Cloud Native

Kubernetes in the Real World Orchestrating Containers Kubernetes helps run many containers across many machines. In practice, teams mix apps with data, users, and budgets. The real world adds complexity: multiple environments, evolving security needs, and the need for predictable updates. The right approach is to use repeatable patterns, clear ownership, and automation that reduces manual steps. Start with simple building blocks. A Deployment keeps your app running with some replicas. Give each pod a resource request and limit so the scheduler can place workloads fairly. Add a Readiness probe to tell traffic controllers when a pod is ready, and a Liveness probe to restart stuck containers. Use a Namespace to separate environments or teams, and apply Role-Based Access Control to limit who can change what. Store configuration in ConfigMaps and sensitive data in Secrets, mounted into pods as files or environment variables. ...

Observability in Cloud Native Environments Observability in cloud native environments means you can understand what your system is doing, even when parts are moving or failing. Teams collect data from many services, containers, and networks. By looking at logs, metrics, and traces together, you can see latency, errors, and the flow of requests across services. Three pillars guide most setups: Logs: structured logs with fields like timestamp, level, service, request_id, user_id, and outcome. Consistent formatting makes searches fast. ...

Kubernetes in Practice: Orchestration for Production Kubernetes acts as a control plane for containers. It schedules workloads on machines, restarts failed pieces, and maintains the desired state even when parts of the system fail. In production, you need more than a single cluster. You need repeatable processes for rollout, failure handling, and observability. In practice, teams follow a few core patterns. Use declarative configuration stored in version control. Isolate teams with namespaces and quotas. Give each workload resource requests and limits to prevent noisy neighbors. Add readiness and liveness probes so the system can recover on its own. Plan rolling updates and canary deployments to release changes safely. Build visibility with centralized logging and metrics. Use RBAC and strong secret management to limit access. Finally, have backups and a simple disaster recovery plan. ...

Cloud-native Development: Build, Deploy, Scale Cloud-native development helps teams build software that can run anywhere—on private clouds, public clouds, or at the edge. It relies on containers, microservices, and automation to stay reliable as demand grows. With this approach, you design for failure, deploy frequently, and measure what matters. The goal is to empower small teams to move fast without breaking production. Build your apps with a clear mindset. Start by packaging each service as a container image. Keep services small, focused, and easy to upgrade. Use clear versioning and immutable artifacts. Store configuration outside the code, using environment variables or a config service. A simple pipeline can build, test, and push images to a registry. This creates a repeatable path from code to running software. ...

Docker and Kubernetes Demystified: Virtualization and Container Orchestration Docker helps run applications in isolated environments called containers. Virtualization uses full virtual machines, but containers share the host system’s kernel and stay lightweight. Docker packages an application and its dependencies into an image that can run anywhere a compatible engine exists. When you start the image, Docker creates a container instance that starts quickly and uses fewer resources than a VM. ...

Kubernetes Fundamentals: Orchestrating Containers at Scale Kubernetes helps teams deploy and manage apps at scale. It turns your desired state into reality, keeping containers running, restarting failed ones, and balancing load across nodes. With declarative configurations, you can reproduce environments and roll out changes safely. A cluster has two parts: the control plane and the worker nodes. The control plane makes decisions via components like the API server, scheduler, and controllers, and it stores state in etcd. On each node, the kubelet talks to the API server and starts containers with a runtime, while kube-proxy handles networking between services and pods. ...

Cloud Native Security Fundamentals Cloud native systems rely on containers, orchestration, and cloud services. Protecting them means designing security into every layer from the start. This defense-in-depth mindset helps reduce risk, detect threats early, and recover quickly. In practice, teams implement secure defaults in infrastructure as code, gate changes in CI/CD, and enforce encryption by default at rest and in transit. Key pillars you should apply every day: Identity and access management (IAM) with least privilege and short‑lived credentials; review roles regularly. Policy as code and automated governance to enforce rules consistently (OPA, Gatekeeper, policies in Git). Secrets management and encryption in transit and at rest; rotate keys, avoid hard-coded credentials, and use vaults or managed services. Guarding the build and supply chain matters too. Use signed images, SBOMs, vulnerability scanning in CI/CD, and enforce reproducible builds. Pin dependencies, monitor for advisories, and require trusted registries so public risk does not flow into production. ...

Cloud Security: Protecting Cloud Native Systems Cloud native systems move fast and scale with demand. Security should keep pace without blocking delivery. In practice, clear boundaries, simple controls, and continuous monitoring are key. Understanding who is responsible for what helps teams act quickly and safely. Understand the shared responsibility model. Cloud providers secure the underlying infrastructure, while you secure workloads, data, and configurations. Focus areas include identity, access controls, secrets, network posture, logging, and incident response. ...

Kubernetes at Scale: Lessons from Large Deployments Kubernetes shines when it runs many services, but large deployments expose gaps in planning and operations. Teams succeed by using repeatable patterns instead of ad hoc fixes. With clear governance, the platform becomes predictable, safe to evolve, and easier to support. Capacity planning and governance matter. Split workloads by environment and consider multiple clusters or strong namespace boundaries. Enforce quotas and naming rules so growth stays visible and manageable. This makes forecasting easier and reduces resource contention. ...

Networking for cloud-native apps: load balancing and DNS Cloud-native apps run across many containers and nodes. A good network design uses load balancing to spread traffic and DNS to locate services. Together they protect performance and reliability. Types of load balancing: L4 load balancers operate at the transport layer, routing packets by IP and port. They are fast and simple. L7 load balancers inspect HTTP and make routing decisions based on path, headers, or query strings. External vs internal: ...