Application performance monitoring (APM) is a hot topic these days. This can be attributed to the increased complexity of application environments and the need for APM solutions that scale and meet the demands of modern applications. This post will provide you with an introduction to what APM is, how it works, where it falls short, and why you should consider using one. It also provides guidelines on selecting an appropriate solution and steps you should take before deploying any APM solution in your environment.
What is Application Performance Monitoring?
APM is a software solution that provides visibility into the performance of network, host, and application-layer transactions. APM solutions are deployed on servers, desktops, or mobile devices to allow you to monitor critical metrics for applications running in your environment. These include transaction response times and errors associated with server resources such as CPU utilization, memory usage, and disk IO, among other things.
You can think of an APM solution like any traditional monitoring tool which measures KPIs related to availability (e.g., time up/down), capacity planning (e.g., average resource consumption) but applied explicitly to measuring the end-user experience of business transactions instead of individual components within IT infrastructure environments.
APM solutions provide a centralized view of application performance across an organization which can help you understand if end-users experience any issues. It also enables you to identify the root cause and determine whether it is related to network, server/host, or even client-side factors such as bandwidth constraints, poor wireless connectivity, etc. This information can be used for things like capacity management (i.e., right-sizing your environment), identifying trends in user behavior to take action based on those observations, and many others depending on what the solution offers its customers.
Difference Between Web Performance Monitoring (WPM) and Application Performance Monitoring (APM).
The main difference between web performance monitoring (WPM) and application performance monitoring (APM) is that WPM solutions focus on delivering individual web pages or assets. In contrast, APM solutions are concerned with transactions across multiple pages, systems, and services. In other words, WPM solutions are typically used to optimize the delivery of static content such as images, CSS files, etc. In contrast, APM solutions are used to monitor and troubleshoot business-critical applications.
Another critical distinction is that most WPM solutions only provide visibility into page-level metrics such as time to first byte (TTFB), page load times, number of requests/second (RPS), and average response times. These measurements can help understand how well a website is performing, but they do not provide any insight into the performance of the underlying application. On the other hand, APM solutions offer visibility into all aspects of an application’s performance, including end-user response times, errors, and resource utilization.
APM solutions can also monitor transactions that span multiple systems and environments (e.g., on-premises vs. cloud), which WPM solutions cannot do. This makes them ideal for troubleshooting issues that may be affecting applications running in hybrid or multi-cloud deployments.
Lastly, WPM solutions are typically less expensive than APM solutions because they lack many features that make APM so valuable, such as transaction tracking and root cause analysis.
In short, WPM solutions are suitable for optimizing the delivery of static content, while APM solutions are ideal for monitoring and troubleshooting business-critical applications.
Why should you consider a commercial APM solution?
There are many reasons why you should consider using a commercial APM solution. One of the main benefits is that they provide real-time visibility into business transactions’ performance and health, which can help you achieve faster mean time to resolution (MTTR) when issues arise. This reduces downtime, increases customer satisfaction, and improves productivity for IT teams because instead of just reacting reactively after an issue occurs, organizations with mature application monitoring capabilities will be able to proactively identify potential problems before end-users experience them in production environments. Furthermore, if your organization does not have any formalized procedures or practices, implementing a commercial solution could quickly increase awareness around app quality within your department or company and improve collaboration between key stakeholders such as developers, operations, and business users.
Another reason to consider using a commercial APM solution is that they offer more features than open-source alternatives. This includes transaction tracking (across multiple systems and environments), root cause analysis, performance analytics, and application mapping, which can be extremely useful for troubleshooting issues that may affect applications running in hybrid or multi-cloud deployments. Lastly, commercial solutions are typically more reliable than open-source alternatives because their code is publicly available, and the quality of support varies from vendor to vendor.
Commercial APM solutions provide a better experience for end-users, leading to higher customer satisfaction and tremendous revenue potential due to increased productivity. This makes them worth considering if your organization has many business transactions that need monitoring across multiple systems and environments, such as on-premises vs. cloud computing platforms since they have several features not found in free/open-source options.
In short, there are many reasons why you should consider using a solid commercial solution instead of an open-source alternative when deciding how to monitor application performance. Doing so can save you time and money while also increasing customer satisfaction.
Essential features of an APM solution.
When choosing an APM solution, you should consider the most critical features of your organization. However, there are some essential features that all APM solutions should have to provide a good experience for end-users and troubleshoot issues effectively.
These features include:
Real-time visibility into the performance and health of business transactions
When choosing an APM solution, one of the most important features that should be at the top of your list is real-time visibility into business transactions. Without this insight, it would be challenging to identify and resolve issues before impacting end-users in production environments, leading to a loss in revenue due to downtime.
