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  3. What Is a Cloud Server? | How Do Cloud Servers Work?

What Is a Cloud Server? | How Do Cloud Servers Work?

  • By Gcore
  • June 9, 2023
  • 12 min read
What Is a Cloud Server? | How Do Cloud Servers Work?

In this article, we’ll deep into what cloud servers are, how they work, their types, benefits, and challenges. We’ll also cover factors to consider when choosing a cloud provider.

What Is a Cloud Server?

A cloud server is a pool of powerful virtual or dedicated physical computer resources. These resources are hosted in the public or private cloud infrastructure and can be accessed through the internet or a virtual private network (VPN.)

Despite their off-site locations, the servers in the cloud provide broadly the same functionality as the traditional on-premises physical servers. However, the cloud environment offers scalability, flexibility, and has a lower cost of entry, since it does not require upfront investments in physical infrastructure like an on-premises data center.

A typical cloud server combines high-performance components and systems in one or more locations via high-speed networks. These may be physically located in one or more machines or distributed across several networks. For example, a physical server cluster may provide the CPU and memory (RAM) while the storage is in another location or system, such as network-attached storage (NAS.)

A physical server cluster

While shared cloud server hosting is adequate for many organizations, it may not suit high-traffic applications or those dealing with sensitive data. So, those projects that require more resources or to be isolated from noisy neighbors find private cloud to be a better fit. Healthcare, banks, and other resource-intensive industries, such as gaming websites, video streaming, and research organizations, prefer private cloud servers where resources are physically isolated from all other users.

Types of Cloud Servers

Cloud servers can be categorized into three types, based on where they reside: public, private, and hybrid.

Public Cloud Server

Public cloud servers are computer resources hosted on a public cloud infrastructure, which means they are owned, managed, and maintained by a third-party service provider. The provider makes all resources available to the public via the internet. For example, Gcore offers bare metal servers, virtual machines, and Kubernetes containers.

Private Cloud Server

A private or dedicated cloud server is a cloud architecture where resources are only available to a single organization. The cloud provider installs the dedicated cloud server, such as Gcore’s Bare Metal, in a private region. Private servers provide better performance, control, and security, making them suitable for highly regulated industries, high-traffic websites, or running mission-critical or sensitive applications.

In-House Versus Third-Party Private Cloud Servers

Organizations can host private cloud servers either in-house or in a third-party cloud environment. In the latter case, the provider owns and manages the hardware and software resources, including the supporting infrastructure. The choice depends on objectives regarding control, convenience, cost, and flexibility. Third-party cloud hosting offers less control, but deploying and scaling are faster, simpler, and more cost-effective.

When the private cloud operates from the in-house data center, users access it over the local area network (LAN.) External users or remote offices can access the server over a private network such as a VPN or the organization’s intranet.

Local area network switch and cabling

Hybrid Cloud Server

Hybrid cloud servers are a mix of public cloud and on-premises or private infrastructure. Hybrid cloud offers the best performance, flexibility, availability, and scalability. A hybrid cloud server enables businesses to take advantage of the best of these two environments to achieve optimal outcomes regarding compliance, availability, and security. A typical configuration could involve an off-site public cloud server combined with an in-house or third-party-hosted private cloud server. An example of a hybrid cloud server is Gcore’s Virtual Private Cloud.

Read: What is a bare metal server? | How does it work?

How Does a Cloud Server Work?

Public and private cloud servers work like traditional on-premises physical servers. They provide processing power, run applications, store data, and perform other functions like running databases, mail servers, etc. However, unlike the in-house servers that run locally from the in-house data center, most cloud servers are hosted and managed by third-party cloud computing providers. They are only accessible over the internet or a virtual private network (VPN.)

Most public cloud servers are software-defined using a virtualization process that creates multiple virtual machines on a single physical server. Providers may use a hypervisor or other virtualization technology to abstract the CPU, memory, storage, and other server resources.

For shared public cloud servers, the virtualization technology pools the configured resources to create multiple cloud servers that function like physical machines, but are only accessible via the Internet. This allows customers to share the hosting server’s compute, memory, storage, and other resources. However, each can access a separate instance with the individual operating system. Clients on the same physical server can run different applications and store data independently.

Cloud computing service providers usually invest in, manage, and maintain a high-capacity infrastructure, benefiting from the economies of scale. Consequently, they can pass on these benefits to customers and offer reliable, high-performance servers at lower costs than clients would have spent deploying equivalent systems in their data centers.

Most cloud computing providers have self-service portals that potential customers use to create and deploy cloud servers in less than ten minutes. Automated systems enable the customers to choose predefined servers or configure custom CPU, storage, memory, and other resources that align with their specific requirements and budget.

Who Should Use Cloud Servers, and Why?

