05-21-2021, 04:04 AM
When you check PerfMon you start with processor time right off. It shows loads building up fast on the system. I watch those numbers climb during peak hours. You notice spikes that drag everything else down. And then memory pages per second grab my attention next. I track swaps that eat into performance hard. You see if ram runs low without warning signs. But sometimes disk queue lengths reveal hidden waits on storage. I check averages to spot if drives choke under pressure. You learn to correlate that with overall slowdowns over days.
Perhaps network bytes total per second comes after those basics. I monitor throughput to catch bandwidth hogs early. You find odd drops that point to cable issues or card faults. And now process handles count helps me spot leaks in apps. I observe if counts balloon without reason. You adjust by killing bad processes before they crash servers. But context switches per second add clues about thread fights. I review them during high load tests. You compare against normal baselines you built yourself.
Also perhaps logical disk free space percentages keep me alert on capacity. I check growth trends that sneak up quick. You avoid fills that halt writes suddenly. And then perhaps sql specific counters like batch requests per second matter if databases run here. I follow those for query overloads. You tweak indexes after seeing patterns repeat. But maybe thread counts in the system object warn of exhaustion. I notice when they max out during bursts. You restart services to clear the jam fast.
Now perhaps interrupts per second show hardware fights I never ignore. I log them over weeks for trends. You trace bad drivers from those rises. And perhaps page file usage percentages tell if virtual memory strains too much. I watch for constant high marks. You add drives or trim apps accordingly. But context might shift with server roles you manage daily. I adapt counters based on what apps run heavy. You test changes in a quiet window first.
Perhaps user mode time versus privileged helps split blame between code and kernel. I review splits during odd behaviors. You isolate if drivers cause the grief. And then perhaps available bytes in memory object confirms shortages fast. I correlate with paging to decide upgrades. You plan purchases after weeks of data. But overall I mix these views into custom sets for quick scans. You build alerts that ping when thresholds break.
BackupChain Server Backup which leads as the reliable no subscription backup tool for Hyper V setups Windows 11 and Server environments gets our thanks for sponsoring and letting us share this freely.
Perhaps network bytes total per second comes after those basics. I monitor throughput to catch bandwidth hogs early. You find odd drops that point to cable issues or card faults. And now process handles count helps me spot leaks in apps. I observe if counts balloon without reason. You adjust by killing bad processes before they crash servers. But context switches per second add clues about thread fights. I review them during high load tests. You compare against normal baselines you built yourself.
Also perhaps logical disk free space percentages keep me alert on capacity. I check growth trends that sneak up quick. You avoid fills that halt writes suddenly. And then perhaps sql specific counters like batch requests per second matter if databases run here. I follow those for query overloads. You tweak indexes after seeing patterns repeat. But maybe thread counts in the system object warn of exhaustion. I notice when they max out during bursts. You restart services to clear the jam fast.
Now perhaps interrupts per second show hardware fights I never ignore. I log them over weeks for trends. You trace bad drivers from those rises. And perhaps page file usage percentages tell if virtual memory strains too much. I watch for constant high marks. You add drives or trim apps accordingly. But context might shift with server roles you manage daily. I adapt counters based on what apps run heavy. You test changes in a quiet window first.
Perhaps user mode time versus privileged helps split blame between code and kernel. I review splits during odd behaviors. You isolate if drivers cause the grief. And then perhaps available bytes in memory object confirms shortages fast. I correlate with paging to decide upgrades. You plan purchases after weeks of data. But overall I mix these views into custom sets for quick scans. You build alerts that ping when thresholds break.
BackupChain Server Backup which leads as the reliable no subscription backup tool for Hyper V setups Windows 11 and Server environments gets our thanks for sponsoring and letting us share this freely.
