Software Performance Optimization

🛠️ Unlocking the Power of SAP Trace: Your Troubleshooting Superpower! If you’ve ever faced a priority issue in an SAP support project where nothing seems to explain why something isn’t working—no business logic, no configuration clues—you’re not alone! This is where SAP Trace comes to the rescue. Let’s break it down: What is SAP Trace? SAP Trace is a diagnostic tool that tracks and logs the steps or activities of a user in the system. It helps uncover hidden issues, such as: • Missing authorizations. • Performance bottlenecks. • Unexpected system behavior. It’s your “last resort” tool when everything else fails to provide clarity. Transaction Codes for SAP Trace 1. ST01 (System Trace): • Monitors system activity for authorizations, kernel, database, and more. • Useful for catching authorization errors or understanding unexpected behavior. 2. ST05 (Performance Trace): • Focuses on SQL, table buffer, RFC, and enqueue traces. • Helps you analyze performance issues or pinpoint inefficient database queries. When to Use SAP Trace? • A user reports “I can’t perform this transaction”, but their roles and authorizations seem correct. • A process runs into performance issues, and you suspect database queries or RFC calls. • You’re dealing with workflow failures or locked objects. • There’s no visible reason for the error, and it’s critical to identify the root cause. How to Use SAP Trace? Here’s a step-by-step guide to using ST01 as an example: 1. Start the Trace • Go to T-code ST01. • Select the components you want to trace: Authorization, Kernel, SQL, etc. • Specify the user ID you want to trace (to focus the analysis). • Click “Activate Trace”. 2. Perform the Issue Activity • Ask the user to repeat the activity that’s causing the issue. 3. Stop the Trace • Return to ST01 and click “Deactivate Trace” to stop logging. 4. Analyze the Results • Review the trace logs to identify errors (e.g., missing authorizations) or steps causing delays. Real-Life Example A client reported that they couldn’t release a maintenance order. All roles and authorizations seemed correct. Using ST01, we found a missing authorization object that wasn’t part of the user’s role. Once added, the issue was resolved in minutes. Why You Should Use SAP Trace • It’s precise: Focuses on the specific user or process. • It’s powerful: Detects errors that are invisible in normal checks. • It’s a lifesaver: Helps you deliver solutions quickly, even under pressure. Have you used SAP Trace before? Share your experience or tips below—let’s help each other master this amazing tool!

How to find a Table behind a Transaction Code In SAP for SAP beginner ✔️ For SAP beginners, identifying the table(s) behind a transaction code (T-code) is a common and important task. Here’s a clear, step-by-step approach using standard SAP tools:✔️ 1. Use Transaction Code ST05 (SQL Trace): Step 1: Open transaction ST05. Step 2: Click "Activate Trace" for your user. Step 3: In a new SAP window, execute the T-code you want to analyze (e.g., VA03 for Sales Order Display) and perform the action you’re interested in. Step 4: Return to ST05 and click "Deactivate Trace". Step 5: Click "Display Trace" and execute the search. Step 6: The results will show all the database tables accessed during your transaction. This method gives you a list of all tables read or written to by the transaction. It’s especially useful for complex transactions that use multiple tables. 2. Use Field Help (F1) for Specific Fields:✔️ In the transaction, place your cursor in the field you’re interested in. Press F1 for help. Click the "Technical Information" (often a hammer and wrench icon). The pop-up will display the table name and field name for that screen field. This is the easiest way to find the table for a specific data field. 3. Use Transaction SE93 (Transaction Codes):✔️ Enter SE93 and input your T-code. The screen will show the program/report behind the transaction. You can then analyze this program (using SE80 or by consulting with an ABAP developer) to see which tables it uses. Join me for daily SAP insights! 📢 https://lnkd.in/gmPNGNJE ✔️ Connect with me: https://lnkd.in/gmaAyV6K ✔️ Follow Jatin Tiwari for daily SAP insights. ✔️ Stay updated with 🔥 fresh content and job-ready SAP knowledge.

