Today’s business world operates in a state of constant change. What the customer wants to buy changes quickly, new competitors appear overnight, and cyber threats are changing faster than ever. In this world, the concept of “resilience,” the ability to adapt, to overcome, and to continue to create value for the enterprise despite the changes, has become a top-level imperative for cybersecurity and technology executives. DevOps, the cultural and technical movement to unify the software development and operations disciplines, has come of age as a key enabler of business resilience.Bridging the Dev and Ops Divide: A Culture of ResilienceBefore DevOps,…
Author: drweb
We’re excited to announce the general availability of Custom Catalogs and Profiles for managing Model Context Protocol (MCP) servers. These two complementary capabilities fundamentally change how teams package, distribute, and manage AI tooling. Custom MCP Catalogs let organizations curate and distribute approved collections of MCP servers. MCP Profiles enable individual developers to easily build, run, and share their MCP tools and configurations across projects and teams. In this post, we’ll walk through how to create your own custom catalog – building on and improving our previous approach. We’ll also introduce Profiles, a new primitive that lets you define portable, named…
I keep running into the same problem when I train neural networks: my model learns something, but how do I actually measure whether it is learning the right thing? The loss function is the answer to that question. It is the single number that tells a model how far off its predictions are from the truth, and every weight update in the network tries to make that number smaller. This article covers PyTorch’s built-in loss functions, from basic ones like MSELoss and CrossEntropyLoss to specialized losses like HuberLoss and TripletMarginLoss. By the end, you will know which loss to reach…
Design Focused Front-End Developer
I ran into a confusing error the first time I tried to install the Levenshtein package on Windows. The pip install failed with a cryptic message about missing build tools, and I had no idea where to start. That confusion is exactly what this article solves. This article covers what Levenshtein distance is, how to implement it manually in Python, and how to install the Levenshtein package without hitting the common Windows errors. By the end, you will have a working installation and a solid grasp of when to use the library versus a manual implementation. TLDR Levenshtein distance measures…
Cloud-native DevOps promised infinite scale and speed, but production failures expose the gap: Deployments pass CI/CD but crumble under real traffic. Continuous testing catches functional bugs, yet misses performance regressions, security drift and capacity limits that only emerge in cloud environments. Observability bridges this divide. Beyond alerting on failures, it reveals why tests fail across distributed systems — traces map API call chains, metrics quantify load impact and logs capture ephemeral errors. In 2026, mature DevOps teams treat testing as an observability problem, not just a quality gate. Recent State of DevOps reports show that teams with observability-integrated testing achieve 3x faster recovery and 50% fewer production incidents. The payoff: The confidence to ship…
I ran into a situation last month where I had to pull individual frames from a recording for a presentation. The video was only 30 seconds long but contained 900 frames, and I needed specific ones to illustrate key points. Manually screenshotting was not an option. OpenCV makes frame extraction straightforward. This article covers reading videos, extracting every frame or every Nth frame, saving them in multiple formats, and handling webcam streams. By the end, you will have a reusable script you can adapt for any video processing task. TLDR cv2.VideoCapture opens video files and webcam streams Loop over frames…
A deployment starts failing late on a Friday evening.The initial assumption is that something changed in the application release. Teams start checking container images, Terraform plans and recent commits. Nothing looks wrong.A few hours later, someone discovers the actual issue: a deployment token tied to an old automation workflow expired months ago. The token was still being used by a pipeline nobody realized was active.The original engineer who created it had already moved to another team.Situations like this are becoming normal in modern delivery environments. Not because organizations suddenly lost visibility into human access, but because CI/CD systems now create…
Copado has added artificial intelligence (AI) agents to its DevOps platform for building and deploying custom applications for the software-as-a-service (SaaS) application platform from Salesforce.At launch, Copado is making available Agentia AI agents specifically that can be assigned plan, build and testing tasks via an orchestration agent that manages the overall workflow. Each Agentia AI agent understands the unique metadata framework that Salesforce developed but also all the dependencies, pipelines and testing activity occurring across the software development lifecycle (SDLC) that is captured via the Agentia Context Hub.Additionally, there is an Agentia Studio tool that can be used to build…
Site reliability engineering (SRE) promised a better way. Born at Google and evangelized by a generation of platform engineers, SRE offered organizations a disciplined, engineering-first path from firefighting chaos to measured, sustainable operations. However, years into the mainstream adoption of SRE, various organizations find themselves spending more on SRE tooling than ever, while their on-call engineers are still drowning at 2 a.m. The pattern is consistent. Titles change. Dashboards multiply. AI-powered AIOps platforms get procured. Error budgets get defined in a spreadsheet and promptly forgotten. Six months later, the postmortems look identical to those from two years ago. What’s going wrong? After surveying dozens of engineering organizations, five mistakes surface repeatedly, and they…