The new integration of SolarWinds Database Performance Analyzer with the SolarWinds Orion technology backbone provides developers, database and systems professionals with unified visibility into the role each element of the infrastructure stack has on application performance, increasing collaboration and reducing friction.
AUSTIN, Texas – June 3, 2015 – SolarWinds (NYSE: SWI), a leading provider of powerful and affordable IT performance management software, today announced the integration of SolarWinds® Database Performance Analyzer (DPA) with the SolarWinds Orion® technology backbone. The integration represents a significant milestone that enables stronger collaboration between database and systems administration teams to ensure the performance of business-critical applications by presenting wait time analysis and other key database performance metrics in the context of the application, all within the familiar SolarWinds Orion user interface.
According to a recent application performance management (APM) survey by Gleanster Research, 88 percent of respondents cited the database as the most common challenge or issue with application performance. Furthermore, 71 percent said their current APM tools only provide hints, but rarely identify the root cause of problems. This lack of visibility into the impact of database performance on applications is a key barrier to ensuring the availability of business-critical applications and also exacerbates a lack of collaboration between database and systems administrators.
With the integration of SolarWinds DPA with SolarWinds Orion—with which other key products in SolarWinds portfolio, including SolarWinds Server & Application Monitor (SAM) and SolarWinds Storage Resource Monitor (SRM), also integrate—SolarWinds now provides database and systems administrators:
- A single view of performance, uptime, capacity and resource utilization across the stack—applications, databases, hypervisors and servers—to help pinpoint inefficient code, resource bottlenecks and application performance issues.
- Deeper application-specific context for database operations, asset management, instance discovery, capacity planning, index fragmentation and agent job status.
- Improved ability to figure out what to fix and more time actually fixing problems with wait-time analytics, performance-to-resource correlation and tuning advice.