Operations | Monitoring | ITSM | DevOps | Cloud

AI NetOps: How AI and Machine Learning Transform Network Operations

AI is changing network operations (NetOps) from static automation into adaptive, data-driven systems that can summarize incidents, retrieve knowledge, and guide remediation with human oversight. In this talk, Phil Gervasi breaks down what “AI for NetOps” really means in practice, including the difference between classical ML and large language models (LLMs), why data pipelines matter more than model tuning, and how patterns like RAG (retrieval augmented generation), text-to-SQL, and agentic workflows turn raw telemetry into decisions.

PagerDuty x Backstage Plugin Demo: Eliminate Context Switching for On-Call Engineers

Join Rocío, Product Manager of the Forward Deploying Engineering team at PagerDuty, as she demonstrates how the PagerDuty Backstage plugin transforms incident response by bringing critical operational data directly into your developer portal.

Heartbeat behind the metrics | Muraleedharan on support, scale, and seeing the product in the wild

What does observability look like when you’re responsible for customers at scale? In this episode of Heartbeat Behind the Metrics, Muraleedharan Sadhasivam, Head of Customer Success, talks about his 15-year journey at ManageEngine and the perspective you only get from being close to customers every day. He shares why custom dashboards matter so much, and why AppLogs is a feature he wishes more users explored to complete the MELT story. From querying logs to turning them into alerts and dashboards, he explains how real insights start when data is brought together.

Track cyber security with Reports in Digital Risk Analyzer

Discover how Site24x7’s Digital Risk Analyzer Reports help you instantly uncover vulnerabilities and assess multi-domain risks. In this quick walkthrough, learn how to view domain health, generate detailed or consolidated reports, schedule automated delivery, and share PDF insights with your team. Perfect for IT admins, DevOps, MSPs, and business leaders who want fast, actionable visibility into their cybersecurity posture.

Silent Failure in Production ML: Why the Most Dangerous Model Bugs don't Throw Errors

You’ve done it. Your machine learning model is live in production. It’s serving predictions, powering features, and quietly doing its job. Dashboards are green. There are no errors in the logs. Nothing appears broken. And yet, something is wrong. Predictions are getting less reliable. Users are waiting a little longer for responses. Conversion rates are slipping. Trust is eroding, but no alert fires, no system crashes, and no one knows there’s a problem until the damage has been done.

Agentic AI in DevOps: The Architect's Guide to Autonomous Infrastructure | Harness Blog

For the last decade, the holy grail of DevOps has been Automation. We spent years writing Bash scripts to move files, Terraform to provision servers, and Ansible to configure them. And for a while, it felt like magic. But any seasoned engineer knows the dirty secret of automation: it is brittle. Automation is deterministic. It only does exactly what you tell it to do. It has no brain. It cannot reason.

6 Underused Git Commands That Solve Real Developer Problems

Most developers spend hours each week wrestling with Git. Not because they’re bad at their jobs, but because Git doesn’t actively teach you its most powerful features. At GitKon 2025, our Senior Product Marketing Manager Jonathan Silva revealed 6 underused Git commands that solve the workflow problems developers face every day: botched rebases, lost commits, and merge conflict chaos. These aren’t advanced techniques.