Database Monitoring: Best Practices & Metrics to Consider

If you’ve ever waited for an airline reservation system or point-of-sale terminal to complete a task, you’ve probably heard an employee mutter the excuse, “Sorry, our systems are slow today.” If you work in IT, you probably wondered what, exactly, was causing the slowdown. The application often gets the blame, but it could be a problem with the network, hardware, or database.

Database performance issues often translate into sub-optimal application responses. Database monitoring helps you avoid this problem. This article explores how database monitoring works, why it’s important, and how to do it right.

What is Database Monitoring?

Database monitoring, also known as database performance monitoring, is a critical IT practice that involves observing how well a database handles its workloads. It’s a process of continuous observation and analysis.

Whether you’re managing relational databases like MySQL, PostgreSQL, or SQL Server, or NoSQL databases like MongoDB or Cassandra, keeping a close eye on key performance metrics can help detect issues before they become major problems.

Using specialized database monitoring tools, database monitoring measures performance factors like database query response times and utilization of hardware resources. It’s one of many IT monitoring practices, including application monitoring and networking monitoring.

How Does the Database Affect System and Application Performance?

Database performance directly affects application performance. If you understand how software applications work, this will make perfect sense. Most enterprise applications run on top of a database, searching for and retrieving data, creating and modifying data as they run. The application calls on the database to perform functions whenever a user needs to complete a task or when the application is running an automated process.

Consider the following simplified example of how an enterprise resource planning (ERP) application handles a customer address change:

1. The user uses the app’s search window to look up the customer’s contact information. This triggers a database search query using structured query language (SQL).
2. The database returns the contact information (a database “read” operation).
3. The user inputs the customer’s new address and saves it (a database “write” operation).

In this case, the application invokes three database operations: one to search for the customer record; one to “read” it; and one to “write” new information into it.

It’s useful to consider the scale of these processes. In a big enterprise, thousands of users could simultaneously invoke database functionality to handle financial transactions, process payroll or generate invoices. The faster the database can handle the read-and-write operations, the more rapidly the process will flow.

However, if the database is not performing well, that will slow application processes down, negatively affecting the user experience. In the worst-case scenario, the volume of process requests will cause the database to crash.

Why is Database Monitoring so Important?

It’s invariably a good decision to monitor databases for performance and related functional factors, and its importance is evidenced by the database monitoring software market reaching $2.4 billion in 2024.

The continual collection and analysis of database performance metrics enables the enterprise to troubleshoot database problems and remediate them quickly. Done right, this leads to a good user experience and employee productivity.

Database monitoring​ is important for the following reasons:

• Troubleshooting database issues—Poor database performance can arise for a variety of reasons. An effective database monitoring solution will be able to determine the cause of the problem.
• Remediating database performance problems—By accurately identifying a performance issue, database monitoring gives database administrators (DBAs) the information they need to correct the problem before it affects user experience and business operations.
• Predicting database problems—With artificial intelligence (AI) and algorithmic techniques (time series analysis, regression analysis, machine learning), database monitoring can enable predictive analytics that assess performance data to determine if a database problem will occur in the future.
• Planning for future load requirements—By generating data on database performance for a given workload, database monitoring can help system architects plan for future load requirements, e.g., peak holiday season needs.
• Optimize overall database performance—Database monitoring helps DBAs spot slow processes or resource-intensive queries that slow down database response times. With this information, they can modify queries and otherwise tune the application to enable optimal database performance.
• Optimize resource utilization—Database performance problems are often related to hardware resources such as random access memory (RAM) utilization and processor speeds. Database monitoring should be able to differentiate between problems in the database and problems in the underlying resources, enabling administrators to optimize resource utilization and performance.
• Build resilience—Database monitoring tools may be able to highlight usage patterns that cause the database to crash. By anticipating these performance thresholds, database monitoring can be a factor in designing failover to secondary database instances, resulting in greater resiliency for the system. Not to mention greater overall IT Resiliency
• Improve application performance—Given the database’s role in driving application performance, strong database monitoring should support the process of improving application performance, e.g., by identifying how certain queries are causing application performance problems.
• Meet service level agreements (SLAs)—In many enterprises, the IT department is bound to meet SLAs. Common SLAs for standard IT maintenance or break-fix support may be a 24x7x4 response time, however in extreme circumstance some applications must respond to inputs within one second worldwide. Database monitoring can flag situations where database performance puts a system at risk of failing to meet the SLA.
• Detect security issues—Data breaches often result in anomalous activities in the database, such as repetitive queries from a single user or a high volume of queries at odd hours. Database monitoring solutions can serve as a frontline detection instrument for cyberattacks. A database monitoring solution can be configured to alert security analysts when it detects suspicious user behaviors or data-processing events in the database. This, accompanied with an effective network data loss prevention solution, would provide a robust security practice.

