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Help! I am out of disk space!

Details
Marco Tusa
MySQL
19 January 2023

How we could  fix a nasty out of space issue leveraging the flexibility of Percona MySQL operator (PMO)  DiskSpaceFull

When planning a database deployment, one of the most challenging factors to consider is the amount of space we need to dedicate for Data on disk.

This is even more cumbersome when working on bare metal. Given it is definitely more difficult to add space when using this kind of solution in respect to the cloud. 

This is it, when using cloud storage like EBS or similar it is normally easy(er) to extend volumes, which gives us the luxury to plan the space to allocate for data with a good grade of relaxation. 

Is this also true when using a solution based on Kubernetes like Percona Operator for MySQL? Well it depends on where you run it, however if the platform you choose supports the option to extend volumes K8s per se is giving you the possibility to do so as well.

However, if it can go wrong it will, and ending up with a fully filled device with MySQL is not a fun experience. 

As you know, on normal deployments, when mysql has no space left on the device, it simply stops working, ergo it will cause a production down event, which of course is an unfortunate event that we want to avoid at any cost.  

This blog is the story of what happened, what was supposed to happen and why. 

The story 

Case was on AWS using EKS.

Given all the above, I was quite surprised when we had a case in which a deployed solution based on PMO went out of space. However we start to dig and review what was going on and why.

The first thing we did was to quickly investigate what was really taking space, that could have been an easy win if most of the space was taken by some log, but unfortunately this was not the case, data was really taking all the available space. 

The next step was to check what storage class was used for the PVC

k get pvc
NAME                         VOLUME    CAPACITY   ACCESS MODES   STORAGECLASS
datadir-mt-cluster-1-pxc-0   pvc-<snip>   233Gi      RWO            io1
datadir-mt-cluster-1-pxc-1   pvc-<snip>   233Gi      RWO            io1
datadir-mt-cluster-1-pxc-2   pvc-<snip>   233Gi      RWO            io1

Ok we use the io1 SC, it is now time to check if the SC is supporting volume expansion:

kubectl describe sc io1
Name:            io1
IsDefaultClass:  No
Annotations:     kubectl.kubernetes.io/last-applied-configuration={"apiVersion":"storage.k8s.io/v1","kind":"StorageClass","metadata":{"annotations":{"storageclass.kubernetes.io/is-default-class":"false"},"name":"io1"},"parameters":{"fsType":"ext4","iopsPerGB":"12","type":"io1"},"provisioner":"kubernetes.io/aws-ebs"}
,storageclass.kubernetes.io/is-default-class=false
Provisioner:           kubernetes.io/aws-ebs
Parameters:            fsType=ext4,iopsPerGB=12,type=io1
AllowVolumeExpansion:  <unset> <------------
MountOptions:          <none>
ReclaimPolicy:         Delete
VolumeBindingMode:     Immediate
Events:                <none>

And no is not enabled, in this case we cannot just go and expand the volume, must change the storage class settings first.
To enable volume expansion, you need to delete the storage class and enable it again. 

Unfortunately we were unsuccessful in doing that operation, because the storage class kept staying as unset for  ALLOWVOLUMEEXPANSION. 

As said this is a production down event, so we cannot invest too much time in digging why it was not correctly changing the mode, we had to act quickly. 

The only option we had to fix it was:

  • Expand the io1 volumes from AWS console (or aws client)
  • Resize the file system 
  • Patch any K8 file to allow K8 to correctly see the new volumes dimension  

Expanding EBS volumes from the console is trivial, just go to Volumes, select the volume you want to modify, choose modify and change the size of it with the one desired, done. 

Once that is done connect to the Node hosting the pod which has the volume mounted like:

 k get pods -o wide|grep mysql-0
NAME                                        READY     STATUS    RESTARTS   AGE    IP            NODE             
cluster-1-pxc-0                               2/2     Running   1          11d    10.1.76.189     <mynode>.eu-central-1.compute.internal

Then we need to get the id of the pvc to identify it on the node

k get pvc
NAME                         STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS
datadir-cluster-1-pxc-0   Bound    pvc-1678c7ee-3e50-4329-a5d8-25cd188dc0df   233Gi      RWO            io1

One note, when doing this kind of recovery with a PXC based solution, always recover node-0 first, then the others.  

So we connect to <mynode> and identify the volume: 

lslbk |grep pvc-1678c7ee-3e50-4329-a5d8-25cd188dc0df
nvme1n1      259:4    0  350G  0 disk /var/lib/kubelet/pods/9724a0f6-fb79-4e6b-be8d-b797062bf716/volumes/kubernetes.io~aws-ebs/pvc-1678c7ee-3e50-4329-a5d8-25cd188dc0df <-----

At this point we can resize it:

root@ip-<snip>:/# resize2fs  /dev/nvme1n1
resize2fs 1.45.5 (07-Jan-2020)
Filesystem at /dev/nvme1n1 is mounted on /var/lib/kubelet/plugins/kubernetes.io/aws-ebs/mounts/aws/eu-central-1a/vol-0ab0db8ecf0293b2f; on-line resizing required
old_desc_blocks = 30, new_desc_blocks = 44
The filesystem on /dev/nvme1n1 is now 91750400 (4k) blocks long.

