Grafana Loki Architecture 🚀In this blog,You will learn the following. - What is Grafana Loki? - Loki Deployment Modes - Features of Grafana Loki - Grafana Loki Architecture - Grafana Loki Components - Difference Between Grafana Loki and EFK Stack - Example of How Chunks and Indexes are Stored in Loki𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gWBz-AAK#devops #grafanaloki

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🌟 Monitoring Like a Pro with Prometheus and Grafana! 🌟In today’s DevOps-driven world, monitoring isn't just a tool—it's a superpower! 🚀🔎 Why Monitoring Matters:Effective monitoring ensures uptime, tracks performance, and enables proactive problem-solving. And when it comes to reliable monitoring stacks, Prometheus and Grafana lead the way!💡 What Makes Prometheus & Grafana a Winning Combo?Prometheus: A powerhouse for collecting metrics and providing real-time alerting. It’s perfect for tracking everything from application performance to Kubernetes cluster health.Grafana: Turns raw data into beautiful, insightful dashboards. With Grafana, storytelling with metrics becomes intuitive and impactful!✅ Here’s How I’ve Used Them:Monitored containerized applications on Kubernetes clusters, tracking CPU/memory usage, pod health, and request latency.Built dynamic Grafana dashboards to visualize trends, detect bottlenecks, and analyze historical data.Configured Prometheus alerts for instant notifications, ensuring no downtime goes unnoticed.🔧 Pro Tips:1️⃣ Define clear metrics and labels in Prometheus for seamless querying.2️⃣ Create actionable Grafana alerts tied to business-critical SLAs.3️⃣ Leverage prebuilt Grafana dashboards for quick insights and customization.💬 What’s Your Go-To Monitoring Setup?Let’s share knowledge and empower each other! Drop your tips or experiences below. 👇#DevOps #Monitoring #Prometheus #Grafana #Kubernetes #TechInnovation RAHAM SHAIK

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🚀 Not everyone needs Kubernetes! Have you heard about HashiCorp Nomad?Many people think Kubernetes is the only way to orchestrate containers and applications, but the truth is, it can be overkill for many companies and projects.In my latest video, I break down Nomad 101 and explain how this lightweight, efficient alternative can simplify your infrastructure without the complexity of Kubernetes.🔹 Easier than Kubernetes🔹 Lower resource consumption🔹 Runs smoothly without a massive cluster💡 Now with AI dubbing! The video is available in both Portuguese and English, so more people can follow along. And if more people tune in, I might start doing the dubs myself!If you’re looking for a simpler way to manage workloads, Nomad might be the perfect solution! Check out the video and see for yourself. 🎥👇https://lnkd.in/e38jPEvN#Nomad #HashiCorp #ContainerOrchestration #Kubernetes #DevOps #Infrastructure #AIDubbing

