How can you address virtual machine storage limitations in cloud computing?

Por mi experiencia e aprendido que el realizar un buen y detallado análisis del core de negocio de los clientes nos permitirá poder conocer en detalle la información que se almacenera sobre las VMs y los tipos aplicaciones que utilizara, con ellos se podrá hacer una proyección aproximada de en que momento genera mas carga de data y preparara las VMs para asumir estos picos

A strong, well defined future strategy is fundemental to ensure compatibility and scalability across an organisation or if the business is expecting long term growth. Plan for tomorrow and implement today.

One way of storage optimization is to set retention for your storage data. If old data is stored unnecessarily, they can be deleted and freed up.

De acuerdo con el tipo de data de data y con las aplicaciones que las consumen se debe customizar el tipo de almacenamiento que se debe presentar a cada una de las VMs con relación a tipos de arreglo y tipo a discos a utilizar

Aside from the technical options, optimisation naturally occurs through clearly defined retention policy and departmental ownership strategies or patterns. In most cases, the infra/IT team won't 'manage' or 'care' about the data consuming their storage, yet will heavily influence their decisions on architecture and solutions based on the types of data. Setup clear guidelines and instructions for departments to follow such as "sensitive documents go in secure cloud storage, daily misc documents go in sharepoint/teams".

Use Scalable Storage Solutions: Consider using scalable storage solutions provided by the cloud provider, such as Amazon Elastic Block Store (EBS) in AWS, Azure Disk Storage in Microsoft Azure, or Google Persistent Disk in Google Cloud Platform. These services offer flexible storage options with features like auto-scaling, snapshotting, and replication to meet changing storage requirements.

If there are too many I/O operations involved and you do not need OS level caching for the disk operations, you can use O_DIRECT(unix-based flag) like flags in your I/O api to let the Operating System know that it need not cache the i/o data. This bypasses the OS's buffer cache providing significant performance. However, use it with care as it has trade-offs and sometimes not recommended. It is used in systems like database servers, virtualization, and high-performance computing.

This is where things like ACLs/JIT access/PIM and security groups shine. From a cloud point of view, Azure offers plenty of native solutions such as policy and ISO standard healthchecks. And I come back to my previous comments, corporate data management patterns and training are what will really drive best practice. Establish the framework, provide the platform and then supply the tools needed for users to govern their data. Azure files is encrypted at rest and in transit, making it ideal. A basic azure files scenario would be: -create azure files departmental folder structure -create security groups with users -apply groups to folders -use on prem file cache servers or provide PiPs for secure network access

It is worth reading up on possible future storage services, such as block chain based decentralized storage and compute. (IPFS, FILECOIN, GOLEM etc)

You can cache the frequently used data in memory. You can use in-memory database. These would offload your storage access by getting the frequently accessed data straight from cache.