Disaster Recovery Planning for Engineering Projects

The recent news on AWS center in the Middle East going down because of the war made me relive my experience decades ago! I once helped build what we proudly called a best-in-class disaster recovery architecture. We did everything right—on paper. ✔️ Business Impact Analysis done ✔️ RTO & RPO agreed with stakeholders ✔️ Sophisticated tools deployed ✔️ DR site fully provisioned We were confident. Almost too confident and then came the day that tested everything ! A dual power supply failure hit our primary data center. Within minutes, 300+ servers went down abruptly. What followed was worse than downtime: Critical application databases got corrupted AND THEN The DR site also got corrupted ! Real-time transactions came to a complete standstill. With every passing hour, we lost millions of dollars in revenue. In that moment, all our architecture diagrams, tools, and planning meant one thing: NOTHING —because the system didn’t recover !!! What this experience taught me: 1) Testing isn’t real until it’s brutal Table-top simulations give comfort. Full-scale failover drills expose truth. Test like it’s already failing: -Simulate real load -Introduce chaos scenarios -Assume components will fail unexpectedly 2) DR is not a technology problem—it’s a systems problem We focused heavily on tools. We underestimated dependencies. Ensure: -End-to-end recovery (infra + app + data integrity) -Isolation between primary and DR (to avoid cascade failures) -Backup validation, not just backup completion 3) Communication is your real recovery engine In crisis, confusion spreads faster than outages. Build: -Clear SOPs for business continuity -Pre-defined escalation paths -Regular cross-team drills (not just IT—include business teams) 4) Leadership presence changes outcomes War rooms are intense. Fatigue, panic, and noise creep in. As a tech leader: -Your presence brings calm -Your clarity drives prioritization -Your energy keeps teams going Sometimes, leadership is less about answers… and more about Stability 5) Assume your DR will fail—and design for that This was the hardest lesson. Build layers: - Immutable backups - Offline recovery options -“Last resort” recovery playbooks Because resilience is not about one backup plan. It’s about what happens when that backup plan fails... Have you ever seen a #DR plan fail in real life? How often do you run full-scale disaster recovery drills? What’s the one thing most organizations still get wrong about resilience? Curious to hear real experiences—those are always more valuable than frameworks. #DR #disasterrecovery #drill #test #BCP #leadership #technology #resilience

Lived through enough disasters to know this truth: Production is where optimism goes to die. Deployments WILL break. Systems WILL crash. You NEED to have a Disaster Recovery plan prepped. Most organizations spend $$ on fancy tech stacks but don’t realize how critical DR really is until something goes wrong. And that’s where the trouble starts. Here are a few pain points I see decision-makers miss: 👉 𝗕𝗮𝗰𝗸𝘂𝗽𝘀 ≠ 𝗗𝗶𝘀𝗮𝘀𝘁𝗲𝗿 𝗥𝗲𝗰𝗼𝘃𝗲𝗿𝘆. Sure, you’ve got backups—but what about your Recovery Point Objective (RPO)? How much data are you actually okay losing? Or your Recovery Time Objective (RTO)—how long can you afford to be down? 👉 "𝗦𝗲𝘁 𝗜𝘁 𝗮𝗻𝗱 𝗙𝗼𝗿𝗴𝗲𝘁 𝗜𝘁” 𝗗𝗥 𝗣𝗹𝗮𝗻𝘀. The app changes, infrastructure evolves, but you’re running on a DR plan you wrote two years ago? 👉 𝗜𝗱𝗹𝗲 𝗕𝗮𝗰𝗸𝘂𝗽 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀. Most teams have “hot spares” (idle infrastructure) sitting around waiting for the next big disaster. Disasters aren’t IF, they’re WHEN. Build DR testing into your CI/CD pipeline. If you’re shipping code daily, your recovery strategy should be just as active. Turn those idle backups into active DevOps workspaces. Load test them, stress test them, break them before production does. Stop relying on manual backups or failovers. Tools like AWS Backup, Route 53, and Elastic Load Balancers exist for a reason. Automate your snapshots, automate your failovers, automate 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. Don’t wait for a disaster to test your DR strategy. Test it now, fail fast, and fix faster. What about you—what’s your top DR strategy tip? 💬 #DisasterRecovery #CloudComputing #DevOps #Infrastructure Zelar - Secure and innovate your cloud-native journey. Follow me for insights on DevOps and tech innovation.

