Jun
14
2018
--

Percona Monitoring and Management: Look After Your pmm-data Container

looking after pmm-datamcontainers

looking after pmm-datamcontainersIf you have already deployed PMM server using Docker you might be aware that we begin by creating a special container for persistent PMM data. In this post, I aim to explain the importance of pmm-data container when you deploy PMM server with Docker. By the end of this post, you will have a fair idea of why this Docker container is needed.

Percona Monitoring and Management (PMM) is a free and open-source solution for database troubleshooting and performance optimization that you can run in your own environment. It provides time-based analysis for MySQL and MongoDB servers to ensure that your data works as efficiently as possible.

What is the purpose of pmm-data?

Well, as simple as its name suggests, when PMM Server runs via Docker its data is stored in the pmm-data container. It’s a dedicated data only container which you create with bind mounts using -v i.e data volumes for holding persistent PMM data. We use pmm-data to compartmentalize the persistent data so you can more easily backup up and move data consistently across instances or containers. It acts as a single access point from which other running containers (in this case pmm-server) can access data volumes.

pmm-data container does not run, but data from the container is used by pmm-server to build graphs. PMM Server is the core of PMM that aggregates collected data and presents it in the form of tables, dashboards, and graphs in a web interface.

Why do we use docker create ?

The

docker create

  command instructs the Docker daemon to create a writable container layer over the docker image. When you execute

docker create

  using the steps shown, it will create a Docker container named pmm-data and initialize data volumes using the -v flag in conjunction with the create command. (e.g. /opt/prometheus/data).

Option -v is used multiple times in current versions of PMM to mount multiple data volumes. This allows you to create the data volume containers, and then use them from another container i.e pmm-server. We do not want to run the pmm-data container, but only to create it. nb: the number of data volumes bind mounted may change with versions of PMM

$ docker create \
   -v /opt/prometheus/data
   -v /opt/consul-data \
   -v /var/lib/mysql \
   -v /var/lib/grafana \
   --name pmm-data \
   percona/pmm-server:latest /bin/true

Make sure that the data volumes you initialize with the -v option match those given in the example. PMM Server expects you to have bind mounted those directories exactly as demonstrated in the deployment steps. For using different mount points for PMM deployment, please refer to this blog post. Data volumes are very useful as once designated and created you can share them and be include them as part of other containers. If you use -v or –volume to bind-mount a file or directory that does not yet exist on the Docker host, -v creates the endpoint for you. It is always created as a directory. Data in the pmm-data volume are actually hosted on the host’s filesystem.

Why does pmm-data not run ?

As we used

docker create

  container and not

docker run

  for pmm-data, this container does not run. It simply exists to make sure you retain all PMM data when you upgrade to a newer PMM Server image. Data volumes bind mounted on pmm-data container are shared to the running pmm-server container as the

--volumes-from

  option is used for pmm-server launch. Here we persisted data using Docker without binding it to the pmm-server by storing files in the host machine. As long as pmm-data exists, the data exists.

You can stop, destroy, or replace a container. When a non-running container is using a volume, the volume is still available to Docker and is not removed automatically. You can easily replace the pmm-server of the running container by a newer version without any impact or loss of data. For that reason, because of the need to store persistent data, we do it in a data volume. In our case, pmm-data container does not write to the same volumes as it could cause possible corruption.

Why can’t I remove pmm-data container ? What happens if I delete it ?

Removing pmm-data container results in the loss of collected metrics data.

If you remove containers that mount volumes, including the initial pmm-server container, or any subsequent containers mounted, such as pmm-server-2, you do not delete the volumes. This allows you to upgrade — or effectively migrate — data volumes between containers. Your data container might be based on an old version of container, with known security problems. It is not a big problem since it doesn’t actually run anything, but it doesn’t feel right.

As noted earlier, pmm-data stores metrics data as per the retention. You should not remove or recreate pmm-data container unless you need to wipe out all PMM data and start again. To delete the volume from disk, you must explicitly call docker rm -v against the container with a reference to the volume.

Some do’s and don’ts

  • Allocate enough disk space on the host for pmm-data to retain data.
    By default, Prometheus stores time-series data for 30 days, and QAN stores query data for 8 days.
  • Manage data retention appropriately as per your disk space available.
    You can take backup of pmm-data by extracting data from container to avoid data-loss in any situation by using steps mentioned here.

