SQL vs NoSQL Databases: How to Choose
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
An architecture style in which an application is built as a collection of small, independent services that communicate over APIs.
In a monolithic application, all features live in one codebase and are deployed together. With microservices, each business capability, such as user accounts, payments, search, or notifications, becomes its own service with its own code and often its own database.
Teams can develop, deploy, and scale each service independently. If the search service is under heavy load, it can be scaled without touching payments. Services communicate through APIs or message queues and are often packaged in containers managed by Kubernetes. The approach adds complexity: network failures, distributed debugging, data consistency, and operational overhead. Many experts recommend starting with a well-structured monolith and splitting out services only when there is a clear need.
A server that sits in front of backend services and handles routing, authentication, rate limiting, and monitoring for API requests.
ContainerA lightweight, portable package that bundles an application with its dependencies so it runs the same way across different environments.
KubernetesAn open-source platform that automates deploying, scaling, and managing containerized applications across clusters of machines.
Monolithic ArchitectureA software design in which an application is built and deployed as a single unit, with all features sharing one codebase.
ObservabilityThe ability to understand what is happening inside a software system by examining the data it produces, such as logs, metrics, and traces.
Service MeshAn infrastructure layer that manages communication between microservices, handling traffic routing, security, and monitoring outside the application code.
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
What OpenTelemetry is, how its APIs, SDKs, Collector and OTLP fit together, and how to start by instrumenting a single service.
What load testing is, how load, stress, spike and soak tests differ, and how to read results like percentiles and error rates before real traffic finds your limits.