Amazon Aurora DB is a relational database engine from Amazon Web Services, available as part of the Amazon Relational Database Service (RDS). Being MySQL and PostgreSQL - compatible and built for the cloud, Amazon Aurora provides security, availability, and reliability with the simplicity of open source databases.
With Applications Manager's AWS monitoring tool, you can monitor Amazon Aurora DB server clusters and the DB instances in the clusters, check the health of the master server (which handles write operations) and the individual Aurora Replicas (which distribute the query workload among multiple servers).
To investigate performance issues and prevent bottlenecks, collect metrics pertaining to the four fundamental resources - CPU, memory, disk, and network. 33-44Visualize current and historical resource usage, know the reason for High CPU utilization and ensure that your database instance is not memory-constrained. Track user connections numbers, to identify if you should constrain database connections if you see high numbers (in conjunction with decreases in instance performance and response time). Collect native metrics for relational DB engines like MySQL, PostgreSQL and more.
Inspect disk space consumption consistently. Gather metrics on read and write IOPS, which indicate how much your database is interacting with backing storage. See how I/O operations queue up so that you can keep your storage volumes in pace with the volume of read and write requests. Capture query latency and measure how long your I/O operations take at the disk level. Maintain the expected values for IOPS metrics depending on disk specification and server configuration. Make sure your storage volumes are providing the right performance for your workloads.
Gather network throughput metrics, track network traffic to/from clients and maintain the expected throughput for your domain network. Stay Informed of the status of your disk queue depth and if latency increases.
Gain a comprehensive view of the health of your Aurora DB clusters.33-44 Aurora supports the creation of up to 15 read replicas from the master instance. Monitor the replica’s connections, throughput, and query performance, just as you would for an ordinary RDS instance. Track the lag in page cache updates from primary to replica. Administrate the lag time for any read replica and make sure the lag is not consistently very long. Monitor latency in transactions for slow reads or writes in any application that relies on Aurora. 33-44 Identify slow query depending on your performance requirements.
Track Query Throughput and make sure that queries are being executed. Monitor the breakdown of read and write commands to better understand your database’s read/write balance and identify potential bottlenecks. Get the DDL Throughput and monitor DDL latency for all for DDL requests (create/alter/drop) to capture a critical measure of query performance, whether or not the query is served from the query cache. Get alerts on sudden changes in query volume and drastic drops in throughput, as this can indicate a serious problem.
Get a jumpstart on monitoring the Amazon Aurora DB database in your environment. Configure thresholds with multiple conditions and get notified via integrated notification channels of performance issues and bottlenecks. Take quick remedial action before your end-users experience issues.With Applications Manager, you gain system-wide visibility into resource utilization, application performance, and operational health of your AWS infrastructure and application performance. Start monitoring your AWS environment with Applications Manager’s full-fledged, 30-day free trial edition.