From d06640e8ed13f3117a7f6e6e1ea1ebe57fb29d31 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Thu, 17 Oct 2024 11:35:10 -0400 Subject: [PATCH 01/22] Adding a Valkey performance blog and dtaivpp profile. Signed-off-by: David Tippett --- content/authors/dtaivpp.md | 8 + .../images/cm4.png | Bin 0 -> 685118 bytes .../images/io_threading_arch.png | Bin 0 -> 51291 bytes .../images/io_threading_htop.png | Bin 0 -> 370704 bytes .../images/io_threads.png | Bin 0 -> 45257 bytes .../images/test_setup.png | Bin 0 -> 17258 bytes .../images/valkey_clustered.png | Bin 0 -> 54262 bytes .../2024-10-21-testing-the-limits/index.md | 239 ++++++++++++++++++ static/assets/media/authors/dtaivpp.jpeg | Bin 0 -> 16641 bytes 9 files changed, 247 insertions(+) create mode 100644 content/authors/dtaivpp.md create mode 100644 content/blog/2024-10-21-testing-the-limits/images/cm4.png create mode 100644 content/blog/2024-10-21-testing-the-limits/images/io_threading_arch.png create mode 100644 content/blog/2024-10-21-testing-the-limits/images/io_threading_htop.png create mode 100644 content/blog/2024-10-21-testing-the-limits/images/io_threads.png create mode 100644 content/blog/2024-10-21-testing-the-limits/images/test_setup.png create mode 100644 content/blog/2024-10-21-testing-the-limits/images/valkey_clustered.png create mode 100644 content/blog/2024-10-21-testing-the-limits/index.md create mode 100644 static/assets/media/authors/dtaivpp.jpeg diff --git a/content/authors/dtaivpp.md b/content/authors/dtaivpp.md new file mode 100644 index 0000000..aff569f --- /dev/null +++ b/content/authors/dtaivpp.md @@ -0,0 +1,8 @@ +--- +title: David Tippett +extra: + photo: '/assets/media/authors/dtaivpp.jpeg' + github: dtaivpp +--- + +David Tippett currently is building search at GitHub. He has nearly a decade of experience building data systems to make search more understandable, systems more observable, and infrastructure more robust. 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}#uLHX`B0C(9&tH$d+C&vF$> z@UYO!%-59TxhQX3jx{d9qrt?nFqe?%SJ@8?{-{pUppf6i(k`jHPAc26uI`)abtk#) zAO!WdL5PSCh+HTd4YP`G5KC6?N@M4^&ZUee|9uy?WRf|1NU+w>N+^?u>bA1J!U&LYKr!4w3Oo z;j7-iX@W6bO3~w+1^T8@y8X5bnTF1P7M}bo8sMnA6jGV`)Y>?0rPH%|9e zGuQ}!Qv*0pO{6|mR3lZi*gT?JRR#%+Hwlq{6Y!=uMUYsb+Opx*`0L_`-~4_q{lLID zA}uI=1FKj5?V~B?2y2Q0D*|;qfBx$-FksZ>C(^Ab;t3R!#1)+cA%9jL z5eK9`Mg4F*zktS-Z8-1CMTAy*D$=7`$ox(F@fI>S^88CKBVRq@6iKW}l8Scf5O4(j z&$Hm{H!_L$`exC_wTF935!d~Cj@Ho4`h>cfxWwXl{&)`jgpI+oBveV8Ap~pAH&p@8 zj>oM1iT$64E21lbu;nUNX~Yn$Aqi`opUJ1Gqi!K6g%UDXsjrrPEIPg!r7;>w|G_-su`Ks*Ujj#aoO}hN)u76kEf}=d8hG~f zef6G79Cek5&sYmDkW@Z!I#uUfG5zDS&QQ}$$v@)_ZQ180tAZo|676X>x3gP6LE$1s= -h 10.0.1.136 +``` + +Test breakdown: +- `-n` - this will run 1,000,000 operations using the commands set in -t +- `-t` - will run the set and get tests +- `-P` - this specifies that we would like the tests to use 16 pipelines (send 16 operations per request). +- `-q` - silences the output to show only the final results +- `-a` - use the specified password +- `-h` - run the test against the specified host + +Honestly, I was asonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? Its amazing. + +```bash +redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +SET: 173040.33 requests per second, p50=4.503 msec +GET: 307031.00 requests per second, p50=2.455 msec +``` + +Between the two tests we averaged 240,000 requests per second with a median time of 3.45 msec (or 0.0034 seconds) for each operation. + +## Raising the CPU clock speed + +Since Valkey is a single threaded application it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. But different servers may be available with different CPU clock speeds. + +**Note:** Clock speeds generally are only comparable between CPU's with a similar architecture. For example, you could reasonably compare clock speeds between an 12th generation Intel i5 and a 12th generation Intel i7. If the 12th gen i7 had a max clock speed of 5Ghz that doesnt necessarily mean it will be slower than a AMD Ryzen 9 9900X clocked at 5.6Ghz. + +If you're following along on a Pi of your own I've outlined the steps to overclock your CM4 below. Otherwise you can skip to the results section below. + +1. Open the below file in a text editor like nano. + - `sudo nano /boot/firmware/config.txt` +2. At the end of the file add this section below the `[all]` tag. + ``` + [all] + over_voltage=8 + arm_freq=2200 + ``` +3. Save with cmd + x, y, enter +4. Restart the server and log back in `sudo restart now` + +We've just increased the speed of the Pi by 47% by raising the clock speed from 1.5Ghz to 2.2Ghz. Now lets re-run our test and see how things look! + +```bash +redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +SET: 394368.41 requests per second, p50=1.223 msec +GET: 438058.53 requests per second, p50=1.135 msec +``` + +We're up to 416,000 requests per second with a 1.2 msec (0.0012s) median latency. The mathmaticians out there might notice that this speed up is a lot more than the expected 47% increase. It's a 73% increase in requests per second and a 65% improvement in processing time. Whats happening?! + +While I haven't gone to machine code to verify here is what I believe is happening. The memory controller for the CM4 also lives on the CPU. Increasing the clock speed of the CPU also increases the performance of the memory. This means we almost are doubling the expected speedup by increasing the clock speed. + +## Adding IO Threading + +With all these gains I was super excited to try the new [IO threading available](https://valkey.io/blog/unlock-one-million-rps/) in Valkey 8. First we will take down the previous running docker instance with `docker compose -f valkey.yaml down`. Then we will modify the file to: + +```yaml +services: + valkey-1: + image: valkey/valkey:latest + hostname: valkey1 + command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} --io-threads 5 + volumes: + - ./data1:/data + network_mode: host + +volumes: + data1: + driver: local +``` + +Then we can `docker compose -f valkey.yaml up -d` to start it again. Remote into the benchmarking server to start the test and...? + +```bash +redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +SET: 345494.75 requests per second, p50=0.911 msec +GET: 327858.09 requests per second, p50=0.879 msec +``` + +Wait a second... These results are worse than the ones before? We went from 416k requests per second to 336k.... What's happening? + +![A picutre of the valkey server with 4 cores represented as boxes. In each of the four core boxes there are other boxes. 2 cores have 1 IO Thread Box, 1 Core has 2 IO thread boxes, and the last one has 1 IO Thread box along with a Valkey Process box.](images/io_threads.png) + +We have over-perscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention they are also competing with the Valkey process for resources to read IO. + +That's why [Valkey recommends](https://github.com/valkey-io/valkey/blob/a62d1f177b7888ec88035a0a1ce600fbc2280ce7/valkey.conf#L1337-L1341) setting the number of threads to be a value less than the number of cores you have. For our little 4 core server lets set it to be 2 threads and try again. + +```bash +redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +SET: 609050.44 requests per second, p50=0.831 msec +GET: 521186.22 requests per second, p50=0.719 msec +``` + +Much better! Now we are seeing around 565,000 requests per second and 0.77 msec (0.0007s) latency for requests. Thats a 35% increase in performance across both metrics! Not to mention in the picture below you can see that we have 100% utilization across all of our CPU's which means there's no more room for improvement! + +![A picture of an HTOP window showing all four of our CPU's at 100% utilization.](images/io_threading_htop.png) + +Right? Well belive it or not we can squeeze even more performance out of our little CM4! + +![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first core box is the Valkey process and in the next two there are IO Threads. The valkey process has a loop showing it communiacting with both of the IO threads. It also has a bracket showing it managing all the memory.](images/io_threading_arch.png) + +Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. + +## Clustered Valkey + +![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first three core boxs are Valkey processes. Each of them has a bracket around a portion of the memory.](images/valkey_clustered.png) + +What we are going to do is spin up a Valkey cluster. This cluster will have individual instances of Valkey runnning that each will be responsible for managing their own keys. With this method Valkey instaces are not