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𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀: 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗔𝗽𝗽𝘀, 𝗜𝗻𝘀𝗶𝗱𝗲 𝗮𝗻𝗱 𝗢𝘂𝘁Understanding how to expose and manage communication for your applications within Kubernetes is paramount. The Kubernetes Service abstraction is a critical component, providing stable network endpoints for your Pods. Let's explore the three fundamental Service types and their strategic uses:🟢 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐈𝐏: 𝐓𝐡𝐞 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐫𝐞𝗣𝘂𝗿𝗽𝗼𝘀𝗲: This is the default and most common Service type, designed for internal-only communication within your Kubernetes cluster.𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀: It assigns a stable, cluster-internal IP address to your Service, which is not accessible from outside the cluster network.𝗪𝗵𝘆 𝘂𝘀𝗲 𝗶𝘁: Ideal for enabling seamless communication between your microservices (e.g., a frontend talking to a backend database). It inherently enhances security by keeping internal traffic private and abstracts away the dynamic nature of Pod IPs.🟣 𝐍𝐨𝐝𝐞𝐏𝐨𝐫𝐭: 𝐃𝐢𝐫𝐞𝐜𝐭 𝐍𝐨𝐝𝐞 𝐄𝐱𝐩𝐨𝐬𝐮𝐫𝐞𝗣𝘂𝗿𝗽𝗼𝘀𝗲: Used when you need to expose an application externally, typically for testing, demonstrations, or specific on-premises deployments where a cloud LoadBalancer isn't an option.𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀: Kubernetes opens a static port (usually in the 30000-32767 range) on the IP address of every Node in your cluster.𝗪𝗵𝘆 𝘂𝘀𝗲 𝗶𝘁: External traffic reaches your application by hitting <NodeIP>:<NodePort>, which is then routed by Kubernetes to your Service and its Pods. It's a straightforward way to get traffic into the cluster.🔵 𝐋𝐨𝐚𝐝𝐁𝐚𝐥𝐚𝐧𝐜𝐞𝐫: 𝐂𝐥𝐨𝐮𝐝-𝐍𝐚𝐭𝐢𝐯𝐞 𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐒𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝗣𝘂𝗿𝗽𝗼𝘀𝗲: This is the industry standard for production-grade external exposure when deploying in a cloud environment.𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀: When created, Kubernetes automatically provisions an external cloud load balancer (e.g., from Azure, AWS, GCP) and assigns it a public, external IP address.𝗪𝗵𝘆 𝘂𝘀𝗲 𝗶𝘁: This external Load Balancer efficiently distributes incoming public traffic to your Service and its underlying Pods. It provides robust public access, high availability, and often includes built-in scaling and health checks from the cloud provider.Ultimately, really grasping these Kubernetes Service types isn't just about configuration, it's about making informed architectural decisions. This understanding empowers you to build applications that are truly resilient, secure, and consistently accessible, forming the very foundation of robust cloud-native deployments.#Kubernetes #K8s #CloudNative #Networking #Microservices

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Mastering Terraform Provider Version Pinning: Semantic Versioning Best Practices 🚀Hey LinkedIn network! 👋 If you're diving into Infrastructure as Code (IaC) with Terraform, you've probably wrestled with provider versions. Today, let's unpack the magic of provider.tf, version pinning, and semantic versioning (SemVer) – with best practices to keep your setups stable and scalable. 🔒 Whether you're a DevOps newbie or a seasoned pro, this will level up your game.First off, why bother with version pinning? Terraform providers (like AWS, Azure, or Google Cloud) evolve rapidly. Without pinning, a simple terraform init could pull in breaking changes, turning your infra into a house of cards. 😱 Pinning ensures reproducibility and prevents surprises in CI/CD pipelines.Enter provider.tf – the file where you declare your providers and their versions. It's your control center! Use the required_providers block inside a terraform block to specify sources and constraints.Semantic Versioning is key here. SemVer follows the MAJOR.MINOR.PATCH format:MAJOR: Breaking changes (e.g., API overhauls).MINOR: New features, backward-compatible.PATCH: Bug fixes, no disruptions.Best practice? Use pessimistic version constraints like ~>. This allows patches and minor updates but blocks major breaks. For example, ~> 4.0 means ≥4.0 and <5.0 – flexible yet safe. 📌 Avoid loose pins like >= 1.0 unless you're feeling adventurous!Other tips:Lock files matter: Run terraform init to generate .terraform.lock.hcl – commit it to Git for team consistency.Test upgrades: Always validate new versions in a staging env before prod.Multiple providers? Group them logically.HashiCorp Verified: Stick to official providers for security.terraform { required_providers { aws = { source = "hashicorp/aws" version = "~> 5.0" # Pins to 5.x series } google = { source = "hashicorp/google" version = ">= 4.0, < 5.0" # Explicit range for control } }}provider "aws" { region = "us-west-2"}provider "google" { project = "my-gcp-project"}This setup keeps things pinned while allowing safe updates. 🌟In summary, mastering version pinning with SemVer turns chaos into confidence. Your deploys stay reliable, and collaboration thrives. What's your go-to Terraform tip? Drop a comment below – let's geek out! 💬 #Terraform #DevOps #IaC #SemanticVersioning

