Software Development Lifecycle In Engineering

Git is a distributed version control system that tracks changes in your code over time. It allows multiple developers to work on the same project without stepping on each other's toes. Key Git Commands: 1. git init    Initializes a new Git repository. It's like saying, "Hey Git, start keeping an eye on this project!" 2. git clone [url]    Creates a copy of a remote repository on your local machine. It's how you download a project to start contributing. 3. git add [file]    Stages changes for commit. Think of it as putting your changes in a shopping cart before checkout. 4. git commit -m "[message]"    Commits your staged changes with a descriptive message. This is like taking a snapshot of your project at a specific point in time. 5. git push    Uploads your committed changes to a remote repository. Share your work with the world (or at least your team)! 6. git pull    Fetches changes from a remote repository and merges them into your current branch. Keep your local copy up-to-date. 7. git branch    Lists all local branches. Useful for seeing what feature branches you have. 8. git checkout -b [branch-name]    Creates a new branch and switches to it. Perfect for working on new features without affecting the main code. 9. git merge [branch]    Combines the specified branch with the current branch. This is how you integrate your new feature back into the main code. 10. git status    Shows the status of changes as untracked, modified, or staged. Your project's health check! 11. git log    Displays a log of all commits. Like a time machine for your code. 12. git stash    Temporarily shelves changes you've made to your working copy so you can work on something else, and then come back and re-apply them later. Pro Tips: - Use meaningful commit messages. Future you (and your teammates) will thank you. - Commit often. Small, frequent commits are easier to manage than big, infrequent ones. - Use branches for new features or experiments. Keep your main branch clean and stable. - Always pull before you push to avoid conflicts. Whether you're a seasoned developer or just starting out, mastering Git is crucial in today's collaborative coding environment. It's not just about tracking changes; it's about streamlining workflows, facilitating collaboration, and maintaining code integrity. What's your favorite Git workflow trick?

✅ Quality Management System (QMS) Components & Key Industry Concepts A QMS is a structured framework used by organizations to ensure that their products or services consistently meet customer and regulatory requirements. A well-implemented QMS fosters continuous improvement, operational efficiency, and enhanced customer satisfaction. 🔹 QMS Core Components 1. Risk Management Identify, assess, and mitigate risks that could impact product quality or safety. Tools: Risk Assessments, FMEA, SWOT Analysis 2. Deviation Management Detect and handle any deviations from standard operating procedures or quality expectations. Tools: Deviation Reports, Root Cause Analysis, Corrective Action Plans 3. Equipment Management Maintain, calibrate, and qualify equipment to ensure reliable and accurate performance. Tools: Maintenance Logs, Calibration Records, Qualification Protocols 4. Document Management Control creation, revision, distribution, and archiving of critical quality documents (SOPs, policies, etc.). Tools: Document Control Systems, SOP Templates, Electronic Record Systems 5. Audits & Inspections Conduct internal and external audits to ensure compliance with quality standards and regulatory requirements. Tools: Audit Checklists, Inspection Reports, Compliance Dashboards 6. CAPA Management Address root causes of nonconformities and implement preventive measures to avoid recurrence. Tools: CAPA Forms, 5 Whys, Fishbone Diagrams 7. Supplier Management Qualify, monitor, and evaluate suppliers to ensure they meet quality expectations. Tools: Supplier Audits, Qualification Protocols, Performance Scorecards 8. Training Management Ensure employees are trained, competent, and aware of QMS responsibilities. Tools: Training Curricula, LMS, Competency Evaluations 📘 Keywords & Industry Concepts 1. Quality Assurance (QA) A process-oriented approach focused on preventing defects by ensuring quality is embedded in every step. 2. Quality Control (QC) A product-focused method involving testing and inspections to detect defects. 3. Lean Manufacturing A production philosophy aimed at reducing waste and optimizing processes without compromising value. 4. Six Sigma (DMAIC) A methodology for process improvement through a structured five-step approach: • Define, Measure, Analyze, Improve, Control 5. 5S Methodology A workplace organization system: • Sort, Set in Order, Shine, Standardize, Sustain 6. ISO 9001 An international standard specifying QMS requirements to ensure consistent product/service quality and continual improvement. 7. FMEA A risk analysis technique used to identify and prioritize potential failure modes and their effects. 8. PDCA (Plan-Do-Check-Act) A cycle for continuous improvement and iterative process enhancement. 9. Total Quality Management (TQM) An organization-wide philosophy where all employees participate in improving processes, products, and services.