waiting on IO threads to return data. They each read from their own IO and can access memory as soon as they get a request. + +I am not going into detail with how the keyspaces work but [here is a good 101 guide](https://valkey.io/topics/cluster-tutorial/) for understanding clustering in Valkey. + +Let's to stop our previous Valkey container. Now we can create our docker compose file for starting the cluster. There are a few things I want to point out here. Because each of these are exposed on the host they will all need to be using different ports. Additionally, all of them need to be aware they are started in cluster mode so they can redirect requests to the appropriate instance. + +```yaml +# valkey-cluster.yaml +services: + valkey-node-1: + hostname: valkey1 + environment: + - ALLOW_EMPTY_PASSWORD=yes + image: valkey/valkey:latest + command: valkey-server --port 6379 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + volumes: + - ./data1:/data + network_mode: host + valkey-node-2: + hostname: valkey2 + environment: + - ALLOW_EMPTY_PASSWORD=yes + image: valkey/valkey:latest + command: valkey-server --port 6380 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + volumes: + - ./data2:/data + network_mode: host + valkey-node-3: + hostname: valkey3 + environment: + - ALLOW_EMPTY_PASSWORD=yes + image: valkey/valkey:latest + command: valkey-server --port 6381 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + volumes: + - ./data3:/data + network_mode: host + +volumes: + data1: + driver: local + data3: + driver: local + data2: + driver: local +``` +Run `docker compose -f valkey-cluster.yaml up -d` to start the cluster. There is one more step to get the cluster running. First, find the name of one of your nodes with `docker ps --format '{{.Names}}'`. + +```bash +docker ps --format '{{.Names}} +kvtest-valkey-node-1-1 +kvtest-valkey-node-3-1 +kvtest-valkey-node-2-1 +``` + +I'll use the first one to finish the cluster creation. Once the containers have started up we have to tell them the details they need to use for the cluster. Below I am using the IP of the host and the port configurations of all the containers to create the cluster. This is because these addresses need to be accessible from the benchmarking or application servers. + +```bash +docker exec -it kvtest-valkey-node-1-1 valkey-cli --cluster create 10.0.1.136:6379 10.0.1.136:6380 10.0.1.136:6381 -a e41fb9818502071d592b36b99f63003019861dad +``` + +Once that command is run we can run our benchmark! We do need to add the `--cluster` flag as well as several threads to generate data fast enough. Also, because this is so fast I ended up moving from 1 million requests to 10 million requests. That way it has time to fully utilize all the resources. + +```bash +redis-benchmark -n 10000000 -t set,get -P 16 -q --threads 10 --cluster -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +Cluster has 3 master nodes: + +Master 0: 219294612b44226fa32482871cf21025ff531875 10.0.1.136:6380 +Master 1: e5d85b970551c27065f1552f5358f4add6114d98 10.0.1.136:6381 +Master 2: 1faf3d0dd22e518eec11fd46c0de6ce18cd15cfe 10.0.1.136:6379 + +SET: 1122838.50 requests per second, p50=0.575 msec +GET: 1188071.75 requests per second, p50=0.511 msec +``` + +**1,155,000 requests per second**. **0.543 msec (0.0005s) latency**. We've managed to double our requests per second and improved our latency by nearly 30% again. All this on a single board computer that's the size of a credit card. + +While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important to start testing with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding more compute. Some other areas I'd reccomend testing is with different pipelineing configurations or with the number of client connections that you anticipate you'd be using in production. If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. 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z>C(t5xk~xOGw&T`G6D+{->WIioMv5qs26E80U%b9&+B|jlgT? zbzm~Xdh-1u&bn_Pq}Di=nIN$4RL%77>@M40rFRG?@peNh)PaIQ^1a@=9A_K8O_{t$ zuy1_J)r=wnJf)T1nImy6N^=K6-TKyY0@F#mN4fv?V?{TbOP9JtbtemWaJ2L?;%Lx4=U7g|a^zuBjinIAFRe9GY zEJ`=n?mqE;INx$1GL=Bs825u{QB2&bbc61UMl-};#PWyhNPJI9{qm4^BFta8OYz@V=@Nw}xoB>mo{^m;$u ziS;{%T_CA0;lgRZ@#dFWi`&)X7q7_Ogq05?W-}5FZ4gM3-m63u@GTw zlYdNQ#hUQVHD)ks#VeMDEB};j9 z8t-V)*1^Gv-Dn5m`83o*N^vyq8 oOj{^;S`S-In|t&6y|``gvD5o2M4-WW9d~&^-%!4fmpJl&0BbX=n*aa+ literal 0 HcmV?d00001 From 73e5b5f8fa96aca975670744c265ec1b8e224ae3 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 21 Oct 2024 16:03:13 -0400 Subject: [PATCH 02/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 8902a88..3cc0e8e 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -1,5 +1,5 @@ +++ -title= "Pushing the limits of Valkey on a Raspberry Pi" +title = "Pushing the limits of Valkey on a Raspberry Pi" description = "While most people won't go to produciton on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it will work in production." date= 2024-10-21 01:01:01 authors= ["dtaivpp"] From 5079bfd14dc8126289cf41bf585dd396d0fc2226 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 21 Oct 2024 16:03:28 -0400 Subject: [PATCH 03/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 3cc0e8e..4275865 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -5,7 +5,7 @@ date= 2024-10-21 01:01:01 authors= ["dtaivpp"] +++ -While this test is silly it's made me realize the importance of performance testing. For example, in some of the tests below I ended up managing to use all of the resources of the Raspberry Pi and achieved terrible performance. Every application has different performance characteristics so we'll walk though what factors to consider when it comes to deploying Valkey. +While doing extensive performance testing on a Raspberry PI is silly, it's made me realize the complexity of performance testing. For example, in some of the tests below I ended up managing to use all of the resources of the Raspberry Pi and achieved terrible performance. Every application has different performance characteristics so we'll walk though what factors to consider when it comes to deploying Valkey. ## The test environment From 554945c42372b0c7dc0e1d7184bb9c0f4e2838c0 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 21 Oct 2024 16:05:01 -0400 Subject: [PATCH 04/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 4275865..69e27e2 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -136,7 +136,7 @@ Wait a second... These results are worse than the ones before? We went from 416k ![A picutre of the valkey server with 4 cores represented as boxes. In each of the four core boxes there are other boxes. 2 cores have 1 IO Thread Box, 1 Core has 2 IO thread boxes, and the last one has 1 IO Thread box along with a Valkey Process box.](images/io_threads.png) -We have over-perscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention they are also competing with the Valkey process for resources to read IO. +We have over-subscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention they are also competing with the Valkey process for resources to read IO. That's why [Valkey recommends](https://github.com/valkey-io/valkey/blob/a62d1f177b7888ec88035a0a1ce600fbc2280ce7/valkey.conf#L1337-L1341) setting the number of threads to be a value less than the number of cores you have. For our little 4 core server lets set it to be 2 threads and try again. From 117d67d154124ec07d6f356800701ed185d494c9 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 21 Oct 2024 16:05:11 -0400 Subject: [PATCH 05/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 69e27e2..9c85671 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -150,7 +150,7 @@ Much better! Now we are seeing around 565,000 requests per second and 0.77 msec ![A picture of an HTOP window showing all four of our CPU's at 100% utilization.](images/io_threading_htop.png) -Right? Well belive it or not we can squeeze even more performance out of our little CM4! +Right? Well believe it or not we can squeeze even more performance out of our little CM4! ![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first core box is the Valkey process and in the next two there are IO Threads. The valkey process has a loop showing it communiacting with both of the IO threads. It also has a bracket showing it managing all the memory.](images/io_threading_arch.png) From 41d1bfb5154ea345811690c6f7b604e5f1ec01de Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 23 Oct 2024 09:44:10 -0400 Subject: [PATCH 06/22] Updated the IO threads to be a parameter Signed-off-by: David Tippett --- .../2024-10-21-testing-the-limits/index.md | 64 +++++++++---------- 1 file changed, 30 insertions(+), 