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🛠️ 10 Terraform Scenarios 🛠️ 1️⃣ Accidentally deleted the state file 😬👉 Always store state in a remote backend (e.g., S3 with DynamoDB for AWS) and turn on versioning.2️⃣ Two people running terraform apply at the same time👉 Enable state locking so you don’t overwrite each other’s work.3️⃣ terraform apply fails halfway👉 Work with smaller, safer change sets and use terraform plan first. Run terraform apply -refresh=true to sync the state.4️⃣ AWS API rate limit errors👉 Configure retries in your provider and stagger deployments to avoid hitting limits.5️⃣ Infrastructure drift (code vs actual cloud state) 👉 Run terraform plan regularly or set up automated drift checks in your CI/CD pipeline.6️⃣ Resource removed from code but still exists in cloud👉 Use terraform destroy -target or terraform state rm after confirming it’s safe.7️⃣ Provider/API behavior changes after upgrades👉 Test changes in staging first and pin provider versions to avoid surprises.8️⃣ Circular dependencies between modules👉 Break them apart using terraform_remote_state or separate Terraform stacks.9️⃣ Hitting AWS quota limits👉 Keep an eye on quotas and request increases before scaling events.🔟 Lost access to remote backend👉 Document access procedures and keep secure backups of state files.#Terraform

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When Kubernetes breaks, most teams go straight to Grafana.We open a terminal and run these 9 commands.Here’s the 9 command 𝐂𝐡𝐞𝐚𝐭𝐬𝐡𝐞𝐞𝐭 that saves us every week.1. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐠𝐞𝐭 𝐞𝐯𝐞𝐧𝐭𝐬 --𝐬𝐨𝐫𝐭-𝐛𝐲=.𝐦𝐞𝐭𝐚𝐝𝐚𝐭𝐚.𝐜𝐫𝐞𝐚𝐭𝐢𝐨𝐧𝐓𝐢𝐦𝐞𝐬𝐭𝐚𝐦𝐩”Your first stop. 90% of clues are hidden in event timing.Not in logs. Not in metrics. Right here.2. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐝𝐞𝐬𝐜𝐫𝐢𝐛𝐞 𝐩𝐨𝐝 <𝐩𝐨𝐝-𝐧𝐚𝐦𝐞>”The “why” behind the crash.We look for: OOMKilled, BackOff, FailedMount, ImagePull.3. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐠𝐞𝐭 𝐩𝐨𝐝𝐬 -𝐧 <𝐧𝐚𝐦𝐞𝐬𝐩𝐚𝐜𝐞> -𝐨 𝐰𝐢𝐝𝐞”Checks which node each pod’s on.Crucial when nodes are misbehaving silently.4. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐭𝐨𝐩 𝐩𝐨𝐝 --𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬”We’ve caught so many memory leaks just by watching container-level spikes.5. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐥𝐨𝐠𝐬 <𝐩𝐨𝐝> -𝐜 <𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫> --𝐩𝐫𝐞𝐯𝐢𝐨𝐮𝐬”The previous logs matter more than you think.Especially for crash loops, “--previous” is non-negotiable.6. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐠𝐞𝐭 𝐧𝐨𝐝𝐞𝐬 | 𝐠𝐫𝐞𝐩 𝐍𝐨𝐭𝐑𝐞𝐚𝐝𝐲”Don’t waste hours debugging pods when the node’s the issue.7. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐚𝐮𝐭𝐡 𝐜𝐚𝐧-𝐢”Works like magic when RBAC silently blocks access.(Especially in multi-team setups.)8. “𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐠𝐞𝐭 𝐞𝐧𝐝𝐩𝐨𝐢𝐧𝐭𝐬”Checks if services are even routing correctly.If this is empty, your pods might be fine. But your traffic’s going nowhere.9. “𝐬𝐭𝐞𝐫𝐧 <𝐩𝐨𝐝-𝐧𝐚𝐦𝐞-𝐩𝐚𝐭𝐭𝐞𝐫𝐧> 𝐨𝐫 𝐤𝐮𝐛𝐞𝐭𝐚𝐢𝐥”Real-time logs across multiple pods.Absolute time-saver when you’re chasing down distributed bugs.These 9 commands won’t solve every problem.But they’ll show you where to look (fast.)That’s 90% of the battle in Kubernetes.

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Grafana vs. Kibana: Which is Better for DevOps?🚀In the world of DevOps, monitoring and troubleshooting are key. Here's how Grafana and Kibana stack up: Grafana: - Best for real-time metrics and system monitoring. - Supports multiple data sources like Prometheus, and more. - Ideal for creating customizable, visually appealing dashboards. Kibana: - Focused on log analysis and troubleshooting. - Works seamlessly with Elasticsearch. - Great for filtering and drilling down into log data to identify issues. Which Should You Choose? - For infrastructure monitoring and performance metrics, go with Grafana. - For log analysis and debugging,Kibana is the winner. DevOps teams often use both tools together for comprehensive observability. #DevOps #Grafana #Kibana #Monitoring #CloudComputing #Observability

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𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐲𝐨𝐮 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐤𝐧𝐨𝐰 👀 1️⃣ 𝐌𝐨𝐝𝐮𝐥𝐚𝐫𝐢𝐭𝐲 – when writing code, make sure you follow the 𝐃𝐑𝐘 𝐩𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞 (don’t repeat yourself). Use modules for reusable code, so you don’t waste time setting up the same infrastructure multiple times.2️⃣ 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞𝐬 – don’t hardcode values directly into your Terraform code. Use variables instead, so you can easily change values in one place without having to search through your files to update them.3️⃣ 𝐂𝐫𝐞𝐝𝐞𝐧𝐭𝐢𝐚𝐥𝐬 – never hardcode sensitive information like your AWS access key or secret key. Use the 𝐞𝐱𝐩𝐨𝐫𝐭 command to store them in 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐯𝐚𝐫𝐢𝐚𝐛𝐥𝐞𝐬 instead. This way, they won’t be exposed in the Terraform state file after you run terraform apply.4️⃣ 𝐅𝐨𝐫𝐦𝐚𝐭𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 – run terraform fmt and terraform validate regularly. This keeps your code clean, consistent, and free of basic errors before applying changes.5️⃣ 𝐍𝐚𝐦𝐢𝐧𝐠 𝐂𝐨𝐧𝐯𝐞𝐧𝐭𝐢𝐨𝐧𝐬 – use clear and consistent naming for resources, variables, and modules. This makes your code easier to read, understand, and maintain over time.6️⃣ 𝐒𝐭𝐚𝐭𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 – always use a remote backend (like 𝐒𝟑 with 𝐃𝐲𝐧𝐚𝐦𝐨𝐃𝐁 for 𝐬𝐭𝐚𝐭𝐞 𝐥𝐨𝐜𝐤𝐢𝐧𝐠) to store your Terraform state file. This ensures your state is consistent, secure, and can be shared safely across your team.What other best practices would you include in this list? Leave it in the comments below 💬 #DevOps #Cloud #Terraform #TerraformBestPractices

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Elevating Monitoring with Prometheus & Grafana🚀📊🛠️Just wrapped up an in-depth journey into Prometheus and Grafana—two of the most powerful open-source tools shaping modern observability.From setting up scalable monitoring systems and writing PromQL queries to designing dynamic Grafana dashboards and configuring proactive alerting, this guide provided a full-stack approach to real-time infrastructure visibility.Key Highlights:✅ Time-series data modeling with Prometheus ✅ Custom dashboards & alerting in Grafana ✅ Exporters for system, Kubernetes, and app metrics ✅ Best practices for scaling, securing & maintaining production-grade setups.Monitoring isn’t just about uptime—it’s about insight, speed, and reliability. Grateful for the opportunity to level up my skills in this space! Let’s connect if you’re exploring observability, DevOps, or cloud-native tooling! #DevOps #Monitoring #Prometheus #Grafana #Observability #CloudNative #SRE #OpenSource ⚙️☁️🔍

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Workload Resources in Kubernetes → because Pods alone can’t survive in the wild. 🚀So, we have mastered the moody teenagers (Pods) of Kubernetes. You know their tantrums (CrashLoopBackOff) and their backstage crew (Init & Sidecar containers). But running individual Pods is like having a bunch of talented musicians without a band manager, a stage, or even a setlist. That's where Workload Resources like Deployments, Services, and ConfigMaps step in!Think of Kubernetes as a massive, futuristic concert venue, and your applications are the bands.1. The Tour Manager: Deployments & StatefulSets 🎤🎻You don't just hire a musician; you hire a manager to handle the entire show.Deployments: Your trusty Tour Manager. You tell it you need five performers on stage, and it ensures that number is always met. It gracefully handles updates (rolling out a new setlist) and can even roll back if the crowd hates the new songs.StatefulSets: The Orchestra Conductor. When every performer's identity and position matters—like with databases or message brokers—StatefulSets keep them in strict order. Pod-0, Pod-1, Pod-2... each has a unique role, ensuring your symphony runs perfectly without any random shuffling.2. The Road Crew: DaemonSets 🎚️Every stage needs a hardworking crew to set up the gear. DaemonSets are your Roadies. They ensure that critical tasks—like logging, monitoring, or security agents run on every single node, quietly getting the stage ready for the main act.3. The Special Guests: Jobs & CronJobs 🎟️Not every act is a headliner. Sometimes you need an opening act or a special guest. Jobs are your one-time Special Guests. They show up, perform their single song (a one-off task like a data migration), and then exit the stage.CronJobs are the Scheduled Opening Act. They perform on a set schedule, like a nightly database backup or a weekly report generation, ensuring the show is always ready for the next day.4. The Setlist & Backstage Passes: ConfigMaps & Secrets 🎶A rockstar is nothing without their material. ConfigMaps are the Lyrics & Setlist. They hold all the non-sensitive configuration data your app needs to perform—like which song to play or what to display on the big screen.Secrets are the Backstage Passes. They contain the sensitive stuff, like database passwords and API keys. You keep them encrypted and never hard-code them into your app, because you never know who might try to sneak in.5. The PA System: Services 🎙️A great show needs a great sound system. Services are your PA System. No matter which Pod is singing into which mic, the audience (your users) hears a consistent, clean sound. Services provide a stable, single access point, so traffic always finds its way to the right performers, even if they're constantly changing or scaling.#Kubernetes #KCNA #CloudNative #DevOps #WorkloadResources #LearningInPublic #SRE

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🚀 Sharing Important Documentation: Jenkins & SonarQube Integration 🚀I'm excited to share some helpful documentation for those working with Jenkins and SonarQube!These two tools are critical for continuous integration and continuous delivery (CI/CD) workflows. By combining Jenkins with SonarQube, you can automate code quality checks and ensure your projects are clean, secure, and maintainable.In this document, I cover:Setup instructionsConfiguration stepsBest practicesTroubleshooting tipsWhether you're a developer, a DevOps engineer, or just starting your CI/CD journey, this guide will help you integrate Jenkins with SonarQube smoothly!Feel free to reach out if you have any questions or need assistance. 💬#Jenkins #SonarQube #CICD #DevOps #Automation #SoftwareDevelopment #ContinuousIntegration #CodeQuality #LookingForJobChang #ImmediateJoiner #SearchingJob #DevOps #DevSecOps #SiteReliabilityEngineer #SRE #Sweden #TechJobs #ITJobs #JobSearch #HiringNow #JobHunt #JobOpening #CareerOpportunity #OpportunityKnocks #NewJob #JobSeeker #TechCareer #TechCommunity #JobPosting #ITCareer #TechTalent #CareerChange #DreamJob #TechLife #JobAlert #WorkInTech #EmploymentOpportunity #Recruiting #HR #TalentAcquisition #Headhunting #Staffing #RecruitmentAgency #JobRecruiter #JobPlacement #CareerTransition #JobApplication 🇸🇪

