Foglight for Databases Reviews

On a day-to-day basis, my main use case for Foglight for Databases is a centralized database for performance monitoring and troubleshooting. I use it to monitor database health, review CPU and memory usage, identify slow-running queries, and performance bottlenecks. I also investigate issues when an application becomes slow. I use the dashboards, alerts, and historical performance data to identify unusual behavior early.

One example was when Foglight for Databases gave me an alert indicating unusually high CPU usage on one of our databases. I used the product performance information to investigate and found that a query was taking much longer than usual and consuming a lot of significant resources. We were able to identify the query and work with the DBA team to address it before it caused noticeable application slowdown. This helped us avoid waiting for users to report the problem and reduced troubleshooting time.

Foglight for Databases has a positive impact mainly by reducing the time my team spends on routine monitoring and troubleshooting. With the centralized dashboards, we have dashboards and alerts ready. In the morning, I can simply look at them, and if there is anything concerning, I can investigate it. This has reduced the amount of manual effort needed to gather performance information across different databases, allowing the team to spend more time addressing issues rather than collecting data.

We have seen a noticeable reduction in the time spent on monitoring and troubleshooting, estimating that twenty to forty percent of troubleshooting activities have been reduced. Although we have not formally measured this, we have been able to manage more databases without increasing our day-to-day monitoring workload. The main benefit is the faster identification of issues and less effort rather than a specific reduction in the number of incidents.

The features that are most valuable to me in Foglight for Databases are real-time monitoring, performance dashboards, and alerts. I particularly value the ability to identify slow queries and investigate what is contributing to a performance issue. The historical performance data is also useful because it helps me compare the current behavior with previous periods and understand when an issue has started. Having multiple databases visible from a central data dashboard makes day-to-day monitoring more efficient.

Foglight for Databases offers centralized monitoring and performance analysis with visibility across the database environment, which supports more consistent oversight and faster issue detection. I appreciate that the tool has AI capability, and I feel confident about the governance and security features. I trust Foglight for these aspects.

The performance and AI capability, accuracy, and reliability of output from Foglight for Databases is good, giving accurate results that I can rely on. Although I still validate the information myself, it gives me trustworthy data.

Foglight for Databases allows me to monitor multiple database platforms from a centralized view. In our environment, I use it across different database platforms, making it easier to monitor overall health and performance without having to manage each platform separately. I monitor Microsoft SQL Server, Oracle Server, PostgreSQL, MySQL, Azure SQL, MongoDB, IBM DB2, SAP HANA, and Snowflake.

I assess Foglight for Databases as very effective for quickly diagnosing emerging database issues. Its real-time monitoring and alerts help me identify unusual behavior early, particularly when a performance issue arises. Using Foglight for Databases, I can understand when the issue starts and look at the timeline for any recent changes, which helps me identify the root cause without impacting performance. It is a vital tool for developers who may not have the capability to run tests independently, as it enables them to assess what is happening after changes are made.

I use Foglight for Databases' monitoring and alerting capability to identify long-running or resource-intensive queries. This capability helps us catch potential performance problems before they have a broader impact on other applications. When a query starts taking significantly longer than usual and consumes excessive CPU, the alert prompts me to investigate the query and its resource usage, allowing the DBA team to address the issue proactively instead of waiting for users to report slow application performance.

I use the solution's user interface to access database performance information. I find the data fairly easy to locate once I am familiar with the interface, as the centralized dashboards provide access to database health, resource utilization, query performance, alerts, and historical trends. When investigating a slow database, I can start from the dashboard and drill into the relevant performance information rather than collecting data manually from multiple sources. The main challenge is that some troubleshooting views can take time to learn and navigate, so a more intuitive interface would improve the experience.

I find Foglight for Databases useful for getting a centralized view of my database environment, especially when database platforms and cloud resources are involved. The ability to bring monitoring information into one place makes it easier to compare performance and understand any unusual behavior. I can determine whether an issue is isolated to one database or is a broader problem with more than one database. When an application becomes slow, I can check database health and resource allocation, monitor query performance, and see alerts and historical trends, which gives me more context while troubleshooting. This reduces the need to check each platform separately, as I can directly analyze what is performing well and what is not.

I would improve the user interface of Foglight for Databases, as I feel it is somewhat complex, especially when using the specific troubleshooting view, particularly for new users. I would also appreciate more flexibility when customizing the dashboards and alerts, so better prioritization based on impact would be beneficial. Reporting could also be more straightforward with more ready-made reports and easier customization. Clearer recommendations during troubleshooting would help users move from identifying a problem to understanding the likely root cause.

There is still room for improvement in the user interface, reporting, and alert customization, but overall Foglight for Databases has been valuable.

I have been using Foglight for Databases for about one year.

Foglight for Databases is stable.

Regarding scalability, as our databases grow, we can add additional databases to the monitoring setup without changing the overall architecture. Once a database is configured, mapping it to the centralized monitoring setup is fairly straightforward.

The customer support for Foglight for Databases has been very good, supportive, and responsive. We do not encounter issues when they involve complicated requirements. However, more complicated issues can sometimes take longer to resolve when multiple teams are involved. Overall, I am satisfied with the support, but faster resolution times and more practical troubleshooting guidance would improve the experience.

I would rate the customer support six out of ten because the support team has been generally helpful with technical issues, although for complex cases, they took considerable time to resolve.

Before using Foglight for Databases, I mainly relied on native monitoring tools provided with our databases, along with some manual reporting. Those tools were adequate for basic monitoring, but managing different database platforms separately became more difficult as our environment grew. I moved to Foglight for Databases because I wanted centralized monitoring, historical performance data, and reporting in one place. I still use native tools for certain tasks, but Foglight for Databases has made overall database monitoring more convenient.

I have seen a return on investment through time savings and better use of my team's resources rather than reducing headcount. I estimate that monitoring and troubleshooting activities take around twenty to forty percent less time. Although this has not been formally measured, we can manage more databases without increasing our day-to-day monitoring workload. Another benefit is that historical performance data makes monthly performance reviews and reporting much less manual.

In terms of pricing, the setup cost and licensing require planning from both perspectives. The initial configuration takes effort because I have to decide which database to monitor and configure according to my requirements. The licensing cost can become significant as the number of monitored databases grows. However, once the initial setup is completed, ongoing management is straightforward. I would appreciate more flexible pricing options when expanding the monitored environment.

I evaluated SolarWinds Database Performance Analyzer and Redgate SQL Monitor before choosing Foglight for Databases. I was looking for a solution that could provide centralized monitoring across my database environment, along with historical performance analysis and reporting. I considered each product's capability, licensing, cost, and setup requirements before selecting Foglight for Databases.

Foglight for Databases provides strong centralized monitoring across all my needs, and I would rate the tool nine out of ten.

When someone is looking for a tool like Foglight for Databases, I would recommend first identifying the database and performance metrics that are most important to your environment rather than trying to monitor everything at once. Start with critical databases, configure them, then create dashboards and alerts around your requirements, and gradually expand. It is worth spending time learning the reporting and historical analysis features.

My main use case for Foglight for Databases is to monitor the performance of servers and to take backups and restores.

We had a blocking issue on one of the production environments, so we use Foglight for Databases to see what processing is blocking what, and what the blocker and blocked processes are. It is easy to identify because it provides a graphical tool. We also use Foglight for Databases to verify after patching that the servers are online and that everything is functioning correctly with good health.

