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Displaying posts with tag: gcp (reset)
Comparing RonDB 21.04.0 on AWS, Azure and GCP using Sysbench

 

Release of RonDB 21.04.0

RonDB is based on MySQL NDB Cluster optimised for use in modern cloud settings. Today we launch RonDB 21.04.0. In RonDB 21.04.0 we have integrated benchmark scripts to execute various benchmarks towards RonDB.


There are three ways of using RonDB. The first is using the managed version provided by Logical Clocks. This is currently available in AWS and is currently being developed to also support Azure. This is still in limited access mode. To access it contact Logical Clocks at the rondb.com website.


The second way is to use a script provided by Logical Clocks that automates the creation of VMs and the installation of the software components required by RonDB. These scripts are available to create RonDB clusters on Azure and GCP (Google Cloud). This script can be downloaded from nexus.hops.works/rondb-cloud-installer.sh.


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3 Things Before Migrating To CloudSQL(MySQL)

If you are going to migrate your MySQL workloads to GCP’s managed database service CloudSQL, then you have to keep these points in mind. We have done a lot of CloudSQL migrations. But sometimes it’s not smooth as we thought. Generally, people don’t even think that these thinks will make the replication failure. I listing 3 things that ate our brain and time while migrating to CloudSQL.

1. Server character set:

CloudSQL by default using utf8 as the server character set. But it is customizable, we can change it any time. But still, it’ll mess up your application later. We had a MySQL server on a VM where the server’s character set was latin1. We dump the database and restore it to CloudSQL. While launching the CloudSQL we didn’t set up any Database flags. So the data restore with utf8 character set.

Before Migration

mysql> SHOW SESSION …
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3 Things Before Migrating To CloudSQL(MySQL)

If you are going to migrate your MySQL workloads to GCP’s managed database service CloudSQL, then you have to keep these points in mind. We have done a lot of CloudSQL migrations. But sometimes it’s not smooth as we thought. Generally, people don’t even think that these thinks will make the replication failure. I listing 3 things that ate our brain and time while migrating to CloudSQL.

1. Server character set:

CloudSQL by default using utf8 as the server character set. But it is customizable, we can change it any time. But still, it’ll mess up your application later. We had a MySQL server on a VM where the server’s character set was latin1. We dump the database and restore it to CloudSQL. While launching the CloudSQL we didn’t set up any Database flags. So the data restore with utf8 character set.

Before Migration

mysql> SHOW SESSION …
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MySQL Adventures: CPU Cores and IOPS on GCE

TL;DR — If you are hosting your database server in GCE, then you have to be very cautious with capacity planning. The number of CPU cores has an impact on IOPS you get. Even if your workload is not CPU intensive, you might want to provision enough depending on the kind of IOPS you are going to need. For more details, read through one of the problems we faced and the RCA.

Problem statement:

We had a master-slave setup for one of the MySQL database servers. The MySQL server’s performance was good, we didn’t notice any performance related issues initially. But we recently noticed replication lag on the slave. and we figured out that the slave thread was very slow.

Server’s Capacity:

Both our master-slave servers are of the same size.

  • 4 Core CPU
  • 16GB Memory
  • 2 databases are hosted
  • 20GB is the database size.
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MySQL Master Replication Crash Safety Part #5a: making things faster without reducing durability - using better hardware

This is a follow-up post in the MySQL Master Replication Crash Safety series.  In the previous posts, we explored the consequences of reducing durability on masters (different data inconsistencies after an OS crash depending on replication type) and the performance boost associated with this configuration (benchmark results done on Google Cloud Platform / GCP).  The consequences are summarised in

MySQL Master Replication Crash Safety Part #5: faster without reducing durability (under the hood)

This post is a sister post to MySQL Master Replication Crash Safety Part #5: making things faster without reducing durability.  There is no introduction or conclusion to this post, only landing sections: reading this post without its context is not not recommended. You should start with the main post and come back here for more details.

And this Part #5 of the series has many sub-parts.  So far,

MySQL Master Replication Crash Safety Part #4: benchmarks of high and low durability

This is a follow-up post in the MySQL Master Replication Crash Safety series.  In the three previous posts, we explored the consequence of reducing durability on masters (including setting sync_binlog to a value different from 1).  But so far, I only quickly presented why a DBA would run MySQL with such configuration.  In this post, I present actual benchmark results.  I also present a

MySQL Master Replication Crash Safety part #4: benchmarks (under the hood)

This post is a sister post to MySQL Master Replication Crash Safety Part #4: benchmarks of high and low durability.  There are no introduction or conclusion to this post, only landing sections: reading this post without its context is not recommended. You should start with the main post and come back here for more details.

Environment

My benchmark environment is composed of three vms in

2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence

Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Or, considering adding a new database to your application and want to see which combinations are most popular? We found all the answers you need at the Percona Live event last month, and broke down the insights into the following free trends reports:

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MySQL PITR The Fastest Way With DevOps

Point In Time Recovery - is a nightmare for DBAs if the MySQL clusters are self managed. It was 10PM, after had my dinner I was simply watching some shows in YouTube. And my phone was ringing, the customer on other side. Due to some bad queries, one of the main table get updated without where clause. Then suddenly everyone joined the call and asking me to bring the data back. That day it took 6 to 8 Hours to bring the data. Yes, every DBAs will do one or two biggest mistakes. In my carrier I would say this was that day. So here is my MySQL PITR the fastest way with DevOps.

Where I failed in this DR setup?

  • PITR starts with last full backup + binlogs
  • I missed in my backup script to add --master-data, So I don’t know how to start applying binlogs.
  • No Delay replica. I got the call within 10mins when the data has been messed up. But all of my replicas are real time sync. Its affected all of …
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