In a recent discussion, the topic of event response in process environments came up. The group was a mix of IT, OT, and engineering roles and backgrounds. There was good input, with some 'IT-centric' perspectives, based on existing IRPs in place, focused on network security, isolation, segmentation, logging, SIEM, SOAR, EDR/MDR, SOC, IDS, IPS, etc. We widened the aperture, looking beyond Ethernet-connected devices like PLCs, HMIs, and Windows-based workstations and servers, addressing vulnerabilities and failures within the physical layer—field devices, instrumentation, and serial and industrial protocols (Modbus RTU, RS-485, HART/WirelessHART, PROFIBUS, and PROFINET, etc.) integral to safe and reliable process control. The significance of these layers can be common shortcomings in existing IRPs where security, IT, OT teams, asset & process owners, must converge in development of adequate response planning. Field devices (transmitters, actuators, sensors, and valves) and serial protocols represent the primary interface between digital control systems and the physical process. A failure or compromise at this level may not be detectable by conventional IT cybersecurity monitoring tools, more importantly can have cascading impact that takes place rapidly, degrading safety and reliability proportionately. Field-level anomalies frequently trigger, as mentioned previously, cascading impacts across multiple system layers. For instance, a malfunctioning RTD sensor feeding incorrect temperature values into a PLC could propagate through PID loops, triggering alarms or auto-shutdowns across unrelated systems. IRPs should consider PHA, SIS, process flows/lockouts, fail-safe, restoration sequencing/timing of process state. Resilience requires acknowledging the physical realities of field-level instrumentation, integrating vendor or component-specific tools and diagnostics, and aligning incident response with the deterministic and safety-critical nature of industrial processes. By addressing these gaps, engineering personnel, asset and process owners, in partnership with IT and security recovery teams ensure faster recovery, safety, productivity, and reliability, in the face of both cyber and physical disruptions.

$𝟵,𝟬𝟬𝟬. 𝗧𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝗰𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗶𝗻𝘂𝘁𝗲 𝘆𝗼𝘂 𝗷𝘂𝘀𝘁 𝘄𝗮𝘀𝘁𝗲𝗱 𝘀𝘁𝗮𝗿𝗶𝗻𝗴 𝗮𝘁 "𝟱𝟬𝟬 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗦𝗲𝗿𝘃𝗲𝗿 𝗘𝗿𝗿𝗼𝗿." For the Fortune 500? The damage multiplies fast. But here's what really hurts: 𝘁𝗵𝗲 𝘁𝗿𝘂𝘀𝘁. I'm looking at my team right now. Brilliant engineers who should be shipping features. Instead, we're writing personal apology emails to customers. X is down. OpenAI is down. We were dark too. Not because our code failed. Not because our infrastructure broke. But because the modern web runs on a single backbone and when Cloudflare hiccups, we all flatline. 𝗛𝗲𝗿𝗲'𝘀 𝘁𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘁𝗿𝘂𝘁𝗵: We promised 99.999% uptime. But we built that promise on infrastructure we don't control. This is where the "Modern Tech Stack" mythology breaks down. We architect for perfection. We obsess over preventing the crash. 𝗪𝗲'𝗿𝗲 𝘀𝗼𝗹𝘃𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. In distributed systems, failure isn't a risk, it's a mathematical certainty. The question isn't if your CDN goes down. It's what happens when it does. 𝗦𝗼 𝘄𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 "𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝗰𝗵𝗮𝗼𝘀" 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗼𝗼𝗸 𝗹𝗶𝗸𝗲? → Multi-CDN failover (Cloudflare + Fastly + AWS CloudFront)  → Circuit breakers that detect and route around failures automatically  → Graceful degradation (serve cached static content when APIs fail)  → Geographic redundancy across providers, not just regions  → Status pages that update before customers start emailing you This isn't theoretical. Companies like Netflix and Stripe do this. They assume failure and code around it. 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗹𝗲𝗮𝗱𝗲𝗿𝘀: Does your disaster recovery plan assume AWS/Cloudflare/Azure stay online, or does it work when they don't? #TechLeadership #SiteReliability #DevOps #CloudInfrastructure #EngineeringExcellence