Foglight for Databases can monitor multiple database platforms, and in my environment, we have Oracle, SQL Server, and Informix. However, we have only used Foglight for Databases for SQL Server, so I can only speak for the SQL Server environment.

Foglight for Databases has positively impacted my organization by saving a lot of time, especially during patching when we need to verify approximately 300-400 servers manually to ensure they come up after patching. This tool has helped us tremendously.

I save three to four hours during patching.

In my opinion, the best features Foglight for Databases offers are the monitoring capabilities and the graphical interface so we can identify what is happening, as well as the ease of backup and restore.

What I appreciate most about the graphical interface is visualizing issues.

Foglight for Databases provides real-time activity data in my database operations because, once active, I can view records and go back to see what happened on a certain day. I can replay the information to see what occurred. I use it in both ways: real-time to resolve issues, especially blocking and locking issues, and I can research past events by replaying information over a certain time period.

I use Foglight for Databases to display intensive database queries. Displaying intensive database queries has greatly affected my ability to determine potential issues because when users complain about slowness, this helps us drill down onto the query that is actually causing the issues, which is very helpful.

When using Foglight for Databases for monitoring databases, it enables me to drill down and see what is causing the issue if something does not look right. This affects my database operations because we work in a very small team, so this tool helps us efficiently navigate and address issues.

My impressions regarding Foglight for Databases's ability to help monitor a variety of aspects such as the operating system, hybrid clouds, hardware, and databases across different platforms show that it is very helpful, especially for the operating system. From the DBA perspective, it helps monitor system resources to ensure the server is up and running, and when resource issues arise, it is easy to determine the cause. Additionally, database space usage is easily visualized, which helps improve operational efficiency.

The capability of Foglight for Databases to quickly diagnose and resolve emerging issues is very important to me because, as a small team, we must address issues quickly, especially in a production environment, to ensure smooth operations.

Foglight for Databases can improve by providing more graphical information, especially in the blocking and locking area, such as showing immediately which process is blocking and how to display it more visibly.

From what I have used, I cannot think of anything else that could be added. However, it would be beneficial if you could automate the development, as we currently have to deploy agents to the servers, and it would be great to reduce that number of steps.

I have been using Foglight for Databases for approximately nine years.

Foglight for Databases is stable since we have been using it for almost five to six years.

Foglight for Databases's scalability is good.

We use the vendor's premier support. Initially, we used it for deployment and training our team to handle Foglight for Databases, but after that, we hardly needed it because our team is resourceful with handling issues. However, we have the option to call premier support if we need it, and we have not had any major issues in the last couple of years.

Premier support has definitely added value to our overall investment with the Quest solution because we have certain licenses. Although I do not remember how much was invested since I was not directly involved in the purchasing process, it has added value in case we need support.

Foglight for Databases's premier support has influenced our decision to purchase additional licenses or products from the vendor. We may have a very limited number of licenses since the initial purchase, but if we were to buy new licenses, the premier support option is definitely a factor in our decision-making process.

The customer support is great, and I have received a lot of feedback from it. I even attended some of the customer meetings at the Quest office in Irvine.

I would rate the customer support an eight on a scale of one to ten.

I previously used Spotlight but switched to Foglight for Databases because Spotlight was phased out by Quest, which forced us to select Foglight for Databases.

While I cannot comment on the financial impact, time-wise, Foglight for Databases saves us three to four hours during patching once a month, which also equates to cost savings when converted into financial terms.

I have seen a return on investment in terms of money saved and fewer employees needed. It definitely saves costs indirectly and is trainable and teachable to new employees. When we were training an Oracle DBA to handle SQL Server tasks, it was very easy for them to adopt and manage, showing there is cost-saving potential.

I do not know the pricing because I was not involved in the licensing cost, so I cannot comment on that aspect. However, the setup was straightforward.

I did not evaluate other options before choosing Foglight for Databases.

My advice to others considering Foglight for Databases is to pursue it and conduct research regarding costs, as I do not know how many licenses would be needed depending on the organization. From my experience as a user for almost nine years, I can say that it is a great product and a good investment for monitoring databases, especially in a SQL Server environment.

My main use case for Foglight for Databases is to monitor database performance and identify issues before they affect our applications. I mainly use it to keep track of database health, check slow running queries, monitor CPU and memory usage, and identify any bottlenecks. One thing I find useful is that I can monitor multiple databases from a single dashboard instead of checking each one separately. Whenever we notice an application running slowly, I can use Foglight for Databases to check what's happening at the database level and find out whether the issue is related to queries, resource usage, or database connection. It also helps us catch performance issues early through alerts, so we don't always have to wait for users to report the problem.

One specific time when Foglight for Databases helped us catch or solve a problem before it affected users was when it alerted us to unusual high CPU usage on one of our databases. When we checked, we found that a query was taking much longer than usual and consuming a lot of resources. We were able to identify the query and work with our DBA team to fix the issue before it started affecting application performance. What I appreciated was that we didn't have to wait for someone to complain about the slow application. We could see the problem early and take action. It saved us quite a bit of troubleshooting time.

The features I value most about Foglight for Databases are its real-time monitoring, alerts, and performance dashboards. The dashboard is useful because I can quickly check how our databases are performing without going through multiple screens. Another feature I really value is the ability to identify slow queries and see what's causing the performance issue. The alerts are helpful, especially when something goes wrong outside regular working hours. I also find the historical performance data useful because I can compare current performance with previous days and figure out when an issue actually started. Overall, these features make my daily monitoring and troubleshooting work much easier.

Foglight for Databases has helped us reduce the time we spend monitoring and troubleshooting database issues. Earlier, we had to spend more time checking different databases to figure out what was causing a problem. Now, we can identify the issues much faster and fix them before they affect our applications. The alerts have also helped us avoid unnecessary downtime, and our team does not have to constantly check everything manually. It has made our daily work easier, saved considerable time, and helped us keep our database running more smoothly.

I think Foglight for Databases could improve its user interface. It can be complex to navigate sometimes, especially when you are trying to troubleshoot a specific issue. It can be overwhelming for someone using it for the first time. I would also appreciate more flexibility in customizing the dashboard and alerts based on our requirements. Sometimes we receive too many alerts, and it takes time to identify which one actually needs attention. Apart from these things, the product works well for our daily database monitoring.

The reporting could be improved. Sometimes when we need to share a performance report with our team or management, it takes extra effort to get the information in the format we want. Having more ready-made reports and easier customization would be helpful. Integration with other monitoring tools could also be simpler. When we are troubleshooting an issue, it would be beneficial to have clearer recommendations on what might be causing the problem instead of having to go through multiple metrics ourselves. These improvements would make our day-to-day work easier.

I have been using Foglight for Databases for one year.

Foglight for Databases has been quite stable for us. We haven't faced any major issues with the tool itself, and it handles our daily monitoring well, even with multiple databases connected. Occasionally, we have noticed some delays in data collection or had to restart an agent after configuration changes. These issues haven't caused any serious problems. Once the initial setup was completed, we haven't had to spend much time maintaining it overall.

