Author: Hiren Dhaduk

Organizations that can achieve peak performance from their core business applications are the ones that can effectively grow, compete, and differentiate themselves. However, many such apps were written quite a few years back, even decades ago.

Over time, most of them start facing various issues, from outdated tech stack to degrading user experience, from data breaches to expensive maintenance. And so, devising an efficient application modernization strategy is necessary to ensure these mission-critical systems stay updated and relevant in this day and age.

Companies have started recognizing software as a strategic corporate asset to combat cutthroat competition. Today, modernization is no longer solely the concern of software-centric organizations. The approach also spans multiple functions, including sales, HR, and core IT, to name just a few.

Here are a few myths that prevent organizations from recognizing the need to modernize their applications and hinder their growth in the long run.

Observability and monitoring are the two different types of DevOps measurement contributing to continuous delivery. These two are often used interchangeably, but there are key differences between them that separate them from each other.

Observability is defined as the ability to understand a system's internal state by analyzing the data generated by the system, such as — logs, metrics, and traces. Monitoring is closely related to Observability. In general, monitoring is classified as the collection and analysis of data that are pulled from IT systems. By analyzing the information about the application’s usage patterns, monitoring helps IT teams detect vulnerabilities beforehand and come up with an appropriate solution. 

Enterprises have a growing need to upgrade their apps and methods for delivering digital experiences to millions of people. One such approach is serverless.

Tech executives are now rethinking their strategy in response to the desire to boost agility and lowering total operational overhead and costs. They had to reconsider how they could effectively, easily, and flawlessly design serverless.

Modern-day application stores a lot of information and data to understand customer expectations and deliver personalized solutions. All these pieces of information are stored in databases. Now, developers can leverage data from databases using various methods. What confuses them most is the choice of service or method they need to pick in order to manage their database. They can pick either relational or non-relational methods of managing databases. In terms of tools and services, there exists a plethora of services in the market that developers can pick. All these options are enough to make a developer trip over! In this article, I have tried to address whether one should pick Amazon RDS or Dynamo DB. But before we can proceed to that, let’s have a quick look at the difference between relational and non-relational databases. 

Understanding Relational vs. Non-Relational Databases

There are two different approaches to constructing a database — relational and non-relational databases.

The Kubernetes service simplifies load balancing and container management of containerized applications. Simply put, it makes it easier for enterprise applications to have greater scalability, flexibility, and portability. After Linux, Kubernetes is one of the fastest-growing projects in the history of open-source software. According to a study by CNFC, the number of Kubernetes engineers grew by 67% to 3.9 million. 

It is a go-to solution for cloud orchestration in distributed environments. But, cloud architecture has become complicated, and organizations find it challenging to fix the bugs. When developers need to address the root cause, they encounter a lack of observability due to non-tracking of the state of Kubernetes, serverless functions, and other aspects of cloud architecture. This lack of visibility into what’s going on led to the need for Kubernetes Observability.

One of the important skills that can boost your career is —  coding. 

Whether you are looking forward to getting a good position in the tech space or just want to create an app for fun, becoming a pro in coding will be the greatest asset to your professional and personal development. 

You have launched your application with an intuitive, user-friendly UI. But if your application is experiencing a load problem, it will frustrate your end customers while using it. Chances are the issue is not within the application but with the database. According to a survey, 38% of database professionals reported database downtime as the significant issue that kept them up at night. The downtime could be due to any number of issues, including improper database configuration, poor load handling, database queries being timed out, and so on. 

In this article, we will discuss whether you need to scale your database and how to tackle database scalability issues. Let’s begin with the most obvious question — why database scaling? 

Is managing and scaling your database becoming a bottleneck as your application grows? Wouldn’t it be great if new databases were made available for your application and capacity added whenever needed? 

There might be a solution to address your database problems–  AWS's Relational Database Service (Amazon RDS). Many enterprises, including Netflix, Airbnb, Unilever, Salesforce, and more, use RDS for the convenience and value it offers. And even if you are a small organization, RDS offloads a sizeable chunk of infrastructure management to AWS so that your small teams can focus on more value-added work.

Developers worldwide are adopting a microservices architecture to deploy their applications across distributed environments. The need for a comprehensive observability solution has naturally become more significant with the rise of distributed app architecture. Tracking and troubleshooting the components within the environment is challenging, though. Organizations need visibility into these components to understand their application behavior. 

And that is where observability tools come into action. But before going deeper into observability tools, let’s understand what observability is. It’s a methodology to observe and regulate the systems autonomously. Organizations are gradually opting for polyglot microservices to reduce cloud complexities and enhance the productivity of their developers. 

Nowadays, enterprises look forward to delivering their software as early as possible. And for this, they must bridge the gap between rapid development and operational stability. Organizations can leverage approaches like CI/CD and DevOps to achieve this goal. But most enterprises get skeptical regarding the CI/CD vs. DevOps mystery. 

Despite systems becoming complex, our expectations for best performance remain the same. Therefore, having a safer and faster way of getting your changes into production is critical. Unfortunately, scripts would not be modified and executed multiple times. Also, you need to understand and differentiate various methodologies. 

With global enterprises shifting to cloud-managed databases, the world of database management has drastically changed. However, meeting the modern world's needs can be challenging, especially for on-premise deployments. Comparatively, managed cloud databases are scalable and relational database services built for the cloud.  

Amazon AWS and Microsoft Azure are excellent options for deploying MS SQL Server databases. These databases have proven to be the harbinger of a new era. However, comparing features, advantages, and limitations is essential before deciding on an Amazon AWS or Azure migration. In this post, we will explore these prominent databases and assist you in choosing the right database for your business.

Organizations increasingly rely on DevOps to streamline business processes in the software-dense world. Meanwhile, their success with DevOps, in turn, can be attributed to the principles of continuous integration and continuous delivery. And the reason is — the best CI/CD tools efficiently use the power of automation to create a streamlined software delivery pipeline.

CI/CD introduces continuous monitoring and continuous testing throughout the lifecycle of applications. So choosing a proper tool is essential, whether it’s reducing the complexity of tasks in continuous delivery pipelines, building automation in workflows, or efficiently managing code changes and bugs.

Mobile app development is an industry that’s constantly changing and evolving. While some of the biggest apps may seem like they’re stuck in time, there are new technologies emerging every day, which means developers have to stay on their toes.

The thing about mobile apps is that the user experience needs to be seamless across all platforms—desktop computers, laptops, tablets, and phones. With different operating systems and screen sizes to consider for each device type, it can be challenging for developers who don’t know how to code for multiple platforms at once. However, there are tools available to make cross-platform development easier than ever before!