The Hits And Misses Of AWS re:Invent 2019
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How the Jenkins to Jira Cloud Integration Was Built (and What You Can Do With It)
A deep dive into the architecture, security model, and pipeline steps behind the official Jira Software Cloud plugin for Jenkins — including how a new OAuth credential type enables secure, one-way data flow from behind-the-firewall CI/CD tools to Jira Cloud.
DevOps Tools for the Monitoring Ecosystem
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How Monzo Isolated 1,500 Microservices Using Kubernetes Network Policies and Calico
Monzo’s security team used Calico-powered Kubernetes network policies and static code analysis to enforce zero-trust isolation across more than 1,500 microservices and 9,300 inter-service connections.
Software Quality in a World of Microservices and Continuous Deployment
How the Guardian’s engineering team evolved the QA function to keep pace with microservices and continuous deployment, introducing the Software Engineer (Tools and Infrastructure) role to embed quality throughout the development lifecycle.
What Does It Take to Become a DevOps Specialist?
DevOps is more than a buzzword — it demands a rare blend of technical depth and interpersonal skill. Here is what it actually takes to build a career as a DevOps specialist.
Developing an Embedded Software Build Pipeline: A Practical Guide
Embedded software development has historically lagged behind mainstream software practices. Learn how to build a modern, automated CI/CD pipeline specifically designed for embedded systems teams.
AWS Applies Machine Learning to Optimize Cloud Deployments: CodeGuru and Compute Optimizer
At re:Invent 2019, AWS unveiled Amazon CodeGuru and AWS Compute Optimizer — two ML-powered tools designed to help DevOps teams reduce infrastructure costs, surface code bottlenecks, and select optimal EC2 instance types automatically.
AWS SageMaker and Kubernetes Integration: What It Means for ML Developers
AWS SageMaker Operators for Kubernetes bridges the gap between container orchestration and managed ML infrastructure, letting data science teams train, tune, and deploy models without leaving their Kubernetes workflows.
If DevOps Is So Awesome, Why Is Your Initiative Failing?
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Did You Forget the Ops in DevOps?
Ten years into the DevOps movement, many organizations still exclude Operations teams from their transformations. Here is what goes wrong — and what genuine Dev-Ops collaboration actually looks like.
IT Solutions Found in the Cloud: A Practical Guide for Businesses
Cloud computing offers businesses scalable, cost-effective IT solutions across service models including SaaS, IaaS, and PaaS. Learn how each model works and which deployment option fits your organization.
Securing Docker Containers: A Practical Primer for DevOps Engineers
Docker containers are not inherently secure just because they are isolated. This guide covers baseline tactics—from image trust and least-privilege access to Kubernetes node hardening and network segmentation—that every DevOps engineer should apply.
How to Achieve Continuous Feedback in DevOps Pipelines
Continuous feedback is critical to optimizing DevOps processes. Learn how to fine-tune CI/CD feedback loops, reduce alert noise, extend feedback beyond IT, and measure success with the right metrics.
Red Hat Ansible: IT Standardization and Automation Explained
IT silos, shadow IT, and manual processes slow down digital transformation. Learn how Red Hat Ansible and Ansible Tower help teams standardize and automate complex IT workflows, including SAP HANA deployments.
Five Ways to Shorten Your Continuous Delivery Cycle
Multi-month release cycles are giving way to CI/CD practices that ship code faster and more reliably. Here are five concrete techniques to reduce cycle time at every stage of delivery.
Ensuring DevOps is secure
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LXC vs Docker: Key Differences Explained for DevOps Engineers
LXC and Docker both use Linux kernel features to isolate workloads, but they solve different problems. This guide explains how each technology works and when to choose one over the other.
Is AI the Key to Improving Software Testing Speed, Coverage, and Developer Wellbeing?
Software testing has barely evolved since the 1990s. AI-powered quality analytics can eliminate bottlenecks, reduce test execution times, close coverage gaps, and restore focus to the work that actually matters.
Singapore Startup Sentient.io Tackles AI Skills Gap with Pre-Trained Microservices
Singapore-based startup Sentient.io is offering a platform of pre-trained AI microservices that allows developers without specialist AI expertise to add capabilities such as speech recognition and natural language processing to their applications via APIs.