Grafana Labs vs PagerDuty

Observability Stack: Prometheus, Node Exporter, Grafana

A technical how-to explaining the three-piece observability stack: Prometheus (time-series database that scrapes metrics), Node Exporter (exposes OS-level metrics at a /metrics HTTP endpoint), and Grafana (visualizes Prometheus data as dashboards). The article describes the pull-based model Prometheus uses, the role of Node Exporter as a translator of OS stats, how Grafana queries Prometheus, default ports (Prometheus 9090, Node Exporter 9100, Grafana 3000), basic install commands, a sample prometheus.yml with scrape_interval and job_name, and next steps such as adding scrape targets, writing PromQL queries, and adding Alertmanager for notifications.

• Prometheus is a time-series database and monitoring system that scrapes metrics from HTTP endpoints and exposes its own metrics on port 9090.
• Node Exporter exposes hardware and OS-level metrics at a /metrics endpoint (default port 9100) and is typically installed one-per-machine.
• Grafana queries Prometheus (e.g., via PromQL) to render dashboards and runs by default on port 3000; it stores no metrics itself.

Building an Internal Developer Platform on Azure AKS

This technical article explains how to create an Internal Developer Platform (IDP) using Azure Kubernetes Service (AKS). It outlines core components including AKS as the managed Kubernetes backbone, a service mesh (e.g., Istio or Linkerd) for microservice communication, CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for automated build and deployment, monitoring and logging tools (Azure Monitor, Prometheus, Grafana, Azure Log Analytics), and security/compliance controls (RBAC, Pod Security Policies, Azure Policy, Azure Security Center). The piece describes an example developer workflow from code push to production and summarizes benefits such as increased efficiency, scalability, security, and consistency.

• An Internal Developer Platform (IDP) is a set of tools, processes, and automations that simplifies development, testing, and deployment for developers.
• Azure Kubernetes Service (AKS) is presented as the central managed Kubernetes environment where containerized applications run.
• Service meshes such as Istio or Linkerd are recommended to manage microservice communication, including load balancing, traffic management, and security policies.

Read-Only SRE: Using AI in Production Safely

The author argues for a conservative, observation-first role for AI in production SRE workflows: grant AI read-only access to telemetry (logs, dashboards, events, commits, deployment history, IaC plans) so it can synthesize incident timelines, summarize recent activity, and surface anomalies — but keep production write actions (restarts, scaling, Terraform changes, firewall edits) under human control. The piece frames AI as a fast, always-available “SRE intern” that helps engineers think faster without taking ownership of risky changes. The author acknowledges AI may earn broader operational responsibilities in the future but recommends an onboarding approach that mirrors human engineers: observe, learn, and prove understanding before receiving write permissions. Published on dev.to on 2026-07-10.

• Author recommends giving AI read-only access to production telemetry (logs, events, monitoring dashboards, deployment history, Terraform plans, Git commits) to help with incident troubleshooting.
• Author explicitly advises against allowing AI to perform production writes (restarts, scaling, deleting resources, changing Terraform, updating firewall rules) due to accountability and business-context gaps.
• Author frames AI as a fast 'SRE intern' useful for preparing incident timelines, summarizing dashboards, highlighting anomalies and suggesting possible causes without making changes.

10-Q Financial Filing Analysis for PagerDuty (2026-08-27)

PagerDuty hat die Ergebnisse für das 2. Quartal des Geschäftsjahres 2027 (Stichtag 31. Juli 2026) vorgelegt. Der Gesamtumsatz stieg leicht um 0,8 % im Jahresvergleich auf 124,4 Mio. USD. Das operative Ergebnis verbesserte sich deutlich von 3,6 Mio. USD im Vorjahresquartal auf 10,2 Mio. USD, gestützt durch strikte Kostenkontrolle und einen Rückgang der operativen Aufwendungen um 6,6 % auf 94,2 Mio. USD. Der GAAP-Nettogewinn belief sich auf 7,8 Mio. USD bei einer Bruttomarge von 83,9 %. Zudem kündigte PagerDuty im August 2026 eine umfassende Restrukturierung an, die einen Abbau der Belegschaft um ca. 15 % beinhaltet, um Ressourcen auf KI-gestützte Arbeitsabläufe auszurichten. Hierfür werden Restrukturierungskosten zwischen 5,5 Mio. USD und 7,5 Mio. USD erwartet.

• Umsatz im 2. Quartal bei 124,4 Mio. USD mit einem operativen GAAP-Gewinn von 10,2 Mio. USD (Vorjahr: 3,6 Mio. USD).
• Jährlich wiederkehrende Umsätze (ARR) beliefen sich auf 501,4 Mio. USD bei 15.506 zahlenden Kunden und einer Net Retention Rate von 98 %.
• Ankündigung eines Restrukturierungsprogramms im August 2026 mit einem Stellenabbau von rund 15 % und Einmalkosten von 5,5 bis 7,5 Mio. USD.

See It, Approve It, Revoke It: Scoped OAuth for Public Apps

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about...

OCI Monitoring Alarms: Six Readiness Traps That Cause Failures

The article explains six common reasons an Oracle Cloud Infrastructure (OCI) alarm can be created correctly yet fail to operate as an effective production control. It highlights mismatches between alarm evaluation interval and metric emission frequency; incorrect or overly narrow metric dimensions; pitfalls of absence alarms (including the need for groupBy); unproven notification paths and unconfirmed subscriptions; inadequate suppression and maintenance handling; and unreviewed trigger-delay settings. The piece provides validation checks, evidence sources (MQL query review, test records, notification receipt), and a ten-point readiness checklist to ensure alarms evaluate the right metric, at the right cadence, for the right resource and notify the right people with actionable guidance.

• The article identifies six failure modes for OCI alarms: metric interval mismatch, wrong dimensions, absence-alarm groupBy issues, unproven notification paths, uncontrolled maintenance/noise, and inappropriate trigger delay.
• Oracle documents that absent() returns 1 when a metric is absent for the entire interval and 0 when present; the default absence detection period is two hours and is configurable from 1 minute through 3 days.
• OCI supports alarm suppression for planned activity; suppression start and end times must each be within 90 days of the current time.