In case of any issues with metrics, here’s a good blog post regarding troubleshooting.

The post Percona Monitoring and Management: Look After Your pmm-data Container appeared first on Percona Database Performance Blog.

May
09
2016
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Rancher Labs raises $20M Series B round for its container management platform

rancher_labs Rancher Labs, a container management platform that supports both Kubernetes and Docker Swarm, today announced that it has raised a $20 million Series B round. This new funding round was led by new investor GRC SinoGreen, a Chinese private equity and venture capital fund, with participation from existing investors Mayfield and Nexus Venture Partners. This round brings the company’s… Read More

Mar
30
2016
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Docker MySQL Replication 101

Docker

Precona Server DockerIn this blog post, we’ll discuss some of the basics regarding Docker MySQL replication. Docker has gained widespread popularity in recent years as a lightweight alternative to virtualization. It is ideal for building virtual development and testing environments. The solution is flexible and seamlessly integrates with popular CI tools.

 

This post walks through the setup of MySQL replication with Docker using Percona Server 5.6 images. To keep things simple we’ll configure a pair of instances and override only the most important variables for replication. You can add whatever other variables you want to override in the configuration files for each instance.

Note: the configuration described here is suitable for development or testing. We’ve also used the operating system repository packages; for the latest version use the official Docker images. The steps described can be used to setup more slaves if required, as long as each slave has a different server-id.

First, install Docker and pull the Percona images (this will take some time and is only executed once):

# Docker install for Debian / Ubuntu
apt-get install docker.io
# Docker install for Red Hat / CentOS (requires EPEL repo)
yum install epel-release # If not installed already
yum install docker-io
# Pull docker repos
docker pull percona

Now create locally persisted directories for the:

  1. Instance configuration
  2. Data files
# Create local data directories
mkdir -p /opt/Docker/masterdb/data /opt/Docker/slavedb/data
# Create local my.cnf directories
mkdir -p /opt/Docker/masterdb/cnf /opt/Docker/slavedb/cnf
### Create configuration files for master and slave
vi /opt/Docker/masterdb/cnf/config-file.cnf
# Config Settings:
[mysqld]
server-id=1
binlog_format=ROW
log-bin
vi /opt/Docker/slavedb/cnf/config-file.cnf
# Config Settings:
[mysqld]
server-id=2

Great, now we’re ready start our instances and configure replication. Launch the master node, configure the replication user and get the initial replication co-ordinates:

# Launch master instance
docker run --name masterdb -v /opt/Docker/masterdb/cnf:/etc/mysql/conf.d -v /opt/Docker/masterdb/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=mysecretpass -d percona:5.6
00a0231fb689d27afad2753e4350192bebc19ab4ff733c07da9c20ca4169759e
# Create replication user
docker exec -ti masterdb 'mysql' -uroot -pmysecretpass -vvv -e"GRANT REPLICATION SLAVE ON *.* TO repl@'%' IDENTIFIED BY 'slavepass'G"
mysql: [Warning] Using a password on the command line interface can be insecure.
--------------
GRANT REPLICATION SLAVE ON *.* TO repl@"%"
--------------
Query OK, 0 rows affected (0.02 sec)
Bye
### Get master status
docker exec -ti masterdb 'mysql' -uroot -pmysecretpass -e"SHOW MASTER STATUSG"
mysql: [Warning] Using a password on the command line interface can be insecure.
*************************** 1. row ***************************
             File: mysqld-bin.000004
         Position: 310
     Binlog_Do_DB:
 Binlog_Ignore_DB:
Executed_Gtid_Set:

If you look carefully at the “docker run” command for masterdb, you’ll notice we’ve defined two paths to share from local storage:

/opt/Docker/masterdb/data:/var/lib/mysql

  • This maps the local “/opt/Docker/masterdb/data” to the masterdb’s container’s “/var/lib/mysql path”
  • All files within the datadir “/var/lib/mysql” persist locally on the host running docker rather than in the container
/opt/Docker/masterdb/cnf:/etc/mysql/conf.d

  • This maps the local “/opt/Docker/masterdb/cnf” directory to the container’s “/etc/mysql/conf.d” path
  • The configuration files for the masterdb instance persist locally as well
  • Remember these files augment or override the file in “/etc/mysql/my.cnf” within the container (i.e., defaults will be used for all other variables)

We’re done setting up the master, so let’s continue with the slave instance. For this instance the “docker run” command also includes the “–link masterdb:mysql” command, which links the slave instance to the master instance for replication.

After starting the instance, set the replication co-ordinates captured in the previous step:

docker run --name slavedb -d -v /opt/Docker/slavedb/cnf:/etc/mysql/conf.d -v /opt/Docker/slavedb/data:/var/lib/mysql --link masterdb:mysql -e MYSQL_ROOT_PASSWORD=mysecretpass -d percona:5.6
eb7141121300c104ccee0b2df018e33d4f7f10bf5d98445ed4a54e1316f41891
docker exec -ti slavedb 'mysql' -uroot -pmysecretpass -e'change master to master_host="mysql",master_user="repl",master_password="slavepass",master_log_file="mysqld-bin.000004",master_log_pos=310;"' -vvv
mysql: [Warning] Using a password on the command line interface can be insecure.
--------------
change master to master_host="mysql",master_user="repl",master_password="slavepass",master_log_file="mysqld-bin.000004",master_log_pos=310
--------------
Query OK, 0 rows affected, 2 warnings (0.23 sec)
Bye

Almost ready to go! The last step is to start replication and verify that replication running:

# Start replication
docker exec -ti slavedb 'mysql' -uroot -pmysecretpass -e"START SLAVE;" -vvv
mysql: [Warning] Using a password on the command line interface can be insecure.
--------------
START SLAVE
--------------
Query OK, 0 rows affected, 1 warning (0.00 sec)
Bye
# Verify replication is running OK
docker exec -ti slavedb 'mysql' -uroot -pmysecretpass -e"SHOW SLAVE STATUSG" -vvv
mysql: [Warning] Using a password on the command line interface can be insecure.
--------------
SHOW SLAVE STATUS
--------------
*************************** 1. row ***************************
               Slave_IO_State: Waiting for master to send event
                  Master_Host: mysql
                  Master_User: repl
                  Master_Port: 3306
                Connect_Retry: 60
              Master_Log_File: mysqld-bin.000004
          Read_Master_Log_Pos: 310
               Relay_Log_File: mysqld-relay-bin.000002
                Relay_Log_Pos: 284
        Relay_Master_Log_File: mysqld-bin.000004
             Slave_IO_Running: Yes
            Slave_SQL_Running: Yes
              Replicate_Do_DB:
          Replicate_Ignore_DB:
           Replicate_Do_Table:
       Replicate_Ignore_Table:
      Replicate_Wild_Do_Table:
  Replicate_Wild_Ignore_Table:
                   Last_Errno: 0
                   Last_Error:
                 Skip_Counter: 0
          Exec_Master_Log_Pos: 310
              Relay_Log_Space: 458
              Until_Condition: None
               Until_Log_File:
                Until_Log_Pos: 0
           Master_SSL_Allowed: No
           Master_SSL_CA_File:
           Master_SSL_CA_Path:
              Master_SSL_Cert:
            Master_SSL_Cipher:
               Master_SSL_Key:
        Seconds_Behind_Master: 0
Master_SSL_Verify_Server_Cert: No
                Last_IO_Errno: 0
                Last_IO_Error:
               Last_SQL_Errno: 0
               Last_SQL_Error:
  Replicate_Ignore_Server_Ids:
             Master_Server_Id: 1
                  Master_UUID: 230d005a-f1a6-11e5-b546-0242ac110004
             Master_Info_File: /var/lib/mysql/master.info
                    SQL_Delay: 0
          SQL_Remaining_Delay: NULL
      Slave_SQL_Running_State: Slave has read all relay log; waiting for the slave I/O thread to update it
           Master_Retry_Count: 86400
                  Master_Bind:
      Last_IO_Error_Timestamp:
     Last_SQL_Error_Timestamp:
               Master_SSL_Crl:
           Master_SSL_Crlpath:
           Retrieved_Gtid_Set:
            Executed_Gtid_Set:
                Auto_Position: 0
1 row in set (0.00 sec)
Bye

Finally, we have a pair of dockerized Percona Server 5.6 master-slave servers replicating!

As mentioned before, this is suitable for a development or testing environment. Before going into production with this configuration, think carefully about the tuning of the “my.cnf” variables and the choice of disks used for the data/binlog directories. It is important to remember that newer versions of Docker recommend using “networks” rather than “linking” for communication between containers.

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