Database Tuning for Private OpenStack Clouds

Want to improve your private OpenStack cloud‘s performance? Start with database optimization. Databases are central to OpenStack, storing metadata and managing service states. Optimizing them can reduce response times, lower resource usage, and save costs.

Key Takeaways:

• Common Issues: Vulnerabilities like single points of failure, performance drops, and complex setups.
• Optimization Benefits: Measurable reductions in CPU usage, virtual machine requirements, and faster response times.
• Metrics to Monitor: Query execution time, memory usage, and network latency.
• Recommended Tools: Percona Monitoring and Management (PMM), OpenStack Ceilometer.
• Scaling Methods: Replication, clustering, sharding, and multi-region setups.

Steps You Should Be Comfortable Executing to Follow This Guide:

1. Adjusting MySQL/MariaDB settings like max_connections and innodb_file_per_table.
2. Using connection pooling tools like pgbouncer.
3. Tweaking caching and indexing for faster queries.
4. Implementing replication and clustering for high availability.

Read on for detailed configuration tips, monitoring tools, and scaling methods to ensure your OpenStack databases are efficient and reliable.

Measuring Database Performance

Tracking database performance in OpenStack environments involves monitoring relevant metrics and using specialized tools. This helps uncover bottlenecks and areas for improvement early on. Let’s get into the important metrics and tools for this process.

Performance Metrics

To get a clear picture of performance, monitoring must happen at different levels. Here are the main categories and their impact:

Start by observing transaction workload patterns to create a reliable baseline for tuning and scaling efforts.

Monitoring Tools

Once you’ve identified your metrics and their baselines, choose tools that can track them in your setup.

• Percona Monitoring and Management (PMM): This open source tool provides detailed insights into performance.
  • Query Analytics: Tracks execution time, resource use, and query patterns to identify areas for optimization.
  • Integrated Advisors: Offers actionable tips for improving performance, security, configuration, and resource allocation.
• OpenStack Ceilometer: Monitors resource usage, aggregates performance data, and sets off alarms when needed.

Set these tools to sample metrics frequently, especially during peak load times. This will build a strong foundation for continuous database optimization in your OpenStack environment.

Database Configuration Steps

Fine-tuning database settings in OpenStack environments is a must for achieving better performance. Below, you’ll find some adjustments to help improve efficiency, based on monitoring data and performance metrics.

MySQL and MariaDB Settings

For smooth and consistent database operations, adjust the [mysqld] section in your configuration file. This is typically located at /etc/my.cnf.d/openstack.cnf or /etc/mysql/mariadb.conf.d/99-openstack.cnf. Here’s a breakdown of the recommended parameters:

Connection Pool Setup

Using a connection pooler like pgbouncer can significantly boost transaction throughput.

Pooling Types and Use Cases

Key Parameters to Configure

Adjust settings such as max_client_conn and default_pool_size to match the demands of your workload.

Cache and Index Optimization

Improving caching and indexing can boost query performance. Proper indexing can greatly reduce transaction response times and CPU load.

Best Practices for Optimization:

• Index columns frequently used in WHERE, JOIN, and ORDER BY clauses.
• Use caching tools like Redis or Memcached to store query results.
• Regularly audit and remove unused indexes to avoid unnecessary overhead.
• Use the EXPLAIN command to identify and refine slow query execution plans.

For OpenStack-specific setups, tweak Nova’s query cache parameters to improve the cache hit ratio. This reduces database load while maintaining data consistency.

Database Scaling Methods

To maintain performance in private OpenStack clouds, use these scaling methods alongside smart configuration and monitoring practices.

Replication and Clustering Setup

Database replication creates real-time copies of the primary database, which is useful for read-heavy workloads. By directing read operations to replicas, the primary database can focus on handling write operations.

For a solid MySQL setup, combine Galera Cluster, HAProxy, and Keepalived. For example, a configuration from Severalnines used three hosts for MySQL-wsrep with Galera Cluster, two hosts for ClusterControl/HAProxy/Keepalived, and one Virtual IP for OpenStack communication.

Here’s how to configure the main components:

To further improve database scalability, partition large datasets with sharding.

Data Sharding Implementation

Data sharding in OpenStack Swift helps break down large container databases into smaller, manageable pieces, improving scalability.

Example of OpenStack Swift Sharding:

1. Identify a container, such as “AUTH_test/c1”, containing 3,349,028 objects.
2. Use the swift-manage-shard-ranges tool to create 7 shard ranges.
3. Ensure consistency with the container-sharder daemon.

This approach efficiently handles large-scale data workloads while maintaining system performance.

Multi-Region Database Management

For multi-region deployments, OpenStack supports regional, cell, and availability zone segregation to optimize performance. This is similar to the structure used by AWS regions.

Regional Optimization Techniques:

For OpenStack Swift, configure read_affinity and write_affinity to balance data distribution and performance. When latency is critical, deploy database services independently across regions, implement inter-region replication, and monitor settings like write_affinity_handoff_delete_count to avoid errors. Additionally, use CockroachDB’s table locality features to further refine multi-region performance.

Database Maintenance Guide

Maintaining your database after optimizing and scaling is crucial to keep things running smoothly. Regular upkeep ensures the OpenStack database remains reliable and performs well.

Backup and Recovery Steps

Automating backups is a smart move. Use the OpenStack Database service to store backup copies in Swift Object Storage. Focus on safeguarding critical OpenStack components:

For database backups, Kolla Ansible’s mariadb_backup utility is very effective. It supports both full and incremental backups of OpenStack service databases. For instance, OpenMetal demonstrated a practical setup using a dedicated Docker volume named mariadb_backup to store database copies.

Once backups are secured, active monitoring becomes your next priority to catch potential issues early.

Monitoring and Alert Setup

To keep tabs on performance, deploy collectd with the sensubility plugin. This setup integrates with Sensu through RabbitMQ. Focus on monitoring major components like:

• API endpoint availability
• Hypervisor status using the openstack.nova.hypervisor.up check
• Database performance metrics like query response times and connection pool usage

Set alert thresholds to trigger actions when needed:

When an issue is flagged, carefully plan updates to resolve it without causing downtime.

Update Procedures

Database updates should be done with minimal disruption. Since downgrades aren’t supported, thorough testing is needed before applying updates in production.

Steps for Updating:

1. Back up the system and test in a mirror environment.
2. Use Ansible for deployment to reduce errors.
3. Monitor performance throughout the update process.
4. Verify database functionality and data integrity post-update.
5. Retain backups until you’re confident the update is successful.

Stay informed by subscribing to the OpenStack Announce mailing list for security updates. Develop a policy to prioritize updates based on their impact level. Additionally, regularly test your backup restoration process to ensure it’s reliable when needed.

Wrapping Up: Database Tuning in OpenStack

Main Points Summary

The tuning techniques mentioned earlier have demonstrated notable improvements in OpenStack’s database performance. Here’s a quick look at the impact of these optimizations:

OpenMetal’s OpenStack Cloud Solutions

OpenMetal offers a platform designed for high-performance and cost-effective database operations. Users have reported saving up to 60% on costs after migrating to OpenMetal. With OpenStack and Ceph integration, the platform ensures reliable database performance. Here are some standout features: