Kubernetes is a thriving open-source project delivering rapid innovation with releases three times a year. If using fully managed Kubernetes from public cloud providers, be prepared for Kubernetes service life cycles that are aggressive ...
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As containers become the default choice for developing and distributing modern applications and Kubernetes (k8s) the de-facto platform for deploying, running, and scaling such applications, enterprises need to scale their Kubernetes environments rapidly to keep up. However, rapidly scaling Kubernetes environments can be challenging ...
DevOps mentality has moved from strictly the development domain into the Ops world. As a result, traditional Ops — a model rooted in manual processes and executed by siloed teams — is dead. Traditional Ops and IT teams were already experiencing rapid change, but the pandemic sped up the adoption of more decentralized operations. Today, Ops doesn't generally refer to a team, but a responsibility. This blog will contrast Ops in a traditional environment vs. a DevOps environment, challenges to be aware of when adopting a DevOps approach, and actionable steps for organizations looking to implement a DevOps culture ...
The first learning from big tech is: Most large companies — wanting to adopt AI — hire teams to build internal platforms for ML practitioners. But these data scientists or ML engineers are often not familiar with enterprise software engineering. Expecting them to learn is feasible but inefficient, which is where MLOps platforms come in ...
Machine learning operations (MLOps), combining ML and software engineering, are becoming more mainstream and intend to improve the quality and speed of delivering ML models to production. Business leaders are missing out on many opportunities without proper MLOps platforms in place. So, how can companies get started? ...
ML engineering can be defined as the technical systems and processes associated with the stages of the ML lifecycle (also referred to as MLOps cycle) from data preparation, modeling building, and production deployment and management. While ML engineering entails the provisioning, deployment, and management of infrastructure that enables model building, data labeling, and model inference, it can go much deeper than that ...
Corporations can spend millions to install effective cybersecurity infrastructure, but what they might fail to notice is that vulnerabilities could be hiding in plain sight in developer repositories. To make database connections, calls to APIs, and many other functions more convenient, developers will often hardcode various credentials, keys, and secrets into a configuration file, or sometimes directly into a function itself. While this practice makes it convenient for developers, it opens up a myriad of vulnerabilities and cybersecurity challenges ...
Infrastructure-as-code (IaC) is regularly used by DevOps teams. However, the increasing complexity of things like data center configurations, security requirements, and changing guidelines means IaC is poised for an overhaul ...
Kubernetes and the ecosystem of cloud native technologies unlock innovation for organizations and provide a means to achieve the goals of elasticity, agility, optimized resource utilization, reduced service costs and workload portability. Security and optimized resource utilization are high priorities for practitioners, reminding us that the cloud native space is maturing, and focus is moving from Day Zero to Day Two operations, according to the Kubernetes and Cloud Native Operations survey report from Canonical ...
Today, native mobile developers are in high demand — and rare. Accessibility-first mobile developers are absolute unicorns. But this must change — and quickly. Look at these statistics ...
Testing is critical for long-term success, however, many enterprise teams are grappling with the timing of their testing. Today, the traditional software development lifecycle begins with requirements, goes to design, then coding, and ends with testing. The problem with conducting testing at the end is that much of the work is already complete, causing last minute surprises, costly defects, and delays in deploying the final product or update ...
Between the impact of COVID-19, shifting customer demands, and a surge in digital transformation, small to midsize business (SMB) owners in retail have been faced with great change in the last couple years. To find out just how much these disruptions have impacted retailers, we surveyed key thought leaders and decision makers at SMB retail companies. The results identified both the critical challenges faced by SMB retailers and the tech initiatives they' re implementing to offset those challenges. Based on our data, we've parsed out three key findings that will help small business owners navigate the new normal ...
Analytics has come a very long way in recent years, with transformational developments widening its impact beyond internal stakeholders and into the hands of external users. This brings with it a range of challenges, and when building analytics applications for customers ...
When execs talk with me about their desire to bring their teams back into the office in this new, post-pandemic world, the main argument I hear centers around the concept of "culture." An amorphous feeling that a return to the office is essential for teams to remain effective. "But," I ask, "weren't your teams effective during the pandemic when we all had no choice but to stay home?" ...
Can DevOps and low code work hand in hand? Philosophically, the two are at odds; DevOps inherently insinuates that code will be involved, while low code/no code insinuates the opposite. So, how can LC/NC and DevOps work together in harmony if they are intrinsically opposed to one another? Can they really be friends, or are they resigned to being foes? ...