SAP HANA Slowness Troubleshoot: ✅ 1. Check System-Wide Health First: Use SAP HANA Cockpit or HANA Studio: 🔍 CPU Usage: Is the CPU maxed out? 💾 Memory Usage: Is HANA consuming more memory than it should? 🚦 Disk I/O: Are there slow write/read speeds? 📡 Network latency (in distributed systems) 🔧 Tool: HANA Cockpit → System Overview → Performance Metrics ✅ 2. Check Expensive SQL Statements: Look for long-running or high-load SQL queries. 📊 Use SQL Plan Cache: SQL QUERY As, SELECT * FROM M_EXPENSIVE_STATEMENTS ORDER BY DURATION_MS DESC; 💡 Analyze: Joins without indexes? Large data scans? Poor filters? 🔧 Tool: HANA Studio → Performance → Expensive Statements ✅ 3. Check Active Sessions & Locks: High concurrency or blocked sessions may cause slowness. 🧍♂️ Use: SQL Query: SELECT * FROM M_ACTIVE_STATEMENTS; SELECT * FROM M_BLOCKED_TRANSACTIONS; SELECT * FROM M_LOCKS; 🔒 Look for: Long-running transactions Deadlocks or waiting on locks ✅ 4. Monitor Memory and Paging: Memory overuse may lead to OS-level swapping. Check: SQL Query: SELECT * FROM M_MEMORY; SELECT * FROM M_HOST_RESOURCE_UTILIZATION; Make sure there is: No memory ballooning No significant OS swap usage 🔧 Tool: HANA Cockpit → Memory Overview ✅ 5. Review Savepoints & Log Writes: Frequent savepoints or slow log writes can delay transactions. Use: SQL Query: SELECT * FROM M_SAVEPOINTS ORDER BY START_TIME DESC; SELECT * FROM M_LOG_SEGMENTS; Check disk latency or log segment size ✅ 6. Examine System Alerts: HANA generates alerts automatically. 🚨 Use: HANA Studio → Alerts HANA Cockpit → Alerting → History Look for: CPU/MEM/Disk threshold breaches Long-running jobs or failed backups ✅ 7. Check Configuration Parameters Sometimes poor default settings or misconfigurations are to blame. Review: global_allocation_limit plan_cache_size log_mode, etc. 🔧 Use: SQL Query: SELECT * FROM M_INIFILE_CONTENTS WHERE LAYER_NAME = 'SYSTEM'; ✅ 8. Application Layer Investigation: If HANA is healthy, the issue could be at the app level: API calls or OData services timing out? Network latency between app and DB? Poor app-side joins or loops? 🧰 Tools & Logs to Use: 📈 SAP HANA Cockpit or Studio 📄 indexserver trace logs (in /usr/sap/<SID>/HDB<instance>/trace/) 🧰 HDBAdmin, HDBSQL, SQL console 📦 SAP EarlyWatch Reports (for ongoing monitoring) 🔄 Optional: Reboot Strategy: If root cause can't be found and system is unresponsive: Gracefully stop/start HANA (HDB stop / HDB start) Clear temporary files if needed Always check logs afterward #saphana #hanadb #hanatroubleshoot

🚀𝗔𝗕𝗔𝗣 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 — 𝗲𝘃𝗲𝗿 𝘁𝘂𝗿𝗻𝗲𝗱 𝗮 𝘀𝗹𝘂𝗴𝗴𝗶𝘀𝗵 𝗿𝗲𝗽𝗼𝗿𝘁 𝗶𝗻𝘁𝗼 𝗮 𝗹𝗶𝗴𝗵𝘁𝗻𝗶𝗻𝗴-𝗳𝗮𝘀𝘁 𝗼𝗻𝗲? In this post, I share how I optimized a SQL query in ABAP and slashed runtime from 60 seconds to just 6. You’ll learn: ✅ 𝗛𝗼𝘄 𝗜 𝘀𝗽𝗼𝘁𝘁𝗲𝗱 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗸𝗶𝗹𝗹𝗲𝗿 𝘄𝗶𝘁𝗵 𝗦𝗧𝟬𝟱  ✅ 𝗪𝗵𝘆 𝗦𝗘𝗟𝗘𝗖𝗧 𝗶𝗻𝘀𝗶𝗱𝗲 𝗮 𝗟𝗢𝗢𝗣 𝗶𝘀 𝗮 𝘁𝗿𝗮𝗽  ✅ 𝗛𝗼𝘄 𝗙𝗢𝗥 𝗔𝗟𝗟 𝗘𝗡𝗧𝗥𝗜𝗘𝗦 𝗮𝗻𝗱 𝗽𝗿𝗼𝗽𝗲𝗿 𝗳𝗶𝗲𝗹𝗱 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝘀𝗮𝘃𝗲𝗱 𝘁𝗵𝗲 𝗱𝗮𝘆  ✅ 𝗞𝗲𝘆 𝗹𝗲𝘀𝘀𝗼𝗻𝘀 𝗳𝗼𝗿 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗔𝗕𝗔𝗣 𝗰𝗼𝗱𝗲 🔁 If you’ve ever dealt with large datasets and performance bottlenecks, this one's for you. 👇 Read the full story, and if it helps — please like, comment, and share it with your SAP network! #SAP #ABAP #PerformanceTuning #SQLTuning #CleanCode #SAPDevelopment #FORALLENTRIES #DatabaseOptimization #ST05 #TechLeadership #SAPCommunity #CodeSmarter #ABAPBestPractices