Foglight for Databases has been quite scalable for our requirements. As our database environment grows, we are able to bring additional databases into monitoring without having to change our entire setup. Since we are using Azure and managing different database platforms, this flexibility is useful. Adding new databases does require some configuration, and we need to consider licensing and monitoring server capacity as the environment grows. Once everything is configured, managing the additional databases is fairly straightforward. We haven't faced any major scalability issues so far, although I feel the process of adding multiple databases at once could be simpler.

Our experience with Foglight for Databases customer support has been generally good. Whenever we raise a technical issue, the support team has been helpful and willing to investigate it. For more complicated issues, getting a resolution can take longer, especially when multiple teams need to be involved. I feel the documentation could also be improved, as sometimes it's easier to contact the support team than to find the exact solution ourselves. Overall, I'm satisfied with the support, but faster resolution times and more practical troubleshooting guides would make the experience better.

Before Foglight for Databases, we were mainly using the native monitoring tools available with our databases, along with some manual reporting. They worked fine for basic monitoring, but managing different database platforms separately was becoming difficult as our environment grew. We moved to Foglight for Databases because we wanted a more centralized solution with better visibility into our entire database environment. The biggest difference for us has been having historical performance data, automated reporting, and monitoring information in one place. We still use native tools occasionally for specific tasks, but Foglight for Databases has made our overall database management much more convenient.

I feel Foglight for Databases is a bit expensive, especially when you're monitoring multiple databases, as the licensing cost can add up. The initial setup also took some planning because we had to decide which databases to monitor and configure everything according to our requirements. Since we are using Azure, we also had to consider the infrastructure costs. Once everything was set up, managing it became much easier. I think the pricing could be more flexible, especially when adding a new database or expanding our environment.

We have definitely seen some return on investment, mainly in terms of time saved and better use of our team's resources. We haven't reduced our team size, but we can now manage more databases without increasing our daily monitoring workload. One example is our monthly performance review. Earlier, collecting information from different databases and preparing the reports took considerable manual effort. Now, we can pull historical data and performance trends directly from Foglight for Databases, which makes the process much easier. I would estimate around twenty to forty percent of time savings in our monitoring and troubleshooting activities, although we haven't formally measured it. I don't have an exact figure for the money saved, but reducing manual work and avoiding unnecessary troubleshooting has definitely helped us use our resources more efficiently.

Before choosing Foglight for Databases, we also looked at SolarWinds Database Performance Analyzer and Redgate SQL Monitor. We wanted to understand which tool would work better for our database environment, especially since we manage different database platforms. SolarWinds had some useful performance monitoring features, while Redgate was more focused on SQL Server. Foglight for Databases offered centralized monitoring and historical reporting capabilities we were looking for. We also considered the licensing cost and the effort required for the setup before making our decision.

I would suggest understanding your database monitoring requirements before going with Foglight for Databases because the licensing and initial setup need some planning. Don't try to configure everything at once. Start with your critical databases, get familiar with the dashboards and alerts, and then gradually add the rest. Also, spend some time understanding the reporting features because there is quite a lot you can do with them. If you're managing multiple database platforms, having everything in one place is really convenient. Just make sure your team gets proper training during the initial setup so you can get the most out of the tool. I would rate this product a nine out of ten.

I use Foglight for Databases to check the historical performance of any SQL and Oracle database, including memory and CPU utilization, current sessions and older sessions, and to tune queries and receive recommendations on whether index creation is required by analyzing the execution plan. I also monitor TempDB, other databases' growth rates, log rates, and current performance issues.

Recently, we faced a G drive incident, meaning the data drive where our data.mdf file resides. By analyzing the database file growth through a graph from Foglight for Databases, I discovered that the data was growing significantly at 100 GB per day. Based on this current growth, we predicted the needed space and worked with the Wintel team to prevent an outage.

For day-to-day operations, I use Foglight for Databases to obtain the query execution time and historical data about the query, such as how much CPU the query used and its performance, as well as to get the execution plan of a query.

Foglight for Databases positively impacts our organization by enabling us to identify slow-running queries and check the historical performance of any SQL Server instance, which is why we have relied on this tool for nine years without facing significant issues.

Using Foglight for Databases saves us time by providing a clean view with good graphical user interface options, as running dynamic management view queries manually would take considerably longer.

The best feature that Foglight for Databases offers is the SQL PI.

With SQL PI, I can perform a deep dive into any session, getting comprehensive information about that session, such as the username, system from which it is running, and the CPU usage, helping my work significantly.

Foglight for Databases provides 100% accuracy, and I do not see instances of inaccurate data.

Foglight for Databases provides real-time activity data, which I check regularly on a daily basis.

This real-time activity data helps my team monitor if a client reports that a query is running slow. We use the activity monitor to identify the head blocker and determine if it can be killed or tuned.

Foglight for Databases' capability to quickly diagnose and resolve emerging issues is essential because I need to monitor database growth, performance, current queries, and user history, allowing me to capture all relevant data.

I use Foglight for Databases to display intensive database queries, which helps us determine potential issues, as I can access the SQL PI for resource-intensive queries and receive recommendations for query tuning or index creation.

When an issue arises, such as an unavailable database instance, we have configured alerts in Foglight for Databases, which notify us through our ServiceNow queue, allowing us to respond quickly with accurate data.

Foglight for Databases allows me to monitor multiple database platforms, including MS SQL, Oracle, and HANA, enhancing our operational capabilities.

Foglight for Databases can be improved as sometimes, when checking the current query in SQL PI, it does not show the complete large query as the text gets truncated.

Otherwise, I find that Foglight for Databases is a great tool, and these needed improvements aside, it is very nice overall.

It is performing well, and we are happy with the monitoring capabilities of Foglight for Databases.

I have been using Foglight for Databases since 2018, as I started using it at the beginning of my time with HCL, while prior to that, I was using Spotlight.

Foglight for Databases is stable.

Foglight for Databases' scalability can guide and predict future storage and CPU memory requirements.

Customer support is awesome, and we have always received timely support.

On a scale of 1 to 10, I would rate customer support 10 out of 10 as we consistently receive support on time.

I previously used SolarWinds DPA and AppDynamics but switched to Foglight for Databases because it provides a much cleaner view, historical data, multiple options, and accuracy.

Foglight for Databases is deployed on-premises, but it monitors both our on-premises servers as well as Azure IaaS servers.

There is a return on investment from Foglight for Databases, as it saves time with a clean UI allowing me to access all details in a single click.

I rate Foglight for Databases a perfect 10 out of 10 because, after using SolarWinds, AppDynamics, and other monitoring tools, I find Foglight for Databases handles tasks far better than the alternatives.

I chose 10 out of 10 as Foglight for Databases offers greater capability, a cleaner view, more user interface options, and being lightweight means it does not consume much CPU or memory.

I advise others considering Foglight for Databases to choose it for its extensive monitoring capabilities across multiple database platforms, its clean user interface, and the accuracy it offers. I would give Foglight for Databases a rating of 10 out of 10.

My main use case for Foglight for Databases is for troubleshooting. We have solved many troubleshooting and performance issues with Foglight in our Oracle production databases. When an application becomes slow, I use it to examine the database workload, resource utilizations, wait events, expensive SQL statements, and blocking sessions until the affected period. This helps narrow down whether the slowdown or performance impact is related to SQL executions, lockings, CPU pressures, or IOs. After addressing the main cause of the problem, I compare the performance before and after the change to confirm the improvement. Historical monitoring is particularly useful for investigating incidents reported after they have occurred.

I faced a problem at the end of last month, specifically from September month end, when a huge batch load was running. During this time, I faced production issues and used Foglight for Databases for the investigation and identification of the problems.

I am also planning to use Foglight for Databases for AI implementations using either an integration with APEX or an integration with any of the monitoring tools because that is where we are planning to pitch in next quarter. I use this project for routine database health check monitors, monitoring, and investigating slowdowns, which are very common in our case, and also for performance alerts. I review the resource utilizations, wait events, expensive SQL statements, and all. This is a very common investigation approach that we follow, and I am planning to integrate AI with Foglight for Databases so that all these things can be taken care of automatically rather than us pitching into the same issues again.

Foglight for Databases has positively impacted my organization by providing improved monitoring and quicker troubleshooting, especially during mission-critical issues. Foglight for Databases has helped us significantly in investigating and troubleshooting problems quickly, rather than following the traditional manual approach.

The best features that Foglight for Databases offers, which I value most, are the SQL workload analysis and historical performance monitoring. They help me identify the resource-intensive SQL and investigate what was happening during a reported slowdown, while wait events analysis and blocking sessions visibility also help narrow down the cause very quickly. Having this information in one console makes troubleshooting much easier and supports proactive database monitoring. Considering this as my base, I am planning to integrate this with AI either on the cloud or on-premises.

Foglight for Databases does provide real-time activity data, and we have faced scenarios in our environment where this has been beneficial. When Foglight for Databases is deployed in our Azure public cloud environments, we use it to centrally monitor database health, performance, and availability, including our Azure SQL Database for Oracle instances.

I do use Foglight for Databases's UI to proactively alert me of long-running queries, and this affects my database operations positively. It helps identify what action can be taken on those respective queries, especially at month-end when we run into performance issues. Our database runs on AWS RDS, and Foglight for Databases significantly aids in proactive monitoring during this period.

Foglight for Databases enables drill-down from database alerts into relevant performance details such as resource usage, wait events, active sessions, and SQL activity. This helps narrow down the cause and makes troubleshooting more focused. For example, when investigating a slow Oracle application response time, I check if the slowdown coincides with CPU pressure, blocking sessions, or resource-intensive SQL statements. I examine the relevant SQLs and validate their execution plans before deciding on corrective actions. This reduces manual investigations, helps identify the right team to involve, and supports quicker incident resolutions with clear evidence.

Foglight for Databases supports monitoring multiple database platforms through a central console in our environment. We use it for Oracle, Amazon RDS for Oracle, SQL Server, PostgreSQL, MongoDB, and many more. Having a common view of database health, alerts, and performance makes daily monitoring easier and helps prioritize incidents across systems. If an application slows down, we can compare the underlying databases and investigate affected instances, which helps coordinate troubleshooting across teams and reduces the time spent switching between separate monitoring tools.

I consider rapid diagnosis one of Foglight for Databases's most valuable capabilities. Bringing alerts and performance details together helps narrow down whether an emerging issue involves an expensive SQL, blocking sessions, resource pressures, or unusual workload activities, which provides the DBA a clear starting point for corrective actions. This feature is very important for me since a slowdown in business-critical databases can quickly affect users and service commitments. Earlier detections and focused investigations help reduce troubleshooting time and prioritize issues before escalating. Foglight for Databases supports investigation, while the DBA validates the cause, applies an approved fix, and checks that performance has recovered.

I regard Foglight for Databases's broader monitoring capabilities as valuable because database performance is closely connected to the underlying infrastructures where monitoring components are configured. Visibilities into databases, operating systems, and cloud resources help put alerts into context. For example, when an Oracle database slows down, correlating its wait with CPU, memory, and disk activities helps distinguish between SQL problems and infrastructure bottlenecks, making investigations more focused and involving the right support team. The main benefit is better insights into how different layers affect each other.

As everyone is slowly shifting towards AI, the most important feature that we are planning is integrating with the current ongoing processes, along with addressing some repetitive issues. We are also planning to integrate AI with the repeated problems to come up with some solutions, but we have not found any solution for that yet. If we can integrate AI, that is my only suggestion; the rest are all good. So far, it is good. I do not have any additional improvements required beyond the AI, which I have already mentioned.

I have been using Foglight for Databases for the last 10 plus years.

Foglight for Databases is very stable.

Its scalability is good, and we are happy with it. As demand increases, it helps us with auto-scaling features as well.

Customer support for Foglight for Databases is very quick, and we are very satisfied with it. They resolve issues efficiently and also provide proper explanations for problems along with permanent solutions. I would rate customer support as nine out of ten.

Before Foglight for Databases, we used Oracle Enterprise Manager for monitoring in conjunction with SQL scripts and manual database checks. The reason for adopting Foglight for Databases was to achieve more centralized visibility across database platforms and simplify performance investigations. We still use Oracle Enterprise Manager, but we find Foglight for Databases to be much better since Oracle Enterprise Manager is useful only for Oracle-specific administrations while Foglight for Databases provides a common monitoring view for wider environments.

Foglight for Databases has helped us a lot in monitoring and performance, but I have not measured a formal financial return. I cannot provide verified figures for money saved or reduced staffing. The operational value I emphasize is more focused troubleshooting and less manual work collecting performance information from separate sources. To quantify the value, I would track average incident diagnosis times, mean time to resolutions, and hours spent on routine monitoring before and after adoption, describing the staffing benefit as freeing DBA time to other priorities rather than claiming fewer employees are needed.

We purchased Foglight for Databases from the Azure Marketplace. Regarding the pricing, setup cost, and licensing for Foglight for Databases, we implemented a project called Project Latte. My involvement was mainly in database operations rather than purchasing, so I cannot provide exact pricing or licensing figures. From an operational perspective, setting up efforts include configuring monitoring connections, permissions, and agents where required. I assess the overall value against database coverage we need, ongoing administration efforts, and the troubleshooting time saved. Clear license terms and visibilities into the cost of expanding coverage are quite important for us, although I do not deep dive personally as a DBA.

We have not evaluated other options because we are very specific to Foglight for Databases.

On a scale of one to ten, I would rate Foglight for Databases as ten out of ten. I choose ten out of ten because it has helped us save a lot of time in doing manual investigations and initial troubleshooting, which has been efficiently handled by Foglight for Databases. Considering the time, it has really helped a lot, along with the reports and the way it works, which is really appreciable.

Regarding Foglight for Databases's AI capabilities, I am cautiously positive about its governance and security from a DBA perspective. Quest documents show that encrypted communications and authenticated access are not used to train AI models, which are reassuring controls when working with database diagnostics. However, I would verify exactly what SQL text schemas and monitoring data leave our environment. Processing takes place in the US Azure regions, with AWS retention exceptions, optional feedback, and use detections in place. Data residencies and sensitive information are crucial, and I would use these AI insights to support DBA operations, following change approval procedures before production changes. Clear visibilities into data sharing, retentions, and administrative controls strengthen my confidence.

I see Foglight for Databases's AI output as a useful starting point for investigating database issues, although its value depends on whether the explanation matches the monitoring evidence and context of the problem. For Oracle troubleshooting, I validate its conclusions against the wait events, SQL execution plans, session activities, and relevant AWR or ASH data. Complex issues involving RAC, application behavior, or multiple simultaneous bottlenecks still require a DBA's judgment, and my confidence increases when the output clearly shows supporting matrices, explains its reasoning, and acknowledges uncertainty. I review and test any tuning recommendations before applying them in production.

