Sejal Pandey

Apache Spark monitoring guide: what the Spark UI shows, how to keep it after a job ends, finding skew and spill, Prometheus metrics, and alerts.

Multi-cloud monitoring guide: why the same metric differs across AWS, Azure and GCP, and how to normalize it with OpenTelemetry into one view.

Set up the NVIDIA DCGM Exporter with Docker or Helm, pick the right DCGM metrics, enable profiling counters, map GPUs to Kubernetes pods, and add alerts.

Dynatrace pricing explained: DPS annual commits, the hourly rate card for hosts, pods, logs and RUM, why memory drives Full-Stack cost, and a worked bill.

An error budget is the unreliability an SLO allows. Learn to calculate it, track burn rate, set multiwindow alerts in PromQL and write an error budget policy.

A practical comparison of the best observability tools in 2026: Last9, Datadog, Grafana Cloud, New Relic, Dynatrace, Honeycomb, Coralogix and SigNoz.

Grafana Cloud pricing broken down: free tier limits, Pro rates for metrics, logs and traces, how active series and DPM are billed, and worked cost examples.

AI agent observability means tracing tool calls, reasoning steps, and handoffs, not just tokens and latency. Here's what to instrument and why.

How to monitor a Rails application in production: reading Puma's stats endpoint, spotting GC pressure, and finding the query that's actually slow.

SRE automation covers four different jobs: runbook automation, self-healing infrastructure, drift detection, and resilience testing.

How to monitor a PHP application in production: reading the PHP-FPM status page, checking OPcache health, and finding the request that is actually slow.

AIOps explained in plain terms: what it means, how it differs from AI-SRE and MLOps, how it detects problems, and whether a small team needs it.

Eight LLM and AI agent observability platforms compared: what each tracks, pricing and free tiers, self-hosting options, and who each is built for.

Observability spend is outgrowing infrastructure budgets. What drives the cost up, how pricing models work, and a practical framework to manage it.

Cribl's credit pricing and setup complexity send teams looking elsewhere. Compare 6 real Cribl competitors and alternatives, for observability and SecOps.

A stage-by-stage playbook for automating incident response: what to automate at detection, triage, and remediation, what to deliberately leave manual, and a checklist to run against your current setup.

A quick-reference guide to reading Nginx, Apache, and Linux syslog error lines: what each field means, with real annotated examples.

An SLO is the internal reliability target your team sets. An SLA is the contractual promise you make to a customer. Here's how they differ, with real examples.