The good thing is that as soon as you do that the MySQL daemon see the space and will restart, however it will happen only on the current pod and K8 will still see the old dimension:

k get pv
NAME                                       CAPACITY   ACCESS MODES   RECLAIM POLICY   STATUS   CLAIM                            STORAGECLASS   REASON
pvc-1678c7ee-3e50-4329-a5d8-25cd188dc0df   333Gi      RWO            Delete           Bound    pxc/datadir-cluster-1-pxc-0   io1

To allow k8 to be align with the real dimension we must patch the information stored, the command is the following:

kubectl patch pvc <pvc-name>  -n <pvc-namespace> -p '{ "spec": { "resources": { "requests": { "storage": "NEW STORAGE VALUE" }}}}'
Ie:
kubectl patch pvc datadir-cluster-1-pxc-0 -n pxc -p '{ "spec": { "resources": { "requests": { "storage": "350" }}}}'

Remember to use as pvc-name the NAME coming from

kubectl get pvc.

Once this is done k8 will see the new volume dimension correctly.

Just repeat the process for Node-1 and Node-2 and …done the cluster is up again.

Finally do not forget to modify your custom resources file (cr.yaml) to match the new volume size. IE:

    volumeSpec:
      persistentVolumeClaim:
        storageClassName: "io1"
        resources:
          requests:
            storage: 350G

The whole process took just a few minutes, it was time now to investigate why the incident happened and why the storage class was not allowing extension in the first place.  

 

Why it happened

Well first and foremost the platform was not correctly monitored. As such there was lack of visibility about the space utilization, and no alert about disk space. 

This was easy to solve just enabling the PMM feature in the cluster cr and set the alert in PMM once the nodes join it (see https://docs.percona.com/percona-monitoring-and-management/get-started/alerting.html for details on how to).

The second issue was the problem with the storage class. Once we had the time to carefully review the configuration files, we identified that there was an additional tab in the SC class, which was causing k8 to ignore the directive. 

Was suppose to be:

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: io1
  annotations:
    storageclass.kubernetes.io/is-default-class: "false"
provisioner: kubernetes.io/aws-ebs
parameters:
  type: io1
  iopsPerGB: "12"
  fsType: ext4 
allowVolumeExpansion: true <----------

It was:
kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: io1
  annotations:
    storageclass.kubernetes.io/is-default-class: "false"
provisioner: kubernetes.io/aws-ebs
parameters:
  type: io1
  iopsPerGB: "12"
  fsType: ext4 
  allowVolumeExpansion: true. <---------

What was concerning was the lack of error returned by the Kubernetes API, so in theory the configuration was accepted but not really validated. 

In any case once we had fix the typo and recreated the SC, the setting for volume expansion was correctly accepted:

kubectl describe sc io1
Name:            io1
IsDefaultClass:  No
Annotations:     kubectl.kubernetes.io/last-applied-configuration={"allowVolumeExpansion":true,"apiVersion":"storage.k8s.io/v1","kind":"StorageClass","metadata":{"annotations":{"storageclass.kubernetes.io/is-default-class":"false"},"name":"io1"},"parameters":{"fsType":"ext4","iopsPerGB":"12","type":"io1"},"provisioner":"kubernetes.io/aws-ebs"}
,storageclass.kubernetes.io/is-default-class=false
Provisioner:           kubernetes.io/aws-ebs
Parameters:            fsType=ext4,iopsPerGB=12,type=io1
AllowVolumeExpansion:  True    
MountOptions:          <none>
ReclaimPolicy:         Delete
VolumeBindingMode:     Immediate
Events:                <none>

What should have happened instead?

If a proper monitoring and alerting was in place, the administrators would have the time to act and extend the volumes without downtime. 

However, the procedure for extending volumes on K8 is not complex but also not as straightforward as you may think. My colleague Natalia Marukovich wrote this blog post (https://www.percona.com/blog/percona-operator-volume-expansion-without-downtime/)  that gives you the step by step instructions on how to extend the volumes without downtime. 

Conclusions

Using the cloud, containers, automation or more complex orchestrators like Kubernetes, do not solve all, do not prevent mistakes from happening, and more importantly do not make the right decisions for you. 

You must set up a proper architecture that includes backup, monitoring and alerting. You must set the right alerts and act on them in time. 

Finally automation is cool, however the devil is in the details and typos are his day to day joy. Be careful and check what you put online, do not rush it. Validate, validate validate… 

Great stateful MySQL to all. 

No comments on “Help! I am out of disk space!”

MySQL Dual password how to manage them programmatically

Details
Marco Tusa
MySQL
17 November 2022

What is dual password in MYSQL and how it works was already covered by my colleague Brian Sumpter here (https://www.percona.com/blog/using-mysql-8-dual-passwords/). rpa cognitive blog img

However let me do a brief recap here about it.

Dual password is the MySQL mechanism that allows you to keep two passwords active at the same time. This feature is part of a more extended set of Password management features implemented in MySQL 8 to enforce better security and secrets management, like:

  • Internal Versus External Credentials Storage
  • Password Expiration Policy
  • Password Reuse Policy
  • Password Verification-Required Policy
  • Dual Password Support
  • Random Password Generation
  • Failed-Login Tracking and Temporary Account Locking

The most important and requested features are the password expiration and verification policy. The problem in implementing them is the complexity of replacing passwords for accounts on very large platforms, like with thousands of applications and hundreds of MySQL servers. 

In fact, while for a single user it is not so complex to change his own password when requested at login, for an application using thousands of sub-services it may require some time. The problem in performing the password change is that while executing the modification some services will have the updated password while others will still use the old one. Without Dual Password a segment of nodes will receive error messages in connecting creating service disruption. 

Now let us cover this blog topic.

