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Application performance monitoring (APM): Tools, metrics, and examples

With contributions from Klaas Hermans .

Application performance monitoring may sound technical and something that your engineers handle, but it’s actually a vital tool for product managers. APM tools measure the quality of the applications that constitute your product, providing key insights into user experience and valuable data to identify areas for improvement.

What is application performance monitoring (APM)?

Application performance monitoring (APM) is the practice of measuring, analyzing, and optimizing an application’s performance. This process involves tracking various metrics and indicators to pinpoint performance issues and bottlenecks. Performance monitoring tools offer insights into the behavior of an application and help identify areas that require improvement.

As a product manager, you’ll likely need APM tools to measure key metrics of your product. For instance, application pages should load within a few seconds because Google search penalizes slow websites in their search result rankings, and users can become frustrated with delays.

Accurate measurement of site performance is crucial, especially because influencing factors can vary across different environments. The performance experienced during testing may not be the same as in production, further emphasizing the importance of APM tools.

At its core, APM is a comprehensive approach to monitoring and analyzing the performance of software applications. It enables you to get real-time insights into critical performance metrics, uncover bottlenecks, and proactively address issues that impact user experience and outcomes.

Benefits of application performance monitoring

Application performance monitoring (APM) offers numerous benefits that extend beyond merely troubleshooting. It serves as a compass for optimization, guiding you toward activities that enhance your product’s performance, scalability, and cost efficiency. APM empowers you to make informed decisions by providing a deep understanding of resource utilization, network dependencies, and scalability potential. With these insights at hand, you can fine-tune resource allocations, optimize code, and streamline operations.

One of the key advantages of APM is its ability to offer actionable insights. These allow you to take immediate action to resolve performance issues and ensure a smooth, uninterrupted user experience. APM tools are instrumental in identifying performance problems such as slow response times, errors, and crashes. Without these tools, significant issues in your product could go unnoticed.

Moreover, APM isn’t limited to technical considerations alone — it also provides valuable insights into user experience. Capturing and analyzing user interactions reveals how customers engage with your product. This data identifies pain points, user preferences, and areas of friction, enabling you to tailor your offering to meet expectations.

For example, Uber relies on APM to ensure the smooth functioning of its ride-hailing platform. Its product teams monitor metrics such as request processing time, GPS accuracy, and driver-to-rider matching efficiency. Optimizing these performance factors through APM tools’ insights enables Uber to provide a seamless experience for both drivers and riders.

Perhaps the most significant benefit of APM is its impact on the bottom line. Application performance monitoring enables you to stay agile and adapt to evolving market demands while gaining a competitive edge, ultimately boosting revenue.

In one case where I worked on a product that was receiving complaints about slow performance times from customers over the phone. The handful of comments we received were not enough to justify investing in improving the performance. However, when we utilized data gathered from our APM tools, we discovered that the problem was significant in certain areas of the application — making it well worth the investment. The data also enabled us to focus our efforts on improving the area of the application that would have the most impact.

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Key APM metrics

To fully harness the potential of application performance monitoring, you need to understand the key metrics and indicators that can help assess and measure your product’s performance.

Some common APM metrics include resource utilization, transaction tracing, database performance, network latency, and user satisfaction. However, three metrics stand out when it comes to assessing and measuring the performance of your software applications:

• Response time
• Error rates

1. Response time

This metric refers to the time it takes for your application to respond to a user request. It measures the overall speed and responsiveness of your application. Lower response times indicate better performance and a more seamless user experience.

2. Throughput

Throughput measures the rate at which your application can process a specific number of transactions or requests within a given time period. It reflects your application’s capacity to handle concurrent user interactions. Higher throughput indicates better performance and scalability.

3. Error rates

Error rates track the frequency and severity of errors occurring within your application. This metric measures the reliability and stability of the software. Lower error rates indicate a more robust and stable application, while higher ones signal potential issues affecting user experience and overall performance.

Common challenges and considerations

While application performance monitoring (APM) offers numerous benefits, it also presents several challenges that need to be addressed for successful implementation.

