Observability
Observability is the degree to which a system's internal state can be understood from its external outputs — typically metrics, logs, and traces — allowing engineers to diagnose novel, unanticipated problems without having to ship new code to add visibility.
62 resources across 3 libraries
Glossary Terms(23)
AWS CloudWatch
AWS CloudWatch is AWS's native monitoring and observability service that collects metrics, logs, and events from AWS resources and applications, and lets teams…
Azure Monitor
Azure Monitor is Microsoft Azure's full-stack monitoring service that collects metrics, logs, and traces from Azure resources and applications, providing dashb…
Google Cloud Operations Suite
Google Cloud Operations Suite (formerly Stackdriver) is Google Cloud's integrated set of monitoring, logging, and tracing tools that gives teams visibility int…
Nagios
Nagios is an open source IT infrastructure monitoring tool that checks the status of hosts and services and alerts administrators when something goes down or c…
Icinga
Icinga is an open source infrastructure monitoring tool that originated as a fork of Nagios, offering host and service monitoring with a modernized interface,…
Checkmk
Checkmk is an infrastructure and application monitoring tool that combines agent-based data collection with a Nagios-derived core, offering auto-discovery of s…
Site24x7
Site24x7 is a cloud-based monitoring service by Zoho that checks website, server, network, and application availability and performance from locations around t…
Uptime Robot
Uptime Robot is a website and service uptime monitoring tool that periodically checks whether a URL or port is reachable and alerts users when it goes down.
Honeycomb
Honeycomb is an observability platform built around high-cardinality, high-dimensionality event data, allowing engineers to ask arbitrary questions about produ…
Lightstep
Lightstep is a distributed tracing and observability platform, now known as ServiceNow Cloud Observability, built to help teams understand performance across l…
Chaos Engineering
Chaos engineering is the practice of deliberately injecting controlled failures into a system — killing servers, dropping network traffic, adding latency — to…
Site Reliability Engineering (SRE)
Site Reliability Engineering (SRE) is an engineering discipline that applies software-engineering practices to operations problems, using measurable reliabilit…
Service Level Objective (SLO)
A Service Level Objective (SLO) is a specific, measurable reliability target for a service — such as '99.9% of requests succeed in under 300ms over 30 days' —…
Incident Management
Incident management is the structured process a team follows to detect, respond to, resolve, and learn from unplanned disruptions to a service — from initial a…
Configuration Drift
Configuration drift is the gradual divergence of a system's actual running configuration from its intended, documented, or version-controlled state, usually ca…
Log Aggregation
Log aggregation is the practice of collecting log output from many distributed sources — servers, containers, and services — into a single centralized system w…
Distributed Tracing
Distributed tracing is a method for tracking a single request as it flows through multiple services in a distributed system, recording the timing and outcome o…
Observability
Observability is the degree to which a system's internal state can be understood from its external outputs — typically metrics, logs, and traces — allowing eng…
Synthetic Monitoring
Synthetic monitoring is the practice of proactively testing a system's availability and performance by running scripted, simulated user interactions — such as…
Real User Monitoring (RUM)
Real User Monitoring (RUM) is the practice of collecting performance and experience data directly from actual users' browsers or devices as they use an applica…
eBPF
eBPF (extended Berkeley Packet Filter) is a Linux kernel technology that lets sandboxed programs run directly inside the kernel, triggered by events like syste…
Chaos Monkey
Chaos Monkey is a chaos engineering tool, originally built by Netflix, that randomly terminates production instances to test whether a system can tolerate unex…
Site Reliability Engineering
Site Reliability Engineering (SRE) is an engineering discipline, pioneered at Google, that applies software engineering practices to operations problems, treat…
Study Notes(5)
Logging and Observability with Serilog
Configure structured logging with Serilog and pair it with metrics and distributed tracing to build real observability into an ASP.NET Core API.
Observability in Microservices
How to understand the internal state of a distributed system from the logs, metrics, and traces it produces, so you can debug failures you never anticipated.
Observability in Kubernetes
Observability in Kubernetes combines metrics, logs, and traces to answer not just whether something is broken, but why, across ephemeral pods and dynamic sched…
Kubernetes Monitoring and Logging
Learn the core tools and patterns for observing cluster and application health: metrics, logs, and the Prometheus/Grafana stack.