With Dual Password it is instead possible to declare a new password keeping the old still active until the whole upgrade has been completed. 

This highlight two very important aspects:

  • When automating the password update, it is better to not use a password expiration policy, but base the expiration on the completion of the new password deployment.
  • We need to be sure the account we are changing the password to keeps the password active until we need it, and that is correctly removed when done. 

As you see I am focusing on the cases when we have automation and not the single interactive user update. 

How dual password works

Let us assume we have create a user like:

create user dualtest@'192.168.4.%' identified by 'password1';
grant all on test.* to dualtest@'192.168.4.%'; 

This will generate an entry in MySQL mysql.user table as:

(root@localhost) [(none)]>select user,host, plugin, authentication_string, password_last_changed,User_attributes from mysql.user where user = 'dualtest'\G
*************************** 1. row ***************************
                 user: dualtest
                 host: 192.168.4.%
               plugin: mysql_native_password
authentication_string: *668425423DB5193AF921380129F465A6425216D0
password_last_changed: 2022-11-17 08:31:37
      User_attributes: NULL
1 row in set (0.00 sec)

At this point our user will be able to connect from any application located in the correct network and act on the test schema. 

After some time, you as application owner,will be notified by your DBA team that the user dualtest is required to change the password in order to respect the security constraints.

At this point there are two options:

  1. You have privileges  to use Dual Password (the required dynamic privilege to use dual Password is APPLICATION PASSWORD ADMIN).
  2. You do not have the right privileges.

In case 2 your DBA team must perform the change for you, and then they will let you know the new password.

In case 1 you can do the operation yourself. 

In the last case what you will do is:

ALTER USER 'dualtest'@'192.168.4.%' IDENTIFIED BY 'password2' RETAIN CURRENT PASSWORD;

Then check it is done properly:

select user,host, plugin, authentication_string, password_last_changed,User_attributes from mysql.user where user ='dualtest' order by 1,2\G
*************************** 1. row ***************************
                 user: dualtest
                 host: 192.168.4.%
               plugin: mysql_native_password
authentication_string: *DC52755F3C09F5923046BD42AFA76BD1D80DF2E9
password_last_changed: 2022-11-17 08:46:28
      User_attributes: {"additional_password": "*668425423DB5193AF921380129F465A6425216D0"}
1 row in set (0.00 sec)

As you can see here the OLD password has been moved to the User_attributes JSON field that is used in MYSQL8 to store several values. 

At this point you can rollout safely the password change and that change can take an hour or a week, no production impact given the applications will be able to use either of them. 

Once the process is complete, you can ask your DBA team to remove OLD password, or do:

ALTER USER 'dualtest'@'192.168.4.%' DISCARD OLD PASSWORD;

Then check if the password has being removed properly:

(root@localhost) [(none)]>select user,host, plugin, authentication_string, password_last_changed,User_attributes from mysql.user where user ='dualtest' order by 1,2\G
*************************** 1. row ***************************
                 user: dualtest
                 host: 192.168.4.%
               plugin: mysql_native_password
authentication_string: *DC52755F3C09F5923046BD42AFA76BD1D80DF2E9
password_last_changed: 2022-11-17 08:46:28
      User_attributes: NULL
1 row in set (0.00 sec)

If all is clean the process can be considered complete. 

Of course all this should be automated and executed by code not by hand high level it should be more or less like this:

{}Input new password  
- Check for additional_password in User_attributes in mysql.user
<> If no value you can proceed otherwise exit (another change is in place) 
 - Read and store authentication_string for the user you need to change password
 - Change current password with: Alter user ... RETAIN CURRENT PASSWORD
 - Check for additional_password in User_attributes in mysql.user
<> If value is present and match the password stored then you can proceed otherwise exit given there is an error in Dual Password or the passwords are different
 - Run update on all application nodes, and verify new password on each application node 
<> At regular interval check the number of completed changes and check the additional_password in User_attributes in mysql.user to be sure it is still there
[] When all application nodes are up to date 
<> If verification is successful 100%
 - Remove OLD password with: ALTER USER ... DISCARD OLD PASSWORD; 
 - Check for additional_password in User_attributes in mysql.user
<> If no value is present close with OK otherwise report Error for password not removed
() complete

Conclusion

As also Brian mentioned, those are the small things that could make the difference when in large deployments and enterprise environments. Security is a topic that very often is underestimated in small companies or start-ups, but that is wrong, security operations like password rotation are crucial for your safety. 

It is nice to see that MySQL is finally adopting simple but effective steps to help DBAs to implement proper procedures without causing production impact and without the need to become too creative. 

 

References 

https://www.percona.com/blog/using-mysql-8-dual-passwords/

https://dev.mysql.com/doc/refman/8.0/en/password-management.html#dual-passwords

No comments on “MySQL Dual password how to manage them programmatically”

ProxySQL support for MySQL caching_sha2_password

Details
Marco Tusa
MySQL
03 November 2022

In our time, every day we use dozens if not hundreds of applications connecting to some kind of data repository. This simple step is normally executed over the network and given so, it is subject to possible sniffing with all the possible related consequences.brokenlock

Given that it is normally better to protect your connection using data encryption like SSL, or at the minimum, make the information you pass to connect less easy to be intercepted. 

At the same time it is best practice to not store connection credential in clear text, not even inside a table in your database. Doing that is the equivalent of writing your password over a sticky note on your desk. Not a good idea.

The main options are instead in either transforming the passwords to be less identifiable like hashing or to store the information in an external centralized vault. 

