Performance Analysis - The USE Method

Brendan Gregg Lead Performance Engineer, Joyent brendan.gregg@joyent.com Performance Analysis: The USE Method Saturday, July 28, 2012 whoami •I work at the top of the performance support chain •I also write open source performance tools out of necessity to solve issues •http://github.com/brendangregg •http://www.brendangregg.com/#software •And books (DTrace, Solaris Performance and Tools) •Was Brendan @ Sun Microsystems, Oracle, now Joyent Saturday, July 28, 2012 Joyent •Cloud computing provider •Cloud computing software •SmartOS •host OS, and guest via OS virtualization •Linux, Windows •guest via KVM Saturday, July 28, 2012 Agenda •Example Problem •Performance Methodology •Problem Statement •The USE Method •Workload Characterization •Drill-Down Analysis •Specific Tools Saturday, July 28, 2012 Example Problem •Recent cloud-based performance issue •Customer problem statement: •“Database response time sometimes take multiple seconds. Is the network dropping packets?” •Tested network using traceroute, which showed some packet drops Saturday, July 28, 2012 Example: Support Path •Performance Analysis 1st Level 2nd Level Top Customer Issues Saturday, July 28, 2012 Example: Support Path •Performance Analysis 1st Level 2nd Level Top Customer: “network drops?” “ran traceroute, can’t reproduce” “network looks ok, CPU also ok” my turn Saturday, July 28, 2012 Example: Network Drops •Old fashioned: network packet capture (sniffing) •Performance overhead during capture (CPU, storage) and post-processing (wireshark) •Time consuming to analyze: not real-time Saturday, July 28, 2012 Example: Network Drops •New: dynamic tracing •Efficient: only drop/retransmit paths traced •Context: kernel state readable •Real-time: analysis and summaries # ./tcplistendrop.d TIME SRC-IP PORT DST-IP PORT 2012 Jan 19 01:22:49 10.17.210.103 25691 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.17.210.108 18423 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.17.210.116 38883 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.17.210.117 10739 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.17.210.112 27988 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.17.210.106 28824 -> 192.192.240.212 80 2012 Jan 19 01:22:49 10.12.143.16 65070 -> 192.192.240.212 80 [...] Saturday, July 28, 2012 Example: Methodology •Instead of network drop analysis, I began with the USE method to check system health Saturday, July 28, 2012 Example: Methodology •Instead of network drop analysis, I began with the USE method to check system health •In < 5 minutes, I found: •CPU: ok (light usage) •network: ok (light usage) •memory: available memory was exhausted, and the system was paging •disk: periodic bursts of 100% utilization •The method is simple, fast, directs further analysis Saturday, July 28, 2012 Example: Other Methodologies •Customer was surprised (are you sure?) I used latency analysis to confirm. Details (if interesting): •memory: using both microstate accounting and dynamic tracing to confirm that anonymous pagins were hurting the database; worst case app thread spent 97% of time waiting on disk (data faults). •disk: using dynamic tracing to confirm latency at the application / file system interface; included up to 1000ms fsync() calls. •Different methodology, smaller audience (expertise), more time (1 hour). Saturday, July 28, 2012 Example: Summary •What happened: •customer, 1st and 2nd level support spent much time chasing network packet drops. •What could have happened: •customer or 1st level follows the USE method and quickly discover memory and disk issues • memory: fixable by customer reconfig • disk: could go back to 1st or 2nd level support for confirmation •Faster resolution, frees time Saturday, July 28, 2012 Performance Methodology •Not a tool •Not a product •Is a procedure (documentation) Saturday, July 28, 2012 Performance Methodology •Not a tool -> but tools can be written to help •Not a product -> could be in monitoring solutions •Is a procedure (documentation) Saturday, July 28, 2012 Why Now: past •Performance analysis circa ‘90s, metric-orientated: •Vendor creates metrics and performance tools •Users develop methods to interpret metrics •Common method: “Tools Method” •List available performance tools •For each tool, list useful metrics •For each metric, determine interpretation •Problematic: vendors often don’t provide the best metrics; can be blind to issue types Saturday, July 28, 2012 Why Now: changes •Open Source •Dynamic Tracing •See anything, not just what the vendor gave you •Only practical on open source software •Hardest part is knowing what questions to ask Saturday, July 28, 2012 Why Now: present •Performance analysis now (post dynamic tracing), question-orientated: •Users pose questions •Check if vendor has provided metrics •Develop custom metrics using dynamic tracing •Methodologies pose the questions •What would previously be an academic exercise is now practical Saturday, July 28, 2012 Methology Audience •Beginners: provides a starting point •Experts: provides a checklist/reminder Saturday, July 28, 2012 Performance Methodolgies •Suggested order of execution: 1.Problem Statement 2.The USE Method 3.Workload Characterization 4.Drill-Down Analysis (Latency) Saturday, July 28, 2012 Problem Statement •Typical support procedure (1st Methodology): 1.What makes you think there is a problem? 2.Has this system ever performed well? 3.What changed? Software? Hardware? Load? 4.Can the performance degradation be expressed in terms of latency or run time? 5.Does the problem affect other people or applications? 6.What is the environment? What software and hardware is used? Versions? Configuration? Saturday, July 28, 2012 The USE Method •Quick System Health Check (2nd Methodology): •For every resource, check: •Utilization •Saturation •Errors Saturday, July 28, 2012 The USE Method •Quick System Health Check (2nd Methodology): •For every resource, check: •Utilization: time resource was busy, or degree used •Saturation: degree of queued extra work •Errors: any errors Saturation Utilization Errors X Saturday, July 28, 2012 The USE Method: Hardware Resources •CPUs •Main Memory •Network Interfaces •Storage Devices •Controllers •Interconnects Saturday, July 28, 2012 The USE Method: Hardware Resources •A great way to determine resources is to find (or draw) the server functional diagram •The hardware team at vendors should have these •Analyze every component in the data path Saturday, July 28, 2012 The USE Method: Functional Diagrams, Generic Example CPU 1 CPU 2 DRAM DRAM I/O Bridge I/O Controller Disk Disk Port Network Controller Port CPU Interconnect Memory Bus Expander Interconnect I/O Bus Interface Transports Saturday, July 28, 2012 The USE Method: Resource Types •There are two different resource types, each define utilization differently: •I/O Resource: eg, network interface •utilization: time resource was busy. current IOPS / max or current throughput / max can be used in some cases •Capacity Resource: eg, main memory •utilization: space consumed •Storage devices act as both resource types Saturday, July 28, 2012 The USE Method: Software Resources •Mutex Locks •Thread Pools •Process/Thread Capacity •File Descriptor Capacity Saturday, July 28, 2012 The USE Method: Flow Diagram Errors Present? Choose Resource High Utilization? Saturation? Problem Identified Y Y Y N N N Saturday, July 28, 2012 The USE Method: Interpretation •Utilization •100% usually a bottleneck •70%+ often a bottleneck for I/O resources, especially when high priority work cannot easily interrupt lower priority work (eg, disks) •Beware of time intervals. 60% utilized over 5 minutes may mean 100% utilized for 3 minutes then idle •Best examined per-device (unbalanced workloads) Saturday, July 28, 2012 The USE Method: Interpretation •Saturation •Any non-zero value adds latency •Errors •Should be obvious Saturday, July 28, 2012 The USE Method: Easy Combinations Resource Type Metric CPU utilization CPU saturation Memory utilization Memory saturation Network Interface utilization Storage Device I/O utilization Storage Device I/O saturation Storage Device I/O errors Saturday, July 28, 2012 The USE Method: Easy Combinations Resource Type Metric CPU utilization CPU utilization CPU saturation run-queue length Memory utilization available memory Memory saturation paging or swapping Network Interface utilization RX/TX tput/bandwidth Storage Device I/O utilization device busy percent Storage Device I/O saturation wait queue length Storage Device I/O errors device errors Saturday, July 28, 2012 The USE Method: Harder Combinations Resource Type Metric CPU errors Network saturation Storage Controller utilization CPU Interconnect utilization Mem. Interconnect saturation I/O Interconnect saturation Saturday, July 28, 2012 The USE Method: Harder Combinations Resource Type Metric CPU errors eg, correctable CPU cache ECC events Network saturation “nocanputs”, buffering Storage Controller utilization active vs max controller IOPS and tput CPU Interconnect utilization per port tput / max bandwidth Mem. Interconnect saturation memory stall cycles I/O Interconnect saturation bus throughput / max bandwidth Saturday, July 28, 2012 The USE Method: tools •To be thorough, you