Salem Kim on LinkedIn: #gcloud #git #git #git #git #git #git #git #git #jenkins #devops… (2024)

🚀Unlocking the Power of Prometheus in Cloud Computing🌐In the dynamic world of cloud computing, monitoring and observability are crucial. EnterPrometheus– an open-source monitoring and alerting toolkit designed for reliability and scalability. 🌟🔍Why Prometheus?Time-Series Data: Collects and stores metrics with timestamps, providing a clear picture of system performance over time.Flexible Querying: With PromQL, you can easily query and analyze your data.Cloud-Native: Seamlessly integrates with Kubernetes, making it perfect for modern, containerized environments.Alerting: Set up alerts to stay ahead of potential issues and ensure system reliability.Prometheus is a game-changer for anyone looking to enhance their cloud infrastructure’s monitoring capabilities. Whether you’re running on GCP, AWS, or any other platform, Prometheus has got you covered! 🌍#CloudComputing #Prometheus #Monitoring #Kubernetes #DevOps #CloudNative #OpenSource #GCP #AWS #TechInnovation

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🚀Unleashing the Power of Locust for Load Testing!🦗Ever wondered how to ensure your website’s frontend can handle a swarm of users? EnterLocust! 🦗 This powerful, open-source load testing tool lets you simulate millions of users to identify bottlenecks and potential failures in your web services. 🌐🔍How it works:Define User Behavior: Write your test scenarios in Python. 🐍Simulate Traffic: Locust swarms your site with virtual users, mimicking real-world traffic. 🌍Monitor in Real-Time: Use the web UI to track performance and pinpoint issues. 📊💡Why Locust?Scalable: Supports thousands of concurrent users on a single machine.Flexible: Easily integrates with your CI/CD pipeline.Insightful: Provides detailed reports to help you optimize performance.🔧Use Case: Imagine launching a new feature on your e-commerce site. With Locust, you can simulate a Black Friday rush, ensuring your frontend remains robust under pressure. 🛒💥Ready to battle-test your website? Dive into Locust and make sure your frontend is ready for anything! 💪hashtag#LoadTesting hashtag#WebDevelopment hashtag#PerformanceTesting hashtag#Locust hashtag#Python hashtag#DevOps hashtag#WebPerformance hashtag#TechTips

🚀Troubleshooting Kubernetes Dashboard and Logs🚀🔍Navigation Path:Observability>Monitoring>Dashboards>GKEKubernetes Engine>Workloads>productcatalogservice🛠️Issue:The pod for theproductcatalogserviceis constantly crashing and restarting.📜Steps to Access Container Logs:Using the Logs TabIn the Overview Tab, Click on Container Logs📊Log Messages & Histogram:The container is repeatedly parsing product catalogs within a short period of time.💥Error Message:panic: runtime error: invalid memory address or nil pointer dereference[signal SIGSEGV: segmentation violation]Segmentation Fault: This error occurs when accessing memory that “does not belong to you.” It protects memory and prevents data corruption.🔍Troubleshooting Steps:Search for the String in the Source Code:# grep -nri 'successfully parsed product catalog json' srcUsing Cloud Shell Editor (Google Cloud):Navigate tomicroservices-demo/src/productcatalogservice/server.goIf the boolean variablereloadCatalogistrue, the service reloads and parses the product catalog each time it’s invoked, which seems unnecessary.Search for thereloadCatalogvariable in the code. It’s controlled by the environment variableENABLE_RELOADand writes a log message for its state.Check the Logs Again:Add this message to your query:json.Payload.message:"catalog reloading"Run the query and view the logs.⚠️Root Cause:The frontend error is caused by the overhead to load the catalog for every request. When the load increased, the overhead caused the service to fail and generate the error.🔧Solution:Adjust thereloadCatalogvariable to prevent unnecessary reloading and parsing of the product catalog.#Kubernetes #GKE #Troubleshooting #DevOps #CloudComputing #Logs #Monitoring #GoogleCloudPlatform #Microservices #TechTips #K8s

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what happens when you flood a web application with huge traffic?1. Server Overload: The server gets overwhelmed and can’t handle all the requests. This can cause it to slow down or crash. 🖥️💥2. Increased Latency: The response time for users increases significantly, making the application feel sluggish. 🐢⏳3. Denial of Service: Legitimate users can’t access the application because it’s too busy handling the flood of requests. 🚫🌐4. Resource Exhaustion: The server’s resources (CPU, memory, bandwidth) get maxed out, leading to potential downtime. 📉🔋5. Potential Security Risks: Such traffic floods can be part of a DDoS (Distributed Denial of Service) attack, which can expose vulnerabilities. 🛡️⚠️#DDoS #ServerManagement #CloudComputing #NetworkSecurity #ITInfrastructure #TechTrends #Scalability #LoadBalancing #PerformanceTesting #DevOps #SiteReliabilityEngineering #HighTraffic.