#From raw materials to finished product—as handled by Quality Control (QC) and Quality Assurance (QA): 1. Raw Materials Testing (QC Stage) Sampling: Raw materials (e.g., APIs, excipients) are sampled as soon as they arrive. ✓Testing: QC analysts perform tests like: =Identification (FTIR, UV-Vis, HPLC) =Purity and potency (Titration, HPLC, GC) =Microbial limits (for certain materials) #Approval/Quarantine: If results meet specifications, the material is released for production; otherwise, it's quarantined or rejected. 2. In-Process Testing (QC Stage) ✓During manufacturing, QC monitors the production steps to ensure everything is within control: =pH, temperature, and reaction times =Tablet hardness, weight, and friability (in solid forms) =Viscosity or clarity (in liquids) ✓These checks help prevent deviations before the final product is made. 3. Finished Product Testing (QC Stage) ✓After production, the final product undergoes =Assay (to check active content) =Dissolution (for tablets/capsules) =Sterility/microbial testing (for injectables/liquids) =Uniformity and physical appearance ✓Results are recorded in a Certificate of Analysis (CoA). 4. Documentation and Review (QA Stage) ✓QA reviews all QC data and batch production records to verify: =Compliance with Good Manufacturing Practices (GMP) =No deviations or out-of-spec results =All procedures were followed correctly ✓QA also ensures traceability and data integrity. 5. Final Product Release (QA Decision) ✓QA has the final say on whether a batch can be: =Released to the market =Held for further investigation =Rejected due to non-compliance

90% of startups don’t fail because of: Bad marketing, a weak team, or even a poor product. They fail because they lack a repeatable decision-making process. Here’s the framework I use to make better, faster decisions in business. I call it “The Iteration Loop.” It’s a structured way to identify what’s working, what’s broken, and what to do next, without getting stuck in endless guesswork. It gives you a systematic way to eliminate bottlenecks, optimize execution, and scale with clarity. Here are the 6 phases: 1. Bottleneck Identification 2. Clarifying the Goal 3. Solution Brainstorming 4. Focused Execution 5. Performance Review 6. Iterate & Improve 1️⃣ Bottleneck Identification Before you can fix anything, you need to identify the real problem. Most entrepreneurs spin their wheels solving the wrong issues because they never dig deep enough. To get clarity, ask: + What's the biggest constraint stopping growth right now? + What metric, if doubled, would create the biggest impact? + What’s preventing us from getting there? If you don’t identify the root problem, every solution you apply will be wasted effort. 2️⃣ Clarifying the Goal Once you know the problem, define the exact outcome you’re solving for. I use a simple Three-Part Goal Formula: 1. What are we trying to achieve? 2. By when? 3. What constraints do we have? Vague goals lead to vague actions. Precision forces progress. 3️⃣ Solution Brainstorming Now, generate every possible solution—without filtering. Most people limit themselves to their existing knowledge, which is why they get stuck. Instead, ask: “If there were no rules, what would I do?” This opens up better, faster, and often simpler solutions you wouldn’t have otherwise considered. 4️⃣ Focused Execution Don’t test everything at once—test one variable at a time. Most teams waste months by making too many changes at once, leading to messy, inconclusive results. Instead, break it down: 1. Test one key assumption. 2. Measure one KPI that proves or disproves it. 3. Execute for a set period, then review. 4. Speed matters. Complexity kills momentum. 5️⃣ Performance Review Your data isn’t just numbers—it’s feedback on your decision-making process. Your job is to analyze: + Did the solution work? + Why or why not? + What does this tell us about our business? Every test refines your ability to make better future decisions. 6️⃣ Iterate & Improve Most companies don’t fail from making the wrong move—they fail from making no moves at all. The only way to win long-term is to keep iterating. Instead of fearing failure, build a culture that rewards learning. Failure + Reflection = Progress. If you aren’t improving your decision-making process, your business will eventually hit a ceiling. That’s why I built The Iteration Loop—so every problem becomes an opportunity for better, faster execution. P.S. If you want the scaling roadmap I used to scale 3 businesses to $100M and beyond, you can get it for free from the link in my profile.

🚀🚀 Why Load Testing & APM Should Be Non-Negotiable in Your SDLC🚀🚀 In today's digital landscape, delivering high-performing applications isn't just nice to have—it's mission-critical. Yet many teams still treat performance as an afterthought. Here's why integrating Load Testing and Application Performance Management (APM) throughout your SDLC is essential: 1. The Performance Reality Check Studies show that 53% of users abandon a mobile site if it takes longer than 3 seconds to load. Even a 100ms delay can hurt conversion rates by 7%. The cost of poor performance? Amazon calculated that every 100ms of latency costs them 1% in sales. 2. Why Early Integration Matters 2.1 Load Testing in SDLC: ✅ Identifies bottlenecks before production deployment ✅ Validates system capacity under expected user loads ✅ Prevents costly post-release performance fixes ✅ Ensures scalability requirements are met 2.2 APM Throughout Development: ✅ Real-time visibility into application behavior ✅ Proactive issue detection and resolution ✅ Performance baseline establishment ✅ Continuous optimization opportunities 3. Grafana: The Game Changer for Performance Monitoring Grafana has revolutionized how we visualize and monitor application performance with it's ✅ Unified Dashboards - Correlate metrics from multiple data sources ✅ Real-time Alerting - Get notified before users experience issues ✅ Historical Analysis - Track performance trends over time ✅ Custom Visualizations - Tailor views for different stakeholders ✅ Cost-Effective - Open-source with powerful enterprise features 4. Key Metrics to Track: ✅ Response times and throughput ✅ Error rates and success ratios ✅ Resource utilization (CPU, memory, disk) ✅ Database query performance ✅ User experience metrics 5. The Bottom Line Performance isn't just a technical concern—it's a business imperative. Teams that embed load testing and APM into their SDLC deliver more reliable, scalable applications that drive better user experiences and business outcomes. Your SDLC needs to include APM / Load testing for optimal customer satisfaction to cost ratio. What's your experience with performance testing in your SDLC? Share your wins and lessons learned below! 👇 #SoftwareDevelopment #LoadTesting #APM #Grafana #DevOps #PerformanceTesting #SDLC #Monitoring #TechLeadership

The Medical Device Iceberg: What’s hidden beneath your product is what matters most. Your technical documentation isn’t "surface work". It’s the foundation that the Notified Body look at first. Let’s break it down ⬇ 1/ What is TD really about? Your Technical Documentation is your device’s identity card. It proves conformity with MDR 2017/745. It’s not a binder of loose files. It’s a structured, coherent, evolving system. Annexes II & III of the MDR guide your structure. Use them. But make it your own. 2/ The 7 essential pillars of TD: → Device description & specification → Information to be supplied by the manufacturer → Design & manufacturing information → GSPR (General Safety & Performance Requirements) → Benefit-risk analysis & risk management → Product verification & validation (including clinical evaluation) → Post-market surveillance Each one matters. Each one connects to the rest. Your TD is not linear. It’s a living ecosystem. Change one thing → It impacts everything. That’s why consistency and traceability are key. 3/ Tips for compiling TD: → Use one “intended purpose” across all documents → Apply the 3Cs: ↳ Clarity (write for reviewers) ↳ Consistency (same terms, same logic) ↳ Connectivity (cross-reference clearly) → Manage it like a project: ↳ Involve all teams ↳ Follow MDR structure ↳ Trace everything → Use “one-sheet conclusions” ↳ Especially in risk, clinical, V&V docs ↳ Simple, precise summaries → Avoid infinite feedback loops: ↳ One doc, one checklist, one deadline ↳ Define “final” clearly 4/ Best practices to apply: → Add a summary doc for reviewers → Update documentation regularly → Create a V&V matrix → Maintain URS → FRS traceability → Hyperlink related docs → Provide objective evidence → Use searchable digital formats → Map design & mfg with flowcharts Clear TD = faster reviews = safer time to market. Save this for your next compilation session. You don't want to start from scratch? Use our templates to get started: → GSPR, which gives you a predefined list of standards, documents and methods. ( https://lnkd.in/eE2i43v7 ) → Technical Documentation, which gives you a solid structure and concrete examples for your writing. ( https://lnkd.in/eNcS4aMG )