The cloud computing delivery model is suitable for all types and sizes of workloads. Since it allows deployment of powerful virtual machines and bare metal servers without the high upfront costs associated with an on-premises system. The flexibility and affordability of cloud’s pay-as-you-go pricing plans enable everyone—including those with limited budgets—to deploy cloud servers that meet their specific needs.

By contrast, setting up an equivalent in-house system would mean installing physical servers and adequate storage in the organization’s data center. This capital-intensive exercise would require significant time and skill to install, configure, and manage, making it impractical and unaffordable for those with inadequate resources.

To understand the problem users of on-premises servers face is to imagine an organization with seasonal traffic spikes—a good example is an e-commerce platform with traffic spikes during the sales season, such as Black Friday.

The company may invest in large local infrastructures with enough capacity to handle traffic spikes, but those expensive resources remain idle most of the time. A cloud server can reduce deployment costs, time, and overprovisioning of resources while improving efficiencies and revenues.

In this article, we’ll discover what a cloud server is, the different types of cloud servers, how a cloud server works, its many benefits and limited challenges, and why cloud is essential for most individuals and organizations.

What Are the Benefits of Cloud Servers?

The specific benefits of a cloud server vary depending on the organization’s objectives, workload, and type of server and plan. However, numerous common advantages to individuals and businesses are worth a closer look.

Low Deployment and Maintenance Costs

Customers can rent virtual cloud servers and storage at a much lower deployment and maintenance cost. This results in savings in CapEx, space, and running costs, such as highly skilled in-house staff, electricity, cooling, and other requirements for maintaining an on-premises system.

Highly Scalable and Flexible Computing Resources

Servers in the cloud are highly scalable, with an almost unlimited capacity to process resource-intensive workloads and store vast quantities of data. Most providers offer flexible plans, enabling users to choose the appropriate configuration and operating system based on workloads. Customers can quickly and easily create or remove the servers or resources depending on current needs, demand, and budget.

Cloud computing providers often invest in vast capacities so that customers can add resources to meet temporary high-demand workloads and then remove them when demand is low. When a configured cloud server capacity cannot handle a particular workload, the customer organization can scale by quickly adding resources. Cloud servers scale up or down to match the current workload quickly and easily.

Easy to Deploy and Use

Provisioning a cloud server is almost instant. It usually takes less than ten minutes to configure and start using a virtual instance. Installation, physical upgrades, and maintenance associated with on-premises infrastructure are all taken care of by the cloud computing provider.

Global Access and Universal Workload Capability

Cloud servers provide the same functions as on-premises servers. However, they are accessible by more users regardless of their location. An on-site server is only accessible by the users on the company’s network. However, a server in the cloud is accessible through the internet, hence the ability to serve a broader user base.

Internet connectivity enables cloud servers to handle global workloads. However, unexpected disruptions, instabilities, and network latency can degrade performance for users, especially in locations with less reliable internet connectivity. To overcome this, cloud service providers can create duplicate instances to process workloads on servers in different locations, thus ensuring faster connectivity, continuity, and better user experience.

Affordable Pricing Plans

Cloud service providers offer a wide variety of pricing plans based on the specifications. Customers can opt for annual, monthly, or pay-as-you-go payment plans. There are usually different commitment plans available, commonly for three or six months or one or two years. In general, cloud services are charged at an hourly rate. Customers pay for the resources used at the end of the month.

Besides the annual and monthly rates, Gcore offers per-hour billing on production-grade instances designed for heavy workloads, complex calculations, and other high CPU-intensive applications. Per-hour billing is suitable for customers who do not want to sign up for monthly or annual contracts. Typical rates range from $0.03496/hr for a 2vCPU, with 2GB RAM, to $2.9/hr for a 32vCPU, 128GB RAM, and 4GPU.

The overall cost of an instance depends on the allocated computing resources, operating system, and usage time, which are calculated from the moment use begins until it is completely stopped. Storage and network usage are charged separately.

Flexible Cloud Server Specifications

Cloud servers allow client customization to suit unique business needs and use cases. While the providers offer some cloud servers with standard specifications, they also allow the customization of various resources.

Highly Available and Reliable

Cloud servers are highly available, and most providers guarantee 99% uptime. As such, it is rare to experience frequent and lengthy downtimes. Unlike a traditional on-premises server that may experience downtime and take time to fix, cloud servers have several redundant components and faster recovery features, which make them highly available and reliable.

Top-Notch Security

Cloud computing providers use highly effective security solutions to protect the infrastructure and data, and have skilled IT security teams to ensure the servers’ constant protection. They also observe security best practices, such as updating the software and tools.

Read: What is Latency? | How to Reduce Latency

What Are the Challenges of Using Cloud Servers?

Before migrating to the cloud, it is essential to evaluate the challenges you are likely to experience. Issues to consider include performance, security reliability, availability, and more. These may differ from one deployment and cloud server type to the other. However, some common issues include cloud server performance issues, meeting regulations, cloud outages, a lack of direct server control, and incompatibility. Let’s review each one in depth.

