How to Upgrade a Graylog Cluster to V7.0
Ethan Keaton takes you through upgrading A Graylog cluster to V7.0.
Operations | Monitoring | ITSM | DevOps | Cloud
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Embracing failure and chaos to improve system reliability and SRE team performance
In this interview with Alex Hidalgo, Field CTO at Nobl9 and author of Implementing Service Level Objectives (O’Reilly Media), we explore how traditional metrics like MTTR and MTTx can give a false sense of reliability. Alex shares how SRE teams can embrace failure, build psychological safety, and design systems that reflect the human factor behind uptime, outages, and real-world reliability.
Gobbling Up Insights: Graylog 7.0 Serves Up a Feast
A feast of new features. A cornucopia of new capabilities. A banquet of breakthroughs (and the T-day puns are just getting started). Graylog 7.0 brings a full plate of advancements that help security teams cut through noise, control cloud costs, and respond with confidence. We’re serving practical improvements across dashboards, automation, and AI support so analysts can focus on action instead of manual effort.
Building dbRosetta Using AI: Part 1 of Many
Like many of you, over the last couple of years, I’ve been using AI, or, well, let’s just name it appropriately, Large Language Models (LLM), as a part of my job. I’ve also used it in my hobby. With it, I’ve generated snippets of code, tested data conversions, even built a small database for a presentation. However, to date, I haven’t tried doing everything through the LLM. Now, I’m going to.
How to Use Nested Queries in Datadog for Advanced Metrics Analysis
Discover how nested queries in Datadog empower you to perform deeper, multilayered metrics analysis. In this video, Colten from the Metrics team walks through how to reuse query results to.
Monitor OCI spend, AI in DDSQL Editor, OTLP Metrics API, and more | This Month in Datadog
See how you can gain insights into cloud costs by tracking OCI spend and easily comparing instance types in October’s episode of This Month in Datadog. Join us for a spotlight of Cloud Cost Management’s support for Oracle Cloud Infrastructure, and the product’s new feature, Instance Explorer, which enables you to visualize and easily compare the cost and performance of instances across AWS, Azure, and Google Cloud.
AWS & Splunk: Accelerating Innovation Through Partnership
Discover how AWS and Splunk are pushing the boundaries of innovation to empower your security, observability, and cloud transformation journey. This video highlights our joint commitment to driving digital resilience through unified visibility, faster threat detection, and seamless integration across AWS services.
Virtual Generated Columns will make your code more efficient #postgresql #pg18
Virtual Generated Columns are another new feature that we're exploring in PG18.
Why AI Coding Assistants Fail (And How to Fix Them)
Why do developers stop using AI coding assistants? According to Carnegie Mellon research, the top reason is unhelpful suggestions. Tabnine's Principal Architect John Feeney explains how context transforms AI coding tools from generic to genuinely useful. Learn the 4 Cs framework for maximizing AI assistant value: Context (workspace indexing), Connection (repo integration), Coaching (rules-based guidance), and Customization (fine-tuning). Discover how Retrieval Augmented Generation (RAG) helps AI understand your codebase, not just open source patterns.
Rovo AI: Create Work Items from Loom | Demo Den | Atlassian
Ever wish you could turn a quick Loom recording into Jira work items without all the manual typing? Now you can! In this Demo Den episode, Pierre walks through a new Rovo AI feature that automatically converts your Loom videos into actionable Jira work items. Whether you're recording bug reports, feature requests, or project updates, Rovo handles the data entry for you. What Pierre covers: Turning Loom videos into work items with Rovo How it works in your AI-enabled Jira instance.