🧪💻 Scenario Planning for IT DR: Preparing for the Unthinkable 💻🧪 Now with real-world examples Hope is not a strategy. In today’s volatile environment, IT Disaster Recovery (IT DR) must go beyond static plans — it requires scenario planning and stress testing to prepare for the truly unexpected. 🔍 What Is Scenario Planning in IT DR? It’s the process of modeling potential disaster events — from cyberattacks to natural disasters — and testing how your systems, teams, and vendors would respond. 📊 Gartner reports that only 40% of organizations conduct regular scenario-based DR testing — yet those that do recover 3x faster from major disruptions. ⚠️ Why It Matters * Disasters aren’t predictable — but your response can be. * Complex systems fail in complex ways — scenario planning reveals hidden dependencies. * Stakeholders need confidence — testing builds trust in your recovery capabilities. 🧪 Real-World Scenario Planning Examples 🔹 Case Study: Capital One After a major cloud misconfiguration incident in 2019, Capital One revamped its IT DR strategy to include scenario-based simulations for cloud failures and data breaches. Their new model includes automated rollback protocols and cross-team incident drills. 🔹 Case Study: FedEx FedEx uses scenario planning to simulate regional outages, cyberattacks, and supply chain disruptions. Their IT DR team runs quarterly stress tests across global hubs, ensuring continuity even during peak logistics seasons. 🔹 Case Study: NHS (UK) The UK’s National Health Service implemented scenario planning after a ransomware attack in 2017. Their updated DR strategy includes simulations for hospital system outages, patient data breaches, and coordinated multi-agency responses. 🧠 How to Get Started ✅ Identify high-impact, low-probability events ✅ Build response playbooks for each scenario ✅ Simulate failures across systems, teams, and vendors ✅ Document lessons learned and update your DR strategy 🔁 Repeat regularly — resilience is a process, not a one-time event. 💡 Strategic Takeaway Scenario planning isn’t about predicting the future — it’s about being ready for it. The more you test, the more you learn. And the more you learn, the faster you recover. 👇 Is your IT DR strategy built for the unthinkable? #DisasterRecovery #BusinessContinuity #ResilienceStrategy

Most Azure environments I see have no real disaster recovery plan. Not because people don't care — because they don't know where to start. Here's the framework I use: 𝟭. Start with business requirements What's your RTO? Your RPO? What does downtime actually cost the business per hour? 𝟮. Define your technical requirements Now translate those business answers into technical constraints. 𝟯. Break down every service component Don't think of your environment as a single thing. Think about: → Virtual Machines → Networking → Storage → App Services → SQL Databases Each one needs its own DR consideration. 𝟰. Check zone-level protection Are you protected if an Azure Availability Zone goes down? 𝟱. Check regional-level protection Are you protected if an entire Azure region goes down? Then work backwards. What gaps do you have? What do you need to fix to become fully protected? Most people only find out they weren't protected when it's too late. Don't be that person. ♻️ Repost if this would help someone on your team. #Azure #DisasterRecovery #CloudArchitecture #MicrosoftAzure #BusinessContinuity #AVD #AzureVMs

⚠️Your Disaster Recovery Strategy Isn’t Ready—Until It Follows These Azure Principle ⚠️ Designing for resiliency is no longer optional—it's a fundamental requirement for mission‑critical workloads. The latest guidance in the Azure Well-Architected Framework highlights architectural strategies to help teams prepare for, respond to, and recover from disruptions with clarity and precision. Here are some powerful takeaways from the page: 🚨 Plan for the unexpected Understand key terminology, define recovery objectives (RPO/RTO), and classify workloads by criticality so your DR strategy matches business needs. 🏗️ Design for redundancy Leverage availability zones, region pairs, and multi‑region architectures to eliminate single points of failure. 🔁 Enable recovery flows Adopt health modeling, incident management planning, and transient fault handling to ensure your system gracefully recovers during adverse events. 🛡️ Use built‑in Azure resilience services From Azure Backup to Front Door, Traffic Manager, and Cosmos DB global distribution—Azure provides the building blocks for predictable failover and restoration. ⚙️ Optimize continuously A disaster recovery plan is not “set and forget.” Continuously test, validate, and improve your DR posture to stay ready for real‑world disruptions. https://lnkd.in/ggUBhmJx #Azure #AzureTipOfTheDay #AzureMissionCritical #AzureWellArchitectedFramework #CloudArchitecture #DisasterRecovery #Resiliency #CloudReliability #AzureGovernance #AzureBestPractices