Cloud Server Performance Issues

Shared or “logical” cloud servers reside in multi-tenant environments. You don’t have direct control over the VM, its location, or other cloud servers on the same physical machine. As such, excessive usage of resources such as network and storage by other tenants may degrade the performance of your server.

One way of overcoming performance degradation is to migrate your workloads to regions with fewer activities. But the ultimate solution is to move to a server with more capacity. The cost of such a server depends on the type and configuration, with dedicated servers being costlier than virtual servers.

For example, Gcore virtual servers that support Linux and Windows operating systems start at $4.99. The entry-level servers have 1vCPU, 512MB RAM, and 20GB disk, and you can adjust the specifications to match your workload. A dedicated server with an E-2236 Intel Xeon CPU, 32 GB RAM, and 2x 480 SSD disks starts at $206 per month and guarantees outstanding performance without exception, even for highly demanding workloads. A user who needs the full capacity of Gcore’s top-end cloud server could experience performance issues if they tried to put that same workload through an entry-level server, which is why it’s important to pick the option that matches your use case. Gcore’s experts can help with that.

Regulations, Compliance, and Governance

Data privacy rules, regulations, and other industry standards mean that cloud users can come up against challenging differences between geographical locations, which limit options for cloud servers. For example, if regulations or industry standards demand that the organization must store its data within its political and geographic boundaries, this means a limited choice of cloud servers.

Unexpected Cloud Server Outages

Cloud servers may experience unexpected outages due to a problem within the service provider’s infrastructure or as a result of internet issues. Since the servers are hosted at a physical distance, customers have no way to remedy outages and are reliant on the cloud provider for both information and a fix.

Such problems may include network issues or slow performance due to spikes in demand. Additionally, unexpected network issues could be beyond even the provider’s control. To safeguard against such a challenge, organizations may opt to keep the critical workloads in on-premises servers. Choosing a reliable cloud provider, such as Gcore, can help to limit such outages.

Limited Direct Control of the Server

The cloud provider manages the cloud infrastructure, including the type of hardware components and location. This leaves you unable to optimize the systems for the best performance, since you have no direct control of the server.

Incompatibility

If the cloud servers only support some of your operating systems, workloads, and applications, you may experience compatibility issues. Selecting a cloud provider and planning carefully upfront can help mitigate this problem but does not always account for future additional or changed needs.

Factors to Consider When Looking for a Cloud Server

The choice of a cloud server depends on a combination of factors, such as your workload, budget, server technology, and providers’ reputations. Below are the key issues to consider.

Type of Cloud Server to Deploy 

Virtual machines are budget friendly and easier to manage. However, performance issues are always a threat, especially when other tenants have a high demand for resources on the same physical machine. As such, they are suitable for less resource-intensive and non-critical workloads. If you want a third-party vendor-controlled virtualized layer, this is the right choice.

If you need more resources and your workload requires an entire system built from the ground up, then you need a bare metal server. Bare metal offers superior resources compared to VM, and other clients’ demands do not affect bare metal. However, bare metal is costlier than VM. You can host the bare metal server on-premises or on a third-party provider’s infrastructure.

Type of Server Virtualization Technology

Providers may use hardware or software virtualization technologies to subdivide a physical server into several virtual machines. In a logical cloud server, virtualization abstracts resources such as the CPU, storage, memory, and network from the physical hardware, so that services and applications can function without depending so much on the hardware.

Besides hypervisor-based virtualization, providers can use other technologies such as OS-level virtualization, hardware virtualization, hardware-assisted virtualization, etc. It’s important to check whether the virtualization technology is suitable for your operating system, applications, and workloads.

Cloud Server Security

Securing your users, workloads, and data on the cloud server should be a priority. This prevents or reduces risks of cyberattacks, DDoS attacks, ransomware, and other security issues that could compromise your systems and lead to performance degradation and even financial and reputation losses for your organization.

Unlike an on-premises data center, where you can protect your digital assets using perimeter security and other technologies, you have less control over the cloud-based server. Instead, you have to rely more on the security measures of the cloud service provider.

It is, therefore, vital to evaluate their technologies and ensure the provider can adequately secure your cloud server. However, cloud security is a shared responsibility between the provider and customers. As such, you still need to deploy various security measures, policies, and practices to protect your users, applications, and data.

Cost-Effective Cloud Services

Good value doesn’t always mean picking the cheapest option available. Select a cloud service that delivers the best features at a fair price. Customizing and optimizing the server comes with added costs, but ensures better performance and security of your workloads and data. It’s also worth paying attention to the available pricing plans, their flexibility, and their compensation policy if you decide to move away before the contract ends.

Support for Private Cloud Server

The public cloud servers offer some level of cost-savings and convenience. However, compliance and data governance requirements may require deploying a private cloud server with resources fenced off from other users. In such a case, you need a provider who supports the private or hybrid cloud server system while offering favorable customization options.

Numerous and Diverse Cloud Features

It is vital to look for a provider who offers a service that meets your current and future needs. Choose a provider offering features such as automatic scaling, load balancing, easy server upgrades, backups, and disaster recovery so that you can feel confident in your efficiency, performance, and continuity.

Reliable and Prompt Support

A good provider must offer reliable support to minimize downtimes. Ideally, look for a provider that provides 24/7 support. Check the reviews to see what other customers have experienced when it comes to support from your potential provider.

Compliance with Regulatory Standards

If you are in an industry that requires compliance with regulations such as GDPR, CCPA, ISO/EIC 27 001, HIPAA, PCI-DSS, and others, look for a compliant provider.

Seamless Migration to the Cloud

Whether switching from an on-premises data center or another cloud provider, your new cloud service provider should assist you in the migration process. Such support ensures a smooth transition and minimal interruption or downtime.

Cloud Server Customization Options

If you anticipate that your business will grow rapidly or experience temporary demand spikes, look for a scalable and customizable service where you can add or remove resources to meet current and future needs. Auto-scaling features enable the automatic addition or removal of server resources, ensuring that you can easily and quickly process any workload while only paying for the computing resources that you actually use.

Should You Switch to a Cloud Server?

Most individuals and organizations benefit from switching to the cloud because it offers cost-effective, scalable, and reliable on-demand computing services without an upfront cost.

However, public cloud is not always the best choice, especially for use cases involving unusually sensitive data (such as healthcare or finance companies) or extreme performance computing requirements. For sensitive workloads, Gcore offers highly secure virtual cloud servers with Intel SGX support. The technology provides extra security such that only authorized users can access the encrypted data.

An assessment of your specific needs and circumstances is important before deciding to switch to cloud, but in almost all cases, it’s a move worth making.

Examples of Cloud Servers

Most organizations and individuals are using cloud servers in one way or another. Some use cases include email, file storage, and web applications. The cloud servers power major platforms and diverse application types, such as Software as a Service (SaaS,) Infrastructure as a Service (IaaS,) and Platform as a Service (PaaS.) Let’s take a look at two examples: Dropbox and Gcore.

Dropbox is a popular web-based file storage, sharing, and synchronization platform. It allows users to store files from their computers and access them from anywhere over the internet and supports real-time collaboration.

Gcore provides customizable cloud computing, CDN, infrastructure, security, and other services to meet computing needs across all industries. These include:

Conclusion

Cloud servers provide customers with a cost-effective solution to meet varying workloads on demand. We have learned about the cloud-based server, how it works, its benefits, and the type to deploy. The next step is to look for a reliable provider with the capacity and ability to meet your needs, which means balancing a number of complex factors.

Choosing the right cloud service provider is critical to achieving your organization’s objectives and success. It’s vital to opt for a service that meets both your current and future needs. At Gcore, we offer high-performance, scalable, affordable cloud servers to support customers and industries with different needs and workloads.

To learn more about Gcore, check out our cloud server products or talk to one of our experts for a free consultation on deploying your cloud servers and improving your operations.

