Rapidly detect, diagnose and resolve performance issues — wherever, whenever and however they occur. Intuitive web-based dashboards alert you to emerging issues that might affect performance or availability, and a clear, enterprise-wide view helps you optimize your entire physical, virtual and cloud-based PostgreSQL environment.
Foglight offers unattended 24x7 data collection. Its agentless architecture and minimal footprint ensure overhead is negligible on monitored hosts. Foglight deploys quickly and easily, too.
Quickly review server health, performance and workload across your PostgreSQL environment. Foglight combines database metrics with host metrics to provide a complete picture of database server performance.
See the amount of work each server is doing to support user requests. Drill down into every dimension of your data, including users, connections, SQL and sessions.
Understand the health and performance of all your databases at a glance, including calculated workload, connections, database size, conflicts and statements executed. Drill down to detailed performance statistics for any database simply by selecting that database.
View all current locks, including the user holding the lock, process ID, lock type, number of locks waiting and granted, and the specific query responsible. Easily clear queries holding specific locks.
Optimize replication and ensure data integrity by monitoring all WAL senders and their connected applications, sender processes and receiver clients, as well as the current states of all WAL senders.
Evaluate the performance of critical statements with a complete breakdown showing the query, number of calls, average response time and more. View, sort or search the top statements collected from the server.
Prevent database performance problems by monitoring write delays, which can limit the amount of memory in the shared buffer pool.
Analyze the behavior of critical PostgreSQL functions, including call rates, functions with the highest average self-time and functions with the highest average total time.
Quickly visualize all tables for a given database on a single screen, with table health, basic properties and calculated table-level operations. Understand if reads from table indexes are successfully sourced from buffer cache rather than physical disk, and see the percentageof tuples returned from index versus sequential scans.
Avoid false alerts with adaptive Intelliprofile thresholds, which ensure alarms are only triggered when baselines are breached. Easily manage and annotate alarms, including scheduling blackouts for maintenance periods.
Speed problem resolution and discover chronic issues with embedded expert advice and convenient drill-down to granular details.
Monitor hundreds of PostgreSQL database servers from a single management server.
Execute data collection through remote agents that ensure minimal overhead (no more than 2% CPU) is added to monitored database instances.
Ensure high-integrity data collection with frequent collections, or customize collection frequency to meet your business requirements.
Store historical monitoring data in the embedded data warehouse — without needing to purchase or install additional database instances for storage of monitoring data. External repositories can be leveraged in larger deployments.
A common challenge in many IT teams is the “blame game” where developers blame DBAs for stability and performance issues and vice versa. What if you had complete visibility and continuous monitoring to understand the root cause of database issues?
To gain insight into the evolving challenges for DBAs, Quest commissioned DBTA to survey DBAs and those responsible for the management of the corporate data management infrastructure. The results are in and the thought-provoking findings are now available
Databases evolve fast and smart database administrators (DBAs) evolve even faster. As the landscape shifts from reliance on relational database management systems (RDBMS) to public-cloud Database as a Service (DBaaS), so do the responsibilities of the DBA
Research reveals how continued data growth, evolving responsibilities and cloud technology are affecting DBAs.
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