Cloud Native Taiwan User Group’s Post

Scenario 5: Securing Ingress Traffic with Ingress Controllers and TLS Question: How do you ensure that ingress traffic to your Kubernetes services is secure, using TLS to encrypt the communication? Answer: Solution: Use Ingress Controllers with TLS certificates. Step-by-Step Implementation: 1. Create a TLS Secret: Store the TLS certificate and key in a Kubernetes secret. kubectl create secret tls my-tls-secret --cert=cert.crt --key=cert.key 2. Create an Ingress Resource: Define an Ingress resource that uses the TLS secret. apiVersion: networking.k8s.io/v1 kind: Ingress metadata:  name: secure-ingress  namespace: production spec:  tls:  - hosts:   - myapp.example.com   secretName: my-tls-secret  rules:  - host: myapp.example.com   http:    paths:    - path: /     pathType: Prefix     backend:      service:       name: myapp-service       port:        number: 80 Explanation: The Ingress resource directs traffic to the myapp-service service, using the TLS secret for secure HTTPS communication. This ensures that all ingress traffic is encrypted, protecting sensitive data in transit. Scenario 6: Logging and Monitoring with Prometheus and Grafana Question: How do you monitor the health and performance of your Kubernetes cluster and microservices in real-time? Answer: Solution: Use Prometheus for metrics collection and Grafana for visualization. Step-by-Step Implementation: 1. Deploy Prometheus: Use the Prometheus Operator to deploy and manage Prometheus. kubectl apply -f https://lnkd.in/d88ii7YK 2. Deploy Grafana: Deploy Grafana and connect it to Prometheus. kubectl apply -f https://lnkd.in/dpaypU57 3. Set Up Dashboards: Create Grafana dashboards to visualize metrics such as CPU, memory usage, and pod availability. Explanation: Prometheus scrapes metrics from Kubernetes nodes, pods, and services. Grafana provides real-time dashboards to visualize these metrics, enabling proactive monitoring and alerting to ensure the health and performance of the Kubernetes cluster and microservices. "🌟 Empowering the Open Source Community! 🚀 Join us in sharing knowledge, tools, and innovations to build a brighter, more connected future. Let's collaborate and grow together! 💻✨ #OpenSource #Community #Innovation"

I just dropped my very first story into the Tines Library! 🚀 🔍 What's the Tines Library, you ask? It's a fantastic resource of pre-built Tines stories that allow users to instantly get started with Tines, a powerful no-code automation platform. 📊 Whats the Story? "Ingest Tines Audit Logs into Datadog" Basically, it's a nifty little automation that sends Tines audit logs straight to Datadog. No muss, no fuss! 🪄✨ 🔗 Check it out here: https://lnkd.in/e2e7iDVp #Tines #Automation #Datadog #SecurityAutomation #NoCode

How to join master node or control plane to Kubernetes cluster #WorkSmartWithK8s #kubernetes #cluster #kudeadm #join #controlplane https://lnkd.in/emqzyWum

🚀 Persistent Volume Troubleshooting in Kubernetes 🚀 Storage management in Kubernetes can be complex, but it’s a critical component of maintaining persistent data. In my latest blog, I cover: 🔹 Understanding Persistent Volumes (PV), Persistent Volume Claims (PVC), and Storage Classes (SC) 🔹 Troubleshooting Common Storage Issues like PVC problems and StatefulSet storage challenges. 🔧 kubectl Techniques for diagnosing and resolving storage issues effectively. Looking to simplify your Kubernetes storage management? Check out my detailed guide, published in FAUN - Developer Community 🔗 https://lnkd.in/gFEsf4iA #Kubernetes #StorageManagement #CloudNative #PersistentVolumes #TechBlog #DevOps #K8s #StatefulSets