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Provisioning new cloud instances can be repetitive and time-consuming if you’re doing everything manually: installing packages, configuring environments, copying SSH keys, and more. With cloud-init, you can automate these tasks and launch development-ready instances from the start.Gcore Edge Cloud VMs support cloud-init out of the box. With a simple YAML script, you can automatically set up a development-ready instance at boot, whether you’re launching a single machine or spinning up a fleet.In this guide, we’ll walk through how to use cloud-init on Gcore Edge Cloud to:Set a passwordInstall packages and system updatesAdd users and SSH keysMount disks and write filesRegister services or install tooling like Docker or Node.jsLet’s get started.What is cloud-init?cloud-init is a widely used tool for customizing cloud instances during the first boot. It reads user-provided configuration data—usually YAML—and uses it to run commands, install packages, and configure the system. In this article, we will focus on Linux-based virtual machines.How to use cloud-init on GcoreFor Gcore Cloud VMs, cloud-init scripts are added during instance creation using the User data field in the UI or API.Step 1: Create a basic scriptStart with a simple YAML script. Here’s one that updates packages and installs htop:#cloud-config package_update: true packages: - htop Step 2: Launch a new VM with your scriptGo to the Gcore Customer Portal, navigate to VMs, and start creating a new instance (or just click here). When you reach the Additional options section, enable the User data option. Then, paste in your YAML cloud-init script.Once the VM boots, it will automatically run the script. This works the same way for all supported Linux distributions available through Gcore.3 real-world examplesLet’s look at three examples of how you can use this.Example 1: Add a password for a specific userThe below script sets the for the default user of the selected operating system:#cloud-config password: <password> chpasswd: {expire: False} ssh_pwauth: True Example 2: Dev environment with Docker and GitThe following script does the following:Installs Docker and GitAdds a new user devuser with sudo privilegesAuthorizes an SSH keyStarts Docker at boot#cloud-config package_update: true packages: - docker.io - git users: - default - name: devuser sudo: ALL=(ALL) NOPASSWD:ALL groups: docker shell: /bin/bash ssh-authorized-keys: - ssh-rsa AAAAB3Nza...your-key-here runcmd: - systemctl enable docker - systemctl start docker Example 3: Install Node.js and clone a repoThis script installs Node.js and clones a GitHub repo to your Gcore VM at launch:#cloud-config packages: - curl runcmd: - curl -fsSL https://deb.nodesource.com/setup_18.x | bash - - apt-get install -y nodejs - git clone https://github.com/example-user/dev-project.git /home/devuser/project Reusing and versioning your scriptsTo avoid reinventing the wheel, keep your cloud-init scripts:In version control (e.g., Git)Templated for different environments (e.g., dev vs staging)Modular so you can reuse base blocks across projectsYou can also use tools like Ansible or Terraform with cloud-init blocks to standardize provisioning across your team or multiple Gcore VM environments.Debugging cloud-initIf your script doesn’t behave as expected, SSH into the instance and check the cloud-init logs:sudo cat /var/log/cloud-init-output.log This file shows each command as it ran and any errors that occurred.Other helpful logs:/var/log/cloud-init.log /var/lib/cloud/instance/user-data.txt Pro tip: Echo commands or write log files in your script to help debug tricky setups—especially useful if you’re automating multi-node workflows across Gcore Cloud.Tips and best practicesIndentation matters! YAML is picky. Use spaces, not tabs.Always start the file with #cloud-config.runcmd is for commands that run at the end of boot.Use write_files to write configs, env variables, or secrets.Cloud-init scripts only run on the first boot. To re-run, you’ll need to manually trigger cloud-init or re-create the VM.Automate it all with GcoreIf you're provisioning manually, you're doing it wrong. Cloud-init lets you treat your VM setup as code: portable, repeatable, and testable. Whether you’re spinning up ephemeral dev boxes or preparing staging environments, Gcore’s support for cloud-init means you can automate it all.For more on managing virtual machines with Gcore, check out our product documentation.Explore Gcore VM product docs

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You get exclusive access and control over the hardware via the cloud provider, which offers the stability and security needed for high-demand applications.The benefits of bare metal serversHere are some of the business advantages of opting for a bare metal server:Maximized performance: Because they are dedicated resources, bare metal servers provide top-tier performance without sharing processing power, memory, or storage with other users. This makes them ideal for resource-intensive applications like high-performance computing (HPC), big data processing, and game hosting.Greater control: Since you have direct access to the hardware, you can customize the server to meet your specific requirements. This is especially important for businesses with complex, specialized needs that require fine-tuned configurations.High security: Bare metal servers offer a higher level of security than their alternatives due to the absence of virtualization. With no shared resources or hypervisor layer, there’s less risk of vulnerabilities that come with multi-tenant environments.Dedicated resources: Because you aren’t sharing the server with other users, all server resources are dedicated to your application so that you consistently get the performance you need.Who should use bare metal servers?Here are examples of instances where bare metal servers are the best option for a business:High-performance computing (HPC)Big data processing and analyticsResource-intensive applications, such as AI/ML workloadsGame and video streaming serversBusinesses requiring enhanced security and complianceAll about virtual machinesA virtual server (or virtual machine) runs on top of a physical server that’s been partitioned by a cloud provider using a hypervisor. This allows multiple VMs to share the same hardware while remaining isolated from each other.Unlike bare metal servers, virtual machines share the underlying hardware with other cloud provider customers. That means you’re using (and paying for) part of one server, providing cost efficiency and flexibility.The benefits of virtual machinesHere are some advantages of using a shared virtual machine:Scalability: Virtual machines are ideal for businesses that need to scale quickly and are starting at a small scale. With cloud-based virtualization, you can adjust your server resources (CPU, memory, storage) on demand to match changing workloads.Cost efficiency: You pay only for the resources you use with VMs, making them cost-effective for companies with fluctuating resource needs, as there is no need to pay for unused capacity.Faster deployment: VMs can be provisioned quickly and easily, which makes them ideal for anyone who wants to deploy new services or applications fast.Who should use virtual machines?VMs are a great fit for the following:Web hosting and application hostingDevelopment and testing environmentsRunning multiple apps with varying demandsStartups and growing businesses requiring scalabilityBusinesses seeking cost-effective, flexible solutionsWhich should you choose?There’s no one-size-fits-all answer. Your choice should depend on the needs of your workload:Choose bare metal if you need dedicated performance, low-latency access to hardware, or tighter control over security and compliance.Choose virtual servers if your priority is flexible scaling, faster deployment, and optimized cost.If your application uses GPU-based inference or AI training, check out our dedicated guide to VM vs. BM for AI workloads.Get started with Gcore BM or VMs todayAt Gcore, we provide both bare metal and virtual machine solutions, offering flexibility, performance, and reliability to meet your business needs. Gcore Bare Metal has the power and reliability needed for demanding workloads, while Gcore Virtual Machines offers customizable configurations, free egress traffic, and flexibility.Compare Gcore BM and VM pricing now

