TL;DR: A Policy Engine says what configurations are allowed. In this post, I will explain the concept of a Policy Engine, followed by Policy as Code (PaC) and the Open Policy Agent (OPA). Policy Engine A Policy Engine is a system that evaluates resource requests against defined rules and determines what configurations are allowed. Instead of checking identity or user permissions (which is handled by Role-Based Access Control, or RBAC), a Policy Engine inspects the resource payload itself to determine whether it adheres to operational and security guardrails. ...

TL;DR: First things first: please remember that Kubernetes is a collection of software running on Linux. Basically, everything that happens in Kubernetes is built on top of Linux kernel primitives and TCP/IP networking foundations. We will describe Kubernetes networking from the smallest to the largest units: Containers Pods Nodes Clusters Basic IP Concepts Do you remember that localhost is the machine’s loopback hostname, associated with the IP address 127.0.0.1? There are also specific IP ranges designated as Private IP addresses: ...

TL;DR: Reconciliation is Kubernetes continuously checking the actual state against the desired state and taking action when they are different. Imagine that you need to keep a certain number of copies of the same thing. Sometimes you need to create 100 copies. Sometimes you need to delete them and leave only one copy. If you do this manually, you need to keep checking the status, count how many copies currently exist, and then create or delete copies to reach the number you need. ...

TL;DR: A Kubernetes Operator extends Kubernetes with application-specific operational knowledge, allowing complex, stateful applications(like databases) to be managed declaratively through the native Kubernetes API. When Kubernetes first emerged, its primary strength was orchestrating stateless applications. If a web server Pod crashed, Kubernetes could recreate it. If traffic increased, a Deployment could scale to additional replicas. Individual Pods could generally be replaced because the application did not depend on the identity or internal state of a specific Pod. ...

TL;DR: For short, I think we can summarize K8s CRD as a Custom API for Kubernetes. For this definition, it is easier to clarify what is in the standard API for Kubernetes and then explain what is not. To see what is in the standard API for Kubernetes click here. A Custom Resource Definition (CRD) is an extension mechanism in Kubernetes that allows you to define your own API objects beyond standard resources like Pods, Services, or Deployments. It acts as a database schema written in YAML (using OpenAPI v3 format) that teaches the Kubernetes API server a new object type, along with its allowed fields and validation rules. ...

Kubernetes Standard API Reference This document provides a comprehensive list of standard, built-in Kubernetes API groups, their associated API versions, key resources, and functional descriptions. 1. Core API Group (/api/v1) The core API group handles primary operational building blocks, runtime workloads, network primitives, and foundational storage resources. API Group Version Key Resources Description Core ("") v1 Pod, Service, Namespace, ConfigMap, Secret, Node, PersistentVolume, PersistentVolumeClaim, ServiceAccount, Endpoints, Event, ResourceQuota, LimitRange Essential infrastructure primitives and execution workloads. 2. Workloads & Orchestration APIs responsible for application execution, deployment strategies, scaling, and scheduled execution. ...

TL;DR: Grafana is the visualization and analytics layer of the cloud-native stack. It connects to telemetry backends such as Prometheus, Loki, and Tempo to query metrics, logs, and traces, turning raw telemetry into interactive dashboards and unified alerts. We previously covered Backstage, Prometheus, and OpenTelemetry: Backstage: Serves as the developer portal and catalog for platform management. Prometheus: Collects, stores, and queries time-series metrics using PromQL. OpenTelemetry (OTel): Provides a standardized framework to generate, collect, transform, and export the three core telemetry signals—Metrics, Traces, and Logs (MELT). What is Grafana? Grafana is an open-source visualization and analytics platform. It does not normally store telemetry data itself; instead, it queries external data sources and storage backends to present operational insights through interactive dashboards. ...

TL;DR: Helm uses templates and variables to make Kubernetes applications easier to configure and implement across different environments. Comparing plain Kubernetes YAML files with Helm-templated YAML highlights why Helm is a widely used package manager and templating tool for Kubernetes. The Core Difference Plain YAML (Static): Every value is hardcoded. To deploy to different environments, you must manually copy, paste, and modify files (or use search-and-replace scripts). Helm YAML (Dynamic): Values are parameterized using placeholders ({{ .Values... }}). A single template generates customized manifests based on a separate values.yaml file. ...

OpenTelemetry (OTel) is a vendor-neutral, open-source observability framework under the Cloud Native Computing Foundation (CNCF), formed by the merger of OpenTracing and OpenCensus. It provides a single set of APIs, SDKs, tooling, and integrations to generate, collect, transform, and export telemetry data—specifically Traces, Metrics, and Logs (the “three pillars of observability”), from software applications. Core Problem It Solves Before OpenTelemetry, every observability vendor (Datadog, New Relic, Dynatrace, Honeycomb, Jaeger, Prometheus) supplied its own proprietary SDKs and agents. This led to high vendor lock-in; switching or routing telemetry data to a new backend required rewriting application instrumentation code or swapping underlying agents across your entire infrastructure. ...

TL;DR: Prometheus is a pull-based monitoring system that collects and stores time-series metrics, while PromQL provides a powerful way to query and analyze those metrics. Prometheus is an open-source monitoring and alerting system designed around time-series data. The core concept is relatively simple: applications and infrastructure expose metrics, and Prometheus regularly scrapes those metrics and stores them with timestamps and labels. This makes Prometheus a vital-signs monitor for infrastructure. If Kubernetes is the environment where our workloads live, Prometheus continuously measures what those workloads are doing. ...