Severalnines Blog
The automation and management blog for open source databases

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748 blog posts in 13 categories

Benchmarking Manual Database Deployments vs Automated Deployments

Good system administrators and devops hate performing mundane tasks and constantly look for ways at automating themselves out of the job. There are plenty of automation tools out there to help the cause. But if automation is a no brainer, why aren’t more people doing it? In this blog post we compare three ways of deploying a MySQL Galera cluster - manual, Ansible playbook and ClusterControl.

How to Perform a Failback Operation for MySQL Replication Setup

In case of master failure in a MySQL Replication setup, the most updated slave can be promoted to new master and all slaves repointed to the new master. But once the failed master has been fixed, what is the best way to re-introduce it as master, so as to restore the original topology.

This blog post shows how to perform the MySQL master failback operation.

Benchmarking Managed PostgreSQL Cloud Solutions - Part Three: Google Cloud

This blog performance benchmarks Google Cloud SQL for PostgreSQL 9.6.10 using pgbench and sysbench.

Scaling Your Time-Series Database - How to Simply Scale TimescaleDB

How do you scale TimescaleDB? How do you convert a single TimescaleDB instance to cluster with no downtime? How does the application know which database node to access? This blog post provides an overview of how to use ClusterControl to scale your time-series data with minimal effort.

How to Achieve Automatic Failover for TimescaleDB

Failover is the process of moving to a healthy standby component, during a failure or maintenance event. The quicker it can be done, the faster you can be back online. If you’re looking at minimizing downtime and meet your SLAs through an automated approach for TimescaleDB, then this blog is for you.

Performance Monitoring for TimescaleDB

Doing a performance monitoring in TimescaleDB is always a challenging task, especially for a very huge time-series data. ClusterControl offers a way to help a DBA or a developer to make things feasible and productive with the aid of the different features integrated within ClusterControl. Check out this blog as we showcases what are these and how you can leverage ClusterControl to monitor your TimescaleDB cluster.

Backup Management Tips for TimescaleDB

Managing backup environments can be complex, and there are a number of options to consider - full, differential, incremental, point in time recovery, automatic restores for backup verification, uploading to remote systems or cloud, and so on. So how can we backup TimescaleDB? In this blog, we’ll see how ClusterControl can help us implement our backup management strategy for TimescaleDB.

How to Easily Deploy TimescaleDB

TimescaleDB is based on PostgreSQL, and therefore, supports streaming replication as the primary method of replication. However, PostgreSQL does not come with automatic failover. This can be a problem in a high availability production environment, as manual failover implies prolonged downtime.

The good news is that failover in TimescaleDB can be completely automated in ClusterControl 1.7.2. This blog shows us how to deploy such a setup.

Monitoring & Ops Management of MySQL 8.0 with ClusterControl

MySQL 8.0 is a big step forward in terms of data consistency, developer features, performance and availability. MySQL 8.0 shortens the gap between proprietary databases and open source world, making the migration decision much easier to take.

But how can you manage it, along with other relational open source databases? In this blog post, we look at the challenges of operating a MySQL 8.0 database, and see how important tasks like monitoring, alerting, backups and failover can be handled in an automated way.

Advanced Database Monitoring & Management for TimescaleDB

Included in the 1.7.2 release of ClusterControl we are proud to announce an expansion of the databases we support to include TimescaleDB, a revolutionary new time-series that leverages the stability, maturity and power of PostgreSQL.