Optimize your workload: a guide to selecting the best virtual machine configuration

Virtual machines (VMs) offer the flexibility, scalability, and cost-efficiency that businesses need to optimize workloads. However, choosing the wrong setup can lead to poor performance, wasted resources, and unnecessary costs.In this guide, we’ll walk you through the essential factors to consider when selecting the best virtual machine configuration for your specific workload needs.﹟1 Understand your workload requirementsThe first step in choosing the right virtual machine configuration is understanding the nature of your workload. Workloads can range from light, everyday tasks to resource-intensive applications. When making your decision, consider the following:Compute-intensive workloads: Applications like video rendering, scientific simulations, and data analysis require a higher number of CPU cores. Opt for VMs with multiple processors or CPUs for smoother performance.Memory-intensive workloads: Databases, big data analytics, and high-performance computing (HPC) jobs often need more RAM. Choose a VM configuration that provides sufficient memory to avoid memory bottlenecks.Storage-intensive workloads: If your workload relies heavily on storage, such as file servers or applications requiring frequent read/write operations, prioritize VM configurations that offer high-speed storage options, such as SSDs or NVMe.I/O-intensive workloads: Applications that require frequent network or disk I/O, such as cloud services and distributed applications, benefit from VMs with high-bandwidth and low-latency network interfaces.﹟2 Consider VM size and scalabilityOnce you understand your workload’s requirements, the next step is to choose the right VM size. VM sizes are typically categorized by the amount of CPU, memory, and storage they offer.Start with a baseline: Select a VM configuration that offers a balanced ratio of CPU, RAM, and storage based on your workload type.Scalability: Choose a VM size that allows you to easily scale up or down as your needs change. Many cloud providers offer auto-scaling capabilities that adjust your VM’s resources based on real-time demand, providing flexibility and cost savings.Overprovisioning vs. underprovisioning: Avoid overprovisioning (allocating excessive resources) unless your workload demands peak capacity at all times, as this can lead to unnecessary costs. Similarly, underprovisioning can affect performance, so finding the right balance is essential.﹟3 Evaluate CPU and memory considerationsThe central processing unit (CPU) and memory (RAM) are the heart of a virtual machine. The configuration of both plays a significant role in performance. Workloads that need high processing power, such as video encoding, machine learning, or simulations, will benefit from VMs with multiple CPU cores. However, be mindful of CPU architecture—look for VMs that offer the latest processors (e.g., Intel Xeon, AMD EPYC) for better performance per core.It’s also important that the VM has enough memory to avoid paging, which occurs when the system uses disk space as virtual memory, significantly slowing down performance. Consider a configuration with more RAM and support for faster memory types like DDR4 for memory-heavy applications.﹟4 Assess storage performance and capacityStorage performance and capacity can significantly impact the performance of your virtual machine, especially for applications requiring large data volumes. Key considerations include:Disk type: For faster read/write operations, opt for solid-state drives (SSDs) over traditional hard disk drives (HDDs). Some cloud providers also offer NVMe storage, which can provide even greater speed for highly demanding workloads.Disk size: Choose the right size based on the amount of data you need to store and process. Over-allocating storage space might seem like a safe bet, but it can also increase costs unnecessarily. You can always resize disks later, so avoid over-allocating them upfront.IOPS and throughput: Some workloads require high input/output operations per second (IOPS). If this is a priority for your workload (e.g., databases), make sure that your VM configuration includes high IOPS storage options.﹟5 Weigh up your network requirementsWhen working with cloud-based VMs, network performance is a critical consideration. High-speed and low-latency networking can make a difference for applications such as online gaming, video conferencing, and real-time analytics.Bandwidth: Check whether the VM configuration offers the necessary bandwidth for your workload. For applications that handle large data transfers, such as cloud backup or file servers, make sure that the network interface provides high throughput.Network latency: Low latency is crucial for applications where real-time performance is key (e.g., trading systems, gaming). Choose VMs with low-latency networking options to minimize delays and improve the user experience.Network isolation and security: Check if your VM configuration provides the necessary network isolation and security features, especially when handling sensitive data or operating in multi-tenant environments.﹟6 Factor in cost considerationsWhile it’s essential that your VM has the right configuration, cost is always an important factor to consider. Cloud providers typically charge based on the resources allocated, so optimizing for cost efficiency can significantly impact your budget.Consider whether a pay-as-you-go or reserved model (which offers discounted rates in exchange for a long-term commitment) fits your usage pattern. The reserved option can provide significant savings if your workload runs continuously. You can also use monitoring tools to track your VM’s performance and resource usage over time. This data will help you make informed decisions about scaling up or down so you’re not paying for unused resources.﹟7 Evaluate security featuresSecurity is a primary concern when selecting a VM configuration, especially for workloads handling sensitive data. Consider the following:Built-in security: Look for VMs that offer integrated security features such as DDoS protection, web application firewall (WAF), and encryption.Compliance: Check that the VM configuration meets industry standards and regulations, such as GDPR, ISO 27001, and PCI DSS.Network security: Evaluate the VM's network isolation capabilities and the availability of cloud firewalls to manage incoming and outgoing traffic.﹟8 Consider geographic locationThe geographic location of your VM can impact latency and compliance. Therefore, it’s a good idea to choose VM locations that are geographically close to your end users to minimize latency and improve performance. In addition, it’s essential to select VM locations that comply with local data sovereignty laws and regulations.﹟9 Assess backup and recovery optionsBackup and recovery are critical for maintaining data integrity and availability. Look for VMs that offer automated backup solutions so that data is regularly saved. You should also evaluate disaster recovery capabilities, including the ability to quickly restore data and applications in case of failure.﹟10 Test and iterateFinally, once you've chosen a VM configuration, testing its performance under real-world conditions is essential. Most cloud providers offer performance monitoring tools that allow you to assess how well your VM is meeting your workload requirements.If you notice any performance bottlenecks, be prepared to adjust the configuration. This could involve increasing CPU cores, adding more memory, or upgrading storage. Regular testing and fine-tuning means that your VM is always optimized.Choosing a virtual machine that suits your requirementsSelecting the best virtual machine configuration is a key step toward optimizing your workloads efficiently, cost-effectively, and without unnecessary performance bottlenecks. By understanding your workload’s needs, considering factors like CPU, memory, storage, and network performance, and continuously monitoring resource usage, you can make informed decisions that lead to better outcomes and savings.Whether you're running a small application or large-scale enterprise software, the right VM configuration can significantly improve performance and cost. Gcore offers a wide range of virtual machine options that can meet your unique requirements. Our virtual machines are designed to meet diverse workload requirements, providing dedicated vCPUs, high-speed storage, and low-latency networking across 30+ global regions. You can scale compute resources on demand, benefit from free egress traffic, and enjoy flexible pricing models by paying only for the resources in use, maximizing the value of your cloud investments.Contact us to discuss your VM needs

