Skip to main content

multi-cloud strategy


A multi-cloud strategy is the use of two or more cloud computing services. While a multi-cloud deployment can refer to any implementation of multiple software as a service (SaaS) or platform as a service (PaaS) cloud offerings, today, it generally refers to a mix of public infrastructure as a service (IaaS) environments, such as Amazon Web Services and Microsoft Azure.

Common uses for multi-cloud computing


Initially, many organizations pursued a multi-cloud strategy because they were uncertain about cloud reliability. Multi-cloud was, and still is, seen as a way to prevent data loss or downtime due to a localized component failure in the cloud. The ability to avoid vendor lock-in was also an early driver of multi-cloud adoption.


While redundancy and vendor lock-in concerns still drive some multi-cloud deployments today, they are also driven largely by enterprises' broader business or technical goals. Those goals can include the use of more price-competitive cloud services or taking advantage of the speed, capacity or features offered by a particular cloud provider in a particular geography.


In addition, some organizations pursue multi-cloud strategies for data sovereignty reasons. Certain laws, regulations and corporate policies require enterprise data to physically reside in certain locations. Multi-cloud computing can help organizations meet those requirements, since they can select from multiple IaaS providers' data center regions or availability zones. This flexibility in where cloud data resides also enables organizations to locate compute resources as close as possible to end users to achieve optimal performance and minimal latency.


A multi-cloud strategy also offers the ability to select different cloud services or features from different providers. This is helpful, since some cloud environments are better suited than others for a particular task.


For example, a certain cloud platform might handle large numbers of requests per unit time, requiring small data transfers on the average, while a different cloud platform might perform better for a smaller numbers of requests per unit time involving large data transfers. Some cloud providers also offer more big data analytics tools or other specialized capabilities, such as machine learning, than their competitors.

Comments

Popular posts from this blog

Understanding the Evolution: AI, ML, Deep Learning, and Gen AI

In the ever-evolving landscape of artificial intelligence (AI) and machine learning (ML), one of the most intriguing advancements is the emergence of General AI (Gen AI). To grasp its significance, it's essential to first distinguish between these interconnected but distinct technologies. AI, ML, and Deep Learning: The Building Blocks Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Machine Learning, a subset of AI, empowers machines to learn from data and improve over time without explicit programming. Deep Learning, a specialized subset of ML, involves neural networks with many layers (hence "deep"), capable of learning intricate patterns from vast amounts of data. Enter General AI (Gen AI): Unraveling the Next Frontier Unlike traditional AI systems that excel in specific tasks (narrow AI), General AI aims to replicate human cognitive abilities across various domains. I...

Normalization of Database

Database Normalisation is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy and undesirable characteristics like Insertion, Update and Deletion Anamolies. It is a multi-step process that puts data into tabular form by removing duplicated data from the relation tables. Normalization is used for mainly two purpose, Eliminating reduntant(useless) data. Ensuring data dependencies make sense i.e data is logically stored. Problem Without Normalization Without Normalization, it becomes difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anamolies are very frequent if Database is not Normalized. To understand these anomalies let us take an example of  Student  table. S_id S_Name S_Address Subject_opted 401 Adam Noida Bio 402 Alex Panipat Maths 403 Stuart Jammu Maths 404 Adam Noida Physics Updation Anamoly :  To upda...

How to deal with a toxic working environment

Handling a toxic working environment can be challenging, but there are steps you can take to address the situation and improve your experience at work: Recognize the Signs : Identify the specific behaviors or situations that contribute to the toxicity in your workplace. This could include bullying, harassment, micromanagement, negativity, or lack of support from management. Maintain Boundaries : Set boundaries to protect your mental and emotional well-being. This may involve limiting interactions with toxic individuals, avoiding gossip or negative conversations, and prioritizing self-care outside of work. Seek Support : Reach out to trusted colleagues, friends, or family members for support and advice. Sharing your experiences with others can help you feel less isolated and provide perspective on the situation. Document Incidents : Keep a record of any incidents or behaviors that contribute to the toxic environment, including dates, times, and specific details. This documentation may b...