Transaction tracking (across multiple systems and environments)
Another essential feature of an APM solution is transaction tracking which allows you to see how transactions are performing across various systems and environments. This can be extremely useful for troubleshooting issues that may affect applications running in hybrid or multi-cloud deployments.
Root cause analysis
One of the essential features of any APM solution is root cause analysis, which helps identify the underlying causes of performance problems. This information can then be used to fix the issues and improve the overall performance of your applications.
A good APM solution should also provide performance analytics to see how your applications are performing over time. This data can be used to make informed decisions about investing resources to improve app performance.
If your organization has specific needs beyond these essentials, you may want to consider commercial options as they typically offer more features than free/open-source alternatives. For example, transaction tracing across hybrid or multi-cloud deployments can be a critical feature for organizations with applications running in those environments.
What are the critical metrics for APM?
When selecting the most critical metrics that should be tracked in an APM solution, they typically fall into one of three categories: business transactions, application health, and infrastructure. Each category is briefly discussed below, and some critical metrics for each object type.
The performance data gathered from your applications can help you troubleshoot issues related to user experience or even identify opportunities where resources can be reallocated across different parts of a multi-tiered application stack. For example, suppose a particular service consistently takes longer than expected. In that case, some areas could benefit from additional hardware such as faster disks or more memory since keeping services running smoothly requires sufficient capacity at all times during peak usage periods due to the shortening of response times.
Some key metrics for business transactions include:
- Average Response Time
- Number of Transactions per Minute/Second
- Transaction Error Rate
In addition to understanding how individual transactions are performing, it is also essential to have a holistic view of an application’s health which can be used to identify and fix systemic issues before they cause customer pain. For example, if an application has high CPU utilization, that could be symptomatic of a problem somewhere in the codebase or even indicative of contention points with other services. Collecting data on all aspects of an application’s health will help you detect these types of issues before they become more significant problems.
Some critical metrics for application health include:
- Average CPU Usage (percentage)
- Memory Utilization (in bytes and percentage)
- The number of Threads and Thread State (e.g., blocked, runnable, etc.)
Infrastructure Performance Monitoring can also help you monitor the performance of your infrastructure components, such as networking equipment or virtual machines. For example, suppose a particular type of network latency is affecting transactions. In that case, that could indicate problems within that specific hardware component, such as overloaded queues, which should then trigger alerts, so they get resolved quickly before causing more widespread issues for other parts in your environment. Some key metrics for monitoring infrastructure performance include:
- Network Latency/Jitter/Packet Loss Rate (%) -Disk Latency
- Data Throughput (Bytes per Second)
- CPU Usage (percentage) for different virtual machines/containers.
When it comes to APM, there is no one size fits all solution, and the critical metrics that are most important to you will vary depending on your organization’s needs. By understanding what type of data should be collected and how it can be used, you can make more informed decisions about which tool is best suited for your specific situation.
Five best practices for APM.
Once you have selected an APM solution, a few best practices can help ensure its success.
Start with a small set of business transactions and grow over time
As your application portfolio grows and becomes more complex, it is important to periodically revisit which transactions should be monitored as some may no longer be representative of the most critical workflows. Adding too many business transactions at once can impact performance and cause data overload, making it difficult to isolate issues.
Map Business Transactions to Services/Microservices
Organizing your applications into services or microservices can make them easier to manage from an operational standpoint and improve APM data usability. In addition, by associating individual business transactions with their related services, you can get a more granular view of performance across all layers of your application.
Instrument Critical Transactions First
Some transactions are more critical to the success of your business than others and should be given higher priority when it comes to being instrumented for APM. Focusing on the essential workflows first will help ensure that bottlenecks are identified and resolved as quickly as possible.
Use Appropriate Metrics for each Transaction
Not all business transactions are created equal, and as such, not all metrics are appropriate for capturing data on every workflow. It is essential to select the right set of metrics based on the specific needs of the transaction so that data overload can be avoided. For example, tracking CPU utilization might be more important than memory usage if a CPU-intensive transaction.
Automate Data Collection and Analysis
The benefits of automation cannot be overstated, and when it comes to APM, automating the data collection and analysis process can save time and improve accuracy.
Companies such as Unravel Data have taken APM solutions to the next level by combining DataOps with AI to provide one platform that improves performance, lowers costs, and accelerates cloud migrations using real-time AI.
By following these best practices and selecting the right tool for the job, you can ensure that your organization’s applications are running smoothly and meeting all business requirements. Performance problems can significantly impact the bottom line and the customer experience, so it is essential to take a proactive approach to monitor and troubleshoot.