How to get the size of a directory in Linux

Understanding how to check directory size in Linux is critical for managing storage space efficiently. Understanding this process is essential whether you’re assessing specific folder space or preventing storage issues.This comprehensive guide covers commands and tools so you can easily calculate and analyze directory sizes in a Linux environment. We will guide you step-by-step through three methods: du, ncdu, and ls -la. They’re all effective and each offers different benefits.What is a Linux directory?A Linux directory is a special type of file that functions as a container for storing files and subdirectories. It plays a key role in organizing the Linux file system by creating a hierarchical structure. This arrangement simplifies file management, making it easier to locate, access, and organize related files. Directories are fundamental components that help ensure smooth system operations by maintaining order and facilitating seamless file access in Linux environments.#1 Get Linux directory size using the du commandUsing the du command, you can easily determine a directory’s size by displaying the disk space used by files and directories. The output can be customized to be presented in human-readable formats like kilobytes (KB), megabytes (MB), or gigabytes (GB).Check the size of a specific directory in LinuxTo get the size of a specific directory, open your terminal and type the following command:du -sh /path/to/directoryIn this command, replace /path/to/directory with the actual path of the directory you want to assess. The -s flag stands for “summary” and will only display the total size of the specified directory. The -h flag makes the output human-readable, showing sizes in a more understandable format.Example: Here, we used the path /home/ubuntu/, where ubuntu is the name of our username directory. We used the du command to retrieve an output of 32K for this directory, indicating a size of 32 KB.Check the size of all directories in LinuxTo get the size of all files and directories within the current directory, use the following command:sudo du -h /path/to/directoryExample: In this instance, we again used the path /home/ubuntu/, with ubuntu representing our username directory. Using the command du -h, we obtained an output listing all files and directories within that particular path.#2 Get Linux directory size using ncduIf you’re looking for a more interactive and feature-rich approach to exploring directory sizes, consider using the ncdu (NCurses Disk Usage) tool. ncdu provides a visual representation of disk usage and allows you to navigate through directories, view size details, and identify large files with ease.For Debian or Ubuntu, use this command:sudo apt-get install ncduOnce installed, run ncdu followed by the path to the directory you want to analyze:ncdu /path/to/directoryThis will launch the ncdu interface, which shows a breakdown of file and subdirectory sizes. Use the arrow keys to navigate and explore various folders, and press q to exit the tool.Example: Here’s a sample output of using the ncdu command to analyze the home directory. Simply enter the ncdu command and press Enter. The displayed output will look something like this:#3 Get Linux directory size using 1s -1aYou can alternatively opt to use the ls command to list the files and directories within a directory. The options -l and -a modify the default behavior of ls as follows:-l (long listing format)Displays the detailed information for each file and directoryShows file permissions, the number of links, owner, group, file size, the timestamp of the last modification, and the file/directory name-a (all files)Instructs ls to include all files, including hidden files and directoriesIncludes hidden files on Linux that typically have names beginning with a . (dot)ls -la lists all files (including hidden ones) in long format, providing detailed information such as permissions, owner, group, size, and last modification time. This command is especially useful when you want to inspect file attributes or see hidden files and directories.Example: When you enter ls -la command and press Enter, you will see an output similar to this:Each line includes:File type and permissions (e.g., drwxr-xr-x):The first character indicates the file type- for a regular filed for a directoryl for a symbolic