Notes on API and vendor monitoring
Uptime checks, incident response, SLA tracking, and the parts of vendor monitoring that actually matter when something breaks.
Multi-Cloud Monitoring Tools: How to Choose in 2026
Four categories of multi-cloud monitoring tool, what each one actually answers, and how to tell which gap you have. Includes where PulsAPI is the wrong choice.
Observability vs Monitoring vs Telemetry: What Teams Need in 2026
Telemetry is the data, monitoring is the practice, observability is the property. What each of the three actually means, when each matters, and where third-party status fits.
OpenTelemetry Getting Started: A Practical Guide for SaaS Teams
A practical OpenTelemetry getting-started guide: what to instrument first, which SDKs to pick, how to ship to any backend, and the mistakes to avoid in production.
Distributed Tracing Best Practices for Microservices in 2026
Distributed tracing best practices for microservices: span design, sampling, context propagation, third-party calls, and the pitfalls that make traces useless during incidents.
Chaos Engineering Introduction: Build Reliability by Breaking Things on Purpose
A practical chaos engineering introduction: principles, game days, third-party failure injection, and how to start without taking production down.
Kubernetes Cluster Monitoring: A Complete Guide for SRE Teams
What to monitor in a Kubernetes cluster, which metrics matter, how to detect control plane issues, and how to combine internal metrics with cloud provider status.
Serverless Monitoring: How to Track AWS Lambda Reliability in Production
How to monitor AWS Lambda in production: cold starts, throttles, async failures, cost spikes, and how regional AWS status fits into the picture.
GraphQL API Monitoring: Beyond REST Health Checks
GraphQL API monitoring done right: schema observability, resolver latency, error coalescing, persisted queries, and the metrics REST monitoring tools miss.
Microservices Monitoring Strategy: From Health Checks to SLOs
A practical microservices monitoring strategy: golden signals, service-level objectives, dependency mapping, and how third-party status fits the picture.
AI API Reliability: Monitoring OpenAI, Anthropic, and the LLM Stack
How to monitor AI API reliability in production: token quotas, model degradation, latency spikes, multi-provider fallback, and live LLM vendor status.