34 deletions(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 9c85671..8f1e75d 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -1,6 +1,6 @@ +++ title = "Pushing the limits of Valkey on a Raspberry Pi" -description = "While most people won't go to produciton on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it will work in production." +description = "While most people won't go to produciton on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it works in production." date= 2024-10-21 01:01:01 authors= ["dtaivpp"] +++ @@ -15,7 +15,7 @@ For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](ht Our operating system will be a 64-bit debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. -We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have it's own benchmark utility that is installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally they both operate nearly the same as of the writing of this article. +We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have it's own benchmark utility that comes installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. ![Test architecture showing two nodes: a Benchmark server with the ip of 10.0.11.221 with an arrow pointing to a Valkey server with an ip of 10.0.1.136](images/test_setup.png) @@ -29,7 +29,7 @@ services: valkey-1: image: valkey/valkey:latest hostname: valkey1 - command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} + command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} --io-threads ${IO_THREADS} volumes: - ./data:/data network_mode: host @@ -44,6 +44,8 @@ Since we are exposing this to our internal network we will create a password for ```bash #.env VALKEY_PASSWORD=e41fb9818502071d592b36b99f63003019861dad +NODE_IP= +IO_THREADS=1 ``` Now by running `docker compose -f valkey.yaml up -d` Valkey server will start with password we set! @@ -53,7 +55,7 @@ Now by running `docker compose -f valkey.yaml up -d` Valkey server will start wi Now we are ready to do some baseline testing. We will log into the benchmarking server. If you haven't installed redis-benchmark yet you can do so with `sudo apt install redis-tools`. ```bash -redis-benchmark -n 1000000 -t set,get -P 16 -q -a -h 10.0.1.136 +redis-benchmark -n 1000000 -t set,get -P 16 -q -a --threads 5 -h 10.0.1.136 ``` Test breakdown: @@ -63,20 +65,21 @@ Test breakdown: - `-q` - silences the output to show only the final results - `-a` - use the specified password - `-h` - run the test against the specified host +- `--threads` - how many threads to generate test data from Honestly, I was asonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? Its amazing. ```bash -redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 SET: 173040.33 requests per second, p50=4.503 msec GET: 307031.00 requests per second, p50=2.455 msec ``` -Between the two tests we averaged 240,000 requests per second with a median time of 3.45 msec (or 0.0034 seconds) for each operation. +Between the two tests we averaged 240,000 requests per second. ## Raising the CPU clock speed -Since Valkey is a single threaded application it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. But different servers may be available with different CPU clock speeds. +Since Valkey is a single threaded application it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. Different servers may be available with different CPU clock speeds. **Note:** Clock speeds generally are only comparable between CPU's with a similar architecture. For example, you could reasonably compare clock speeds between an 12th generation Intel i5 and a 12th generation Intel i7. If the 12th gen i7 had a max clock speed of 5Ghz that doesnt necessarily mean it will be slower than a AMD Ryzen 9 9900X clocked at 5.6Ghz. @@ -91,62 +94,55 @@ If you're following along on a Pi of your own I've outlined the steps to overclo arm_freq=2200 ``` 3. Save with cmd + x, y, enter -4. Restart the server and log back in `sudo restart now` +4. Restart the Pi and log back in `sudo restart now` We've just increased the speed of the Pi by 47% by raising the clock speed from 1.5Ghz to 2.2Ghz. Now lets re-run our test and see how things look! ```bash -redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 SET: 394368.41 requests per second, p50=1.223 msec GET: 438058.53 requests per second, p50=1.135 msec ``` -We're up to 416,000 requests per second with a 1.2 msec (0.0012s) median latency. The mathmaticians out there might notice that this speed up is a lot more than the expected 47% increase. It's a 73% increase in requests per second and a 65% improvement in processing time. Whats happening?! +We're up to 416,000 requests per second (reminder this is the average between the two operations). The mathmaticians out there might notice that this speed up is a lot more than the expected 47% increase. It's a 73% increase in requests per second. What's happening?! -While I haven't gone to machine code to verify here is what I believe is happening. The memory controller for the CM4 also lives on the CPU. Increasing the clock speed of the CPU also increases the performance of the memory. This means we almost are doubling the expected speedup by increasing the clock speed. +I actually had to take this one back to the Valkey team to figure out and we've yet to figure out exactly what is happening here. ## Adding IO Threading -With all these gains I was super excited to try the new [IO threading available](https://valkey.io/blog/unlock-one-million-rps/) in Valkey 8. First we will take down the previous running docker instance with `docker compose -f valkey.yaml down`. Then we will modify the file to: +With all these gains I was super excited to try the new [IO threading available](https://valkey.io/blog/unlock-one-million-rps/) in Valkey 8. First we will take down the previous running docker instance with `docker compose -f valkey.yaml down`. Then we will modify the `.env` file's `IO_THREADS` parameter to 5. -```yaml -services: - valkey-1: - image: valkey/valkey:latest - hostname: valkey1 - command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} --io-threads 5 - volumes: - - ./data1:/data - network_mode: host +```bash +#.env +VALKEY_PASSWORD=e41fb9818502071d592b36b99f63003019861dad +NODE_IP= +IO_THREADS=5 -volumes: - data1: - driver: local ``` Then we can `docker compose -f valkey.yaml up -d` to start it again. Remote into the benchmarking server to start the test and...? ```bash -redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 SET: 345494.75 requests per second, p50=0.911 msec GET: 327858.09 requests per second, p50=0.879 msec ``` Wait a second... These results are worse than the ones before? We went from 416k requests per second to 336k.... What's happening? -![A picutre of the valkey server with 4 cores represented as boxes. In each of the four core boxes there are other boxes. 2 cores have 1 IO Thread Box, 1 Core has 2 IO thread boxes, and the last one has 1 IO Thread box along with a Valkey Process box.](images/io_threads.png) +![A picture of the valkey server with 4 cores represented as boxes. In each of the four core boxes there are other boxes. 2 cores have 1 IO Thread Box, 1 Core has 2 IO thread boxes, and the last one has 1 IO Thread box along with a Valkey Process box.](images/io_threads.png) -We have over-subscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention they are also competing with the Valkey process for resources to read IO. +We have over-subscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention, they are also competing with the Valkey process for resources to read IO. -That's why [Valkey recommends](https://github.com/valkey-io/valkey/blob/a62d1f177b7888ec88035a0a1ce600fbc2280ce7/valkey.conf#L1337-L1341) setting the number of threads to be a value less than the number of cores you have. For our little 4 core server lets set it to be 2 threads and try again. +That's why [Valkey recommends](https://github.com/valkey-io/valkey/blob/a62d1f177b7888ec88035a0a1ce600fbc2280ce7/valkey.conf#L1337-L1341) setting the number of threads to be a value less than the number of cores you have. For our little 4 core server lets change the `IO_THREADS` parameter to be 2 threads in the `.env` file and try again. ```bash -redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 SET: 609050.44 requests per second, p50=0.831 msec GET: 521186.22 requests per second, p50=0.719 msec ``` -Much better! Now we are seeing around 565,000 requests per second and 0.77 msec (0.0007s) latency for requests. Thats a 35% increase in performance across both metrics! Not to mention in the picture below you can see that we have 100% utilization across all