I used to spend days deploying an ML model.... until I discovered this. Imagine you have ✔️ defined the Machine Learning problem ✔️ trained a good model ✔️ created a REST API for your model using FastAPI, and It is time to deploy the model... but how? 🤔 Here are 3 strategies to help you, from beginner to PRO 🚀 1️⃣ 𝗠𝗮𝗻𝘂𝗮𝗹 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 → Push all the Python code and the serialized model (pickle) to the GitHub repository → Ask the DevOps in the team guy to wrap it with docker and deploy it to the same infrastructure used for the other microservices, e.g. Kubernetes cluster. This approach is simple, but it has a problem. ❌ ML models need to be frequently re-trained. So you need to bother your DevOps colleague every week to refresh the model. Fortunately, there is a well-known solution for this, called Continuous Deployment (CD). 2️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗮𝗰𝘁𝗶𝗼𝗻𝘀 → Create a GitHub action that is automatically triggered every time you push a new version of the model to the GitHub repo → This action dockerizes and pushes the code to the inference platform (e.g. Kubernetes, AWS Lambda). This method works like a charm... ❌ until the model, you automatically pushed to production is bad. Is there a way to control model quality before deployment, and quickly decide which model (if any) should be pushed to production? 3️⃣ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝗲𝗱 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗠𝗼𝗱𝗲𝗹 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆 The Model Registry is where you push every trained ML mode so you can → access the entire model lineage (aka what exact dataset and code generated it) → compare models → promote models to production → automatically trigger deployments via webhooks. 𝗠𝘆 𝗮𝗱𝘃𝗶𝗰𝗲 🧠 I strongly recommend you add a Model Registry to your ML toolset, as it brings reliability and trust to the ML system and enhances collaboration between team members. ---- Hi there! It's Pau 👋 Every day I share free, hands-on content, on production-grade ML, to help you build real-world ML products. 𝗙𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 and 𝗰𝗹𝗶𝗰𝗸 𝗼𝗻 𝘁𝗵𝗲 🔔 so you don't miss what's coming next #machinelearning #mlops #realworldml