Title: Tame the Performance Beast: Mastering SAP Basis Optimization Introduction Is your SAP system sluggish, leaving users frustrated and hindering productivity? Don't fret! Here's your one-stop guide to conquering performance optimization in SAP Basis. Buckle up, and let's unleash the hidden potential of your system! Unveiling the Bottlenecks Performance issues can stem from various culprits. Here's how to identify them: 1.System Monitoring: Utilize transactions like ST03 (System Overview) and SM50 (System Monitoring) to pinpoint bottlenecks like high CPU usage, memory limitations, or slow database access. 2.User Analysis: Analyse user behavior and identify resource-intensive tasks or reports causing strain. Tools like SUIM (User Information System) can help. 3.Background Job Scrutiny: Unearth inefficient background jobs impacting system performance. Analyse job logs (SM37) and optimize job scheduling to avoid peak usage times. Sharpening Your Tools: SAP offers a plethora of tools to optimize performance: 1.Database Statistics: Regularly update database statistics (using DBST or ST04) to ensure the database queries retrieve data efficiently. 2.Buffer Management: Optimize buffer utilization (RZ10) by allocating sufficient memory for frequently accessed data, minimizing disk I/O. 3.Background Job Tuning: Schedule background jobs strategically (SM37) to avoid overloading the system during peak hours. Pro Tip: The Power of Simplification 1.Simplify authorization checks (SU01): Grant authorizations only when necessary, reducing unnecessary checks that can slow down user actions. 2.Decommission unused custom code: Regularly review and remove unused custom code to streamline system processes. Visualize Your Success: -Track key performance indicators (KPIs): Monitor response times, transaction throughputs, and system resource utilization before and after optimization to measure the impact. Continuous Improvement: A Winning Formula 1.Stay updated with SAP Notes and patches: Implement SAP recommendations to address known performance bottlenecks and incorporate best practices. 2.Schedule regular performance assessments: Proactive monitoring helps nip performance issues in the bud before they significantly impact users. Embrace the Challenge! By following these steps and leveraging the available tools, you can transform your SAP system into a performance powerhouse. Remember, a well-tuned SAP Basis is the foundation for a smooth and efficient user experience. Let's discuss your SAP Basis optimization challenges in the comments! #SAPBasis #PerformanceOptimization #SAP #ERP #SysAdmin

I advise most of my clients to STOP using industry benchmarks Here's why I stay to stop using industry benchmarks: ❌ Too broad "Retail" may include Target and a tiny mom & pop shop so it's hard to tell if you're comparing your brand against an actually comparable brand. ❌ Inconsistent tracking Not every ESP tracks metrics the same way (example: email opens can vary drastically dependent on if machine opens included). ❌ Zero context Industry benchmarks ignore your brand strategy - so your campaign targeting a specific segment for a specific goal shouldn't be compared to industry averages. So what should you do? Benchmark against your own performance. ✅You know your company goals. Align benchmarks around these. ✅You know your targeting strategies. Track results when they change. Stop stealing your joy by looking at where the industry is at. Start evaluating results against your own performance. #EmailMarketing and #SMSMarketing community - ----- ❓ Do you like using industry benchmarks? ❓ Why or why not? ⬇️ Comment below⬇️ ♻️ Reshare this post if it was helpful! ----- P.S. - Want to know how to build better benchmarks for your email or SMS program? Sign up for BearMail, my newsletter, to get the full details - revealed next Monday (4/28).