Different Factors that Impact Database Performance

To monitor database performance is to measure and parse five core factors that affect how the database functions:

1. Workload—This comprises the complete volume of requests coming from applications, users, and administrators. The workload includes queries, batch jobs, system commands, and transactions, e.g., e-commerce order processing.Workloads vary from one moment to the next. At peak times, such as during holiday sales, the workload may be quite high volume. During off hours, the workload might be nonexistent.
2. Throughput—This is a measure of work performed during a period, e.g., queries per second. Throughput can be a potential bottleneck. For instance, if a database can handle 100 queries per second, but the application is sending 200, the database will slow down or crash.
3. Resources—Databases run on hardware. Relying on elements like memory, disk storage, caches, and central processing unit (CPU) affect database performance. For example, poorly optimized queries can consume excessive CPU, memory, and I/O, affecting the performance of the entire database server.
4. Database optimization—To optimize a database for performance, DBAs can execute strategies that increase the database’s speed and efficiency. For instance, they can get rid of unused tables or ensure the database indexing is correct. Indexes that are inaccurate or outdated force the database to work excessively hard.
5. Contention—When more than two processes need to access the same data at the same time, e.g., two users trying to update the same record simultaneously, the resulting contention can lead to a “locking” of the record. This is necessary, as it ensures data quality. The contention reduces throughput, however.

Different Modes of Database Monitoring

Database monitoring operates in three modes. Not everyone does all three at the same time, but each is necessary to track overall database functioning and achieve an optimal state of operation:

Performance Monitoring

Performance monitoring comprises a deep and comprehensive gathering of database performance data, establishing baseline performance for normal operation and analyzing the metrics to spot problems and identify issues.

Metrics include query performance (for workload and throughput), database response times, the efficiency of query execution, and the utilization of resources.

Modern performance monitoring often uses real-time dashboards, automated alerts, and historical data visualization to facilitate proactive management and ongoing optimization.

Availability Monitoring

Availability monitoring measures database uptime and proactively searches for issues that can affect database availability. The goal is to minimize database downtime. Some common strategies include:

• Service pinging to confirm operational status
• Redundancy and replication monitoring – particularly in clustered or distributed environments
• Incident tracking and alerting systems – these reduce mean time to recovery (MTTR).

Database Log and Event Monitoring

Databases generate activity logs that contain patterns and other signifiers of performance that reveal current or future problems. It helps in root cause analysis and proactive issue resolution.

The records are read and analyzed by specialized tools, and once analyzed they enable diagnostics and performance optimization, along with awareness of security threats. Logs may also be integrated with SIEM tools, for enhanced threat detection.

10 Key Database Metrics to Monitor

To serve its purpose, the database monitoring process needs to collect diverse database monitoring metrics​.

Each of the following database metrics on its own tells a part of the story, but it’s impossible to get a comprehensive sense of database performance without collecting multiple data points and analyzing them as a whole. Here are 10 database performance metrics​ to monitor to achieve this goal:

1. Response time—This measures how much time has elapsed between a database query or transaction and the database’s response. The metric is valuable as a standalone datapoint, especially when compared to SLAs. Response time is also useful to track as a trend. If it’s getting slower over time, that suggests a problem of load management or other factors that need to be addressed.
2. Open connections—A database maintains connections to users and other systems that requires its functionality. The number of open connections is a metric that relates to load. If database access monitoring shows that the number is too high, that will affect performance.
3. Database throughput—This refers to the volume of work the database can execute in a given period of time, e.g., queries answered per second. If the number is low, that suggests a performance problem that needs to be remediated. Getting this metric might involve database server monitoring.
4. Shard distribution and load—Sharding is the process of storing pieces of a database on different servers. Its purpose is to facilitate stronger performance and scalability. However, it’s helpful to understand how much load each shard is supporting. If a shard is experiencing a load that is too heavy, that can affect the overall performance of the database.
5. Most frequent queries—Understanding the most common queries, i.e., the top 10, provides an opportunity to examine the efficiency of the queries that are using the biggest portion of database capacity. By making these top queries more efficient, it is possible to improve database performance.
6. Memory usage—The amount of system memory a database uses relates to efficiency and performance. Measuring memory usage is a way to determine if memory is a performance bottleneck that slows down database functioning.
7. CPU usage—Measuring the proportion of CPU capacity used by a database with a database monitoring system​ helps admins optimize resources. If CPU usage is high, which diminishes database performance, then splitting the database load between multiple servers will improve the situation.
8. Query details—A database health monitor can examine how a query is executed and how it affects database performance. Detailed analysis of queries should lead to query optimization.
9. Events and Errors—Database events like system notifications and user logins create a data stream useful for identifying problematic patterns and trends. When a database generates an error message, the frequency and specifics of those errors shed light on what’s going wrong in the database. Knowledge of errors informs database remediation and performance optimization.
10. Database Size – If the database size is growing rapidly, it may indicate inefficient data management or an impending storage problem. Monitoring the growth rate of tables, database size, and space available for expansion will help in avoiding storage problems.

Collectively and separately, these metrics can appear on a database monitoring dashboard. Admins should be able to see metrics and trends in real time using the dashboard.