Following the recent AWS N. Virginia outage, it’s a good reminder to ask ourselves: How resilient are our systems, really? When designing disaster recovery, it all starts with two fundamentals: ✅ RTO (Recovery Time Objective): how long can we afford to be down? ✅ RPO (Recovery Point Objective): how much data can we afford to lose? Everything else flows from there. Once these are defined, I look at what we’re protecting against 👇 1️⃣ Provider or On-Prem Downtime Whether your data center goes offline or a cloud provider faces a regional issue, you’ll need redundancy across environments. That might mean multi-cloud or hybrid setups sometimes active/passive, sometimes active/active with live data synchronization to keep things running. 2️⃣ Region failure within a provider Handled through multi-region architecture, ensuring near real-time data sync. The choice between active/active and active/passive depends on performance, latency, and cost trade-offs. 3️⃣ Availability Zone failure Managed with multi-AZ redundancy, allowing systems to fail over automatically without manual intervention. Throughout all of this, Infrastructure as Code (IaC) is the backbone ensuring environments are consistent, reproducible, and recoverable across regions, providers, or even between on-prem and cloud. Ultimately, it’s about finding the right balance between resilience, cost, and complexity, aligned with your business priorities. 💬 How do you approach disaster recovery in your setup ? do you lean more toward multi-region, multi-cloud, or hybrid resilience?

Disaster Recovery (DR) strategies on AWS. 1: Set Up Your Primary Region (Normal Operations) This is your main, live environment where all traffic flows under normal circumstances. Deploy Core Compute: Create an  (ASG) for your Web and App Servers (typically on EC2 or containers). Place these behind an  (ELB) to distribute traffic. Set Up Primary DB & Storage: Use  RDS in a Multi-AZ deployment. This provides high availability within the primary region by maintaining a synchronous standby replica in a different (AZ). Use  S3 for static assets, uploads, and backups. Configure automated Data Backups (RDS snapshots, EBS snapshots) and store them in S3. Implement Governance & Monitoring: Use IAM for security and access control. Set up Monitoring with CloudWatch for alarms and dashboards. 2: Choose DR Strategy & Set Up the DR Region Select a secondary Region for disaster recovery. The setup varies based on target (RTO) and (RPO). Strategy A: Pilot Light (Lowest Cost, Slowest Recovery) Replicate only the most critical core elements to the DR region and keep them in an idle state. Database: Set up asynchronous cross-region DB replication (RDS Read Replica, database-native replication). Core Resources: Prepare minimal versions of core infrastructure (like RDS instances, key EC2 AMIs) but don't run them. State: The environment is Idle until a disaster is declared. Strategy B: Warm Standby (Balanced Cost & Recovery Time) Maintain a scaled-down, functional version of your full stack in the DR region. Database: Maintain synchronous or frequent async backups/replicas. Compute: Run a scaled-down version of App Servers (e.g., minimal instance size, fewer nodes). Storage: Enable S3 Replication (Cross-Region Replication - CRR) to keep data synced. State: The system is running and can be quickly scaled up to handle production traffic. Strategy C: Active-Active (Highest Cost, Highest Resilience) Run a full, production-scale stack in both regions. Traffic: Use Route 53 (with geolocation/latency routing) or a Global Load Balancer to distribute Live Traffic to both regions. Compute: Have an Auto Scaling Group & Load Balancer in the DR region. Data: Implement bi-directional App Data Sync (requires careful architectural design to handle conflicts). This is a true Multi-Region active deployment. State: Both regions are active. 3: Implement Cross-Region Enablers These components are crucial for making any DR strategy work. Data Replication: Enable Cross-Region Replication for all critical data stores: S3 CRR for object storage. Failover Mechanism: Configure DNS Failover with Route 53. Set up health checks on your primary region endpoints. Automation: Develop and store Automated Recovery Scripts (using Lambda, Step Functions, or CloudFormation). Security & Identity: Extend IAM & Security policies to the DR region. 4: Operational Principles (The "How" Matters) Treat DR as Day-1 Architecture: Design it from the start, don't add it later. Understand RTO & RPO: