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➡️ 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 🔬 Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. Below is a an overview of the Prometheus architecture: 🏮 Components: 🖥 Prometheus Server: - Core for collecting, storing, and querying time-series data. - It’s pull-based and scrapes metrics from targets at regular intervals. - Stores data in a local time-series database. ❤️ Metrics (Targets/Exporters): - Apps or services expose metrics. - Prometheus scrapes metrics from these targets. 📶 Data Model: - Time-series data with metric names and labels. - Example: `http_requests_total{method="GET", status="200"}`. ⚠️ PromQL: - Query language for time-series data. - Allows filtering, grouping, and math operations on metrics. ⚠️ Alertmanager: - Handles alerts from Prometheus. - Manages notifications and integrates with third-party channels. ☁️ Storage: - Uses local on-disk storage. - Data retention policies. - Data is organized in blocks and compacted over time. 🏮 Workflow: 🌐 Configuration: - Targets and scrape intervals defined in Prometheus config files. - Relabeling allows modifying or filtering metrics before storage. 📚 Scraping: - Prometheus Server scrapes metrics from configured targets. - Targets expose metrics typically at /metrics endpoint. ☁️ Storage: - Scraped metrics stored in the local time-series database. - Data organized by metric name and labels. 📚 Querying: - Users utilize PromQL to query and analyze stored metrics. - Grafana or Prometheus's UI visualizes query results. ⚠️ Alerting: - Prometheus evaluates alerting rules based on queries. - Alerts sent to Alertmanager if conditions are met. ⚠️ Alertmanager Handling: - Alertmanager receives alerts and manages their lifecycle. - Handles deduplication, grouping, and sends notifications to configured channels. ❤️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

🔤 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞 𝐘𝐨𝐮𝐫 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐰𝐢𝐭𝐡 𝐉𝐞𝐧𝐤𝐢𝐧𝐬 Jenkins is a powerful tool for revolutionizing software delivery, not merely a CI/CD tool. 🔤Here's a fresh take on using Jenkins efficiently if you want to speed up deployments and beat the competition. 1️⃣. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐌𝐮𝐥𝐭𝐢-𝐄𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 Tired of manually configuring environments? Jenkins pipelines allow you to set up workflows for multi-environment deployments (e.g., dev, staging, production) with ease. • Use parameterized builds to dynamically deploy to specific environments. • Leverage environment-specific configurations using tools like Ansible or Helm. 2️⃣. 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐅𝐞𝐚𝐭𝐮𝐫𝐞-𝐁𝐚𝐬𝐞𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐁𝐥𝐮𝐞-𝐆𝐫𝐞𝐞𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬 Jenkins simplifies feature-based rollouts using Blue-Green Deployment Pipelines: • Create two identical environments (blue and green). • Use Jenkins to seamlessly route traffic to the “green” environment once the new version is stable. 3️⃣. 𝐄𝐦𝐩𝐨𝐰𝐞𝐫 𝐓𝐞𝐚𝐦𝐬 𝐰𝐢𝐭𝐡 𝐒𝐞𝐥𝐟-𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 Stop the bottleneck of centralized deployment processes. •Use Jenkins with developer portals like Backstage to enable self-service deployments for teams. •Integrate RBAC (Role-Based Access Control) to ensure that only authorized users can trigger specific pipelines. 4️⃣. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐇𝐞𝐚𝐥𝐭𝐡 𝐢𝐧 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞 Don’t wait for failures to escalate-track them in real time. •Integrate Jenkins with monitoring tools like Prometheus, Grafana, or Splunk to visualize pipeline metrics. •Use custom notifications (Slack, email, or Teams) to alert teams about deployment performance or anomalies. 5️⃣. 𝐔𝐬𝐞 𝐉𝐞𝐧𝐤𝐢𝐧𝐬 𝐟𝐨𝐫 𝐏𝐫𝐨𝐠𝐫𝐞𝐬𝐬𝐢𝐯𝐞 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 Implement modern delivery techniques like: • 𝐂𝐚𝐧𝐚𝐫𝐲 𝐑𝐞𝐥𝐞𝐚𝐬𝐞𝐬: Gradually expose new features to a subset of users and expand after validation. •𝐂𝐚𝐧𝐚𝐫𝐲 𝐑𝐞𝐥𝐞𝐚𝐬𝐞𝐬:Manage feature visibility dynamically during or after deployment. 6️⃣. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫-𝐍𝐚𝐭𝐢𝐯𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐉𝐞𝐧𝐤𝐢𝐧𝐬 Accelerate containerized application deployment by integrating Jenkins with Kubernetes and Docker. •Automate container builds and push them to registries like Docker Hub or Amazon ECR. •Deploy containers directly to Kubernetes clusters using plugins like Kubernetes Continuous Deploy. 7️⃣. 𝐃𝐫𝐢𝐯𝐞 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐆𝐢𝐭𝐎𝐩𝐬 Jenkins can supercharge GitOps workflows by syncing deployments with code repositories. •Trigger pipelines based on Git commits or pull requests. •Validate changes automatically through linting, testing, and security scans. 🔤 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

The general process of using Docker. 🐬 Give it a read. ⚡️𝐃𝐨 𝐲𝐨𝐮 𝐤𝐧𝐨𝐰? Docker emerged from dotCloud, a Platform-as-a-Service (PaaS) company. It started as an internal project by Solomon Hykes in France, aimed at simplifying application deployment. 2013 => Docker was first unveiled at PyCon. It quickly gained popularity due to its innovative approach to containerization. Docker was released as open-source in March 2013. ⚡️𝐃𝐫𝐢𝐯𝐢𝐧𝐠 𝐅𝐨𝐫𝐜𝐞𝐬 - ◾️ Developer Pain Points => developers struggled with inconsistent application environments across different stages ◾️ Operational Efficiency ◾️ Cloud Adoption Alright, 🔖 Let's understand the 𝐃𝐨𝐜𝐤𝐞𝐫 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 - [1.] Develop ◾️ Write your application code. [2.] Dockerfile ◾️ Create a Dockerfile that defines the environment and dependencies for your application. [3.] Build Image ◾️ Use docker build to create a Docker image from your Dockerfile. [4.] Run Container ◾️ Use docker run to launch a container from your image. ◾️ The container is an isolated instance of your application. [5.] Test ◾️ Test your application within the container. ◾️ If you make changes, rebuild the image and recreate the container. [6.] Push => This is Optional ◾️ Use docker push to share your image on a registry (e.g. Docker Hub). [7.] Pull => This is Optional ◾️ Others can use docker pull to download your image and run your application in their own environments. 📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs