Skip to main content

Using Elastic File System for Out-Scaled Deployers


In a scaled-out scenario for Content Delivery Deployers, it is possible to setup a shared file system as the Binary Storage medium for incoming transport packages.

The Deployer Receiver writes these transport package zip files into the Binary Storage folder. Then it is up to the Deployer Workers to read these zip files as they deployer/underploy the content.

Below, we present the configurations for an AWS Elastic File System (EFS) acting as storage medium for transport packages.

Start by simply creating an EFS in AWS console. This whole step might take you 5 minutes :)



AWS is going to generate a hostname where this file system is available and it will give instructions on how to mount it in your server.

For example, in Linux CentOS, one can mount an FS using the mount command. The following command will mount the EFS drive under folder /efs01 on the current server:


sudo mount -v -t nfs4 -o nfsvers=4.1,rsize=1048576,wsize=1048576,hard,timeo=600,retrans=2 fs-a17668.efs.eu-west-1.amazonaws.com:/ /efs01


Another way of performing permanent mounts, is to add the following line to file /etc/fstab:


fs-a17668.efs.eu-west-1.amazonaws.com:/ /efs01 nfs4 nfsvers=4.1,rsize=1048576,wsize=1048576,hard,timeo=600,retrans=2,_netdev 0 0

Once mounted, we can verify the EFS drive state issuing the following command:

mount | grep efs01

The response should look something like this:

fs-a17668.efs.eu-west-1.amazonaws.com:/ on /efs01 type nfs4 (rw,relatime,vers=4.1,rsize=1048576,wsize=1048576,namlen=255,hard,proto=tcp,timeo=600,retrans=2,sec=sys,clientaddr=10.10.2.173,local_lock=none,addr=10.10.2.145,_netdev)

At this moment, the EFS drive is ready and we can configure it in our deployer-conf.xml:


    <BinaryStorage Id="PackageStorage" Adapter="FileSystem">

        <Property Name="Path" Value="/efs01/deployer-queues"/>
    </BinaryStorage>

The same BinaryStorage node must be present on the Deployer Receiver as well as on all Deployer Workers.



Comments

Popular posts from this blog

Scaling Policies

This post is part of a bigger topic Autoscaling Publishers in AWS . In a previous post we talked about the Auto Scaling Groups , but we didn't go into details on the Scaling Policies. This is the purpose of this blog post. As defined earlier, the Scaling Policies define the rules according to which the group size is increased or decreased. These rules are based on instance metrics (e.g. CPU), CloudWatch custom metrics, or even CloudWatch alarms and their states and values. We defined a Scaling Policy with Steps, called 'increase_group_size', which is triggered first by the CloudWatch Alarm 'Publish_Alarm' defined earlier. Also depending on the size of the monitored CloudWatch custom metric 'Waiting for Publish', the Scaling Policy with Steps can add a difference number of instances to the group. The scaling policy sets the number of instances in group to 1 if there are between 1000 and 2000 items Waiting for Publish in the queue. It also sets the

Toolkit - Dynamic Content Queries

This post if part of a series about the  File System Toolkit  - a custom content delivery API for SDL Tridion. This post presents the Dynamic Content Query capability. The requirements for the Toolkit API are that it should be able to provide CustomMeta queries, pagination, and sorting -- all on the file system, without the use third party tools (database, search engines, indexers, etc). Therefore I had to implement a simple database engine and indexer -- which is described in more detail in post Writing My Own Database Engine . The querying logic does not make use of cache. This means the query logic is executed every time. When models are requested, the models are however retrieved using the ModelFactory and those are cached. Query Class This is the main class for dynamic content queries. It is the entry point into the execution logic of a query. The class takes as parameter a Criterion (presented below) which triggers the execution of query in all sub-criteria of a Criterio

Running sp_updatestats on AWS RDS database

Part of the maintenance tasks that I perform on a MSSQL Content Manager database is to run stored procedure sp_updatestats . exec sp_updatestats However, that is not supported on an AWS RDS instance. The error message below indicates that only the sa  account can perform this: Msg 15247 , Level 16 , State 1 , Procedure sp_updatestats, Line 15 [Batch Start Line 0 ] User does not have permission to perform this action. Instead there are several posts that suggest using UPDATE STATISTICS instead: https://dba.stackexchange.com/questions/145982/sp-updatestats-vs-update-statistics I stumbled upon the following post from 2008 (!!!), https://social.msdn.microsoft.com/Forums/sqlserver/en-US/186e3db0-fe37-4c31-b017-8e7c24d19697/spupdatestats-fails-to-run-with-permission-error-under-dbopriveleged-user , which describes a way to wrap the call to sp_updatestats and execute it under a different user: create procedure dbo.sp_updstats with execute as 'dbo' as