 GMT

Created page with "Renan Wiki is a specialized digital platform designed to serve as a comprehensive knowledge base, often focusing on technical documentation, project tracking, or specific academic research. Built using the MediaWiki engine, it leverages a containerized, serverless architecture on AWS, specifically utilizing Docker and AWS Fargate to ensure high availability and scalability without the need for manual server management. The project emphasizes a modern approach to cloud i..."

New page

Renan Wiki is a specialized digital platform designed to serve as a comprehensive knowledge base, often focusing on technical documentation, project tracking, or specific academic research. Built using the MediaWiki engine, it leverages a containerized, serverless architecture on AWS, specifically utilizing Docker and AWS Fargate to ensure high availability and scalability without the need for manual server management.

The project emphasizes a modern approach to cloud infrastructure, integrating secure networking practices and efficient data storage. It functions as a central repository for technical insights, ranging from cybersecurity analysis and network defense strategies to detailed cloud orchestration guides. By transitioning traditional hardware-based management into a cloud-native environment, the wiki provides a streamlined, narrative-driven resource for documenting complex technological implementations and individual academic achievements.

User:Prometheus

Prometheus — Tue, 21 Apr 2026 19:22:00 GMT

User account Prometheus was created