Introduction For optimal outcomes it’s imperative that security should be built-in from the inception of the project. The applicability of this conventional wisdom is compelling in the ever-evolving landscape of software development with distributed containerized services, container orchestration and prevalence of cloud native and multi-cloud computing. Secure Development Lifecycle (SDL) stands as a comprehensive and
In an era dominated by cloud native and hybrid cloud technologies, where data traverses virtual boundaries at unprecedented speeds, the need for a robust and adaptive cybersecurity framework has never been more critical. Enter Zero Trust Architecture (ZTA), a revolutionary approach that not only aligns seamlessly with the dynamics of cloud computing but also places
Kubernetes has become a cornerstone for managing containerized applications in the cloud. It simplifies the deployment, scaling, and operations of application containers, but the complexity of these systems requires robust observability to ensure their health and performance. AI and Generative AI are revolutionizing how we approach observability. This blog post will delve into how AI
In the rapidly evolving landscape of cloud-native infrastructure, developers and cloud operators face a myriad of challenges in ensuring effective observability. The dynamic nature of these environments, coupled with the prevalence of technologies like Kubernetes and the diversity of deployment models (public, private, and hybrid cloud), presents a complex observability landscape. Understanding and addressing these
What does it mean to be “cloud native”? Cloud-native infrastructure refers to the design, deployment, and management of IT resources that leverage cloud computing principles. It involves building and running applications that take full advantage of the dynamic, scalable, and distributed nature of cloud environments. Characteristics include microservices architecture, containerization (e.g., Docker), and orchestration tools
In an earlier blog post, Kubernetes Overview, we introduced Kubernetes. We introduced key capabilities of Kubernetes i.e. Portability, Extensibility, Declarative Configuration and Automation. Let’s take a closer look at these capabilities to acquire deeper insights into the technology. Portability The portability of Kubernetes refers to its ability to enable consistent and seamless deployment and management
In today’s digital world, many services we rely on, like online shopping, social media, and streaming, run on complex software systems. When something goes wrong with these systems, it can affect thousands or even millions of users. Observability helps engineers understand how these systems are performing and quickly find and fix issues. This blog post
Kubernetes is an open-source platform for automated orchestration and management of Containerized applications. Before dwelling into the specifics, let’s briefly explore its origins. Kubernetes is a Greek word, meaning “helmsman” or a “pilot”. Kubernetes was originally developed at Google to run containerized workloads, then released as open source in 2014 and maintained by the Cloud
Natural Language Processing (NLP) gives the machines the ability to read, understand and derive meaning from human languages. Nearly 90% of data generated today from various channels is unstructured such as email, social media, news feeds & blogs, text and OTT messages, audio, video and more. Some of the real-world applications of NLP include sentiment