of our CPU's which means there's no more room for improvement! +Much better! Now we are seeing around 565,000 requests per second. Thats a 35% increase in performance across both metrics! Not to mention in the picture below you can see that we have 100% utilization across all of our CPU's which means there's no more room for improvement! ![A picture of an HTOP window showing all four of our CPU's at 100% utilization.](images/io_threading_htop.png) @@ -164,7 +160,7 @@ What we are going to do is spin up a Valkey cluster. This cluster will have indi I am not going into detail with how the keyspaces work but [here is a good 101 guide](https://valkey.io/topics/cluster-tutorial/) for understanding clustering in Valkey. -Let's to stop our previous Valkey container. Now we can create our docker compose file for starting the cluster. There are a few things I want to point out here. Because each of these are exposed on the host they will all need to be using different ports. Additionally, all of them need to be aware they are started in cluster mode so they can redirect requests to the appropriate instance. +Lets stop our previous Valkey container. Now we can create our docker compose file for starting the cluster. There are a few things I want to point out here. Because each of these are exposed on the host they will all need to be using different ports. Additionally, all of them need to be aware they are started in cluster mode so they can redirect requests to the appropriate instance. ```yaml # valkey-cluster.yaml @@ -214,7 +210,7 @@ kvtest-valkey-node-3-1 kvtest-valkey-node-2-1 ``` -I'll use the first one to finish the cluster creation. Once the containers have started up we have to tell them the details they need to use for the cluster. Below I am using the IP of the host and the port configurations of all the containers to create the cluster. This is because these addresses need to be accessible from the benchmarking or application servers. +I'll use the first container to finish the cluster creation. Once the containers have started up we have to tell them the details they need to use for the cluster. Below I am using the IP of the host and the port configurations of all the containers to create the cluster. This is because these addresses need to be accessible from the benchmarking or application servers. ```bash docker exec -it kvtest-valkey-node-1-1 valkey-cli --cluster create 10.0.1.136:6379 10.0.1.136:6380 10.0.1.136:6381 -a e41fb9818502071d592b36b99f63003019861dad @@ -223,7 +219,7 @@ docker exec -it kvtest-valkey-node-1-1 valkey-cli --cluster create 10.0.1.136:63 Once that command is run we can run our benchmark! We do need to add the `--cluster` flag as well as several threads to generate data fast enough. Also, because this is so fast I ended up moving from 1 million requests to 10 million requests. That way it has time to fully utilize all the resources. ```bash -redis-benchmark -n 10000000 -t set,get -P 16 -q --threads 10 --cluster -a e41fb9818502071d592b36b99f63003019861dad -h 10.0.1.136 +redis-benchmark -n 10000000 -t set,get -P 16 -q --threads 10 --cluster -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 Cluster has 3 master nodes: Master 0: 219294612b44226fa32482871cf21025ff531875 10.0.1.136:6380 @@ -234,6 +230,6 @@ SET: 1122838.50 requests per second, p50=0.575 msec GET: 1188071.75 requests per second, p50=0.511 msec ``` -**1,155,000 requests per second**. **0.543 msec (0.0005s) latency**. We've managed to double our requests per second and improved our latency by nearly 30% again. All this on a single board computer that's the size of a credit card. +**1,155,000 requests per second**. We've managed to double our requests per second. All this on a single board computer that's the size of a credit card. While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important to start testing with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding more compute. Some other areas I'd reccomend testing is with different pipelineing configurations or with the number of client connections that you anticipate you'd be using in production. If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! From 796ed489573a3b59537b0e7023ea9868b3c686b6 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 28 Oct 2024 09:16:32 -0400 Subject: [PATCH 07/22] updates for clarity Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 8f1e75d..da98148 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -59,7 +59,7 @@ redis-benchmark -n 1000000 -t set,get -P 16 -q -a --threads ``` Test breakdown: -- `-n` - this will run 1,000,000 operations using the commands set in -t +- `-n` - this will run 1,000,000 operations using the commands in -t - `-t` - will run the set and get tests - `-P` - this specifies that we would like the tests to use 16 pipelines (send 16 operations per request). - `-q` - silences the output to show only the final results @@ -67,7 +67,7 @@ Test breakdown: - `-h` - run the test against the specified host - `--threads` - how many threads to generate test data from -Honestly, I was asonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? Its amazing. +Honestly, I was asonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? It's amazing. ```bash redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 @@ -81,7 +81,7 @@ Between the two tests we averaged 240,000 requests per second. Since Valkey is a single threaded application it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. Different servers may be available with different CPU clock speeds. -**Note:** Clock speeds generally are only comparable between CPU's with a similar architecture. For example, you could reasonably compare clock speeds between an 12th generation Intel i5 and a 12th generation Intel i7. If the 12th gen i7 had a max clock speed of 5Ghz that doesnt necessarily mean it will be slower than a AMD Ryzen 9 9900X clocked at 5.6Ghz. +**Note:** Clock speeds generally are only comparable between CPU's with a similar architecture. For example, you could reasonably compare clock speeds between an 12th generation Intel i5 and a 12th generation Intel i7. If the 12th gen i7 had a max clock speed of 5Ghz that doesn't necessarily mean it will be slower than a AMD Ryzen 9 9900X clocked at 5.6Ghz. If you're following along on a Pi of your own I've outlined the steps to overclock your CM4 below. Otherwise you can skip to the results section below. @@ -132,7 +132,7 @@ Wait a second... These results are worse than the ones before? We went from 416k ![A picture of the valkey server with 4 cores represented as boxes. In each of the four core boxes there are other boxes. 2 cores have 1 IO Thread Box, 1 Core has 2 IO thread boxes, and the last one has 1 IO Thread box along with a Valkey Process box.](images/io_threads.png) -We have over-subscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention, they are also competing with the Valkey process for resources to read IO. +We have over-subscribed our CPU. This means we've created more worker threads than CPU cores. When a thread is under constant load it is competing with other threads on that core for resources. Not to mention, they are also competing with the Valkey process for resources. That's why [Valkey recommends](https://github.com/valkey-io/valkey/blob/a62d1f177b7888ec88035a0a1ce600fbc2280ce7/valkey.conf#L1337-L1341) setting the number of threads to be a value less than the number of cores you have. For our little 4 core server lets change the `IO_THREADS` parameter to be 2 threads in the `.env` file and try again. @@ -150,7 +150,9 @@ Right? Well believe it or not we can squeeze even more performance out of our li ![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first core box is the Valkey process and in the next two there are IO Threads. The valkey process has a loop showing it communiacting with both of the IO threads. It also has a bracket showing it managing all the memory.](images/io_threading_arch.png) -Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. +Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. + +Now there is actually one more optimization we can use to make single threaded Valkey even faster. Pinning threads ## Clustered Valkey From 9842c15404d0740b43636ef1aad3c49facf65b68 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 28 Oct 2024 18:47:05 -0400 Subject: [PATCH 08/22] Adding stats for io threading Signed-off-by: David Tippett --- .../2024-10-21-testing-the-limits/index.md | 32 +++++++++++-------- 1 file changed, 19 insertions(+), 13 deletions(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index da98148..b57f2a3 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -152,25 +152,31 @@ Right? Well believe it or not we can squeeze even more performance out of our li Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. -Now there is actually one more optimization we can use to make single threaded Valkey even faster. Pinning threads +Now there is actually one more optimization we can use to make single threaded Valkey even faster. Valkey recently has done a substantial amount of work to support speculative execution. This work allows Valkey to predict which values will be needed from memory in future processing steps. This way Valkey server does't have to wait for memory access which is an order of magnitude slower than L1 caches. While I won't go through the details of how this works as there's already a [great blog that describes how to take advanage of these optimizations](https://valkey.io/blog/unlock-one-million-rps-part2/) here are the results: + +```bash +redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 +SET: 632791.25 requests per second, p50=1.191 msec +GET: 888573.00 requests per second, p50=0.695 msec +``` + +While these results are better they are a bit confusing. After talking with some of Valkey's maintainers it seems there may be something different in the way that Rasbian is configured when it comes to memory writes. In their testing the `GET/SET` requests were nearly identical but in my testing so far the write speed seems to always be behind read speed. If you think you know why please reach out! ## Clustered Valkey ![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first three core boxs are Valkey processes. Each of them has a bracket around a portion of the memory.](images/valkey_clustered.png) -What we are going to do is spin up a Valkey cluster. This cluster will have individual instances of Valkey runnning that each will be responsible for managing their own keys. With this method Valkey instaces are not waiting on IO threads to return data. They each read from their own IO and can access memory as soon as they get a request. +For our last step we are going to spin up a Valkey cluster. This cluster will have individual instances of Valkey runnning that each will be responsible for managing their own keys. This way each instance can execute operations in parallel much more easily. I am not going into detail with how the keyspaces work but [here is a good 101 guide](https://valkey.io/topics/cluster-tutorial/) for understanding clustering in Valkey. -Lets stop our previous Valkey container. Now we can create our docker compose file for starting the cluster. There are a few things I want to point out here. Because each of these are exposed on the host they will all need to be using different ports. Additionally, all of them need to be aware they are started in cluster mode so they can redirect requests to the appropriate instance. +First we'll stop our previous Valkey container `docker compose -f valkey.yaml down`. Now we can create our docker compose file for the cluster. Because each of these are exposed on the host they will all need to be using different ports. Additionally, all of them need to be aware they are started in cluster mode so they can redirect requests to the appropriate instance. ```yaml # valkey-cluster.yaml services: valkey-node-1: hostname: valkey1 - environment: - - ALLOW_EMPTY_PASSWORD=yes image: valkey/valkey:latest command: valkey-server --port 6379 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} volumes: @@ -178,8 +184,6 @@ services: network_mode: host valkey-node-2: hostname: valkey2 - environment: - - ALLOW_EMPTY_PASSWORD=yes image: valkey/valkey:latest command: valkey-server --port 6380 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} volumes: @@ -187,8 +191,6 @@ services: network_mode: host valkey-node-3: hostname: valkey3 - environment: - - ALLOW_EMPTY_PASSWORD=yes image: valkey/valkey:latest command: valkey-server --port 6381 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} volumes: @@ -203,7 +205,7 @@ volumes: data2: driver: local ``` -Run `docker compose -f valkey-cluster.yaml up -d` to start the cluster. There is one more step to get the cluster running. First, find the name of one of your nodes with `docker ps --format '{{.Names}}'`. +Run `docker compose -f valkey-cluster.yaml up -d` to start the cluster. There is one more step to get the cluster running. Find the name of one of your nodes with `docker ps --format '{{.Names}}'`. ```bash docker ps --format '{{.Names}} @@ -212,13 +214,13 @@ kvtest-valkey-node-3-1 kvtest-valkey-node-2-1 ``` -I'll use the first container to finish the cluster creation. Once the containers have started up we have to tell them the details they need to use for the cluster. Below I am using the IP of the host and the port configurations of all the containers to create the cluster. This is because these addresses need to be accessible from the benchmarking or application servers. +I'll use the first container to finish the cluster creation. Once the containers have started up we have to tell them the details they need to use for the cluster. Below I am using the IP of the host and the port configurations of all the containers to create the cluster. This is because these addresses need to be accessible from the benchmarking server. ```bash docker exec -it kvtest-valkey-node-1-1 valkey-cli --cluster create 10.0.1.136:6379 10.0.1.136:6380 10.0.1.136:6381 -a e41fb9818502071d592b36b99f63003019861dad ``` -Once that command is run we can run our benchmark! We do need to add the `--cluster` flag as well as several threads to generate data fast enough. Also, because this is so fast I ended up moving from 1 million requests to 10 million requests. That way it has time to fully utilize all the resources. +Now we can run our benchmark! We need to add the `--cluster` flag to our benchmarking command. Also, because this is so fast I ended up moving from 1 million requests to 10 million requests. That way we can make sure Valkey has time to fully utilize all it's resources. ```bash redis-benchmark -n 10000000 -t set,get -P 16 -q --threads 10 --cluster -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 @@ -234,4 +236,8 @@ GET: 1188071.75 requests per second, p50=0.511 msec **1,155,000 requests per second**. We've managed to double our requests per second. All this on a single board computer that's the size of a credit card. -While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important to start testing with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding more compute. Some other areas I'd reccomend testing is with different pipelineing configurations or with the number of client connections that you anticipate you'd be using in production. If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! +While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. + +Testing should mirror your production workload as best it can. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! + +If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! From da5a94e92fbe189f35395d750b3e4bc319a3caa3 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 15:02:11 -0400 Subject: [PATCH 09/22] Addressing editorial comments. Signed-off-by: David Tippett --- .../2024-10-21-testing-the-limits/index.md | 19 +++++++++---------- 1 file changed, 9 insertions(+), 10 deletions(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index b57f2a3..1697eb1 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -1,17 +1,17 @@ +++ title = "Pushing the limits of Valkey on a Raspberry Pi" -description = "While most people won't go to produciton on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it works in production." +description = "While most people won't go to prodcution on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it works in production." date= 2024-10-21 01:01:01 authors= ["dtaivpp"] +++ -While doing extensive performance testing on a Raspberry PI is silly, it's made me realize the complexity of performance testing. For example, in some of the tests below I ended up managing to use all of the resources of the Raspberry Pi and achieved terrible performance. Every application has different performance characteristics so we'll walk though what factors to consider when it comes to deploying Valkey. +While doing extensive performance testing on a Raspberry Pi is silly, it's made me realize the complexity of performance testing. For example, in some of the tests below I ended up managing to use all of the resources of the Raspberry Pi and achieved terrible performance. Every application has different performance characteristics so we'll walk through what factors to