Visibility into Database Performance, Regardless of Cloud Provider or Managed Service
In addition to supporting on-premises servers and self-managed cloud databases on EC2, Compute Engine, and Azure Virtual Machine, SolarWinds Database Performance Monitor (DPM) currently offers robust support for monitoring PostgreSQL databases hosted in Amazon Web Services RDS and Aurora, Google Cloud Platform CloudSQL, and Azure Database for PostgreSQL managed services. SolarWinds DPM has been a leading solution for years to monitor AWS RDS-hosted databases, so we’re excited to highlight below how improvements made in PostgreSQL ver. 10 have led to our expanded support for monitoring PostgreSQL databases hosted in GCP and Azure. Additionally, we’re excited to highlight how persistent efforts by our engineering team has led to product improvements enabling deeper analysis into cloud-hosted managed database servers.
Why PostgreSQL Version 10 and Above?
Starting in PostgreSQL v10, the pg_monitor role was included in the default roles PostgreSQL offers to simplify monitoring a database server without “superuser” privileges. Up until this point, DPM strongly suggested having a database user with SUPERUSER privileges for the agent to connect, to simplify reading information from the pg_stat tables for ALL query traffic across a server. Without these privileges, enabling EXPLAIN plans and other functionality required manual steps to create, configure, and maintain tables specific to monitoring functions. The three major cloud providers restrict SUPERUSER privileges to an admin user in their managed service offerings, which isn’t accessible to end users of the platform. The creation of the pg_monitor role overcomes this limitation, by granting a subset of privileges necessary for monitoring tools to read configuration settings, statistics, and other system data.
What Product Advancements Expand Support for These Platforms?
SolarWinds DPM has been an industry leader for years, offering full engineering teams full visibility into their RDS systems, including the underlying system metrics, like CPU and memory utilization, alongside query data, with our CloudWatch integration. This method utilizes an IAM role that can leverage managed policies, or our custom policy, to access this data via the AWS API. Our engineering team persistently applied this same principle to build a Stackdriver integration to pull in system metrics for related CloudSQL managed database servers.
Amazon Aurora Support
As Amazon RDS service has grown and evolved, SolarWinds DPM’s support for monitoring databases hosted in those systems has kept pace in continuing to build and expand support. DPM is proud to be an industry leader in offering early and comprehensive support for databases hosted in Amazon Aurora, both MySQL and PostgreSQL varieties, comparable to our known support for RDS-hosted systems. This support ensures our clients can update, migrate, or even rearchitect their PostgreSQL databases confidently, knowing the unprecedented detail DPM offers to monitor their systems will persist across the variety of hosting methods available.
Expansion of Tag Import and Management in DPM
SolarWinds DPM offers several ways to track and import tags defined at the query and infrastructure level, including integration steps to automatically import and define tags set at the cloud provider level. The DPM agent now can track every tag associated with every query monitored within DPM, enabling further filtering functionality for those used to identifying unique resources and query executions using query tags. Additionally, we’ve made it easier to automate the process of importing host tags for cloud infrastructure and applying those tags to the monitored host within the native DPM host tagging scheme directly from the point of installation.
What Functionality to Expect From DPM? What Metrics Does DPM Capture?
Many current DPM clients depend on the ability of DPM’s agent to remotely monitor database servers hosted in managed services across the three major cloud providers. We accomplish this by installing the agent on its own server, virtual machine, or container on the same network as the monitored server and ensuring it can connect to the database server with a privileged monitoring user. Our agent then captures and aggregates PostgreSQL query and system metrics from the pg_stat_statements extension, as well as other informational views.
Some high-level query metric information we can collect:
- Host that executed, user connected, origin, count, latency, and errors specific to all query traffic
- Missing index flags, affected rows, shared blocks hit/read, and many other indicators of a query’s efficiency reading and writing data
- Long-running queries in pg_stat_activity and queries that held or waited on a lock to execute
- EXPLAIN plans alongside execution performance metadata to analyze outliers
What Does the Install Process Look Like?
After logging in to your DPM account, the DPM install wizard will provide the following instructions:
- Enabling the pg_stat_statements extension for the database/schema you plan to monitor on the PostgreSQL server
- Modifying and verifying database configuration parameters for monitoring functionality
- Granting privileges to a database user for our agent to connect with and view pg_stat tables
- Installing our agent on a server capable of connecting to the database being monitored
You can also receive our step-by-step install guide and answers to any questions you may have about the trial and install process, by emailing email@example.com.
Interested in Evaluating DPM for Your team? We Offer a Free Trial!
What to Expect From Your Free Trial
Our free trial lasts 14 days, gives ungated access to application features and our client support, and allows you trial licenses to monitor up to 20 database servers. During the trial process, we’re also happy to review metric data with your team, to enable you to incorporate DPM into your daily workflows. You can sign up for a free trial here.