In MySQL the passwords are transformed in order to not be clear text, and several different plugins are used to authenticate the user. From version 8 MySQL uses caching_sha2_password as default authentication plugin. The caching_sha2_password and sha256_password authentication plugins provide more secure password encryption than the mysql_native_password plugin, and caching_sha2_password provides better performance than sha256_password. Due to these superior security and performance characteristics of caching_sha2_password, it is as of MySQL 8.0 the preferred authentication plugin, and is also the default authentication plugin rather than mysql_native_password.

In this regard recently I got the same question again “Can we use ProxySQL with MySQL 8 authorization mechanism?”, and I decided it was time to write this short blog post.

The short answer is “Yes you can”, however do not expect to have full caching_sha2_password support.

This is because ProxySQL does not fully support the caching_sha2_password mechanism internally and given that a “trick” must be used. 

So, what should we do when using MySQL 8 and ProxySQL? 

In the text below we will see what can be done to continue to use ProxySQL with MySQL and Percona server 8. 

Note that I have used the Percona proxysql_admin tool to manage the users except in the last case.
Percona
proxysql_admin tool is a nice tool that helps you to manage ProxySQL and in regard to user it also manage and synchronize users from your Percona or MySQL  

In the following examples:

Proxysql is on 192.168.4.191

User name/password is msandbox/msandbox

Using hashing.

By default MySQL comes with caching_sha2_password as such if I create a user names msandbox I will have:

DC1-1(root@localhost) [(none)]>select user,host, authentication_string,plugin from mysql.user order by 1,2;
+----------------------------+--------------------+------------------------------------------------------------------------+-----------------------+
| user                       | host               | authentication_string                                                  | plugin                |
+----------------------------+--------------------+------------------------------------------------------------------------+-----------------------+
| msandbox                   | %                  | $A$005$Z[z@l'O%[Q5t^ EKJDgxjWXJjDpDEUv91oL7Hoh/0NydTeCzpV.aI06C9.      | caching_sha2_password |      <---- this user     
+----------------------------+--------------------+------------------------------------------------------------------------+-----------------------+ 

Then I use percona_scheduler_admin to sync the users:

./percona-scheduler-admin --config-file=config.toml --syncusers 
Syncing user accounts from PXC(192.168.4.205:3306) to ProxySQL
Removing existing user from ProxySQL: msandbox
Adding user to ProxySQL: msandbox

Synced PXC users to the ProxySQL database!

mysql> select * from mysql_users ;
+------------+------------------------------------------------------------------------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+-----------------------------+
| username   | password                                                               | active | use_ssl | default_hostgroup | default_schema | schema_locked | transaction_persistent | fast_forward | backend | frontend | max_connections | attributes | comment                     |
+------------+------------------------------------------------------------------------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+-----------------------------+
| msandbox   | $A$005$Z[z@l'O%[Q5t^ EKJDgxjWXJjDpDEUv91oL7Hoh/0NydTeCzpV.aI06C9       | 1      | 0       | 100               | NULL           | 0             | 1                      | 0            | 1       | 1        | 10000           |            |                             |
+------------+------------------------------------------------------------------------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+-----------------------------+

And set the query rules:

insert into mysql_query_rules (rule_id,proxy_port,username,destination_hostgroup,active,retries,match_digest,apply) values(1048,6033,'msandbox',100,1,3,'^SELECT.*FOR UPDATE',1);
insert into mysql_query_rules (rule_id,proxy_port,username,destination_hostgroup,active,retries,match_digest,apply) values(1050,6033,'msandbox',101,1,3,'^SELECT.*$',1);

load mysql query rules to run;save mysql query rules to disk;

Now I try to connect passing by ProxySQL:

# mysql -h 192.168.4.191 -P6033  -umsandbox -pmsandbox
ERROR 1045 (28000): ProxySQL Error: Access denied for user 'msandbox'@'192.168.4.191' (using password: YES)

My account will fail to connect given failed authentication.

To fix this I need to drop the user and recreate it with a different authentication plugin in my MySQL server:

drop user msandbox@'%';
create user 'msandbox'@'%' identified with mysql_native_password  BY 'msandbox';
grant select on *.* to 'msandbox'@'%';

select user,host, authentication_string,plugin from mysql.user order by 1,2;
+----------+--------------------+-------------------------------------------+-----------------------+
| user     | host               | authentication_string                     | plugin                |
+----------+--------------------+-------------------------------------------+-----------------------+
| msandbox | %                  | *6C387FC3893DBA1E3BA155E74754DA6682D04747 | mysql_native_password |
+----------+--------------------+-------------------------------------------+-----------------------+

At this point I can re-run

./percona-scheduler-admin --config-file=config.toml --syncusers

if I try to connect again:

# mysql -h 192.168.4.191 -P6033  -umsandbox -pmsandbox
mysql: [Warning] Using a password on the command line interface can be insecure.
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 6708563
Server version: 8.0.28 (ProxySQL). <---------------------------- Connecting to proxysql

Copyright (c) 2000, 2022, Oracle and/or its affiliates.

Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql> show global variables like 'version%';
+-------------------------+------------------------------------------------------------------------------------+
| Variable_name           | Value                                                                              |
+-------------------------+------------------------------------------------------------------------------------+
| version                 | 8.0.25-15.1         <--- Percona/MySQL version                                     |
| version_comment         | Percona XtraDB Cluster binary (GPL) 8.0.25, Revision 8638bb0, WSREP version 26.4.3 |
| version_compile_machine | x86_64                                                                             |
| version_compile_os      | Linux                                                                              |
| version_compile_zlib    | 1.2.11                                                                             |
| version_suffix          | .1                                                                                 |
+-------------------------+------------------------------------------------------------------------------------+
6 rows in set (0.02 sec)

This is the only way to keep the password hashed in MySQL and in ProxySQL.

Not using Hashing

What if you cannot use mysql_native_password for the password in your MySQL server?

There is a way to still connect, however I do not recommend it given for me is highly insecure, but for completeness I am going to illustrate it.

First of all disable password hashing in Proxysql:

update global_variables set Variable_Value='false' where Variable_name='admin-hash_passwords'; 

At this point instead sync the user you can locally create the user like:

insert into mysql_users (username,password,active,default_hostgroup,default_schema,transaction_persistent,comment) values ('msandbox','msandbox',1,100,'mysql',1,'generic test for security'); 
mysql> select * from runtime_mysql_users where username ='msandbox'; 
+----------+----------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+---------------------------+ 
| username | password | active | use_ssl | default_hostgroup | default_schema | schema_locked | transaction_persistent | fast_forward | backend | frontend | max_connections | attributes | comment                   | 
+----------+----------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+---------------------------+ 
| msandbox | msandbox | 1      | 0       | 100               | mysql          | 0             | 1                      | 0            | 1       | 0        | 10000           |            | generic test for security | 
| msandbox | msandbox | 1      | 0       | 100               | mysql          | 0             | 1                      | 0            | 0       | 1        | 10000           |            | generic test for security | 
+----------+----------+--------+---------+-------------------+----------------+---------------+------------------------+--------------+---------+----------+-----------------+------------+---------------------------+

As you can see doing that will prevent the password to be hashed and instead it will be clear text.

At this point you will be able to connect to MySQL 8 using the caching_sha2_password, but the password is visible in ProxySQL.

Let me repeat, I DO NOT recommend using it this way, because for me it is highly insecure. 

 

Conclusion

While it is still possible to configure your user in MySQL to connect using ProxySQL, it is obvious that we have a gap in the way ProxySQL supports security. 

The hope is that this gap will be filled soon by the ProxySQL development team, also if looking to the past issues this seems pending from years now. 

References

https://proxysql.com/documentation/mysql-8-0/

https://github.com/sysown/proxysql/issues/2580

https://www.percona.com/blog/upgrade-your-libraries-authentication-plugin-caching_sha2_password-cannot-be-loaded/

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Zero impact on index creation with Aurora 3

Details
Marco Tusa
MySQL
20 April 2022

aurora ddl notesLast quarter of 2021 AWS released Aurora version 3. This new version aligns Aurora with the latest MySQL 8 version porting many of the advantages MySQL 8 has over previous versions.

While this brings a lot of new interesting features for Aurora, what we are going to cover here is to see how DDLs behave when using the ONLINE option. With a quick comparison with what happens in MySQL 8 standard and with Group Replication. 

Tests

All tests were run on an Aurora instance r6g.large with secondary availability zone.
The test was composed by:

        4 connections

    • #1 to perform ddl
    • #2 to perform insert data in the table I am altering
    • #3 to perform insert data on a different table 
    • #4 checking the other node operations

In the Aurora instance, a sysbench schema with 10 tables and 5 million rows was created, just to get a bit of traffic. While the test table with 5ml rows as well was:

CREATE TABLE `windmills_test` (
  `id` bigint NOT NULL AUTO_INCREMENT,
  `uuid` char(36) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
  `millid` smallint NOT NULL,
  `kwatts_s` int NOT NULL,
  `date` date NOT NULL,
  `location` varchar(50) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
  `active` tinyint NOT NULL DEFAULT '1',
  `time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `strrecordtype` char(3) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
  PRIMARY KEY (`id`),
  KEY `IDX_millid` (`millid`,`active`),
  KEY `IDX_active` (`id`,`active`),
  KEY `kuuid_x` (`uuid`),
  KEY `millid_x` (`millid`),
  KEY `active_x` (`active`),
  KEY `idx_1` (`uuid`,`active`)
) ENGINE=InnoDB AUTO_INCREMENT=0 DEFAULT CHARSET=utf8mb3 COLLATE=utf8_bin ROW_FORMAT=DYNAMIC

The executed commands:

Connection 1:
    ALTER TABLE windmills_test ADD INDEX idx_1 (`uuid`,`active`), ALGORITHM=INPLACE, LOCK=NONE;
    ALTER TABLE windmills_test drop INDEX idx_1, ALGORITHM=INPLACE;
    
Connection 2:
 while [ 1 = 1 ];do da=$(date +'%s.%3N');mysql --defaults-file=./my.cnf -D windmills_large -e "insert into windmills_test  select null,uuid,millid,kwatts_s,date,location,active,time,strrecordtype from windmills4 limit 1;" -e "select count(*) from windmills_large.windmills_test;" > /dev/null;db=$(date +'%s.%3N'); echo "$(echo "($db - $da)"|bc)";sleep 1;done

Connection 3:
 while [ 1 = 1 ];do da=$(date +'%s.%3N');mysql --defaults-file=./my.cnf -D windmills_large -e "insert into windmills3  select null,uuid,millid,kwatts_s,date,location,active,time,strrecordtype from windmills4 limit 1;" -e "select count(*) from windmills_large.windmills_test;" > /dev/null;db=$(date +'%s.%3N'); echo "$(echo "($db - $da)"|bc)";sleep 1;done