Top 4 Challenges of Database Monitoring

DB performance monitoring comes with its share of challenges. Here are four common issues that arise in database monitoring and performance management​:

1. Being Locked Out of the Controls

In some cases, such as with packaged applications, you may not have access to the queries that affect database performance. They’re built into the application code, and you can’t change them. You might see clearly in the monitoring data that the queries are inefficient, but you’re stuck.

It’s not a hopeless situation, however; as you can observe how the database responds to application processes and modifies the database’s resources and configuration to achieve optimal performance within these constraints.

2. Lacking Skills

The IT department needs specialized skills to monitor DBs. Not all team members will have the knowledge to do the work. Alternatively, you may not have the budget to hire, train, and retain database monitoring people.

Outsourcing to an infrastructure managed services provider can be an option, as such providers often provide database monitoring services. An MSP can set up monitoring and deploy the necessary tooling, and the in-house IT team support ongoing monitoring.

3. Dealing with Complexity

Databases are just one element in complex IT environments. And, there may easily be more than one type of database at work. This leads to a need to engage in cross-platform database monitoring and other complicated processes.

One solution is to focus on database monitoring where it counts the most, such as in supporting the performance of customer-facing applications. Another solution is to use a database agnostic monitoring tool that presents data from multiple database types in a single pane of glass.

4. Coping with Analysis/Paralysis

Database monitoring is a data- and analytics-intensive process. It’s possible to get overwhelmed with data and run into the classic analysis/paralysis dilemma. It can be hard to know where to start.

The solution is to prioritise monitoring tasks and focus on critical metrics, like the ones that support optimization of databases for key operational applications.

4 Database Monitoring Best Practices

IT departments that want to start database monitoring can embrace a growing body of best practices.

1. Choose a Place to Start, Review, and Improve, but Plan for Growth

Database monitoring can be an intimidating process to start. There are many different metrics to collect, and complexity in the IT estate makes it difficult to know where to begin. The best practice is to start in an area of monitoring that’s relatively simple to execute.

Define Clear Performance Benchmarks – baseline performance for normal operation, and thresholds. Gather your database monitoring requirements​ and socialize with the team members assigned to the work. Once you have agreement on the goals and requirements, select a tool and get started. Review the process periodically to assess whether database monitoring is improving database performance. The data being collected will help you understand if you’re succeeding.

2. Select the Right Tools

You have a wide choice of tooling for database monitoring. The best practice is to find a tool that will be relatively easy to support. This might mean it works on a familiar technology stack. Also, database monitoring tools are now often part of a broader “observability platform” (or network observability) that can also monitors infrastructure or cloud environments.

The choice of database monitoring tool may be predetermined, in that you simply have to switch on the database monitoring functions of a platform that’s already been deployed. This may not be a bad thing, in that it allows you to align database monitoring with other monitoring processes and integrate database performance analytics with observations about network performance.

It’s important that a database monitoring tool can manage the following at the very least:

1. Analyze historical data to generate forecasts and detect trends for insight into future scalability and resource allocation.
2. Schedule regular health checks for errors, response time, throughput, memory and CPU usage, etc.
3. Monitor database performance for slow and inefficient queries that could result in performance bottlenecks.
4. Segment metrics by environment to ensure issues are not promulgating to production – separate monitoring for production, pre-production, and development databases.
5. Monitor database access logs for failed login attempts, and privileges to ensure that security standards are followed.

3. Align with Business Goals

Database monitoring should align with business and IT goals. For example, if the business wants to improve customer experience by speeding up e-commerce transaction processing, database monitoring should focus on that.

4. Seek Specialist Guidance

Database monitoring can be difficult to get right. External expertise can help a lot. Don’t be afraid to ask for help.

This does not necessarily mean setting up a long-term service relationship. It could be a matter of getting help setting up the monitoring so existing team members can do the work.

Database Monitoring Checklist

Database monitoring can be a difficult process to navigate if the required steps are not in place at the beginning. Using the points highlighted in this article, we have developed a concise database monitoring checklist to get you started:

• Identify high-priority metrics to collect
• Gather database monitoring requirements
• Understand the goals of database performance analysis
• Select a tool that enables:
  • Real-time monitoring
  • Performance metrics
  • Query performance analysis
  • Resource utilization analysis
  • Audit logging
  • Anomaly detection
• Select a database monitoring tool that has:
  • Automated alerts
  • Customizable alerts
  • Scalability
  • Cloud and on-premises measurement capabilities
  • Multi-database platform monitoring support
  • Customizable dashboards

Work with a Database Monitor Partner in Park Place Technologies

Database monitoring is a critical aspect for your infrastructure; however, it is complex. Every stage, from setup to continuous monitoring, requires careful planning, which can be hard to manage for an in-house team.

Our Infrastructure monitoring tool, Entuity Software™, provides database monitoring for your entire environment. Entuity offers support for database instances, engines, services and utilization and performance metrics, ensuring that your database is healthy and infrastructure Uptime is consistent.

To learn how Entuity can scale up your database monitoring processes, speak to Park Place Technologies today.