Here are six challenges and considerations to be aware of:

• Navigating complex environments
• Ensuring scalability
• Managing data overload
• Managing alerts effectively
• Promoting organizational collaboration
• Adapting continuously

1. Navigating complex environments

Modern applications often consist of complex architectures, including multiple layers, microservices, and third-party integrations. Monitoring all these elements requires specialized tools and techniques to accurately capture data across the entire stack.

2. Ensuring scalability

As applications grow in size and user base, your APM solution needs to scale accordingly. The monitoring infrastructure should handle increased data volume, provide real-time insights, and support growing demands without impacting application performance.

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3. Managing data overload

APM generates a vast amount of data. Handling and analyzing this data can be overwhelming.

It’s crucial to have effective data management and analysis strategies in place to efficiently extract valuable insights and avoid information overload.

4. Managing alerts effectively

APM tools generate alerts based on predefined thresholds and anomalies. Managing these alerts effectively is critical to avoid alert fatigue and focus on incidents that require your attention.

Setting up intelligent alerting mechanisms helps you prioritize and respond promptly to critical issues.

5. Promoting organizational collaboration

Effective APM implementation requires collaboration between different teams — development, operations, quality assurance. Establishing clear communication channels, shared goals, and cross-functional collaboration ensures a holistic approach.

6. Adapting continuously

Application environments are dynamic with frequent updates, deployments, and changes. You need to adapt your APM strategy to these changes.

Regular evaluation and adjustment of monitoring configurations, performance baselines, and metrics are necessary to keep up with your evolving application landscapes.

Real-world examples of successful application performance monitoring

To truly understand the power and potential of application performance monitoring (APM), let’s examine some real-world examples of companies that have successfully implemented APM to optimize their product performance and enhance user experience:

Cushman & Wakefield

• Jaguar Land Rover (JLR)
• Macmillan Learning

When Rappi, a popular delivery app in Latin America, started seeing performance issues and bugs within its web app, it sought out an application performance monitoring tool to help its product team elevate its user experience .

LogRocket’s session replay feature enabled Rappi’s team see exactly what users were experiencing and pinpoint the precise moments when issues arose. The ability to view the application through the users’ eyes provided them with actionable insights on areas that needed improvement.

As a result, Rappi managed to significantly cut down the time spent on debugging and troubleshooting, thereby increasing their overall productivity. This case study underscores the critical role of effective application performance monitoring in enhancing both user experience and operational efficiency.

Cushman & Wakefield, a global commercial real estate services firm, tapped into the potential of APM to improve the usability of its digital platforms. The company had historically faced challenges related to performance issues and bugs that were hindering smooth user interactions.

Using LogRocket’s unique session replay feature enabled Cushman & Wakefield to view user interactions firsthand and identify exact points where users encountered problems most frequently. Armed with this detailed understanding of user experiences, they were able to identify opportunities for improvements within their digital platforms and drastically reduce the time spent on debugging and troubleshooting.

Dojo, a leading fitness platform, leveraged LogRocket’s application performance monitoring capabilities to enhance its user experience.

When it encountered performance issues and bugs within its web application, Dojo turned to LogRocket for its unique session replay feature, which allowed the team to see exactly what users were experiencing and pinpoint the precise moments when users encountered issues.

LogRocket enabled Dojo to significantly reduce the time spent on debugging and troubleshooting, thereby improving the team’s overall productivity. This case study highlights the importance of effective application performance monitoring in enhancing user experience and operational efficiency.

Application performance monitoring tools

The most commonly used APM tools include:

• IBM (Instana)
• VMware (TO)

Best practices for implementing APM tools

Effective implementation and utilization of application performance monitoring tools requires a strategic approach. Here are eight best practices to consider:

• Clearly define objectives
• Choose the appropriate APM tool
• Monitor key performance indicators (KPIs)
• Implement proper instrumentation
• Establish baselines and alerts
• Continuously monitor and analyze
• Foster collaboration across teams
• Iterate and optimize

1. Clearly define objectives

Start by defining your objectives and desired outcomes for APM implementation. Understand which specific metrics and insights you want to gather and how they align with your goals. This will guide you in selecting the right APM tools and establishing relevant performance benchmarks.