Connections 4:
     while [ 1 = 1 ];do echo "$(date +'%T.%3N')";mysql --defaults-file=./my.cnf -h <secondary aurora instance> -D windmills_large -e "show full processlist;"|egrep -i -e "(windmills_test|windmills_large)"|grep -i -v localhost;sleep 1;done
     

Operations:
1) start inserts from connections
2) start commands in connections 4 - 5 on the other nodes
3) execute: DC1-1(root@localhost) [windmills_large]>ALTER TABLE windmills_test ADD INDEX idx_1 (`uuid`,`active`), ALGORITHM=INPLACE, LOCK=NONE;

With this, what I was looking to capture is the operation impact in doing a common action as creating an Index. My desired expectation is to have no impact when doing operations that are declared “ONLINE” such as creating an index, as well as data consistency between nodes. 

Let us see what happened…

Results

While running the insert in the same table, performing the alter:

mysql>  ALTER TABLE windmills_test ADD INDEX idx_1 (`uuid`,`active`), ALGORITHM=INPLACE, LOCK=NONE;
Query OK, 0 rows affected (16.51 sec)
Records: 0  Duplicates: 0  Warnings: 0

Is NOT stopping the operation in the same table or any other table in the Aurora instance.

We can only identify a minimal performance impact:

[root@ip-10-0-0-11 tmp]# while [ 1 = 1 ];do da=$(date +'%s.%3N');mysql --defaults-file=./my.cnf -D windmills_large -e "insert into windmills_test  select null,uuid,millid,kwatts_s,date,location,active,time,strrecordtype from windmills4 limit 1;" -e "select count(*) from windmills_large.windmills_test;" > /dev/null;db=$(date +'%s.%3N'); echo "$(echo "($db - $da)"|bc)";sleep 1;done
.347
.283
.278
.297
.291
.317
.686  ← start
<Snip>
.512  ← end
.278
.284
.279

The secondary node is not affected at all, and this is because Aurora managed at storage level the data replication. Given that there is no such thing as Apply from Relaylog, as we have in standard MySQL asynchronous or data replicated with Group Replication.  

The result is that in Aurora 3, we can have zero impact index (or any other ONLINE/INSTANT) operation, with this I include the data replicated in the other instances for High Availability. 

If we compare this with Group replication (see blog):

                               	 	 	  GR         Aurora 3
Time on hold for insert for altering table   	~0.217 sec   ~0.523 sec
Time on hold for insert for another table   	~0.211 sec   ~0.205 sec 

However, keep in mind that MySQL with Group Replication will still need to apply the data on the Secondaries. This means that if your alter was taking 10 hours to build the index, the Secondary nodes will be misaligned with the Source for approximately another 10 hours. 

With Aurora 3 or with PXC, changes will be there when Source has completed the operation.    

What about Percona XtraDB Cluster (PXC)? Well, with PXC we have a different scenario:

                               	 	 	 PXC(NBO)     Aurora 3
Time on hold for insert for altering table   	~120 sec      ~0.523 sec
Time on hold for insert for another table   	~25  sec      ~0.205 sec

We will have a higher impact while doing the Alter operation, but the data will be on all nodes at the same time maintaining a high level of consistency in the cluster. 

Conclusion

Aurora is not for all use, and not for all budgets, however it has some very good aspects like the one we have just seen. The Difference between standard MySQL and Aurora is not in the time of holding/locking (aka operation impact), but on the HA aspects. If I have my data/structure on all my Secondary at the same time of the Source, I will feel much more comfortable, than having to wait an additional T time. 

This is why PXC in that case is a better alternative if you can afford locking time, if not, well Aurora 3 is your solution, just do your math properly and be conservative with the instance resources. 

 

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A face to face with semi-synchronous replication

Details
Marco Tusa
MySQL
12 April 2022

Last month I performed a review of the Percona Operator for MySQL Server (https://www.percona.com/doc/kubernetes-operator-for-mysql/ps/index.html) which is still Alpha.  That operator is based on Percona Server and uses standard asynchronous replication, with the option to activate semi-synchronous  replication to gain higher levels of data consistency between nodes. 

The whole solution is composed as:

Additionally, Orchestrator (https://github.com/openark/orchestrator) is used to manage the topology and the settings to enable on the replica nodes, the semi-synchronous flag if required.
While we have not too much to say when using standard Asynchronous replication, I want to spend two words on the needs and expectations on the semi-synchronous (semi-sync) solution. 

A look into semi-synchronous

Difference between Async and Semi-sync.
Asynchronous:

The above diagram represents the standard asynchronous replication. This method is expected by design, to have transactions committed on the Source that are not present on the Replicas. The Replica is supposed to catch-up when possible.   

It is also important to understand that there are two steps in replication:

  • Data copy, which is normally very fast. The Data is copied from the binlog of the Source to the relay log on the Replica (IO_Thread).
  • Data apply, where the data is read from the relay log on the Replica node and written inside the database itself (SQL_Thread). This step is normally the bottleneck and while there are some parameters to tune, the efficiency to apply transactions depends on many factors including schema design. 

Production deployments that utilize the Asynchronous solution are typically designed to manage the possible inconsistent scenario given data on Source is not supposed to be on Replica at commit. At the same time the level of High Availability assigned to this solution is lower than the one we normally obtain with (virtually-)synchronous replication, given we may need to wait for the Replicare to catch-up the gap accumulated in the relay-logs before performing the fail-over.

