There’s this persistent concern in the industry I've run across over my career: while it’s fine to automatically deploy to pre-production environments, production deployments should always be manual. I get it—many bright professionals who’ve been burned by bad deployments feel this way. I know how crucial stable infrastructure is—my sleep depends on it too. But here’s why you should deploy with CI/CD. Yes, even to production. 1. Practice Makes Perfect: Automation codifies your team’s collective knowledge, running consistent processes through all environments. This isn’t just for pre-production—it’s crucial for production too. The errors you come across in lower environments are fixed as you move up through the environments. 2. Reducing Human Errors: When you manually skip the CI/CD trigger, you risk missing critical steps. Have you ever forgotten to generate API documentation or update config files? CI/CD ensures nothing is overlooked. 3. Building Confidence: If you’re still concerned, consider starting with a dry-run job. It shows what changes would be made without actually deploying, giving you a confidence boost. You can also implement a manual approval step for production, where everything is prepared, but the final action requires your green light. The goal? To make full automation so reliable that you won’t need that manual approval. Run it this way until you’re confident your process works—then let CI/CD do what it’s designed to do: make deployments safer, more reliable, and stress-free.
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1. Blue-Green Deployment 🌊🟢 Description: Maintain two environments: Blue (current) and Green (new). Deploy to Green and switch traffic when ready. Advantages: Minimal user impact 🌟 Easy rollback 🔄 Considerations: Requires duplicate infrastructure 💰 2. Canary Releases 🦠 Description: Roll out the new version to a small segment of users first, then gradually expand. Advantages: Early detection of issues 🔍 Easier rollback if needed 🔄 Considerations: Needs strong monitoring 📊 3. Rolling Deployments 🔄 Description: Gradually replace the old version with the new one across servers or instances. Advantages: Reduces full-scale failure risk ⚠️ No need for duplicate infrastructure 🏷️ Considerations: Requires handling version compatibility 🤔 4. Feature Flags 🚩 Description: Deploy new code with features turned off, then enable them selectively. Advantages: Controlled feature release 🎛️ Allows testing in production 🚀 Considerations: Adds code complexity 🔍 5. Dark Launches 🌑 Description: Deploy new features hidden from users, then gradually reveal them. Advantages: Test in production without user impact 🕵️♂️ Can be combined with feature flags 🎯 Considerations: Adds deployment complexity ⚙️ 6. A/B Testing ⚖️ Description: Deploy different versions to different user segments and compare results. Advantages: Data-driven insights 📈 Reduces risk by testing before full rollout 🧪 Considerations: Requires careful planning and metrics 📉 7. Immutable Infrastructure 🏗️ Description: Deploy new versions to new instances rather than updating existing ones. Advantages: Reduces risks with live servers ⚠️ Simplifies rollbacks 🔄 Considerations: Requires rapid provisioning and scaling 🚀 Best Practices for Zero Downtime Deployments: Automate 🤖: Use CI/CD pipelines for deployment, testing, and rollbacks. Monitor 📊: Implement robust monitoring and alerting systems. Test 🧪: Test thoroughly in staging environments. Rollback Plan 🔄: Have a clear rollback plan ready. Communication 📢: Keep stakeholders informed about deployment plans and impacts. By choosing the right strategy and following these best practices, you can achieve smooth and uninterrupted deployments. 🚀
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Learn how self-healing IT automation can revolutionize your operations and streamline incident resolution.
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Is your engineering team still tied up with post-development deployments? We've seen that performing product deployments at client sites can be quite time-consuming due to their IT approval processes, which often restrict external personnel from making deployments. Furthermore, clients have their own scheduling priorities for these deployments, making it less than ideal to keep your engineering team waiting. Let’s work together to tackle this challenge and enable your clients to handle deployments on their own at their convenience, reaching out to you only for critical issues. #softwaredeployments, #productinstallations, #systemintegrations, #technicaldocumentation, #processdocumentation, #knowledgebase
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🚨 Production incidents are inevitable. As a software engineering leader, having an outage or performance issues is your biggest nightmare. To the outside world, it might seem like software is perfect and never fails, but there's no such thing as 100% uptime. 🛠️ Why are incidents inevitable? Human error and third-party software are common culprits. Even the biggest companies have production incidents, showing that no one is immune. As a software engineering leader, your responsibility is to minimize these risks and be prepared for when incidents do occur. 📊 Proactivity is key. Implementing comprehensive monitoring and alerting systems, having a clear incident response plan, and continuously training your team can make a significant difference. When downtime happens, these preparations enable you to minimize the outage and its impact. 💡 The cost of a production incident is hard to measure but can be significant, affecting brand positivity and customer trust. By being prepared and having the right processes in place, you can mitigate these risks and maintain your software's reliability. 🤔 How much time and money should you invest in incident management? Share your thoughts in the comments below! #SoftwareEngineering #DevOps #IncidentManagement #TechLeadership #Uptime #SoftwareReliability #BrandTrust #ProactiveManagement
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Should you integrate Fault Injection with deployment tools? While integrating with deployment tools can be a high-leverage way for teams to drive acceptance of Fault Injection testing, it's worth calling out the trade-offs associated with doing so. The cause of fragility is not always deployments to the code in question. Changes to dependencies, consumers, infrastructure, and even the network itself, can all undermine resilience mechanisms. Systems which do not experience constant deployments (e.g. less frequently than once a week) may miss serious regressions if they rely solely on deployment mechanisms to drive their Fault Injection testing. Additionally, the goal of CI/CD systems is to focus on delivering software quickly. For many systems, running a complete suite of FI tests can take hours to complete. This can be at odds with the goals and purpose of CI/CD systems. Depending on the organization, some teams may find it preferable to instead run these sorts of Validation tests on a weekly cron, and only run the most critical tests as part of deployments. This allows them to retain confidence that regressions haven't slipped through without negatively impacting their development goals. Read on in our full post: https://ow.ly/WInq50QJuIB
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Learn how self-healing IT automation can revolutionize your operations and streamline incident resolution.
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Learn how self-healing IT automation can revolutionize your operations and streamline incident resolution.
Jumpstart your self-healing IT with BigPanda and Ansible
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Learn how self-healing IT automation can revolutionize your operations and streamline incident resolution.
Jumpstart your self-healing IT with BigPanda and Ansible
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Learn how self-healing IT automation can revolutionize your operations and streamline incident resolution.
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Engineering Lead | Full-Stack, SaaS, CI/CD, Data in Motion, Agile
3moAgreed! Also blue/green deploys with some sanity checks go a very long way.