Category: Blog

Software Telemetry: How it Works and Why it is Important

Software telemetry, effectively monitors and enhances your applications by collecting, storing, and analyzing data from the system and application.  The history of telemetry spans centuries and can be traced back to steam power monitors developed during the Industrial Revolution. Telemetry has evolved substantially and now applies to software development, healthcare, meteorology, agriculture, and many other fields. This guide focuses on software telemetry, explains how it pertains to application monitoring, details the working principles, and clarifies the distinction between telemetry and monitoring. 

Guide to Azure Cognitive Services by Microsoft

The world is currently amidst an Artificial Intelligence (AI) renaissance. While AI models continue to make headlines for passing impressive tests, developers also look to incorporate AI into their workflows to solve fundamental, everyday problems. Companies are scrambling to leverage AI research for newsworthy performance and more banal functions, and Cognitive Services rise to the occasion. But what exactly are Cognitive Services? This guide focuses on the definition, benefits, use cases, and application principles of Azure Cognitive Services. 

Guide to Private Federated Learning for Healthcare

Federated Learning is an emerging technology practice that has incredible potential. It is a collaborative and decentralized approach that allows scientists to train Artificial Intelligence (AI) and Machine Learning (ML) models using sensitive data without uploading data to servers. Even without direct data uploading, it is important to note that the Federated Learning model alone is not properly secured, and there are many opportunities for malicious activities. For this reason, conversations about Federated Learning are always centered around privacy and security and how to use data responsibly without compromising results. Many industries are exploring the possibilities that federated learning can bring

Event Stream Processing – How Does it Work and Common Use Cases

In recent years, Event Stream Processing, sometimes called ESP, has emerged as a powerful data processing technique that empowers businesses with real-time data insights and decision-making capabilities. By implementing Event Stream Processing, companies gain access to real-time data analysis, which allows them to improve efficiency, optimize operations, mitigate risks, and more. This guide provides business leaders with the definition, purpose, working principles, use cases, and benefits of Event Stream Processing. 

What is Composable Architecture & Why Does it Matter?

Monolithic systems are fading into the past as businesses confront the need to evolve continually against market pressures, technology innovations, and changing consumer needs. Rather than relying on massive, traditional configurations, companies are pivoting to flexible and scalable technology practices. Many agile solutions on the market today deploy Composable Architecture, but what is it, and why does it matter? This guide defines the concept, details the benefits, and explains when and how to implement Composable Architecture. 

What is Codeless Automated Testing & How Does it Work?

Codeless platforms relieve the time-intensive burden of writing code to automate tests. Codeless automated testing has emerged as an excellent way to enhance testing protocols and streamline repetitive manual processes. However, many companies have yet to adopt this innovative technology practice. This guide focuses on codeless test automation, how it works, when to use it, and how to choose the right solution for your business. 

A Guide to Decentralized Applications: Pros, Cons, Examples

Decentralized applications are emerging as an application solution with the potential to transform industries, transactions, and even ways of life. By shifting the control from corporations or singular entities to users, decentralized applications are a technology practice that significantly improves privacy, transparency, and efficiency. This guide provides the definition, working principles, examples, and pros and cons of decentralized applications. 

Best Practices for Headless CMS and SEO

Headless CMS is gaining widespread popularity as businesses opt for a CMS solution that provides more control and flexibility on the backend. However, a Headless CMS does not control how the content is rendered on the frontend. So, how do businesses ensure top search results with a Headless CMS? This guide to Headless CMS SEO lists best practices and tips to achieve SEO success with headless CMS’es. 

How to Boost Teamwork with Asynchronous Communication

While real-time, face-to-face interaction holds its value, the reality of modern workplaces often requires the utilization of asynchronous collaboration. When implemented effectively and combined with direct interaction, asynchronous collaboration can foster team alignment and improve overall efficiency.

How to Adopt Scrum in Your Team

Over the past decade, the role of the Scrum Master has gained immense relevance in the global market. This can be attributed to the increasing number of companies striving to embrace agile to effectively address their customers’ needs.

AI-Augmented Observability: GPT-4-powered cloud Insights for everyone

You’ve undoubtedly heard the buzz surrounding OpenAI’s GPT-4. You might have even dabbled with it, integrating its capabilities into your daily tasks. But now, as you delve deeper, you’re on the lookout for more advanced use cases. You’re probably wondering if you could leverage GPT-4 capabilities to achieve tasks related to cloud-based applications and perhaps, looking to achieve more cloud-strategic goals. Have you ever wanted a way to easily inventory your cloud resources? Perhaps you’re considering reviewing your cloud attack surface? Or are you pondering effective planning for cloud costs? All of the above?  

What We Learned from Using GitHub Copilot to Develop a Machine Learning Project

Background   The history of software engineering is defined by the journey from complexity to simplicity through ever-growing levels of abstraction. Tools, such as programming languages, debuggers, static code analyzers, version control tools, and integrated development environments (IDEs), aim to make the work of software engineers easier and faster by allowing them to operate with code at increasingly higher levels of abstraction. This, combined with the advancements in hardware processing power, has enabled the development of progressively intricate and powerful systems.   

Can Agile and AI Work Together?

Agile methodologies have gained widespread adoption across all market sectors since their conception, yielding positive results. The industry’s acceptance of Agile continues to grow even today. As companies increasingly integrate Artificial Intelligence-powered technologies into their products, questions arise regarding project and initiative management around these products. Is Agile the solution for AI development, or should organizations seek alternative methods to manage their AI-related software projects?To begin, AI development differs in many ways from traditional software development. The programming paradigm varies between the two, making it challenging to apply the same agile or predictive framework to support the necessary activities for anticipated

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