Semi-sync:

The above diagram represents the Semi-sync replication method.The introduction of semi-sync adds a checking step on the Source before it returns the acknowledgement to the client.
This step happens at the moment of the data-copy, so when the data is copied from the Binary-log on Source to the Relay-log on Replica. 

This is important, there is NO mechanism to ensure a more resilient or efficient data replication, there is only an additional step, that tells the Source to wait a given amount of time for an answer from N replicas, and then return the acknowledgement or timeout and return to the client no matter what. 

This mechanism is introducing a possible significant delay in the service, without giving the 100% guarantee of data consistency. 

In terms of availability of the service, when in presence of high load, this method may lead the Source to stop serving the request while waiting for acknowledgements, significantly reducing the availability of the service itself.   

At the same time only acceptable settings for rpl_semi_sync_source_wait_point is AFTER_SYNC (default) because:  In the event of source failure, all transactions committed on the source have been replicated to the replica (saved to its relay log). An unexpected exit of the source server and failover to the replica is lossless because the replica is up to date.

All clear? No? Let me simplify the thing. 

  • In standard replication you have two moments (I am simplifying)
    • Copy data from Source to Replica
    • Apply data in the Replica node
  • There is no certification on the data applied about its consistency with the Source
  • With asynchronous the Source task is to write data in the binlog and forget
  • With semi-sync the Source writes the data on binlog and waits T seconds to receive acknowledgement from N servers about them having received the data.

To enable semi-sync you follow these steps:  https://dev.mysql.com/doc/refman/8.0/en/replication-semisync-installation.html

In short:

  • Register the plugins
  • Enable Source rpl_semi_sync_source_enabled=1
  • Enable Replica rpl_semi_sync_replica_enabled = 1
    • If replication is already running STOP/START REPLICA IO_THREAD

And here starts the fun, be ready for many “wait whaaat?”. 

What is the T and N I have just mentioned above?

Well the T is a timeout that you can set to avoid having the source wait forever for the Replica acknowledgement. The default is 10 seconds. What happens if the Source waits for more than the timeout? 
rpl_semi_sync_source_timeout controls how long the source waits on a commit for acknowledgment from a replica before timing out and reverting to asynchronous replication.

Careful of the wording here! The manual says SOURCE, so it is not that MySQL revert to asynchronous, by transaction or connection, it is for the whole server.

Now analyzing the work-log (see https://dev.mysql.com/worklog/task/?id=1720 and more in the references) the Source should revert to semi-synchronous as soon as all involved replicas are aligned again. 

However, checking the code (see  https://github.com/mysql/mysql-server/blob/beb865a960b9a8a16cf999c323e46c5b0c67f21f/plugin/semisync/semisync_source.cc#L844 and following), we can see that we do not have a 100% guarantee that the Source will be able to switch back. 

Also in the code:
But, it is not that easy to detect that the replica has caught up.  This is caused by the fact that MySQL's replication protocol is  asynchronous, meaning that if thesource does not use the semi-sync protocol, the replica would not send anything to thesource.

In all the runned tests the Source was not able to switch back. In short Source was moving out from semi-sync and that was forever, no rollback. Keep in mind that while we go ahead.

What is the N I mentioned above? It represents the number of Replicas that must provide the acknowledgement back. 

If you have a cluster of 10 nodes you may need to have only 2 of them involved in the semi-sync, no need to include them all. But if you have a cluster of 3 nodes where 1 is the Source, relying on 1 Replica only, is not really secure. What I mean here is that if you choose to be semi-synchronous to ensure the data replicates, having it enabled for one single node is not enough, if that node crashes or whatever, you are doomed, as such you need at least 2 nodes with semi-sync.

Anyhow, the point is that if one of the Replica takes more than T to reply, the whole mechanism stops working, probably forever. 

As we have seen above, to enable semi-sync on Source we manipulate the value of the GLOBAL variable rpl_semi_sync_source_enabled.

However if I check the value of rpl_semi_sync_source_enabled when the Source shift to simple Asynchronous replication because timeout:

select @@rpl_semi_sync_source_enabled;

select @@rpl_semi_sync_source_enabled;
+--------------------------------+
| @@rpl_semi_sync_source_enabled |
+--------------------------------+
|                              1 |
+--------------------------------+

As you can see the Global variable reports a value of 1, meaning that semi-sync is active also if not.

In the documentation it is reported that to monitor the semi-sync activity we should check for Rpl_semi_sync_source_status. Which means that you can have Rpl_semi_sync_source_status = 0 and rpl_semi_sync_source_enabled =1 at the same time.

Is this a bug? Well according to documentation:
When the source switches between asynchronous or semisynchronous replication due to commit-blocking timeout or a replica catching up, it sets the value of the Rpl_semi_sync_source_status or Rpl_semi_sync_source_status status variable appropriately. Automatic fallback from semisynchronous to asynchronous replication on the source means that it is possible for the rpl_semi_sync_source_enabled or rpl_semi_sync_source_enabled system variable to have a value of 1 on the source side even when semisynchronous replication is in fact not operational at the moment. You can monitor the Rpl_semi_sync_source_status or Rpl_semi_sync_source_status status variable to determine whether the source currently is using asynchronous or semisynchronous replication.

It is not a bug. However, because you documented it, it doesn’t change the fact this is a weird/unfriendly/counterintuitive way of doing, that opens the door to many, many possible issues. Especially given you know the Source may fail to switch semi-synch back.  