consider when it comes to deploying Valkey. ## The test environment ![Picture of the Compute Module 4 credit Raspberry Pi Ltd (CC BY-SA)](images/cm4.png) -For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](https://www.raspberrypi.com/products/compute-module-4/?variant=raspberry-pi-cm4001000). It's a single board computer (SBC) that comes with a tiny 1.5Ghz 4 core Broadcomm CPU and 8GB of system memory. This is hardly the first device someone would pick when deciding on a production system. Using the CM4 makes it easy to showcase how to optimize Valkey depending on your different hardware constraints. +For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](https://www.raspberrypi.com/products/compute-module-4/?variant=raspberry-pi-cm4001000). It's a single board computer (SBC) that comes with a tiny 1.5Ghz 4-core Broadcomm CPU and 8GB of system memory. This is hardly the first device someone would pick when deciding on a production system. Using the CM4 makes it easy to showcase how to optimize Valkey depending on your different hardware constraints. Our operating system will be a 64-bit debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. @@ -67,7 +67,7 @@ Test breakdown: - `-h` - run the test against the specified host - `--threads` - how many threads to generate test data from -Honestly, I was asonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? It's amazing. +Honestly, I was astonished by the first set of results I got. Sure, I expected Valkey to be fast but this speed from a single board computer?? ON A SINGLE THREAD?? It's amazing. ```bash redis-benchmark -n 1000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 @@ -85,16 +85,17 @@ Since Valkey is a single threaded application it makes sense that higher clock s If you're following along on a Pi of your own I've outlined the steps to overclock your CM4 below. Otherwise you can skip to the results section below. -1. Open the below file in a text editor like nano. +**Warning** Just a reminder overclocking your device can cause damage to your device. Please use caution and do your own research for settings that are safe. + +1. Open the below file - `sudo nano /boot/firmware/config.txt` -2. At the end of the file add this section below the `[all]` tag. +2. At the end of the file add this section below the `[all]` tag ``` [all] over_voltage=8 arm_freq=2200 ``` -3. Save with cmd + x, y, enter -4. Restart the Pi and log back in `sudo restart now` +3. Restart the Pi and log back in `sudo restart now` We've just increased the speed of the Pi by 47% by raising the clock speed from 1.5Ghz to 2.2Ghz. Now lets re-run our test and see how things look! @@ -106,8 +107,6 @@ GET: 438058.53 requests per second, p50=1.135 msec We're up to 416,000 requests per second (reminder this is the average between the two operations). The mathmaticians out there might notice that this speed up is a lot more than the expected 47% increase. It's a 73% increase in requests per second. What's happening?! -I actually had to take this one back to the Valkey team to figure out and we've yet to figure out exactly what is happening here. - ## Adding IO Threading With all these gains I was super excited to try the new [IO threading available](https://valkey.io/blog/unlock-one-million-rps/) in Valkey 8. First we will take down the previous running docker instance with `docker compose -f valkey.yaml down`. Then we will modify the `.env` file's `IO_THREADS` parameter to 5. From a61cfdf897ad875f72ffdede6d27415fa02ed0a0 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 15:08:07 -0400 Subject: [PATCH 10/22] Calling out this test uses synthetic data. Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 1697eb1..2263882 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -237,6 +237,6 @@ GET: 1188071.75 requests per second, p50=0.511 msec While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. -Testing should mirror your production workload as best it can. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! +Testing should mirror your production workload as best it can. This test is using syntehtic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! From 79b1e94a46792406fd85ff5485bfa72815ceaa10 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 15:19:03 -0400 Subject: [PATCH 11/22] Calling out that threading may work differently when not using syntehtic data Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 2263882..cdd1078 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -237,6 +237,6 @@ GET: 1188071.75 requests per second, p50=0.511 msec While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. -Testing should mirror your production workload as best it can. This test is using syntehtic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! +Testing should mirror your production workload as best it can. This test is using syntehtic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! You may find that IO threading works better for your use case than I did in this case. If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! From 46f18b315130a6505dbe39c53150cc40c22a910c Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:52:43 -0400 Subject: [PATCH 12/22] Removing saving Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index cdd1078..e0d9f27 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -29,7 +29,7 @@ services: valkey-1: image: valkey/valkey:latest hostname: valkey1 - command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} --io-threads ${IO_THREADS} + command: valkey-server --port 6379 --requirepass ${VALKEY_PASSWORD} --io-threads ${IO_THREADS} --save "" volumes: - ./data:/data network_mode: host @@ -177,21 +177,21 @@ services: valkey-node-1: hostname: valkey1 image: valkey/valkey:latest - command: valkey-server --port 6379 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + command: valkey-server --port 6379 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} --save "" volumes: - ./data1:/data network_mode: host valkey-node-2: hostname: valkey2 image: valkey/valkey:latest - command: valkey-server --port 6380 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + command: valkey-server --port 6380 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} --save "" volumes: - ./data2:/data network_mode: host valkey-node-3: hostname: valkey3 image: valkey/valkey:latest - command: valkey-server --port 6381 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} + command: valkey-server --port 6381 --cluster-enabled yes --cluster-config-file nodes.conf --cluster-node-timeout 5000 --requirepass ${VALKEY_PASSWORD} --save "" volumes: - ./data3:/data network_mode: host From 6e2e923facf994139dd9a210c70d1f1ca497058a Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:53:49 -0400 Subject: [PATCH 13/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index e0d9f27..c43d7cf 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -237,6 +237,6 @@ GET: 1188071.75 requests per second, p50=0.511 msec While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. -Testing should mirror your production workload as best it can. This test is using syntehtic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! You may find that IO threading works better for your use case than I did in this case. +Testing should mirror your production workload as best it can. This test is using synthetic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! You may find that IO threading works better for your use case than I did in this case. If you enjoyed this read make sure to check out my blog [TippyBits.com](https://tippybits.com) where I post content like this on a regular basis. Stay curious my friends! From 451ba4c3e29c38c93a48c45d517cd1a0fe556659 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:53:58 -0400 Subject: [PATCH 14/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index c43d7cf..c87f374 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -165,7 +165,7 @@ While these results are better they are a bit confusing. After talking with some ![A picture of our Valkey server with the 4 core boxes and to the right of them is a memory box. In the first three core boxs are Valkey processes. Each of them has a bracket around a portion of the memory.](images/valkey_clustered.png) -For our last step we are going to spin up a Valkey cluster. This cluster will have individual instances of Valkey runnning that each will be responsible for managing their own keys. This way each instance can execute operations in parallel much more easily. +For our last step we are going to spin up a Valkey cluster. This cluster will have individual instances of Valkey running that each