We use Foglight for Databases to monitor the databases hosted on AWS, including Amazon RDS for Oracle. Foglight for Databases itself is deployed across all our different areas; we use it on AWS, Azure, and on-premises servers. It actually depends on the project and environment. We predominantly use Azure and very rarely use AWS.

My advice to others looking into using Foglight for Databases is to start with a proof of concept using representative databases, and I do recommend them to use Foglight for Databases. I have given Foglight for Databases an overall review rating of ten out of ten.

I am currently using Foglight for Databases with real-time monitoring only.

We use this tool for monitoring purposes only. Frequently, we monitor the tool by logging into all servers and fetching the output using queries. We can check the homepage of Foglight for Databases and verify whether all databases are running fine or not. We can differentiate based on different types of databases such as Oracle databases, MS SQL, and MySQL, and we can monitor them separately as well.

Foglight for Databases enables me to monitor multiple database platforms. It is currently monitoring MS SQL databases and Oracle databases for me. We can divide the databases based on types and monitor using those specific database types only.

Using Foglight for Databases will drastically reduce the employee size. Without Foglight for Databases, we have to use multiple employees for monitoring different databases. By using Foglight for Databases, we can significantly reduce those employees, thus saving their salaries.

Foglight for Databases saves costs when performing root cause analysis.

Foglight for Databases is a user-friendly tool. On the homepage, we can see whenever it is connected to all production and disaster recovery databases, and it is easy to monitor on the homepage itself. It displays indications such as CPU utilization, load average, and session details including the number of sessions and active sessions. It shows details such as critical outages with three indications: warning in orange color and critical outage in red color. It also displays error messages regarding what errors have occurred in that particular database, allowing us to fetch and find the error and solve the issue as soon as possible.

By clicking the database by server name, it can be divided to show the report on a node-by-node basis. In that report, we can see multiple data such as the users connected to the database, the SQL running, and how much time it has been taking. We can also see the output in pie charts, making it very easy to analyze.

Foglight for Databases is easy to monitor, and we can fetch the report node-by-node. We can obtain all other database information such as backup information, table space size information, disk group size, ASM storage, and SP file parameter files. We can directly fetch everything in Foglight rather than using commands in the server itself. Report generation is also easier in Foglight, and using this, we can optimize performance and queries.

Foglight for Databases is very useful; however, the negative side we face is that customer care support is not frequent. If any issues related to Foglight arise, we cannot reach customer care support as soon as possible. It takes much longer compared to other third-party tools, and that is a major issue we are facing with Foglight for Databases.

Foglight for Databases is good for monitoring, and we can fetch problematic issues and queries. However, the only main drawback is the customer care support. It is available only during the general shift, so if any issue occurs after 6:00 p.m. or before 9:00 a.m., there is usually no one to handle it. I think there are only two or three people handling customer care for Foglight for Databases.

I have been using Foglight for Databases for nearly two to two and a half years.

I did not have any issues with Foglight for Databases.

Foglight for Databases is very useful; however, the negative side we face is that customer care support is not frequent. If any issues related to Foglight arise, we cannot reach customer care support as soon as possible. It takes much longer compared to other third-party tools, and that is a major issue we are facing with Foglight for Databases.

Foglight for Databases is good for monitoring, and we can fetch problematic issues and queries. However, the only main drawback is customer care support. It is available only during the general shift, so if any issue occurs after 6:00 p.m. or before 9:00 a.m., there is usually no one to handle it. I think there are only two or three people handling customer care for Foglight for Databases.

For customer support regarding Foglight for Databases, I would rate it a three out of ten.

Before going with Foglight for Databases, we were using inbuilt services in Oracle databases only. We could utilize certain queries and services in Oracle to fetch and find problematic solutions, and we worked in that format only.

Foglight for Databases saves costs when performing root cause analysis.

Using Foglight for Databases will drastically reduce the employee size. Without Foglight for Databases, we have to use multiple employees for monitoring different databases. By using Foglight for Databases, we can significantly reduce those employees, thus saving their salaries.

For intensive database queries, Foglight for Databases is useful. If any abnormal activity occurs such as sessions, CPU load average, or any kind of issue on the database side, we can fetch what the problematic query is, who runs that query, and what the issue is. We can then gather that output and optimization query to send to the application team.

Monitoring different aspects such as the operating system, hybrid clouds, hardware, and databases across different platforms is important because at one point, we can monitor different types of operations such as the operating system side and the database side. If we are using Oracle cluster, we can fetch information regarding the cluster, ASM info, and everything else. We can monitor everything in one single point, and it is very useful to us.

Foglight for Databases is the best tool for monitoring all aspects such as database, backup information, storage information, and operating system side. Everything is very easy to analyze, and it throws error and warning messages as soon as it completes the tasks. It is very useful for monitoring. However, the only issue is customer care support.

I rate this review an eight out of ten.

I use Foglight for Databases to monitor resources like PostgreSQL, MySQL, MariaDB, and Mongo, and I check all the resources in the database tools to identify where complications arise. Foglight for Databases helps by monitoring all parameters and SQLs that are running for a long time and provides a useful dashboard.

On a day-to-day basis, I configure new resources on the database, and for that, I enable monitoring on Foglight for Databases for resources like MySQL and Mongo. I recently observed that when I upgrade my database from one version to another, the agent sometimes stops responding. At that time, I found that deactivating and reactivating the agent helps it reconfigure the resources properly. I also noticed that SQL PI data loads very slowly at times, affecting the dashboard population until I reactivate the agent.

For all resources, I have integrated the ticketing system for alerts generated, and in that capacity, Foglight for Databases provides accurate monitoring. I would say Foglight for Databases does its job well because sometimes I don't have oversight on every resource, and the alarm system configured on Foglight for Databases gives timely and relevant responses for all resources while also displaying week-wise data to help prioritize alerts and database issues.

Foglight for Databases is currently deployed on-premises, as I am utilizing my own data centers without onboarding any public or private cloud resources.

I do not utilize the solution's angular UI for proactive alerting of long-running queries, as the alerts are generally configured differently.

I have not yet implemented the angular UI extensively. I would like to expand my knowledge about this feature, but I currently do not have a significant number of resources using it.

Foglight for Databases has positively impacted my organization by addressing critical scenarios, particularly with network issues, as it highlights problems accurately, which I consider a fantastic feature. Foglight for Databases's SQL PI provides extensive insights on database operations, connection pooling, and user connections through accurate graphical representations, and its capabilities ensure that even during outages, it shares the latest data information.

In the context of Foglight for Databases, I have seen a reduction in downtime as accessing the dashboard helps me monitor resources efficiently. This is essential for investigating and explaining data happenings at the database level, which has streamlined my operational response time significantly.

Foglight for Databases does provide real-time activity data, which I find very useful in my database operations, although sometimes it triggers false alarms. This feature aids in monitoring and streamlining my operational tasks.

Foglight for Databases is assisting me with monitoring intensive database queries, which helps me identify potential issues, especially when SQL PI presents data that illustrates the performance of database activities and shows how resources are utilized, enhancing my ability to address ongoing challenges.

In terms of monitoring databases, Foglight for Databases enables me to drill down and understand the underlying issues effectively. For example, it helps me assess how maintenance can inadvertently affect running queries, allowing me to manage ongoing processes without significant disruptions.

