
Enterprises aim at competitive advantage through process agility and innovative business models at low costs. Cloud solutions provide the much-needed flexibility to enterprises to develop the capabilities necessary to innovate and seize new business opportunities. Businesses look at a better customer experience, business agility and flexibility, a reduction in hardware and IT staffing expenditure, and improved security, among other things when they decide to shift to the cloud.
According to a report by Allied Market Research, the hybrid cloud market was valued at US$ 96.7 billion in 2023, and is estimated to reach US$ 414.1 billion by 2032, growing at a CAGR of 17.2% between 2024 and 2032. Gartner predicts that by 2025 enterprises will spend more on public cloud services than traditional IT solutions. As per IDC, by 2025, 85% of organisations will see a 35% increase in sustainable efficiencies by using software and cloud-based infrastructures. And according to a Delvens report, the global hybrid cloud market size was estimated at US$ 96.2 billion in 2023 and is projected to reach US$ 278.51 billion in 2030 at a CAGR of 16.4% during the forecast period 2023-2030.
CIOs across industries are busy working with multiple cloud providers, essentially to retain what works and check what to improve across the enterprise cloud estate. One of the fundamental decisions they need to make is how to balance the onsite, remote, public and private elements of that combination. CIOs need to derive a strategy to adopt emerging technologies to provide more business value than before. Interestingly, security concerns regarding adoption of public cloud providers are falling while those regarding vendor lock-in are increasing. Enterprises do not want to put all their eggs in one cloud provider’s basket to minimise their dependency on it.
Important factors that CIOs must consider before promoting a hybrid cloud model across the enterprise are:
هذه القصة مأخوذة من طبعة October 2024 من Open Source For You.
ابدأ النسخة التجريبية المجانية من Magzter GOLD لمدة 7 أيام للوصول إلى آلاف القصص المتميزة المنسقة وأكثر من 9,000 مجلة وصحيفة.
بالفعل مشترك ? تسجيل الدخول
هذه القصة مأخوذة من طبعة October 2024 من Open Source For You.
ابدأ النسخة التجريبية المجانية من Magzter GOLD لمدة 7 أيام للوصول إلى آلاف القصص المتميزة المنسقة وأكثر من 9,000 مجلة وصحيفة.
بالفعل مشترك? تسجيل الدخول

Modelling Toeplitz Networks with SageMath
A Toeplitz network refers to a graph that has a comparable regularity in its structure. SageMath is an excellent tool for facilitating the creation, analysis, and visualisation of graphs. Hence, SageMath can be used to effectively model Toeplitz networks and get insights into their structural characteristics, leading to advancements in network design and analysis.

It's the Age of AI Agents!
Businesses must get ready to work with AI agents if they want to stay competitive. Many have already adopted them, while others are gearing up to do so. These agents will soon be part of almost every organisation, making up a large global digital workforce.

Building Machine Learning Models with Scikit-learn
Scikit-learn scores over other machine learning libraries because it is easy to use, comes with a comprehensive feature set, has strong community support, and is customisable. Here's a quick look at its features and use cases.

SageMath: Deeper Insights into Cybersecurity
In the previous article in this SageMath series (published in the January 2025 issue of OSFY), we concluded our discussion of classical encryption techniques and moved on to the exploration of modern cryptography by looking at symmetric-key cryptography. In this ninth article in the series, we will continue the focus on symmetric-key cryptography.

Why You Should Go for Grafana
Explore the main characteristics of Grafana, the open source analytics and visualisation tool for application in the Internet of Things, and see how it compares with other similar popular tools.

Metaverse and Digital Twins: Partnering to Innovate
Let's explore Al-powered digital twin technology and the Metaverse, delving into what they promise, their limitations, and how large language models and generative Al help address these challenges.

How Open Source LLMs are Shaping the Future of AI
The future of AI isn't locked behind proprietary paywalls—it's open and collaborative, with open source LLMs giving businesses the power to innovate on their own terms.

Netbooting a Large Language Model-based OS in an Ubuntu Live Server
This brief tutorial explores the wireless netbooting of the LLM model Gemini AI in an Ubuntu server.

NLP: Text Summarisation with Python
Here's a simple Python method based on the Natural Language Toolkit for extractive text summarisation in natural language processing.

MLOps vs AlOps: What, Where, and Why
MLOps and AIOps excel at driving efficiency and innovation in an organisation. Let's find out what they are, where they can be used, and why we should do so.