Why does treating the application as just code no longer work?
Most “application issues” don’t start in the code. They start somewhere deeper in the delivery system. If you can’t see beyond the trace, you’re only seeing half the story.
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Harness Cursor Plugin Demo: AI for Software Delivery from Your IDE
Stop context-switching between your IDE and your CI/CD dashboards. In this video, we demonstrate the new Harness Cursor Plugin, a native integration that brings the full power of the Harness AI Software Delivery Platform directly into Cursor. Using the Cursor Agent window and the new Harness Model Context Protocol (MCP) server, you can now manage your entire software delivery lifecycle through natural language. From triggering pipelines to governing deployments, this plugin ensures you stay in your flow while maintaining enterprise-grade security and control.
Inside Atlassian's Merge Queues: How we ship faster with fewer incidents
At Atlassian, we use Merge Queues to ship frequent changes with confidence and streamline pull request merges. Across some of our busiest codebases, Merge Queues have sharply reduced incident frequency and turned merging from a stressful bottleneck into a background task. Today, most of our largest repositories rely on Merge Queues—over 70 large repos across products like Jira, Rovo, Trello, and others—having safely landed 30,000 pull requests since adopting Merge Queues Beta last quarter.
End-to-End Trace Propagation Across SQS and Lambda with OpenTelemetry
SQS doesn't propagate trace context automatically. You instrument both sides, deploy, and get two disconnected traces. This post shows how to wire them into one waterfall — and the ESM format gotcha that silently breaks it every time. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.
Why Ubuntu for enterprise operations?
OEDIV shares how Ubuntu helps deliver speed, consistency, and flexibility across thousands of Linux systems. Watch the full story on @UbuntuOS.
Deploy Redgate Test Data Manager with Docker
Redgate Test Data Manager now ships as a Docker image. Pull it, run it, and you're in the product in minutes. For teams working with containers, this is the fastest way to get started.
last9-genai: Closing the Conversation Gap in LLM Observability
OpenTelemetry's GenAI instrumentation gives you spans and token counts. It does not give you conversations, workflow cost rollups, or prompts visible in your dashboard. last9-genai is an OTel extension that fills those three gaps — without replacing your existing observability stack. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.
How to Exclude Health Check Endpoints from Python OTel Traces
Health check endpoints generate thousands of identical, useless spans per day. Here are two production-ready approaches to filter them from your Python OTel traces — and the correctness trap most implementations miss. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.
15: Optimizing AI Workloads: Balancing Cost, Performance, and Scalability with Bijit Ghosh
In this episode, Andrew Hillier and Bijit Ghosh discuss the evolving landscape of AI, discussing the growing prominence of inference over training, hybrid cloud strategies, balancing cost with performance, and the orchestration of complex hardware environments. The conversation also touches on emerging concepts like AI factories, the challenges of sovereign cloud, and how enterprises are navigating data gravity and regulatory constraints. It's a deep dive into optimizing AI infrastructure, managing costs, and the disruptive changes that are transforming both technology and business outcomes.
Introducing the Cortex AI Assistant (now in Slack)!
Mention @Cortex in any Slack channel the Assistant has been invited to, public or private, and get grounded answers pulled from your Cortex data. Questions can be as simple as "who owns payments-api?" or as analytical as "what's driving our incident trends this quarter?" The Assistant pulls context from all across Cortex, including ownership, Scorecards, Initiatives, on-call, dependencies, and Eng Intelligence metrics, and holds context across a threaded conversation.