I monitor various database platforms using Foglight for Databases, including MySQL, PostgreSQL, Mongo, Oracle, and MS SQL. This capability to visualize and manage multiple database operations from one dashboard significantly enhances my overall monitoring and response efficiency.

Foglight for Databases's ability to track various aspects of the OS, hybrid clouds, hardware, and multiple databases has been beneficial for my insights. While it accurately collects performance data, there are instances of inaccuracies when the agent is not configured properly, which I must address manually.

Foglight for Databases's capacity to quickly diagnose and resolve emerging issues is essential, especially when databases enter hung states. I assess emerging issues using the dashboard, which greatly aids in analyzing past performance and managing ongoing challenges.

I would like to add that a feature that would enhance the database environment is that Foglight for Databases should work on updating inactive resources by reflecting them on the main dashboard. Although it is currently doing this, I believe it should be more specific about inactive resources instead of deactivating the whole agent manager, which can lead to disconnections due to network issues, causing a cluster of alerts to spike, which could be optimized.

Regarding improvements for Foglight for Databases, I believe that after a database upgrade, the response updates should be configured automatically, ensuring it indicates when the database is not reflecting data.

I believe I have covered everything regarding improvements needed for Foglight for Databases, and there are no additional concerns from my side.

I have been using Foglight for Databases for almost one year and two months.

I find Foglight for Databases to be very stable.

Foglight for Databases scales efficiently and is reliable for scaling my resources.

As of now, I do not have vendor premier support and rely on Quest support for any issues. I have provided feedback on their effectiveness in handling my needs.

While I primarily use Quest for support, it has added value since their solutions have helped me streamline Foglight for Databases's response. I find their assistance helpful in addressing both operational and technical inquiries.

Customer support is well-mannered, well-managed, and provides accurate information. They are very helpful, and I would rate them high.

I would rate customer support a 10 out of 10 because they assist me promptly, even in situations beyond my control.

Previously, I used Grafana and some monitoring tools like Zabbix, which were quite complicated. I switched to Foglight for Databases because it simplifies and enhances my database investigation capabilities.

Foglight for Databases has saved me costs by contributing significantly to root cause analysis. For example, it has saved me a considerable amount of time and resources, preventing unnecessary expenses that could arise when rectifying database issues.

Currently, I am not pursuing additional licenses or products. Purchases and vendor management are handled on the client side.

The setup of Foglight for Databases requires considerable time for onboarding, but it facilitates the streamlining of processes that would otherwise require manual intervention.

Before implementing Foglight for Databases, I evaluated various options and found that it stands out due to its extensive features and the wide range of database flavors it supports.

I would rate Foglight for Databases 9.5 out of 10. Some flaws I noticed include Quest support taking time to rectify issues, which is why I deduct half a point.

The reason I rate it 9.5 is that, as a DBA, Foglight for Databases has significantly aided me in investigating various aspects, making my workflows more manageable.

In terms of AI capabilities in Foglight for Databases, I have not extensively expanded my resources within AI, but I think AI could further enhance my functionalities. For instance, if the AI agent could monitor resource availability and alert me to connectivity issues, it would be an invaluable tool for my operations.

While AI capabilities have not yet been broadly configured in my organization, I believe Foglight for Databases is already performing well in terms of accuracy. If AI enhancements were implemented, they could enable compliance with more precise data and allow quick rectifications that manual checks may miss.

I highly recommend Foglight for Databases over other tools due to its detailed analytical capabilities that can assist in various aspects beyond just databases.

For example, when production CPU is at 95%, I identify which query is consuming excessive CPU by checking Foglight. I then review the execution plan in SQL Server Management Studio and verify the indexes, statistics, and whether the query has recently changed. I coordinate with the development team if query modification is required and monitor CPU after the remediation.

I have also monitored blocking in Foglight. When Foglight shows significant blocking, I identify the head blocker first rather than identifying and killing the session. I check the blocking session ID, blocked session ID, SQL statement, transaction duration, database involved, application, and locks to determine whether the transaction is expected or abnormal. If necessary, after appropriate approval, I terminate the blocking session and investigate the underlying causes.

Foglight for Databases is deployed in a hybrid environment in our organization. We monitor the databases running on-premise infrastructure as well as the databases hosted in AWS. This is useful for our DBA team because we can have centralized monitoring access with different environments instead of using separate monitoring solutions for each platform. We primarily use Foglight for Databases for database health checks, performance monitoring, alerts, troubleshooting, and historical performance analysis across these environments.

Foglight for Databases has positively impacted our database operation mainly by improving monitoring and troubleshooting efficiency. It provides a centralized view of database health checks and performance, which helps us identify issues such as high CPU, memory blocking, and slow running queries more quickly. It has also helped us reduce the time spent on the initial investigation during production incidents because we can quickly identify the affected database based on the relevant performance metrics, with historical data being useful for trend analysis and root cause investigation.

I estimate Foglight for Databases can save around 20 to 30 minutes during the initial investigation for production database issues because it gives me a centralized view of CPU, memory, blocking, waits, sessions, and query activity. During a production incident, Foglight for Databases helped me quickly identify that the issue was related to high resource utilization and blocking sessions. Instead of checking multiple metrics separately, I start with the Foglight for Databases dashboard to identify the affected database and session, then validate the details in SSMS.

Foglight for Databases features like monitoring information and dashboard presentation are prominent in the product. Feature capabilities I usually use include database health check monitoring, real-world performance monitoring, CPU memory, disk space issues monitoring, block and deadlock detection, SQL query performance analysis, alert and notification, historical performance trend analysis, database availability monitoring, capability and storage monitoring, and centralized monitoring for multiple database environments.

The features I use most are real-time database performance monitoring and troubleshooting, which give me a centralized view of important metrics such as CPU, disk space monitoring, blocking sessions, waits, and query performance. It adds the most value during a production incident because I can quickly identify which database is responsible for the SQL activity that caused the issue, validating the findings in SSMS. The historical performance data is also useful for identifying trends and comparing performance before and after changes. Overall, it helps me reduce the time required to identify the root cause of any database performance issue.

I use Foglight for Databases's real-time activity and performance monitoring capability during database operations, particularly for production troubleshooting. For example, if an application suddenly becomes slow, I use Foglight for Databases to check the current database activity, active sessions, CPU utilization, waits, blockings, and resource investigation in SQL.

I use Foglight for Databases Angular UI to monitor database activity and identify long-running or resource-intensive queries. For example, if a query starts running significantly longer than the normal execution plan time, Foglight for Databases can bring it to our attention. I review the query details along with CPU, I/O, waits, and blocking information, then validate the issue in SSMS using the execution plan and DMVs.

Foglight for Databases allows us to drill down from a high-level database server alert into more detailed performance information. For example, if I see something unusual in a high-level alert, I first validate the alert and identify which server or database is affected. I then use Foglight for Databases's drill-down capability to move from the overall health view into the specific performance that's causing the alert.

One useful capability of Foglight for Databases is that it provides centralized monitoring across multiple database platforms.

I assess Foglight for Databases's capability to quickly diagnose emerging database issues as very useful for day-to-day production operations. This ability to start with a high-level alert and drill down into database activity, sessions, queries, blocking, and CPU waits shortens the initial troubleshooting process. It's especially important in production environments where sudden performance issues can quickly affect application users.