linkThe next nine characters are permissions in groups of three (rwx):r = readw = writex = executePermissions are shown for three classes of users: owner, group, and others.Number of links (e.g., 2):For regular files, this usually indicates the number of hard linksFor directories, it often reflects subdirectory links (e.g., the . and .. entries)Owner and group (e.g., user group)File size (e.g., 4096 or 1045 bytes)Modification date and time (e.g., Jan 7 09:34)File name (e.g., .bashrc, notes.txt, Documents):Files or directories that begin with a dot (.) are hidden (e.g., .bashrc)ConclusionThat’s it! You can now determine the size of a directory in Linux. Measuring directory sizes is a crucial skill for efficient storage management. Whether you choose the straightforward du command, use the visual advantages of the ncdu tool, or opt for the versatility of ls -la, this expertise enhances your ability to uphold an organized and efficient Linux environment.Looking to deploy Linux in the cloud? With Gcore Edge Cloud, you can choose from a wide range of pre-configured virtual machines suitable for Linux:Affordable shared compute resources starting from €3.2 per monthDeploy across 50+ cloud regions with dedicated servers for low-latency applicationsSecure apps and data with DDoS protection, WAF, and encryption at no additional costGet started today

How to Run Hugging Face Spaces on Gcore Inference at the Edge

Running machine learning models, especially large-scale models like GPT 3 or BERT, requires a lot of computing power and comes with a lot of latency. This makes real-time applications resource-intensive and challenging to deliver. Running ML models at the edge is a lightweight approach offering significant advantages for latency, privacy, and resource optimization.  Gcore Inference at the Edge makes it simple to deploy and manage custom models efficiently, giving you the ability to deploy and scale your favorite Hugging Face models globally in just a few clicks. In this guide, we’ll walk you through how easy it is to harness the power of Gcore’s edge AI infrastructure to deploy a Hugging Face Space model. Whether you’re developing NLP solutions or cutting-edge computer vision applications, deploying at the edge has never been simpler—or more powerful. Step 1: Log In to the Gcore Customer PortalGo to gcore.com and log in to the Gcore Customer Portal. If you don’t yet have an account, go ahead and create one—it’s free. Step 2: Go to Inference at the EdgeIn the Gcore Customer Portal, click Inference at the Edge from the left navigation menu. Then click Deploy custom model. Step 3: Choose a Hugging Face ModelOpen huggingface.com and browse the available models. Select the model you want to deploy. Navigate to the corresponding Hugging Face Space for the model. Click on Files in the Space and locate the Docker option. Copy the Docker image link and startup command from Hugging Face Space. Step 4: Deploy the Model on GcoreReturn to the Gcore Customer Portal deployment page and enter the following details: Model image URL: registry.hf.space/ethux-mistral-pixtral-demo:latest Startup command: python app.py Container port: 7860 Configure the pod as follows: GPU-optimized: 1x L40S vCPUs: 16 RAM: 232GiB For optimal performance, choose any available region for routing placement. Name your deployment and click Deploy.Step 5: Interact with Your ModelOnce the model is up and running, you’ll be provided with an endpoint. You can now interact with the model via this endpoint to test and use your deployed model at the edge.Powerful, Simple AI Deployment with GcoreGcore Inference at the Edge is the future of AI deployment, combining the ease of Hugging Face integration with the robust infrastructure needed for real-time, scalable, and global solutions. By leveraging edge computing, you can optimize model performance and simultaneously futureproof your business in a world that increasingly demands fast, secure, and localized AI applications. Deploying models to the edge allows you to capitalize on real-time insights, improve customer experiences, and outpace your competitors. Whether you’re leading a team of developers or spearheading a new AI initiative, Gcore Inference at the Edge offers the tools you need to innovate at the speed of tomorrow. Explore Gcore Inference at the Edge

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