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🚀Mastering Autoscaling with Custom Google Cloud Monitoring Metrics!🚀Ever wondered how to efficiently manage your cloud resources? 🤔 Let’s dive into an example of autoscaling instance groups using custom Google Cloud Monitoring metrics! 📊🔍Scenario Overview:Initial Setup:Autoscaling group starts with a single instance.Metric Target:Aggregate custom metric target is set at 150.Scale-Up:As metrics exceed targets, new instances are added.Scale-Down:Instances are removed when metrics fall below targets, with a built-in delay to ensure stability.🕒Timeline Breakdown:11:27:Autoscaling starts with 1 instance.11:31:Metric > 150 ➡️ 2nd instance added.11:33:Metric > 300 ➡️ 3rd instance added.11:37:Metric > 450 ➡️ 4th instance added.11:42:Metric > 600, but max group size reached.11:44:Low metric period begins.11:54:Metric < 600 for 10 mins ➡️ 2 instances removed.12:00:High metric period resumes ➡️ 3rd instance added.12:04:Metric > 450 ➡️ 4th instance added.📈Key Takeaways:Efficiency:Autoscaling ensures optimal resource usage.Flexibility:Custom metrics allow tailored scaling policies.Stability:Built-in delays prevent rapid fluctuations.Harness the power of autoscaling to keep your applications running smoothly and cost-effectively! 💡#CloudComputing #GoogleCloud #Autoscaling #DevOps #Kubernetes #CloudNative #TechInnovation #ITInfrastructure #CloudManagement #CustomMetrics

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🚀 What is Jenkins and How to Use it with Kubernetes Engine on Google Cloud 🌐Hey LinkedIn community! 👋Today, I want to share some insights about Jenkins and how it can be seamlessly integrated with Kubernetes Engine on Google Cloud to supercharge your CI/CD pipelines. 💡What is Jenkins? 🤔Jenkins is an open-source automation server that helps developers build, test, and deploy their applications efficiently. It’s a powerful tool for continuous integration and continuous delivery (CI/CD), enabling teams to iterate quickly and deliver high-quality software. 🛠️Why Use Jenkins with Kubernetes Engine? 🌟Combining Jenkins with Kubernetes Engine (GKE) on Google Cloud offers several advantages:Scalability 📈: Kubernetes dynamically allocates resources, allowing Jenkins to create ephemeral build agents as containers. This means you can scale your build processes based on demand.Efficiency ⚡: Ephemeral build agents reduce resource overhead and improve build times, as they are only active when needed.Flexibility 🔄: Run jobs on multiple operating systems within the same cluster, thanks to containerization.Load Balancing 🌐: GKE comes with Google’s global load balancer, ensuring efficient traffic routing to your Jenkins instance.Getting Started 🚀Provision Jenkins on GKE: Use Helm to deploy Jenkins on your Kubernetes cluster.Configure Jenkins: Set up your Jenkins application and integrate it with your CI/CD pipeline.Run Pipelines: Create and execute Jenkins pipelines to automate your build, test, and deployment processes.By leveraging Jenkins with Kubernetes Engine on Google Cloud, you can achieve a robust, scalable, and efficient CI/CD setup that accelerates your software delivery. 🌍💻Happy coding! 🎉#Jenkins #Kubernetes #GoogleCloud #CICD #DevOps #CloudComputing #Automation

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🚀Setting Up a VPN Between Cloud and On-Premises Infrastructure🌐In today’s hybrid cloud environments, establishing a secure connection between your on-premises infrastructure and cloud infrastructure is crucial. Here’s a quick guide to setting up a VPN and testing the connection using iPerf. 💡Steps to Set Up the VPN:Choose Your VPN Gateway: Select a VPN gateway that supports IPsec for secure communication.Configure the VPN Connection:On-Premises: Set up your on-premises VPN device to terminate the VPN connection.Cloud: Configure your cloud VPN gateway (e.g., Google Cloud, Azure) to establish the site-to-site VPN.Test the Connection with iPerf:Install iPerf: Ensure iPerf is installed on both the on-premises server and the cloud VM.Run iPerf: Use iPerf to measure the bandwidth and performance of your VPN connection.Example iPerf Command:# On the server (on-premises)iperf -s# On the client (cloud VM)iperf -c <server-ip>By following these steps, you can ensure a robust and secure connection between your on-premises and cloud environments. 🌟Feel free to reach out if you have any questions or need further assistance! 🤝#CloudComputing #VPN #HybridCloud #Networking #iPerf #TechTips #GoogleCloud

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🚀Creating a Secure IPsec VPN🚀🔒IPsec: A protocol suite for secure Internet Protocol (IP) communications by authenticating and encrypting each IP packet of a communication session. It includes protocols for establishing mutual authentication between agents at the beginning of the session and negotiation of cryptographic keys to be used during the session. IPsec can protect data flows between hosts (host-to-host), security gateways (network-to-network), or between a security gateway and a host (network-to-host). It operates in the Internet Layer of the Internet Protocol Suite.🌐Tunnel: A virtual path or route over a network used to securely transmit data between two or more devices. Google Cloud supports the use of multiple tunnels.🛠️Creating a VPN:Create a VPCon both the cloud and on-premises.Create VPN gateways, forwarding rules, and addresses for the cloud VPC.Form a tunnelfor the new VPN and route traffic through it.Repeat the VPN creation processfor the on-premises VPC, creating a second VPN.🔗 Secure your data and enhance your network’s reliability with IPsec VPNs! #CloudComputing #IPsec #VPN #GoogleCloud #NetworkSecurity #TechTips

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🚀Unlock the Power of Kubernetes with Google Kubernetes Engine!🌐👋I’m thrilled to share my latest Medium article on provisioning a complete Kubernetes cluster using Google Kubernetes Engine (GKE). If you’re passionate about cloud computing, container orchestration, or just looking to expand your tech skills, this article is for you! 🌟In this step-by-step guide, you’ll learn how to:🔑 Activate and authorize your Google Cloud account🌍 Set up your project and compute zone🌐 Create and manage a Kubernetes cluster with GKE🐳 Deploy and manage Docker containers using kubectl📦 Understand and work with pods and volumesWhether you’re a seasoned pro or just starting out, this guide will help you harness the full potential of Kubernetes with GKE. Don’t miss out on this opportunity to level up your skills! 💪Check out the full article on Medium and let’s embark on this cloud journey together! 🚀#CloudComputing #Kubernetes #GoogleCloud #GKE #Docker #TechSkills #MediumArticle #LearningJourney #ContainerOrchestration #DevOps

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