Monitoring and Observability
The practices and tooling — metrics, logs, and traces — that let engineers understand a distributed system's internal state from its external outputs and detec…
Interview Questions(34)
What Are Time-Series Databases and When Should You Use One?
A time-series database is a storage engine purpose-built for data points indexed by time, optimizing for high-volume append-only writes, time-range queries, an…
What Key Metrics Should You Monitor for a Database?
The core database metrics to monitor are query latency and throughput, connection pool saturation, replication lag, cache hit ratio, disk I/O and space usage,…
How Do You Design a Robust Database Health Check?
A robust database health check goes beyond a simple TCP ping by verifying that the database can actually execute a real query within an acceptable time, checki…
How Would You Design a Distributed Logging System?
Design a distributed logging system as a pipeline: lightweight agents on each host tail and buffer log lines locally, ship them to a durable, partitioned inges…
How Would You Design a Metrics Monitoring System (like Prometheus)?
Design a metrics monitoring system around periodic pull-based (or push-based via a gateway) scraping of numeric time series from every service, storage in a ti…
How Would You Design a Feature Flag System?
A feature flag system decouples code deployment from feature release by storing flag state in a fast, centrally managed store that services poll or subscribe t…
How to Design a Log Aggregation System
A log aggregation system collects logs from many hosts via lightweight shippers, ships them through a durable buffer to decouple producers from indexing speed,…
What is Distributed Tracing and Why Is It Needed?
Distributed tracing tracks a single request as it flows across many microservices by propagating a shared trace ID and recording timed spans at each hop, letti…
SLA vs SLO vs SLI: What Is the Difference?
An SLI (Service Level Indicator) is a measured metric like request latency or error rate, an SLO (Service Level Objective) is the internal target you set for t…
What Are the Principles of Chaos Engineering?
Chaos engineering is the disciplined practice of deliberately injecting failures into a production or production-like system to verify it actually withstands t…
Why Does Tail Latency (p99) Matter More Than Average Latency?
Tail latency (measured as p95, p99, or p999 percentiles) matters more than average latency because a system with a low average can still have a meaningful frac…
What Is the API Gateway Pattern?
An API gateway is a single entry point that sits in front of a set of backend services, routing each incoming request to the right service while centrally hand…
What is Monitoring vs Observability?
Monitoring is watching a predefined set of metrics and alerts to detect known failure conditions, while observability is the broader capability to ask arbitrar…
What is a Service Mesh?
A service mesh is an infrastructure layer that handles service-to-service communication for you by injecting a lightweight proxy alongside every service instan…
What is Log Aggregation?
Log aggregation is the practice of collecting log output from many distributed services, containers, and hosts into one centralized system where it can be sear…
What is Prometheus and How Does it Collect Metrics?
Prometheus is an open-source monitoring and alerting toolkit that pulls time-series metrics from configured targets over HTTP at regular intervals, stores them…
What is Grafana and How Does it Relate to Prometheus?
Grafana is an open-source visualization and dashboarding platform that queries data sources like Prometheus, Loki, or Elasticsearch and renders their results a…
What is the ELK Stack and How Do Its Components Work Together?
The ELK Stack is a set of three open-source tools — Elasticsearch, Logstash, and Kibana — that together ingest, parse, index, and visualize log data, letting t…
What is Distributed Tracing and Why Does it Matter in Microservices?
Distributed tracing is a technique that follows a single request as it travels across multiple microservices, recording a chain of timed operations called span…
What is Jaeger and How Does it Implement Distributed Tracing?
Jaeger is an open-source, CNCF-graduated distributed tracing system that collects, stores, and visualizes traces from instrumented applications, letting engine…
What is OpenTelemetry?
OpenTelemetry is a vendor-neutral open-source standard — a set of APIs, SDKs, and a collector agent — for generating, collecting, and exporting metrics, logs,…
What Are Metrics, Logs, and Traces?
Metrics, logs, and traces are the three pillars of observability: metrics are aggregated numeric time-series data showing system health at a glance, logs are t…
How Do You Design Effective Alerting?
Effective alerting fires only on symptoms that indicate real, actionable user-facing impact — not on every internal anomaly — and every alert should be tied to…
What is APM (Application Performance Monitoring)?
APM (Application Performance Monitoring) is the practice of instrumenting an application to capture traces, latency, throughput, and error data for every reque…
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