will be responsible for managing their own keys. This way each instance can execute operations in parallel much more easily. I am not going into detail with how the keyspaces work but [here is a good 101 guide](https://valkey.io/topics/cluster-tutorial/) for understanding clustering in Valkey. From 2162ed911e77ba2d82506fcd60eda2d2b2fedc9d Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:54:11 -0400 Subject: [PATCH 15/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index c87f374..70dda2c 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -151,7 +151,7 @@ Right? Well believe it or not we can squeeze even more performance out of our li Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. -Now there is actually one more optimization we can use to make single threaded Valkey even faster. Valkey recently has done a substantial amount of work to support speculative execution. This work allows Valkey to predict which values will be needed from memory in future processing steps. This way Valkey server does't have to wait for memory access which is an order of magnitude slower than L1 caches. While I won't go through the details of how this works as there's already a [great blog that describes how to take advanage of these optimizations](https://valkey.io/blog/unlock-one-million-rps-part2/) here are the results: +Now there is actually one more optimization we can use to make single threaded Valkey even faster. Valkey recently has done a substantial amount of work to support speculative execution. This work allows Valkey to predict which values will be needed from memory in future processing steps. This way Valkey server doesn't have to wait for memory access which is an order of magnitude slower than L1 caches. While I won't go through the details of how this works as there's already a [great blog that describes how to take advantage of these optimizations](https://valkey.io/blog/unlock-one-million-rps-part2/) here are the results: ```bash redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136 From 668e2832dc00c71daf296c914ec5e7da32bd905b Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:54:19 -0400 Subject: [PATCH 16/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 70dda2c..54c0f14 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -235,7 +235,7 @@ GET: 1188071.75 requests per second, p50=0.511 msec **1,155,000 requests per second**. We've managed to double our requests per second. All this on a single board computer that's the size of a credit card. -While this is far from what I would recommend for a production server these are the same steps I'd reccomend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. +While this is far from what I would recommend for a production server these are the same steps I'd recommend to someone evaluating Valkey. It's important test with a single instance to start finding the optimal settings. Then you can begin to scale up your test by adding either more IO Threads or Valkey instances. Testing should mirror your production workload as best it can. This test is using synthetic data. That's why I'd recommend checking out the documentation to find what other settings you may need to test with. For example, we tested with the default settings of 50 client connections and 3 byte payloads. Your production workload may look different so explore all the settings! You may find that IO threading works better for your use case than I did in this case. From cfc97e73163eb52b6e09efb55146441bdf1c5bf4 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:54:43 -0400 Subject: [PATCH 17/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 54c0f14..e6dc34d 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -39,7 +39,7 @@ volumes: driver: local ``` -Since we are exposing this to our internal network we will create a password for our default user. I used `head -16 /dev/urandom | openssl sha1` to generate a random password. Because of how fast Valkey can process requests a brute force attack could try hundereds of thousands of passwords per second. After generating that password I put it in a `.env` file in the same directory as our docker compose. +Since we are exposing this to our internal network we will create a password for our default user. I used `head -16 /dev/urandom | openssl sha1` to generate a random password. Because of how fast Valkey can process requests a brute force attack could try hundreds of thousands of passwords per second. After generating that password, I put it in a `.env` file in the same directory as our docker compose. ```bash #.env From 945a8b921aa0b9068340919e015576b764073958 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:54:50 -0400 Subject: [PATCH 18/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index e6dc34d..3ac0745 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -79,7 +79,7 @@ Between the two tests we averaged 240,000 requests per second. ## Raising the CPU clock speed -Since Valkey is a single threaded application it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. Different servers may be available with different CPU clock speeds. +Since Valkey is a single threaded application, it makes sense that higher clock speeds would lead to more performance. I don't expect most people will overclock their servers in production. Different servers may be available with different CPU clock speeds. **Note:** Clock speeds generally are only comparable between CPU's with a similar architecture. For example, you could reasonably compare clock speeds between an 12th generation Intel i5 and a 12th generation Intel i7. If the 12th gen i7 had a max clock speed of 5Ghz that doesn't necessarily mean it will be slower than a AMD Ryzen 9 9900X clocked at 5.6Ghz. From b2be3d865a6a0df3f52b3d5cce96be438295f405 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:55:06 -0400 Subject: [PATCH 19/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 3ac0745..90eefb0 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -15,7 +15,7 @@ For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](ht Our operating system will be a 64-bit debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. -We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have it's own benchmark utility that comes installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. +We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have its own benchmark utility that comes installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. ![Test architecture showing two nodes: a Benchmark server with the ip of 10.0.11.221 with an arrow pointing to a Valkey server with an ip of 10.0.1.136](images/test_setup.png) From 93762f21f7f64b8ecabd84eb281d5da54724ab58 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Wed, 30 Oct 2024 16:55:25 -0400 Subject: [PATCH 20/22] Update content/blog/2024-10-21-testing-the-limits/index.md Co-authored-by: Madelyn Olson Signed-off-by: David Tippett --- content/blog/2024-10-21-testing-the-limits/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-10-21-testing-the-limits/index.md index 90eefb0..e8b4d3e 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-10-21-testing-the-limits/index.md @@ -13,7 +13,7 @@ While doing extensive performance testing on a Raspberry Pi is silly, it's made For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](https://www.raspberrypi.com/products/compute-module-4/?variant=raspberry-pi-cm4001000). It's a single board computer (SBC) that comes with a tiny 1.5Ghz 4-core Broadcomm CPU and 8GB of system memory. This is hardly the first device someone would pick when deciding on a production system. Using the CM4 makes it easy to showcase how to optimize Valkey depending on your different hardware constraints. -Our operating system will be a 64-bit debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. +Our operating system will be a 64-bit Debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have its own benchmark utility that comes installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. From bbfecbf9b6301d20e8f6740be38e87963c1c170f Mon Sep 17 00:00:00 2001 From: Madelyn Olson Date: Fri, 1 Nov 2024 15:56:54 -0700 Subject: [PATCH 21/22] Add quicklink to the github page to make edits Signed-off-by: Madelyn Olson --- templates/command-page.html | 9 ++++++++- templates/docs-page.html | 9 ++++++++- 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/templates/command-page.html b/templates/command-page.html index f632909..eff33a8 100644 --- a/templates/command-page.html +++ b/templates/command-page.html @@ -93,4 +93,11 @@

History

{% endif %} -{% endblock main_content %} \ No newline at end of file +{% endblock main_content %} + +{% block related_content %} +