Most companies suck at launching products. They’re like Alice in Wonderland — chasing shiny objects and getting lost along the way. Here’s the 11-step process we perfected after 25 years of product launches (in a collaboration with Jason Oakley): 1. Competitive Research The key to great strategy is to look externally. Take notes on competitor's features and how they grow. Build a database so you can counter-position appropriately. 2. Segmentation A launch aimed at “everyone” will miss everyone. Instead, build a laser-focused Ideal Customer Profile (ICP). Follow this chain of thought: What are they craving? → What frustrates them daily? → What job are they trying to accomplish? 3. Pricing & Packaging Even the smallest feature can have a ripple effect on your pricing and packaging. Don’t wait until launch week to figure this out. Before launching, assess things like: Will this be a paid feature or free? Who will get access? What’s the plan for feature gating? 4. Positioning Now it’s time to craft a message that resonates. Speak to their deeper desires, not just their immediate problems. Communicate the outcome your product delivers and why you’re different from the rest. 5. Assemble Your Launch Team You can’t do it alone, and you shouldn’t. A successful launch involves stakeholders across the company. Use the RACI framework to assign clear roles. 6. Clear Objectives Too many teams dive into a launch without defined goals. And that’s why they miss the mark. Set clear objectives and key results. 7. Distribution Channels Many teams fall into the trap of trying to be everywhere; LinkedIn, email, ads, you name it. Reality check: Most startups only have 1-2 effective distribution channels. Find yours and double down on it. 8. Launch Milestones Planning your entire launch around individual tasks will overwhelm you. Instead, focus on major milestones and build a work-back plan. Some key milestones to include: Early access launch → Customer launch → Kickoff meeting. 9. Bill of Materials Your Bill of Materials is the content engine of your launch. Focus on: → Writing the message they want to hear → Designing visuals that captivate and appeal to them → Creating email sequences tailored to every user flow 10. Sales & Customer Success Teams Too many launches fail because these teams are looped in at the last minute. Enable them early with a messaging deck, internal FAQs, and demo materials... And they’ll become powerful advocates for your product. 11. Launch Day Make sure everything is launched smoothly and on time. If you achieve early wins, be the first to celebrate them and rally the team. And don’t forget to keep pushing the momentum forward. There's much more in the deep dive: https://lnkd.in/eB7s6umA If you don't plan your launches, even the best products will fail.

How to fail in #agile interview Topic: Retrospective ---------------- How to Fail 😒 ---------------- 👸 Interviewer: "How do you typically run a sprint retrospective with your team?" 👨🦱 Candidate: "We usually ask what went well and what didn’t, then discuss how to improve." 👸 Interviewer: "That’s a basic format. But what if the team is disengaged, and you notice the same issues coming up in every retrospective?" 👨🦱 Candidate: "Well, I’d try to motivate them to speak up more." 👸 Interviewer: "Let’s get more specific. Suppose the team feels retrospectives aren’t useful and sees no real changes after their input. How would you handle this?" 👨🦱 Candidate: "I’d probably bring it up with the team during the next retrospective and see why they feel that way." 👸 Interviewer: "And if this lack of engagement affects continuous improvement, causing the same issues to repeat every sprint, what would you do?" 👨🦱 Candidate: "Maybe we’d focus on smaller changes to make things easier for them." ----------------- How to Pass 😊 ----------------- 👸 Interviewer: "How do you typically run a sprint retrospective with your team?" 👨🦱 Candidate: "I use different formats based on the team’s needs. Sometimes it’s ‘What went well, what didn’t,’ but I like to switch it up with activities like Start-Stop-Continue or using data-driven insights to stimulate discussions. My goal is to create an open, constructive environment where the team feels safe to discuss both successes and areas for growth." 👸 Interviewer: "What if the team is disengaged and the same issues keep surfacing?" 👨🦱 Candidate: "That signals we’re not addressing the root cause. I’d use techniques like the ‘5 Whys’ to drill deeper and focus on actionable items. If disengagement continues, I’d have one-on-one conversations to understand their concerns and re-energize retrospectives by varying the format or focusing on quick wins." 👸 Interviewer: "The team feels retrospectives aren't driving real change. How do you handle that?" 👨🦱 Candidate: "First, I’d check if we’re tracking action items and following up. If improvements aren’t visible, it’s often because we’re not holding ourselves accountable. I’d help the team create smaller, more tangible actions and make sure we review progress in the next sprint." 👸 Interviewer: "What if the same problems persist after implementing changes?" 👨🦱 Candidate: "If the issues persist, I’d revisit the changes and work with the team to measure their impact. Maybe the solution isn’t effective, or the problem was misunderstood. It’s also important to look at broader system-level challenges or external blockers and address those with the help of stakeholders." 💡 Key Takeaway: Effective #retrospectives require: ✍️ Engaging the team, ✍️ Addressing root causes, and ✍️ Ensuring actionable feedback drives change.