Just to close this part, we can summarize as follows:

  • You activate semi-sync setting a global variable
  • Server/Source can disable it (silently) without changing that variable 
  • Server will never restore semi-sync automatically
  • The way to check if semi-sync works is to use the Status variable
  • When Rpl_semi_sync_source_status = 0 and rpl_semi_sync_source_enabled =1 you had a Timeout and Source is now working in asynchronous replication
  • The way to reactivate semi-sync is to set rpl_semi_sync_source_enabled  to OFF first then rpl_semi_sync_source_enabled = ON. 
  • Replicas can be set with semi-sync ON/OFF but unless you do not STOP/START the replica_IO_THREAD the state of the variable can be inconsistent with the state of the Server.

What can go wrong?

Semi-synchronous is not seriously affecting the performance

Others had already discussed semi-sync performance in better details. However I want to add some color given the recent experience with our operator testing.
In the next graphs I will show you the behavior of writes/reads using Asynchronous replication and the same load with Semi-synchronous.
For the record the test was a simple Sysbench-tpcc test using 20 tables, 20 warehouses, 256 threads for 600 seconds.   

The one above indicates a nice and consistent set of load in r/w with minimal fluctuations. This is what we like to have. 

The graphs below, represent the exact same load on the exact same environment but with semi-sync activated and no timeout. 

Aside from the performance loss (we went from Transaction 10k/s to 3k/s), the constant stop/go imposed by the semi-sync mechanism has a very bad effect on the application behavior when you have many concurrent threads and high loads. I challenge any serious production system to work in this way.   

Of course results are inline with this yoyo game:

In the best case, when all was working as expected, and no crazy stuff happening I had something around the 60% loss. I am not oriented to see this as  a minor performance drop. 

But at least your data is safe

As already stated at the beginning the scope of semi-synchronous replication is to guarantee that the data in server A reaches server B before returning the OK to the application. 

In short, given a period of 1 second we should have minimal transactions in flight and limited transactions in the apply queue. While for standard replication (asynchronous), we may have … thousands. 

In the graphs below we can see two lines:

  • The yellow line represents the number of GTIDs “in flight” from Source to destination, Y2 axes.  In case of Source crash, those transactions are lost and we will have data loss.
  • The blue line represents the number of GTIDs already copied over from Source to Replica but not applied in the database Y1 axes. In case of Source crash we must wait for the Replica to process these entries, before making the node Write active, or we will have data inconsistency.

Asynchronous replication:

As expected we can see a huge queue in applying the transactions from relay-log, and some spike of transactions in flight. 

Using Semi-synchronous replication:

Yes, apparently we have reduced the queue and no spikes so no data loss.

But this happens  when all goes as expected, and we know in production this is not the normal.
What if we need to enforce the semi-sync but at the same time we cannot set the Timeout to ridiculous values like 1 week? 

Simple, we need to have a check that puts back the semi-sync as soon as it is silently disabled (for any reason).
However doing this without waiting for the Replicas to cover the replication gap, cause the following interesting effects:

Thousands of transactions queued and shipped with the result of having a significant increase of the possible data loss and still a huge number of data to apply from the relay-log. 

So the only possible alternative is to set the Timeout to a crazy value, However this can cause a full production stop in the case a Replica hangs or for any reason it disables the semi-sync locally. 

 

Conclusion

First of all I want to say that the tests on our operator using Asynchronous replication, shows a consistent behavior with the standard deployments in the cloud or premises.  It has the same benefits, like better performance and same possible issues as longer time to failover when it needs to wait a Replica to apply the relay-log queue. 

The semi-synchronous flag in the operator is disabled, and the tests I have done bring me to say “keep it like that!”. At least unless you know very well what you are doing and are able to deal with a semi-sync timeout of days.

I was happy to have the chance to perform these tests, because they gives me a way/time/need to investigate more on the semi-synchronous feature.
Personally, I was not convinced about the semi-synchronous replication when it came out, and I am not now. I never saw a less consistent and less trustable feature in MySQL as semi-sync.  

If you need to have a higher level of synchronicity in your database just go for Group Replication, or Percona XtraDB Cluster and stay away from semi-sync. 

Otherwise, stay on Asynchronous replication, which is not perfect but it is predictable.  

References

https://www.percona.com/blog/2012/01/19/how-does-semisynchronous-mysql-replication-work/

https://www.percona.com/blog/percona-monitoring-and-management-mysql-semi-sync-summary-dashboard/

https://www.percona.com/blog/2012/06/14/comparing-percona-xtradb-cluster-with-semi-sync-replication-cross-wan/

https://datto.engineering/post/lossless-mysql-semi-sync-replication-and-automated-failover

https://planetscale.com/blog/mysql-semi-sync-replication-durability-consistency-and-split-brains

https://percona.community/blog/2018/08/23/question-about-semi-synchronous-replication-answer-with-all-the-details/

https://dev.mysql.com/doc/refman/8.0/en/replication-semisync-installation.html

https://dev.mysql.com/worklog/task/?id=1720

https://dev.mysql.com/worklog/task/?id=6630

https://dev.mysql.com/worklog/task/?id=4398

https://github.com/mysql/mysql-server/blob/beb865a960b9a8a16cf999c323e46c5b0c67f21f/plugin/semisync/semisync_source.cc#L844

https://github.com/mysql/mysql-server/blob/beb865a960b9a8a16cf999c323e46c5b0c67f21f/plugin/semisync/semisync_source.cc#L881

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