Long Live Containerization!
Docker, Inc. today revealed it picked up an additional $105 million in financing that, among other things, will be applied to extending the reach of the Docker container application development tools that developers use into the realm of serverless computing frameworks and emerging WebAssembly (Wasm) and Web3 platforms. Overall, this
Running stateful, often business-critical applications in Kubernetes is increasingly common. It’s simple, right? Kubernetes just wants fast, simple access to persistent volumes and databases. With the right storage management, optimization, automation and developer self-service, this is possible. Here is the hard part—someone needs to know what the “right” solution is
From microservices to multi-cloud, modern application architectures have evolved significantly and created new challenges that are drowning engineers and DevOps teams in data and increasing the number of tools they are being required to manage. Today’s modern cloud applications are complex and the IT infrastructure supporting them has become dispersed, with
Kubernetes plays a leading role in deploying applications across different platforms. This is a major step up compared to the traditional way of deploying applications and offers a more comprehensive way of achieving continuous integration (CI) and continuous deployment (CD) enabling robust resource management using Kubernetes API. This blog explains
GitLab has made available a 14.9 update to its namesake continuous integration/continuous delivery (CI/CD) platform that adds epic-linking, integrated security training, rule mode for scanning result policies and a revamped design, among other capabilities. The updated environment makes it easier to discover the state of the application development projects, GitLab said. Cindy Blake, senior product […] The post GitLab Updates CI/CD Platform to Improve Dev Productivity appeared first on DevOps.com. [...]
Intelligent applications are (by their very nature) complex. While conventional software basically consists of one thing (code), intelligent software involves code, models and data. As previously discussed, three distinct fields—DevOps, MLOps and DataOps—have evolved to govern each of these interconnected disciplines. Moving through the ML life cycle quickly and efficiently requires collaboration between teams in […] The post Positioning ML Devs and Teams for Success appeared first on DevOps.com. [...]
As companies grow and expand to become global enterprises, IT infrastructure inevitably becomes more complex. When it comes to cloud computing, that usually means maintaining multiple clouds. There are many reasons for using different cloud service providers (CSPs)—some by choice and others by mandate. For instance, a large enterprise with operations around the world may […] The post Designing Your DevOps Ecosystem for Multi-Cloud appeared first on DevOps.com. [...]
