When benchmarking a mysql clustering using sysbench, do you have to install sysbench on every machine in the cluster to benchmark the cluster performance? Is there a way to install sysbench on one machine and use it to benchmark other mysql servers on different machines?
If, for example i have HAProxy as the load balancer for the cluster which is configured on its own machine separate from the cluster nodes, then can you use the HAProxy machine only to benchmark the entire cluster since HAProxy machine will be doing the load balancing and acts as the window to all other cluster nodes?
I am knew to MySQL benchmarking, and new to using sysbench.
Thanks.
Yes, you will need to install sysbench on every SQL node, your intending to use and benchmark. (not the NDB data node).
HAProxy & ProxySQL are two different things but you can get the best of both worlds if you really want to.
HAProxy is a very fast and reliable solution offering high availability, load balancing, and proxying for TCP and HTTP-based applications. It is particularly suited for very high traffic web-sites and powers quite a number of the world's most visited ones. HAProxy(High Availability Proxy) is an open source load balancer which can load balance any TCP service. It is particularly suited for HTTP load balancing as it supports session persistence and layer 7 processing.
ProxySQL is an open-source MySQL proxy server, meaning it serves as an intermediary between a MySQL server and the applications that access its databases. ProxySQL can improve performance by distributing traffic among a pool of multiple database servers and also improve availability by automatically failing over to a standby if one or more of the database servers fail.
To run the sysbench benchmarks, follow this guide:
https://wiki.gentoo.org/wiki/Sysbench
To setup the ProxySQL:
https://www.digitalocean.com/community/tutorials/how-to-use-proxysql-as-a-load-balancer-for-mysql-on-ubuntu-16-04
Set Up Highly Available HAProxy Servers with Keepalived and Floating IPs: https://www.digitalocean.com/community/tutorials/how-to-set-up-highly-available-haproxy-servers-with-keepalived-and-floating-ips-on-ubuntu-14-04
To create multi-node SQL Cluster: https://www.digitalocean.com/community/tutorials/how-to-create-a-multi-node-mysql-cluster-on-ubuntu-16-04
Set the engine to use sysbench - ENGINE=NDBCLUSTER; on mysql client.
you will need to create database and then prepare the sysbench before running it. Good luck!
Related
As I found, the best way to have zero down time even when one datacenter is down, is using kubernetes between at least two servers from two datacenters.
So because I wanted to use servers in Iran. I've heard low performance about infrastructure.
The question is that if I want to have master-master replication for mysql, in one server failure, how can I sync repaired server in kubernetes clustring?
K8s is the platform, it doesn't change how MySQL HA works. Example, if you have dedicated servers for MySQL, these servers become "pods" in K8s. What you need to do at MySQL level when any of the server is gone for whatever reason; is the same as what you need to do when you run it as a pod. In fact, K8s help you by automatically start a new pod. Where in former case, you will need to provision a new physical server - the time required is obvious here. You will normally run script to re-establish the HA, the same apply to K8s where you can run the recovery script as the init container before the actual MySQL server container is started.
I am running Django Rest API on an AWS ec2-server. Right now the Api's are using MySql localhost database. Should I shift my database from MySql localhost to Amazon RDS instance?
As per what I Know for remote servers would take a little extra time to transmit the request and shared resources. Would this little extra time be worth migrating my database from MySql localhost to Amazon RDS instance?
I read this answer but it didn't helped me much.
MySql localhost vs Amazon RDS instance
An answer with all possible Pros and Cons will really be appreciated.
Pros for local MySQL
Slightly faster, because of proximity to the application
Cons for local MySQL
Not Easily Scalable
If you want to use autoscaling for your application load and traffic then you might have nightmares, because as you scale you will have even the MySQL servers running on each new node.
Pros for RDS
You don't have to worry about installing and maintaining MySQL server
You don't have to worry about scaling
You don't have to worry about load balancing
You don't have to worry about EC2 upgrades and patching
You don't have to worry about failure recovery because when you provision a Multi-AZ DB Instance, Amazon RDS synchronously replicates the data to a standby instance in a different Availability Zone (AZ)List item
Cons for RDS
Slightly slower due to network latency
It depends how database intensive your application is.
See this benchmark The local database blew RDS out of the water on query latency with low load.
The answer is probably use both? Use both a local Redis/MySQL for quick queries and an off server RDS for long queries over large data sets where paying the additional network latency makes sense.
Also think about using SQLite on S3. If you can easily shard your data, and most queries are read intensive it could be a lot cheaper, especially with something like Redis on the server to cache frequent queries.
If you want to really eek out performance per $$, you can use a lot of Pang's tricks by having a hierarchy of SQLite files.
I host my two MySql databases on Amazon RDS, which is db.m3.medium and db.r3.large having 5.6.27 innodb engine. Now I want to know, how many concurrent connections these instances can handle? How to load test it? What will be the impact if 1000 concurrent users access the databases?
It depends on many factors like MySQL servers configuration, data volumes, nature of requests, etc. The only way to tell it for sure is simulating your 1000 users with a load testing tool.
Few examples:
Tsung -> MySQL
Apache JMeter -> The Real Secret to Building a Database Test Plan With JMeter
Grinder -> Grinding a database with JDBC
If you will be happy with the databases performance with 1000 users you can gradually increase the load to identify the breaking point
I have the following situation:
I have to set up a high-performance server-cluster with maximum availability with nginx and MySQL. The cluster consists of four web servers which are load ballanced with nginx+gluster which works just fine.
In addition there's another server with 2 SSDs in RAID1. On that server I intend to install 2 VMs each with 12GB of RAM where I set up the MySQL cluster with Master-Master replication.
But that only prevents the system to break down if the MySQL service breaks down on one of the VMs, not if the host system is offline.
To counter that I thought of adding 2 more nodes on other machines to the MySQL cluster as failover. Unfortunately I don't have more machines with SSDs.
Now my question: Would I have to expect performance issues because of the much slower hard drives on the failover machines? And if so, would these issues occur only when inserting data or also when calling pure select queries?
Of course I'd set the loadballancer to prioritize the faster nodes.
I'm trying to understand how to architect an Amazon Web Services application.
I have an instance running off of EBS. As far as I understand, I need to mount the EBS drive so that I can store my MySQL database on it.
When I later want to scale up, how do I do so? I understand that I can add more server instances, but how will they be accessing the database? Since from what I understand, the EBS volume can only be attached to one server instance.
I can't speak to this particular setup as I do not have experience using EBS with a MySQL instance but how this type of scaling is typically accomplished is by dedicating a particular instance as the master database server. Any time you spin up additional web servers those are still using the master DB IP to connect. At the time in which your database is the bottleneck you then spin up a slave DB instance on one of the boxes (or its own dedicated box). You can then configure replication in either a master to slave direction or a circular replication so that you can write to the slave instance as well.
If you choose the classic master to slave replication then you will have to make sure your writes are only performed on the master DB instance.
You can setup something like Zeus or any other connection load balancer so that you only ever have to connect to a single Database IP which will then round-robin route your read connections to your pool of servers. Otherwise you'd have to manage the connections yourself which is definitely not trivial. Good luck.
Growing Amazon EBS Volume sizes
You can give a try to MySQL clustering on your EBS backed instances. I have similar query, with more requirements, posted here.
EBS Volumes capacity can be scaled up using Snapshot->launch new volume technique, alternatively storage capacity can be scaled out using EBS Striping (RAID 0).
In AWS you cannot mount same EBS Volume to 2 EC2 instances simultaneously, so when you are scaling your application you need to scale out / up your MySQL DB either thru Replication or clustering. AWS RDS is a very good option for MySQL , if your application is read intensive then you can scale out using RDS Read replica's as well. If you need write scaling then functional partition or MySQL Shards can be explored.
AWS has an entire product dedicated to this: RDS.
In all but the rarest and most specialized of circumstances you're going to be better off using RDS than trying to create and tune your own EBS/EC2/MySQL infrastructure.
RDS also directly answers your question - they directly enable the creation of readonly databases to use as query slaves. RDS also performs backups, upgrades, and all sorts of fail-over infrastructure for you.
With EBS there's no way to attach a disk to multiple EC2 instances, so you're not going to be able to build out a failure cluster using that approach. Instead you're going to need replication or backup tools of some type.