+{% endblock related_content %} diff --git a/templates/docs-page.html b/templates/docs-page.html index 4060f55..a56ac01 100644 --- a/templates/docs-page.html +++ b/templates/docs-page.html @@ -38,4 +38,11 @@

Documentation: {{ frontmatter_title }}

{% else %} {{ content_with_fixed_links | markdown | safe }} {% endif %} -{% endblock main_content %} \ No newline at end of file +{% endblock main_content %} + +{% block related_content %} +
+ See an error? + Update this Page on Github! +
+{% endblock related_content %} \ No newline at end of file From b8440f118b1b9eb34fe49075958b3aac437dba3c Mon Sep 17 00:00:00 2001 From: "Kyle J. Davis" Date: Thu, 21 Nov 2024 15:24:50 -0700 Subject: [PATCH 22/22] Fixes pub date and small typos before publishing Signed-off-by: Kyle J. Davis --- content/authors/dtaivpp.md | 2 +- .../images/cm4.png | Bin .../images/io_threading_arch.png | Bin .../images/io_threading_htop.png | Bin .../images/io_threads.png | Bin .../images/test_setup.png | Bin .../images/valkey_clustered.png | Bin .../index.md | 6 +++--- 8 files changed, 4 insertions(+), 4 deletions(-) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/cm4.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/io_threading_arch.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/io_threading_htop.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/io_threads.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/test_setup.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/images/valkey_clustered.png (100%) rename content/blog/{2024-10-21-testing-the-limits => 2024-11-21-testing-the-limits}/index.md (97%) diff --git a/content/authors/dtaivpp.md b/content/authors/dtaivpp.md index aff569f..c076a03 100644 --- a/content/authors/dtaivpp.md +++ b/content/authors/dtaivpp.md @@ -5,4 +5,4 @@ extra: github: dtaivpp --- -David Tippett currently is building search at GitHub. He has nearly a decade of experience building data systems to make search more understandable, systems more observable, and infrastructure more robust. If you enjoy open source or reading technical deeps dives make sure to check out his website [TippyBits.com](https://tippybits.com). \ No newline at end of file +David Tippett currently is building search at GitHub. He has nearly a decade of experience building data systems to make search more understandable, systems more observable, and infrastructure more robust. If you enjoy open source or reading technical deep dives make sure to check out his website [TippyBits.com](https://tippybits.com). \ No newline at end of file diff --git a/content/blog/2024-10-21-testing-the-limits/images/cm4.png b/content/blog/2024-11-21-testing-the-limits/images/cm4.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/cm4.png rename to content/blog/2024-11-21-testing-the-limits/images/cm4.png diff --git a/content/blog/2024-10-21-testing-the-limits/images/io_threading_arch.png b/content/blog/2024-11-21-testing-the-limits/images/io_threading_arch.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/io_threading_arch.png rename to content/blog/2024-11-21-testing-the-limits/images/io_threading_arch.png diff --git a/content/blog/2024-10-21-testing-the-limits/images/io_threading_htop.png b/content/blog/2024-11-21-testing-the-limits/images/io_threading_htop.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/io_threading_htop.png rename to content/blog/2024-11-21-testing-the-limits/images/io_threading_htop.png diff --git a/content/blog/2024-10-21-testing-the-limits/images/io_threads.png b/content/blog/2024-11-21-testing-the-limits/images/io_threads.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/io_threads.png rename to content/blog/2024-11-21-testing-the-limits/images/io_threads.png diff --git a/content/blog/2024-10-21-testing-the-limits/images/test_setup.png b/content/blog/2024-11-21-testing-the-limits/images/test_setup.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/test_setup.png rename to content/blog/2024-11-21-testing-the-limits/images/test_setup.png diff --git a/content/blog/2024-10-21-testing-the-limits/images/valkey_clustered.png b/content/blog/2024-11-21-testing-the-limits/images/valkey_clustered.png similarity index 100% rename from content/blog/2024-10-21-testing-the-limits/images/valkey_clustered.png rename to content/blog/2024-11-21-testing-the-limits/images/valkey_clustered.png diff --git a/content/blog/2024-10-21-testing-the-limits/index.md b/content/blog/2024-11-21-testing-the-limits/index.md similarity index 97% rename from content/blog/2024-10-21-testing-the-limits/index.md rename to content/blog/2024-11-21-testing-the-limits/index.md index e8b4d3e..3f9b6ff 100644 --- a/content/blog/2024-10-21-testing-the-limits/index.md +++ b/content/blog/2024-11-21-testing-the-limits/index.md @@ -1,7 +1,7 @@ +++ title = "Pushing the limits of Valkey on a Raspberry Pi" description = "While most people won't go to prodcution on a Raspberry Pi we'll cover how to thoroughly performance test Valkey to understand how it works in production." -date= 2024-10-21 01:01:01 +date= 2024-11-21 01:01:01 authors= ["dtaivpp"] +++ @@ -15,7 +15,7 @@ For hardware we are going to be using a Raspberry Pi [Compute Module 4 (CM4)](ht Our operating system will be a 64-bit Debian based operating system (OS) called [Rasbian](https://www.raspbian.org/). This distribution is specifically modified to perform well on the CM4. Valkey will run in a docker container orchestrated with docker compose. I like deploying in containers as it simplifies operations. If you'd like to follow along here is [a guide for installing Docker](https://docs.docker.com/engine/install/debian/). Make sure to continue to the [second page of the installation process](https://docs.docker.com/engine/install/linux-postinstall/) as well. It's easy to miss and skipping it could make it harder to follow along. -We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have its own benchmark utility that comes installed Valkey instance. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. +We'll be using two CM4s for testing. The first will host Valkey and the second will host the benchmarking software. This setup probably better reflects how most people will run in production. Benchmarking is being done with redis-benchmark because it can be installed with `sudo apt install redis-tools`. Valkey does have its own benchmark utility that comes installed with Valkey. To use valkey-benchmark instead you would need to install Valkey on the benchmarking server or spin up a container and connect into it. Functionally, they both operate nearly the same as of the writing of this article. ![Test architecture showing two nodes: a Benchmark server with the ip of 10.0.11.221 with an arrow pointing to a Valkey server with an ip of 10.0.1.136](images/test_setup.png) @@ -151,7 +151,7 @@ Right? Well believe it or not we can squeeze even more performance out of our li Above is a representitive outline of what's happening on the server. The Valkey process has to take up valuble cycles managing the IO Threads. Not only that it has to perform a lot of work to manage all the memory assigned to it. That's a lot of work for a single process. -Now there is actually one more optimization we can use to make single threaded Valkey even faster. Valkey recently has done a substantial amount of work to support speculative execution. This work allows Valkey to predict which values will be needed from memory in future processing steps. This way Valkey server doesn't have to wait for memory access which is an order of magnitude slower than L1 caches. While I won't go through the details of how this works as there's already a [great blog that describes how to take advantage of these optimizations](https://valkey.io/blog/unlock-one-million-rps-part2/) here are the results: +Now there is actually one more optimization we can use to make single threaded Valkey even faster. Valkey recently has done a substantial amount of work to support speculative execution. This work allows Valkey to predict which values will be needed from memory in future processing steps. This way Valkey server doesn't have to wait for memory access which is an order of magnitude slower than L1 caches. While I won't go through the details of how this works as there's already a [great blog that describes how to take advantage of these optimizations](https://valkey.io/blog/unlock-one-million-rps-part2/). Here are the results: ```bash redis-benchmark -n 10000000 -t set,get -P 16 -q -a e41fb9818502071d592b36b99f63003019861dad --threads 5 -h 10.0.1.136

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