How can you optimize virtual machines for different cloud computing platforms?

1. Instance types should be optimized for workloads, choose VM instances with appropriate CPU, memory, storage, and networking resources based on workload requirements. 2. Auto-scaling can be configured. 3. Container orchestration (eg: Kubernetes)- Automates management and scaling across VM and clusters.

Think simple - in the end it's a pricing compute decision ... . For example, Google Cloud has compute-optimized VMs that are ideal for compute-intensive and high performance computing (HPC) workloads, while Azure has reserved instances and savings plans that can help you save costs for consistent or dynamic workloads. You should compare the features, specifications, and prices of different VM options and select the ones that match your requirements and budget.

Cada provedor de nuvem oferece diferentes tipos de instância com características específicas, como CPU, RAM, armazenamento e capacidades de rede. Escolha o tipo de instância mais adequado às suas necessidades de aplicação, considerando fatores como carga de trabalho, escalabilidade e custo.

Optimizing virtual machines for different cloud computing platforms involves several key steps:🎯 1. Choose the right instance type: Each cloud computing platform offers a variety of instance types with different combinations of CPU, memory, storage, and network resources. Select an instance type that best matches your workload requirements. 🚀

Cloud platforms VM types based on use cases/workloads such as balanced CPU-to-memory ratio, high CPU performance, high memory capacity, storage optimized, and GPU optimized. Begin with a minimum requirement, choose instance types with cost savings in mind. Your cost optimization strategy might include deploying on-demand VMs, reserving VM instances for discounts, most cloud platforms allow changing VM types, so you're not stuck with one. Leverage features like CPU/disk bursting and factor in network bandwidth. Cloud platforms provide resource monitoring, leverage them for insights allowing for optimization. The right VM type depends on your workload, performance needs and budget, evaluate them and make an informed choice.

Tailor the size of your VM to match the resource requirements of your application. Avoid overprovisioning or underprovisioning resources, as this can lead to unnecessary costs or performance bottlenecks. Utilize tools provided by the cloud provider to accurately estimate resource needs and select the optimal VM size accordingly.

Choose the right VM SKU based on your workload requirements, whether more CPU cores, memory, storage, GPU capacity. Cloud platforms provide VM selector tools (Azure VM Selector, AWS Instance Type Explorer) to find the best fit for your specific workload. VMs can be resized, explore the available sizes and optimize the VM for performance and cost efficiency by monitoring them. Monitoring is crucial to optimize performance, resource utilization and cost.

A virtual machine (VM) is a digital version of a physical computer. Virtual machine software can run programs and operating systems, store data, connect to networks, and do other computing functions, and requires maintenance such as updates and system monitoring Thanks Engr. sangobiyi abolaji.

📍When optimizing virtual machines for different cloud computing platforms, selecting the right VM size is crucial. For example, on AWS, you can choose from a variety of instance types such as General Purpose, Compute Optimized, Memory Optimized, and Storage Optimized based on your workload requirements. On Azure, you can select VM sizes ranging from basic to memory-optimized or compute-optimized series. Google Cloud offers predefined machine types or custom machine types for flexibility. By carefully choosing the appropriate VM size that aligns with your workload characteristics, you can ensure optimal performance, cost efficiency, and scalability on each cloud platform. 💥

Shut down idle or unused VMs. One of the easiest ways to optimize your VMs is to turn them off when they are not needed. This can help you reduce unnecessary costs and free up resources for other workloads. You can use automation tools or scripts to schedule or trigger VM shutdown based on certain conditions, such as time, activity, or demand. You can also use scaling mechanisms, such as virtual machine scale sets on Azure or managed instance groups on Google Cloud, to automatically adjust the number and size of your VMs based on load or performance metrics.

A otimização da imagem de ima VM também passa pela implementação de firewalls e políticas de segurança adequadas, aumentando a proteção contra ameaças externas. Restringir o tráfego de rede desnecessário e aplicar práticas recomendadas de segurança, como a autenticação multifatorial e a criptografia de dados, também podem ser alternativas valiosas.

Customize the VM image by removing unnecessary software, services, and configurations to streamline performance and reduce overhead. Implement best practices for image optimization, such as minimizing disk space usage, optimizing startup scripts, and configuring security settings to enhance efficiency and security.

1. Right-sizing VMs: Choose the correct VM size for your workload. Monitor performance and scale up or down as necessary. 2. Storage Optimization: Use the right type of storage (SSD vs. HDD, object storage, block storage, etc.) based on your performance and cost requirements. 3. Network Optimization: Minimize data transfer costs by understanding the network topology and optimizing data flows. 4. Cost Management: Use cost-management tools to monitor and control spending, or the simplest hack is to shut down idle VMs. You can also customize the software running on your VM There are SaaS tools for all the aforementioned solutions, try some of them and see if you are able to optimize for any of these functions.

Don't load anything in the VM you don't need. Having only the necessary binaries/apps minimizes the security attack surface. follow prescribed guidance to build and load VMs on cloud platforms, keep in mind performance and VM security. Tools like Azure VM Image Builder and AWS EC2 Image Builder help reduce the effort of keeping images up-to-date and secure.

Cloud automation is more than just provisioning VMs. Consider orchestration, from AWS CloudFormation to Azure Resource Manager, these are well documented. Your VM deployment could be using one cloud provider or multiple. The orchestration layer should therefore provide visualisation across all. Abstracting the automation of your cloud infrastructure from the cloud workload allows easier switching between cloud providers also. Monitor the process to help streamline your cloud operations and enhance overall efficiency.

Using VMs in cloud computing offers the advantage of automating the deployment process. This means you can set up, control, and remove VMs automatically, saving time and effort. Utilizing tools like AWS CloudFormation or Ansible streamlines the process further.

Consider platform-level monitoring for cloud VMs, to collect host-level metrics such as CPU usage, disk activity, network usage and various resource-related data. Consider guest-level monitoring, to collect specific metrics and logs from within the VM. This typically requires installing a monitoring agent, allowing the collection of detailed OS data, application-specific performance data, custom logs and diagnostic information. To summarize, platform-level monitoring - broad overview of VM health ; guest-level monitoring - deeper insights into specific aspects of VM.

L'article est bien rédigé, mais à tout ceci, il faut aussi automatiser les tests des machines après provisionnement afin de se rassurer que la VM repond bien sans scratchs ou bug avant de la livrer. Desactiver les mise à jours automatique de certains paquets afin d'éviter des conflits ou incompatibilité de nous provisionnement de base.

Use tags and labels to organize and manage your VMs. Tags and labels are key-value pairs that you can assign to your VMs to identify and group them by various criteria, such as owner, project, environment, or function. This can help you track and optimize your resource usage, billing, security, and governance.