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Grafana Loki Architecture 🚀In this blog,You will learn the following.- What is Grafana Loki?- Grafana Loki Architecture- Grafana Loki Components- Loki Deployment Modes- Features of Grafana Loki- Difference Between Grafana Loki and EFK Stack- Example of How Chunks and Indexes are Stored in Loki𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gVqKjkqQDo you have any thoughts?Drop in the comment!- ---👉 Just last week, we have shared a detailed breakdown with a hands-on guide for this approach in my newsletter.→ Sign up here (100% free): https://bit.ly/dcube-nlLet's connect 1:1: https://lnkd.in/gsSBNa4r#devops #grafanaloki

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🏗️ State Management in Terraform — The Backbone of Infrastructure as CodeIn Terraform, state management is one of the most critical yet often overlooked aspects of Infrastructure as Code (IaC).It’s what allows Terraform to track, compare, and synchronize your real-world infrastructure with the configurations you define in code.💡 What Is Terraform State?Terraform stores information about your deployed infrastructure in a file called terraform.tfstate.This file acts as the source of truth, recording details like resource IDs, configurations, and dependencies.Without state, Terraform wouldn’t know:Which resources it created.What’s already deployed vs. what needs updating.How to perform incremental changes safely.🔹 Why State Management MattersChange TrackingTerraform uses the state file to determine what changed between your code and real infrastructure.Dependency MappingIt tracks relationships between resources (e.g., EC2 instances and Security Groups) for safe updates.Performance OptimizationReading state locally or remotely is faster than repeatedly querying the cloud provider’s APIs.Collaboration & ConsistencyRemote state backends (like S3 + DynamoDB) ensure teams don’t overwrite each other’s changes.⚙️ Best Practices for State ManagementUse Remote BackendsStore state in a remote backend like AWS S3, GCS, or Terraform Cloud for team collaboration and recovery.Enable State LockingUse DynamoDB (AWS) or Google Cloud Storage locking to prevent concurrent updates to the same state file.Encrypt State FilesAlways encrypt state files at rest (e.g., S3 SSE-KMS) and in transit to protect sensitive data like credentials.Version Control (Indirectly)Never check in terraform.tfstate to Git. Instead, use versioned S3 buckets or Terraform Cloud workspaces.Regular State ValidationRun terraform refresh and terraform plan to validate drift between the configuration and actual environment.#Terraform #IaC #InfrastructureAsCode #DevOps #CloudEngineering #AWS #GCP #Azure #TerraformState #StateManagement #Automation #CloudOps #DevSecOps #TerraformBestPractices #InfrastructureAutomation #CICD #CloudNative #Engineering #SRE #Ops

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Exploring Prometheus & Grafana for Kubernetes MonitoringToday I've been exploring the powerful combination of Prometheus and Grafana for Kubernetes monitoring.Key Insights:- Prometheus acts as the data collector and time-series database, while Grafana transforms this data into beautiful, actionable dashboards.Why This Matters:- Real-time monitoring is crucial for maintaining healthy Kubernetes clusters. The visualization helps quickly identify resource constraints and capacity planning needs.Future Scope I'm Excited About:1. Creating custom dashboards for application-specific metrics2. Exploring service mesh integration for deeper insights3. Implementing PromQL for advanced queryingAll of this monitoring setup was executed on my #homelab - because this is a place where I can #experiment and transform theory into #practice, without the fear of breaking #production.What monitoring setups are you using in your Kubernetes environments? Would love to hear your experiences.Special thanks to Saikiran Pinapathruni, and TrainWithShubham for their extraordinary support.#Kubernetes #DevOps #Monitoring #Cloud #AWS #tech #linux #Prometheus #Grafana #Docker

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Hello everyone,We continue improving our Terraform provider for Apache Superset: https://lnkd.in/eEBnGFtXIn this release, we have added new features:Resource: superset_dataset – define and manage datasets via TerraformResource: superset_meta_database – manage a meta database connection in Superset for cross-database queriesData Source: superset_datasets – query existing datasets to reuse in Terraform configsApache Superset is an open-source modern data exploration and visualization platform: https://lnkd.in/ejHuGZY2Terraform Registry: https://lnkd.in/eBUvgmvsGitHub: https://lnkd.in/eRQrEs3rI hope these updates will be useful.

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