My impression is that Foglight for Databases provides useful visibility across different layers of the environment, particularly database and infrastructure metrics that are relevant to DBA operations. Having information about database performance, server resources, CPU, memory, blocking, and query activity in a centralized monitoring platform is invaluable.

Foglight for Databases is useful for database monitoring and troubleshooting, but there are a few areas where it could be improved. I would appreciate more customization in the dashboard and simpler configuration of alerts. It would help to easily customize the dashboard based on the specific requirements for different DBA teams and environments. Another useful improvement would be more intelligent alert correlation and root cause analysis so that related alerts can be grouped and the tool can clearly indicate the issues.

I have used Foglight for Databases over the last 12 months.

Foglight for Databases is stable in my experience.

Foglight for Databases handles growth reasonably well, especially when additional database instances need to be brought under centralized monitoring. As our database environment changes, we can add monitoring instances and continue using the same monitoring and alert approach.

I have not personally interacted with Foglight for Databases customer support team frequently, but my experience with them has been positive. Whenever we need assistance, the support process is handled through the appropriate organizational support channels.

Before Foglight for Databases, we relied more heavily on native database and infrastructure monitoring tools such as SQL Server Management Studio, SQL Server agent alerts, and Windows manual checks. The biggest improvement for DBA operations was the ability to quickly identify and drill down into performance issues and use historical information for troubleshooting and trend analysis.

I have seen a return on investment using Foglight for Databases for our database operations.

I was not involved in the formal evaluation process, so I do not know which competing solutions were evaluated before Foglight for Databases was selected. I understand that the key requirements were centralized database monitoring, performance visibility, proactive alerting, troubleshooting capability, and support for the organization's database environment.

Governance and security are important considerations when using AI capabilities in database monitoring. AI-driven recommendations must follow the same access control and security policy as the underlying monitoring platform. I particularly look for strong role-based access control, secure handling for database and performance information, auditability, and clear visibility into how AI-generated recommendations are produced and what data they use.

I find the output from Foglight for Databases most valuable as a starting point for troubleshooting rather than as a replacement for DBA analysis. For production issues, I always validate the recommendations against SQL Server metrics, execution plans, DMVs, logs, and the actual application behavior before taking corrective action. This is particularly important because database performance issues can have multiple contributing factors. Overall, I consider the output useful for accelerating investigation, but I still rely on data validation before making production changes.

I recommend that organizations evaluate Foglight for Databases by first identifying their main monitoring and troubleshooting requirements and then validating those requirements with a representative setup of their database environment.

I give Foglight for Databases an overall rating of 8 out of 10 because it is very helpful for any database monitoring such as CPU and memory, which is essential for my daily routine work.

Foglight for Databases serves as a proactive database monitoring and performance troubleshooting tool for identifying bottlenecks such as blocked sessions, deadlocks, and resource contentions in database issues, particularly for SQL Server, Oracle, and PostgreSQL.

In my daily work, I regularly use similar monitoring tools to investigate SQL Server performance issues. For example, I recently investigated high CPU utilization and blocked sessions by analyzing active queries, wait statistics, and execution plans, which helped identify the root cause and improve database performance. I have used Foglight monitoring dashboards and historical performance analysis to follow the same troubleshooting approach.

Although my direct experience with Foglight is not advanced, I have extensive experience with similar database monitoring solutions. I see Foglight as a valuable tool to support monitoring, capacity planning, performance optimization, and incident prevention. It can also help DBAs like myself and infrastructure teams collaborate more effectively by providing centralized visibility, historical performance data, and alerts to improve availability and reduce downtime.

Our database infrastructure embraces a hybrid environment, combining on-premises systems with AWS and Azure for cloud services. We primarily use AWS and Microsoft Azure, with AWS being my primary cloud.

Foglight for Databases has positively impacted my work and organization by improving my team's efficiency through similar monitoring tools, which have reduced manual checks and helped prevent production incidents. The proactive monitoring has allowed us to quickly identify CPU spikes, blocked sessions, and resource bottlenecks.

The best features for me are the real-time performance monitoring, historical performance analysis, and the intelligent alerting in a centralized dashboard across multiple database platforms offered by Foglight for Databases. I find its ability to easily identify SQL bottlenecks, blocked sessions, and deadlocked resource contention very useful.

A centralized view helps my work by making it easier to monitor multiple database environments from a single dashboard, allowing us to quickly identify performance issues and prioritize the critical ones. In my experience with similar monitoring tools, this is particularly relevant when managing dozens of SQL Server, Oracle, and PostgreSQL instances. For example, during a high CPU or blocking incident, having consolidated metrics helps the team quickly find the affected database and reduce troubleshooting time.

Foglight for Databases provides near-real-time database activity monitoring. In a recent SQL Server production incident, I used the real-time monitoring to investigate high CPU utilization and a blocked session. I analyzed active queries, wait statistics, and execution plans, and identified resource contention in queries, helping the team address the performance bottleneck. Although I use monitoring tools other than Foglight for Databases, its real-time activity monitoring could support the same troubleshooting process, helping reduce investigation time and minimize application impact.

I have not directly used Foglight for Databases' Angular UI for proactive alerts, but I use a similar monitoring tool that alerts for long-running queries, blocked sessions, and performance bottlenecks. For example, configuring alerts based on query execution time, CPU consumption, and block duration helps our DBA team proactively identify issues, investigate the potential execution plan, and take corrective action before database performance is significantly affected.

I have not used Foglight for Databases for displaying intensive database queries, but I use a similar monitoring tool to identify resource-intensive queries based on CPU and I/O usage. Foglight for Databases' performance analysis capabilities can support the same proactive troubleshooting approach.

Foglight for Databases offers drill-down capabilities to investigate performance issues including SQL execution, wait events, blocked sessions, and resource utilization. Although my direct experience with Foglight for Databases is not advanced, I use similar functionality in other monitoring tools. For example, when investigating high CPU, I drill down into active sessions and specific queries and execution plans to find the root cause. This process reduces troubleshooting time and helps my team perform optimally.

Foglight for Databases supports monitoring multiple databases, including SQL Server, PostgreSQL, MySQL, and Oracle. My database environment includes these technologies across AWS, Azure, and on-premises infrastructure. I have not personally managed how these platforms integrate with Foglight for Databases, but a centralized solution that can provide performance and availability, CPU utilization, and blocked sessions for the application is crucial.

I see Foglight for Databases' cross-platform monitoring capability as a major advantage, especially for hybrid environments that combine AWS, Azure, and on-premises infrastructure. Correlating database performance with OS metrics, CPU, memory, storage, and infrastructure health provides a more complete view of system behavior and helps identify root causes faster. In my experience with similar monitors, this visibility is especially valuable for distinguishing database-level bottlenecks from infrastructure issues, improving troubleshooting efficiency, capacity planning, and overall system availability.

I consider Foglight for Databases' diagnostic capability a strong advantage. This feature is extremely important to me because I manage business-critical databases where rapid incident detection and root cause identification are essential. In my experience with similar tools, quickly identifying blocked sessions, inefficient database queries, and resource contention significantly improves troubleshooting efficiency, reduces MTTR, and minimizes production impact.

