Over the recent years, software development organizations have seen a major shift in where they build and run their applications. Teams have transitioned from building applications that run exclusively on-prem to microservices applications that are built to run natively in the cloud. This shift gives businesses more flexibility as well as quick and easy access to enterprise services without the need to host costly applications and infrastructure.
Kong for Kubernetes is a Kubernetes Ingress Controller and a full-fledged edge-router which can route traffic to any destination of your choice. In addition to Ingress management, it provides enhanced security and management capabilities. With Kong, you can use Kubernetes not just for running your workloads but also for securing and monitoring connectivity between your workloads – all managed via Kubernetes manifests .
It's easy to get lost in today's continuously changing landscape of cloud native technologies. The learning curve from a beginner's perspective is quite steep, and without proper context it becomes increasingly difficult to sift through all the buzzwords. If you have been developing software, chances are you may have heard of Kubernetes by now. Before we jump into what Kubernetes is, it's essential to familiarize ourselves with containerization and how it came about.
Most of our blog posts are dedicated to Android, iOS and JavaScript development because those are the most interesting platforms for our users. However, from time to time, we also think it’s important to share what’s happening behind the scenes. In this post we’ll be highlighting some of the recent improvements we’ve made to Bugfender’s infrastructure.
Kubernetes and Docker each play a vital role in modern, microservices-based application development. Since Kubernetes and Docker work in unison to help develop, deploy, and manage large-scale applications – they are not mutually exclusive technologies and they are certainly not in competition with each other. Nevertheless, Kubernetes and Docker are often misunderstood by the non-developer community. To clear up the confusion around Kubernetes vs. Docker, we’ve written this guide.
The “as a service” business model continues to grow rapidly, largely thanks to the rise of cloud computing. “As a service” offerings deliver IT products and technologies such as software, hardware, and data storage to consumers via the Internet, rather than having to install or manage them themselves. Serverless and containers are two such “as a service” technologies that have seen increasing adoption in recent years.
Kubernetes is an open-source platform for container orchestration. You can use it to deploy a highly resilient, self-healing infrastructure using automation and infrastructure as code (IaC). Kubernetes includes features for zero downtime deployments, scaling, automatic rollout and rollback of updates, and service discovery. Kubernetes is designed to help you manage container deployments at scale via REST API.
If your company has already started getting into machine learning / deep learning, you will quickly relate to the following story. If your company is taking its first steps into data-science, here is what is about to be dropped on you. If none of the above strikes a chord, well it’s probably good to know what’s out there because data-science is all the rage now, and it won’t be long until it gets you too 🙂
As new advances in software development have allowed developers to increase their velocity and push out new software at ever increasing speeds, one less measured metric is software understandability. Although it probably seems obvious, when building new software the goal should always be to build software that is as simple and easy to understand as possible.