The 30% Email Revenue Benchmark Is Pointless. Here’s Why: For years, agencies have pushed the narrative that “30% of your revenue should come from email.” Sounds authoritative, right? But here’s the problem— It’s meaningless without context. A brand selling impulse-buy jewelry isn’t the same as one selling supplements with long consideration windows and recurring purchases. Different industries. Different customer behaviours. Different buying cycles. Yet, many founders obsess over hitting this arbitrary “30%” as if it’s the gold standard. What happens? 1. Chasing numbers ⤷ Sending more campaigns despite declining engagement. 2. Audience fatigue ⤷ Burning out your list just to make dashboards look good. 3. Short-term hacks ⤷ Relying on flash sales to inject temporary revenue. And the reality is— Attribution itself is flawed. Just compare Klaviyo’s attribution windows by tweaking a single day—you’ll see revenue figures swing dramatically. So, which number is actually right? Neither. Because it’s the wrong question. The real question isn’t “Is email driving 30% of revenue?” It’s “Is retention marketing driving profitable, sustainable growth for the business?” Any agency fixated solely on attributed revenue is missing the bigger picture. Retention isn’t about hitting vanity metrics—it’s about how your strategies impact broader business KPIs. Yes, revenue matters. But if it’s your north star, you’re steering the ship off course.

Title: "Database Optimization in SAP: Best Practices for Performance" Database performance is one of the most crucial factors in ensuring that your SAP system runs smoothly. Poor database performance can lead to slow system response times, impacting user experience and business productivity. 🔧 Key Steps for Optimizing Database Performance: Index Management: Proper indexing speeds up data retrieval times and reduces unnecessary database load. Pro Tip: Use transaction DB02 to monitor index usage and rebuild fragmented indexes regularly. Database Statistics: Regularly update database statistics to ensure the optimizer selects the best execution plan for queries. Tip: Use DBACOCKPIT to monitor and collect statistics on table and index performance. Table Maintenance: Remove old or unused data from large tables to avoid performance degradation. Consider using data archiving to move historical data from active tables. SQL Tuning: Analyze slow SQL queries and tune them to improve execution times. Use ST04 to view the execution plan of SQL statements and identify any bottlenecks. 🔧 Real-World Example: In one case, a large SAP system suffered from slow performance during peak business hours. After analyzing the database with DB02, it was found that several indexes were fragmented, and some critical tables were growing too large. Rebuilding the indexes and archiving old data improved system response times significantly. 👉 What database optimization strategies have you found most effective in your SAP system?

🚫 Industry benchmarks are bullsh*t - especially when you are using them wrong 🚫 Stop comparing your marketing metrics to companies playing a completely different game. The data you see should be a "cool fact" - nothing else. Your competitor's: • $250 CPL • 2.8% CTR • 50% demo-to-close rate All irrelevant. Why? Because they might have: ✅ Different positioning and sales motion ✅ Different stage of product-market fit ✅ Different brand awareness (that took YEARS to build) & trust in the market You’re not competing against their numbers — you’re competing against their context. Of course benchmarks have value.They help you spot outliers, sanity check your funnel, and sense-check your GTM motion. But chasing them? Stressing over them? Comparing blindly?That’s where teams go wrong. When you blindly chase their benchmarks, you start: • Making bad optimisation decisions • Killing experiments too early • Burning out your team • Wasting budget Instead: ✅ Benchmark against your own baselines ✅ Double down on what moves your revenue ✅ Optimise for your business model — not someone else’s highlight reel (which for all we know could be a lie, as Dave Chapelle would say "LinkedIn is not a real place") The game isn’t who gets the cheapest leads. It’s who builds the most durable, scalable growth engine. Focus on your own levers. Play your game.

Industry benchmarks are overrated. There, I said it. Every year, reports from HubSpot, LinkedIn, WordStream, and many others tell B2B marketers what their numbers should look like. - A “good” CPL is under $150 - A “strong” Google CTR for fintech is 2% - Email open rates “should” be 25% And the list goes on and on... But here’s the problem: benchmarks don’t know your business. A $300 CPL could be a steal if your deal size is six figures. A 1% CTR might be fine if conversion rates are strong. A lower email open rate doesn’t matter if response rates are high. Your business is unique, from what you sell to how you sell it. Comparing yourself to industry averages is meaningless if it doesn’t align with your pricing, sales cycle, and audience. Instead of stressing over whether your numbers match a report, ask: - Are we generating the pipeline we need to hit revenue goals? - Are our lead and conversion metrics tracking in a way that makes sense for our business? - Are we measuring against our own historical data, not just an industry average? Because at the end of the day, the only benchmark that actually matters is the one that moves your business forward. #b2b #b2bmarketing #saas #advertising #measurement #growth