Foglight for Databases could improve by offering a more intuitive, responsive user interface, easier initial configuration, and more customizable dashboards. I would also like to see stronger AI-driven anomaly detection with more predictive and fewer active alerts to reduce false positives and integration with cloud platforms such as AWS and Azure.

A valuable improvement would be more automated root cause analysis, better integration with DevOps and incident management tools, and simplified monitoring configuration for large environments with hundreds of instances.

From a database and security perspective, Foglight for Databases should provide very strong governance with role-based access control, encryption, and data loss prevention of sensitive database information.

We could use infrastructure as code tools such as Terraform or Ansible to enable automated monitoring deployment configuration.

I have been using Foglight for Databases for more than 10 years.

Foglight for Databases is very stable.

Foglight for Databases offers strong scalability potential for growing environments, supporting centralization across multiple database platforms and instances and accommodating growing infrastructure. Proper sizing, configuration, and resource management are essential.

However, I believe the biggest value would be fast access to experienced support engineers during critical production incidents. When managing business-critical databases, having good support and expanded guidance for quick issue resolution can significantly reduce downtime and operational risks.

In my experience, Premier Support is not a direct influence on additional license purchase decisions, as I have not been involved in those decisions. However, I believe that having a good support experience to assure resolution of vendor expertise would be very important for future decisions to expand the existing license.

I would rate the customer support a potential eight.

I have experience with monitoring solutions such as Datadog and Zabbix.

A good database monitoring tool can significantly reduce operational costs by accelerating root cause analysis. While I do not have specific time and cost savings for Foglight for Databases, I know that faster troubleshooting reduces manual investigation and also lowers the business impact of performance issues.

While I cannot quantify an ROI for Foglight for Databases, I have seen clear benefits from similar monitoring solutions. For example, when managing approximately 40 database instances, centralized monitoring reduces the need to manually connect to each instance to check CPU, block, and storage utilization.

I would rate Foglight for Databases an eight. I choose eight out of ten because Foglight for Databases offers strong database monitoring performance, but I see room for improvement for a better user experience, simplicity, AI-driven root cause analysis, and cloud integration. Since my direct experience is limited, this rating is primarily based on its capabilities and how they compare with similar monitoring solutions that I have used extensively.

Based on my experience with similar monitoring tools, AI-driven insights can be valuable for identifying anomalies, performance bottlenecks, and potential issues. I would always validate recommendations against actual data and historic trends, especially in critical production environments.

I recommend starting with a proof of concept focused on the most critical database to evaluate its accuracy, performance, scalability, and integration with existing tools.

Monitoring databases is a major use case for Foglight for Databases. We use Foglight for Databases to display intensive database queries.

Foglight for Databases is not a tool that you use to see before a problem happens. However, after we have an issue such as downtime, service failure, or performance issues on the database, we use it to identify the queries that are causing problems, maybe a stored procedure, identify the user that is running that query, the machine where that query is coming from, and do our job as database administrators to optimize the query.

When using Foglight for Databases for monitoring databases, it enables me to drill down and see what is causing the issue if something does not look right. We often use it to drill down and see how long something has happened for, especially for performance tuning, looking at how long any current issue has run for, identify bottlenecks, and get recommendations, because Foglight for Databases gives recommendations on some levels. We use those recommendations to improve or optimize the system.

The best features of Foglight for Databases should be the real-time dashboard and the overview dashboard.

I find the overview and real-time dashboards the most beneficial in Foglight for Databases. For example, with the overview dashboard, I could know what is happening on the database in real-time. Most especially when it comes to blocking sections, I can see if the blocking sections are increasing and then take actions. With the real-time dashboard, I can see performance on a bigger scale, including CPU usage, memory usage, and general performance.

In terms of scalability with Foglight for Databases, I think the tool is somewhat robust compared to other monitoring tools that I have used. I would say it is somewhat rigid to understand if you are a beginner, and it might take a while to understand how to go about using the tool, which requires that training must be done. I would not say there are significant limitations or scalability issues with it.

Besides scalability and customization aspects, I think with the newer version of Foglight for Databases, there are many bugs that need addressing. We encountered instances where it was not even monitoring databases at all or giving us false alerts, which impacts our usage of the application. So I would say that needs improvement, as it leads to confusion about whether databases are down or if the alerts are accurate.

I have been working with Foglight for Databases for about three years.

I have had stability issues, crashes, downtimes, and performance issues with Foglight for Databases in this recent version I have been using. I have not experienced many issues with it in other organizations. However, with the latest version, we have had many crashes, sometimes it stops working entirely, and it can take days to restart the service. Therefore, I think it is an issue related to the new version that has been upgraded.

In terms of scalability with Foglight for Databases, I think the tool is somewhat robust compared to other monitoring tools that I have used. I would say it is somewhat rigid to understand if you are a beginner, and it might take a while to understand how to go about using the tool, which requires that training must be done. I would not say there are significant limitations or scalability issues with it.

I use the vendor's premier support for Foglight for Databases. On occasions when we have issues, we always call Quest, and they come on the call to help us out.

I would rate tech support on a scale of one to ten as a six. The reason I give it a six is that most of the time we have an issue, the support seems time-framed. Even if the issue is not resolved, they often want to get off the call because their time has elapsed, which leads us to go back and forth on the same issue until we eventually get it solved.

Prior to adopting Foglight for Databases, I previously used other solutions of the same kind, including Dynatrace and Ash viewer.

I decided to switch to Foglight for Databases because, as I mentioned earlier, it is more robust and gives more insights compared to the other tools I have used. However, the application's robustness makes it somewhat hard for beginners to understand how it works, which requires additional training to ensure everyone can adjust and fully utilize it.

I evaluated other solutions before choosing Foglight for Databases. The decision to go with Foglight for Databases stemmed from its robustness and the insights it provides compared to other applications and tools.

My experience with the deployment process of Foglight for Databases was challenging because the installation was done on a Linux environment instead of Windows. With Linux, we faced many configuration and permission issues, particularly ensuring that the agent server and management server could communicate with the database server. There was much back-and-forth in getting the installation fully set up before we started using it.

A consultant was used for the deployment of Foglight for Databases, and I think he was from Egypt, but I cannot remember his country exactly.

I would not say Foglight for Databases saves me cost when performing root cause analysis because, based on what I know, payments are made upfront. Regardless of what I use the tool to do, you have to make payment upfront for the license and support, and then you use it based on whatever issues that arise. So in terms of payment or fees, I do not think it matters.

Prior to adopting Foglight for Databases, I previously used other solutions of the same kind, including Dynatrace and Ash viewer.

I decided to switch to Foglight for Databases because it is more robust and gives more insights compared to the other tools I have used. However, the application's robustness makes it somewhat hard for beginners to understand how it works, which requires additional training to ensure everyone can adjust and fully utilize it.

I evaluated other solutions before choosing Foglight for Databases. The decision to go with Foglight for Databases stemmed from its robustness and the insights it provides compared to other applications and tools.

My impressions of Foglight for Databases' ability to help me monitor a variety of aspects such as the OS, hybrid clouds, hardware, and databases across different platforms have been great so far. I have used it in multiple organizations, and my impression is that it is a tool that every organization should use or buy into because they understand its value.

Based on my experience with Foglight for Databases, I recommend running it on a Windows server, as it is much more flexible compared to Linux. Additionally, trainings should be conducted after installation so that everyone can understand how to use the application and utilize it fully. I would rate this review a seven out of ten.