High Availability (HA) is critical for the overall stability of a cluster, especially when considering the Kubernetes control plane. It's essential to have replicas of it, but the question arises: how many? Kubernetes follows the principle of "majority n/2 + 1" to ensure availability and consistency in systems with replicated components. Here's how it works: n: This represents the total number of replicas or instances in the cluster. Majority: For a distributed system to maintain consistency and availability, it often requires a majority of its replicas to agree on certain decisions or states. This is typically achieved by ensuring more than half of the replicas are available and in agreement. n/2 + 1: This calculation determines what constitutes a majority. By dividing the total number of replicas by 2 and adding 1, you get the minimum number required for a majority. For example, if you have 3 replicas: n = 3 n/2 = 3/2 = 1.5 (rounded down to 1) n/2 + 1 = 1 + 1 = 2 Here, the majority is 2, meaning you need at least 2 replicas available for the system to maintain quorum and continue functioning properly. Similarly, if you have 5 replicas: n = 5 n/2 = 5/2 = 2.5 (rounded down to 2) n/2 + 1 = 2 + 1 = 3 In this case, you need at least 3 replicas. Always remember to take odd replicas of control plane and never take 2 as if by chance one replica is down second one cant save u and all these control plane nodes comes with price too so its good to have 3 or 5 but avoid 2 or 7.

# kubernetes best practices tips Preventing Kubernetes Nodes from Crashing Due to High Disk Usage We encountered an issue where our Kubernetes nodes were crashing due to high disk usage. After some investigation, we found that disk space was being consumed faster than expected, causing the nodes to become unresponsive. To tackle this, we introduced “node-pressure eviction” in our Kubernetes configuration. This allows us to set disk usage thresholds, so that when the usage exceeds the defined limit, pods are automatically evicted to free up space. As a result, the nodes stay operational, and we avoid unexpected crashes. While you can configure similar thresholds for memory and image storage, in our case, disk space was the top priority. This simple adjustment has made a big difference in ensuring our cluster remains stable. For more info, check this out :- https://lnkd.in/gdtniAhH If you've faced similar challenges or have other tips on optimizing Kubernetes performance, feel free to share your insights! #Kubernetes #DevOps #CloudComputing #K8s #SRE #TechTips #ITInfrastructure #CloudNative #TechLeadership #DevOpsBestPractices #InfrastructureManagement

Dear Network, Under the guidance of Ms. Meriem Kassar, my partner Amal Abbes and I embarked on an exciting journey into the realm of software-defined networks (SDN). Our project focused on creating a distributed SDN controller using a microservices architecture. Our aim was to redefine large-scale network traffic management through a modular and decentralized approach. We delved into the intricacies of large-scale network traffic management while adopting a modular and decentralized architecture. Our specific focus was on the Simple Switch module of the Ryu controller, aiming to comprehend its role in managing data flow between hosts within a controlled environment. #SDN #docker #kubernetes #microservices #distributedNetworks

Why Do We Need the Control Plane (Master Plane) in Kubernetes? 1. Centralized Management of the Cluster 2. Resource Scheduling and Allocation 3. Maintaining Desired State 4. Cluster-wide Configuration and API Management 5. Cluster Health and Self-Healing 6. Consistent State with Etcd 7. Multi-Cluster and High Availability 8. Security and Access Control Conclusion #Kubernetes #DevopsTools #Masternode #Controlplane #cluster #node #Tutorial #learner #Devopstools #learner #K8S #etcd #Kubernetes

After implement and maintain Thanos stack. We have logs metrics for production with size 6Ti saved on GCS. How we improve our availability of Thanos? Lets start from Store Gateway by enable persistent volumes (PV). As Thanos Sidecar backs up data into the object storage bucket (GCS), we can decrease Prometheus’s retention in order to store less data locally. However, we need a way to query all that historical data again. Store Gateway does just that, by implementing the same gRPC data API as Sidecar, but backing it with data it can find in object storage bucket. Just like sidecars and query nodes, Store Gateway exposes a Store API and needs to be discovered by Thanos Querier. Store Gateway uses a small amount of disk space for caching basic information about data in the object storage bucket. This will rarely exceed more than a few gigabytes and is used to improve restart times. It is useful but not required to preserve it across restarts. But with our size of GCS, we decided to enable PV with more then few gigabytes. We put 128Gi. Then for this big size log metrics we need 6 replicas for Store Gateway. Each replicas need resource: Request (1CPU, 19GB RAM) and Limit (2CPU, 23GB RAM). That is big resource to keep our Thanos work on track. this is part3. #thanos #devops #prometheus