Business of DevOps
From Reactive Monitoring to AI-Driven Operational Intelligence
Sneha Gullapalli | | AI observability, Amazon Q, Apache Iceberg, automated root cause analysis, AWS CloudWatch, AWS operations, CloudWatch Logs, DevOps observability, Distributed Tracing, Five Whys, GenAI observability, incident response, LLM monitoring, log lake, MTTR reduction, operational intelligence, proactive monitoring., RAG latency, S3 Tables, token usage monitoringTraditional monitoring often meant chasing alerts and toggling between dashboards after an issue had already impacted users. AWS CloudWatch — long the backbone of metrics, logs and traces on AWS — is ...
AI-Assisted Development Under Deadline: What It Takes to Ship Production Code on an Unfamiliar Stack
Ihor Riazantsev | | AI code risk, AI coding tools, AI-assisted development, AI-generated code, Claude Code, code consistency, code review, devops teams, engineering discipline, feature isolation, manual testing, memory leak debugging, Next.js development, production readiness, production validation, production-ready code, rapid feature delivery, React development, software architecture, software engineering judgment, technical debt, TypeScript development, unfamiliar codebaseHow Claude Code accelerated development on an unfamiliar stack while proving that production-ready AI-generated code still requires human judgment ...
When the Message Broker Becomes the Bottleneck: Scaling Push and SMS With MongoDB Polling
Pavel Zavialov | | asynchronous processing, atomic task claiming, backend engineering, database-backed queue, dead-letter queue, distributed systems, Go microservices, idempotency, , microservices architecture, MongoDB performance, MongoDB polling queue, notification architecture, notification service, push notifications, RabbitMQ scaling, retry strategy, Ruby monolith, SMS delivery, Wheely engineeringA back-end team extracted notification delivery from a large Ruby monolith into a centralized Go service, only to discover that their shared RabbitMQ cluster could not reliably support the new workload. Here's ...
New Copilot Dashboard Shows Enterprises Which Developers Are Actually Using AI — Not Just Who’s Logged In
GitHub's new Copilot dashboard shows enterprises which developers use AI deeply — turning adoption data into a real productivity business case ...
The Trust Graph: Why Infrastructure Diagrams No Longer Describe Modern Systems
Igboanugo David Ugochukwu | | AI agent security, CI/CD security, GitHub Actions security, IAM governance, identity security, machine identities, non-human identities, OAuth tokens, OIDC federation, platform engineering, reliability engineering, SaaS integrations, secrets sprawl, service accounts, Software Supply Chain, trust amplification, trust bottlenecks, trust cascades, trust graph, workload identityTraditional architecture diagrams miss the identity relationships that now drive breaches and outages. Platform teams need trust graphs that map who and what can act across modern systems ...
Signed, Attested, and Malicious: The Software Supply Chain Has a Deepfake Problem
Nigel Douglas | | AI coding agents, AntV packages, behavioural analysis, continuous scanning, dependency security, Developer Security, GitHub Actions compromise, malicious packages, Miasma worm, Mini Shai-Hulud, npm malware, OIDC tokens, open source security, package provenance, package quarantine, policy as code, Red Hat npm attack, registry scanning, Shai-Hulud worm, SLSA provenance, software attestation, Software Supply Chain Security, TanStack compromise, trusted pipeline attacksA developer pulls a package from a reliable repo. It is signed, has provenance, and has been scanned. And then…it contains malware. That is no longer hypothetical. When the Miasma worm tore ...
AI Moved the Bottleneck From Writing Code to Understanding and Trusting It
Ted Julian | | AI code generation, AI code security, AI coding tools, AI investment ROI, AI-generated code, application security, automated code review, code quality, code review, codebase visibility, compliance, dependency risk, developer productivity, devsecops, Engineering leadership, engineering metrics, engineering ROI, production incidents, pull request review, SCA, software composition analysis, software delivery, software development productivity, software governance, technical debtAI coding boosts velocity, but without stronger review, governance and codebase visibility, teams risk higher costs, security gaps and production failures. TL;DR ...
xAI Open-Sources Grok Build Coding Agent After Cloud Upload Exposes SSH Keys, Repos
Tom Smith | | AI agent governance, AI coding agent, Apache 2.0, credential exposure, developer privacy, devops security, github, Grok Build, open-source coding agent, Repository Security, source code security, xAIxAI has published the full source code for Grok Build, its terminal-based AI coding agent, on GitHub under an Apache 2.0 license. The release lands three days after a security researcher showed ...
HashiCorp Introduces tfpolicy, a Native Policy Framework for Terraform
Tom Smith | | Cloud Security, compliance automation, Hashicorp, HCL, HCP Terraform, infrastructure as code, Infrastructure Governance, OPA, Open Policy Agent, platform engineering, policy as code, Sentinel, Terraform, tfpolicyHashiCorp’s new tfpolicy framework brings native policy-as-code governance to Terraform using HCL and lifecycle-aware infrastructure checks ...
Anaconda Doesn’t Want to Be Just the Python Company Anymore
The question is no longer whether Anaconda wants to be more than the Python company. It is how much of the AI development stack DeSanto ultimately intends to own ...
GitHub API Abuse, ‘Ghost’ Accounts Part of Malicious Efforts to Map Organizations
Jeff Burt | | Cofense, Data Exfiltration, data mapping, data scraping, datadog, Fortran, GitHub API, GitHub ghost accounts, gitlab, GraphQL, personal tokens, REST APIsDatadog researchers uncover months-long overlapping campaigns to scrape data about companies and their developers ...
IBM Bob Gets Multi-Agent Muscle and a Cost Dashboard for Enterprise Coding
IBM Bob adds multi-agent coordination, cost analytics, and modernization workflows for IBM Z, IBM i, and Java as AI governance takes center stage ...
