Snapt Blog

The introduction of containers has revolutionized the software development industry and made building, testing, and deploying applications significantly easier. However, modern applications and infrastructure require an ever-growing number of containers and servers. These generate such a volume of logs and information that monitoring everything is a massive challenge. Deadlines, inexperience, culture, and management are just some of the obstacles that can affect how successful teams are at overcoming this challenge. 

In a previous article, we provided an introduction to artificial intelligence (AI) and the different learning types. Machine learning (ML) is one of the biggest types of AI development—and the one that gets the most attention from many companies.

Engineers are making massive strides in the field of artificial intelligence (AI). There is no denying that AI will have a massive impact on how we interact with computing systems in the future and on what we can do with them. This guide will help you to understand what exactly AI—and, more specifically, ML (machine learning)—is and how it works so we can begin our journey into building systems that use this exciting technology.

If there is one thing the software development world loves, it’s following the latest development trends. Call it the “cool factor” or simply a desire to be at the cutting edge of technology, but there is a big rush for many companies to adopt certain development and software processes. One such trend—which admittedly has been around for many years now—is that of continuous integration or continuous development (CI/CD), commonly associated with the DevOps world.

Kubernetes has been a revelation for companies working with containers. It makes container orchestration consistent, which can streamline development and make CI/CD processes more reliable. However, your success depends on more than developing containerized applications and integrating Kubernetes into your CI tooling. You still need to consider how you will deploy your containers into a production environment. This process can be just as challenging as introducing containers into your software architecture in the first place.

Every business exposing online applications, services, and APIs needs a Web Application Firewall (WAF) to operate safely and protect against cybersecurity threats. A WAF identifies and blocks attacks that lead to downtime, leaked data, and compromised transactions and accounts. However, you might find that choosing the right WAF is a tricky business. 

Application delivery is moving fast and has recently seen significant advances in centralized control, containerization, integration, and intelligence. If we follow these threads, and broader industry trends, what more might we see in the next five years?

If you are thinking of deploying applications in containers and using a container orchestration platform like Kubernetes, you must consider security. Smaller and simpler apps will reduce your development, testing, and maintenance costs – but security can be more challenging when compared with deploying in VMs. 

Many organizations have realized that they can scale more easily and deploy updates and features fast by building applications in containers. You can replicate containers across multiple servers and clouds to ensure that your application scales up or down in response to demand and responds to failures seamlessly.