will need to use: •CPU performance counters •For bus and interconnect activity; eg, perf events, cpustat •Dynamic Tracing •For missing saturation and error metrics; eg, DTrace •Both can get tricky; tools can be developed to help •Please, no more top variants! ... unless it is interconnect-top or bus-top •I’ve written dozens of open source tools for both CPC and DTrace; much more can be done Saturday, July 28, 2012 Workload Characterization •May use as a 3rd Methodology •Characterize workload by: •who is causing the load? PID, UID, IP addr, ... •why is the load called? code path •what is the load? IOPS, tput, type •how is the load changing over time? •Best performance wins are from eliminating unnecessary work •Identifies class of issues that are load-based, not architecture-based Saturday, July 28, 2012 Drill-Down Analysis •May use as a 4th Methodology •Peel away software layers to drill down on the issue •Eg, software stack I/O latency analysis: Application System Call Interface File System Block Device Interface Storage Device Drivers Storage Devices Saturday, July 28, 2012 Drill-Down Analysis: Open Source • With Dynamic Tracing, all function entry & return points can be traced, with nanosecond timestamps. •One Strategy is to measure latency pairs, to search for the source; eg, A->B & C->D: static int arc_cksum_equal(arc_buf_t *buf) { zio_cksum_t zc; int equal; mutex_enter(&buf->b_hdr->b_freeze_lock); fletcher_2_native(buf->b_data, buf->b_hdr->b_size, &zc); equal = ZIO_CHECKSUM_EQUAL(*buf->b_hdr->b_freeze_cksum, zc); mutex_exit(&buf->b_hdr->b_freeze_lock); return (equal); } A B C D Saturday, July 28, 2012 Other Methodologies •Method R •A latency-based analysis approach for Oracle databases. See “Optimizing Oracle Performance" by Cary Millsap and Jeff Holt (2003) •Experimental approaches •Can be very useful: eg, validating network throughput using iperf Saturday, July 28, 2012 Specific Tools for the USE Method Saturday, July 28, 2012 illumos-based •http://dtrace.org/blogs/brendan/2012/03/01/the-use- method-solaris-performance-checklist/ • ... etc for all combinations (would span a dozen slides) Resource Type Metric CPU Utilization per-cpu: mpstat 1, “idl”; system-wide: vmstat 1, “id”; per-process:prstat -c 1 (“CPU” == recent), prstat - mLc 1 (“USR” + “SYS”); per-kernel-thread: lockstat -Ii rate, DTrace profile stack() CPU Saturation system-wide: uptime, load averages; vmstat 1, “r”; DTrace dispqlen.d (DTT) for a better “vmstat r”; per-process: prstat -mLc 1, “LAT” CPU Errors fmadm faulty; cpustat (CPC) for whatever error counters are supported (eg, thermal throttling) Memory Saturation system-wide: vmstat 1, “sr” (bad now), “w” (was very bad); vmstat -p 1, “api” (anon page ins == pain), “apo”; per-process: prstat -mLc 1, “DFL”; DTrace anonpgpid.d (DTT), vminfo:::anonpgin on execname Saturday, July 28, 2012 Linux-based •http://dtrace.org/blogs/brendan/2012/03/07/the-use- method-linux-performance-checklist/ • ... etc for all combinations (would span a dozen slides) Resource Type Metric CPU Utilization per-cpu: mpstat -P ALL 1, “%idle”; sar -P ALL, “%idle”; system-wide: vmstat 1, “id”; sar -u, “%idle”; dstat -c, “idl”; per-process:top, “%CPU”; htop, “CPU%”; ps -o pcpu; pidstat 1, “%CPU”; per-kernel-thread: top/htop (“K” to toggle), where VIRT == 0 (heuristic). [1] CPU Saturation system-wide: vmstat 1, “r” > CPU count [2]; sar -q, “runq-sz” > CPU count; dstat -p, “run” > CPU count; per- process: /proc/PID/schedstat 2nd field (sched_info.run_delay); perf sched latency (shows “Average” and “Maximum” delay per-schedule); dynamic tracing, eg, SystemTap schedtimes.stp “queued(us)” [3] CPU Errors perf (LPE) if processor specific error events (CPC) are available; eg, AMD64′s “04Ah Single-bit ECC Errors Recorded by Scrubber” [4] Saturday, July 28, 2012 Products •Earlier I said methodologies could be supported by monitoring solutions •At Joyent we develop Cloud Analytics: Saturday, July 28, 2012 Future •Methodologies for advanced performance issues • I recently worked a complex KVM bandwidth issue where no current methodologies really worked •Innovative methods based on open source + dynamic tracing •Less performance mystery. Less guesswork. •Better use of resources (price/performance) •Easier for beginners to get started Saturday, July 28, 2012 Thank you •Resources: •http://dtrace.org/blogs/brendan • http://dtrace.org/blogs/brendan/2012/02/29/the-use-method/ • http://dtrace.org/blogs/brendan/tag/usemethod/ • http://dtrace.org/blogs/brendan/2011/12/18/visualizing-device- utilization/ - ideas if you are a monitoring solution developer •brendan@joyent.com Saturday, July 28, 2012