2. Choose the appropriate APM tool

Evaluate and select an APM tool that aligns with your needs. Consider factors such as scalability, ease of integration, real-time monitoring capabilities, and the ability to track both application and infrastructure performance.

3. Monitor key performance indicators (KPIs)

Identify and monitor KPIs that directly impact user experience and business outcomes. Focus on metrics that provide actionable insights and align with your objectives.

4. Implement proper instrumentation

Equip your application code with the necessary monitoring agents and libraries to capture relevant performance data. However, ensure this does not significantly impact the application’s performance itself. Use distributed tracing techniques to trace requests across multiple components and gain insights into end-to-end performance.

5. Establish baselines and alerts

Set baselines for normal performance behavior and establish alerts to notify you when performance deviates from the expected range. This enables quick identification and response to potential issues, minimizing downtime and user impact. Define thresholds for different metrics and configure alerting mechanisms accordingly.

6. Continuously monitor and analyze

APM is an ongoing process, so it’s crucial to continuously monitor and analyze performance data. Utilize real-time dashboards, reports, and analytics to gain insights into application behavior, identify performance bottlenecks, and prioritize optimization efforts.

7. Foster collaboration across teams

Encourage collaboration between development, operations, and quality assurance teams for a holistic approach to performance monitoring. Cross-functional collaboration can help your teams effectively troubleshoot issues, optimize code, and improve application performance.

8. Iterate and optimize

Use APM insights to iteratively optimize your application’s performance. Continually evaluate and refine your monitoring strategy. Regularly review and update performance baselines and KPIs as your application evolves.

Using LogRocket for application performance monitoring

If you’re considering adopting an application performance monitoring (APM) tool , whether you’re managing web-based or mobile apps, LogRocket offers several advantages and unique features, including:

Instrumentation

Session replay.

• Error tracking and severity scoring

Network errors and frustrating network requests

Performance monitoring, continuous monitoring, collaboration and troubleshooting, optimization and iteration.

Integrating LogRocket into your application is as simple as adding the LogRocket SDK to your codebase. Once integrated, LogRocket autocaptures user sessions, ensuring you don’t miss out on any data. This includes user interactions, network requests, JavaScript errors, and other key performance data that is crucial for understanding your application’s behavior and performance from a user’s perspective.

With this level of detail at your fingertips, you’re equipped to make evidence-based decisions for enhancing your product.

LogRocket’s session replay feature helps you gain a profound understanding of how performance impacts user behavior. Through replaying user sessions, you can observe firsthand how users interact with your application under various performance conditions.

Identifying and understanding usability issues that arise from these interactions can shed light on the subtle ways in which performance shapes user behaviors. Observing this cause-effect relationship provides you with actionable insights to guide your efforts toward enhancing the user experience.

Error tracking

LogRocket’s Galileo extends the capabilities of traditional error tracking by automatically capturing and logging JavaScript errors that occur in your app. With its severity score feature, Galileo quantifies the impact of each error on your users — a high score indicates a serious issue leading to a significant number of negative user experiences.

Using these features together results in receiving real-time notifications about errors along with detailed error reports and stack traces — all leading to quicker diagnosis and resolution of issues.

Understanding where network performance intersects with user experience is crucial in maintaining a smooth and responsive application. Particularly, knowing which network requests fail or perform poorly can point to areas of your application that may be negatively impacting the user experience.

LogRocket’s performance monitoring capabilities allow you to identify not just failed network requests, but also those that take an unreasonably long time to complete. By providing insights into the request size, response size, and duration of every network call, LogRocket helps you pinpoint troublesome requests that might result in slow page loads or unresponsive features.

Additionally, LogRocket allows you to understand these issues in context. Instead of viewing them as isolated incidents, you can review them within actual user sessions. This broader perspective reveals how users interact with your application when these issues occur — whether they abandon their task or find a way around it.

Monitor and analyze key performance metrics provided by LogRocket, such as page load times, network requests, and CPU and memory usage. Identify performance bottlenecks, slow-loading pages, and resource-intensive operations that impact user experience.

Maintain continuous monitoring of your application using LogRocket to identify emerging issues and trends. Regularly review performance metrics, user sessions, and error reports to stay proactive in identifying and resolving potential issues before they impact users. You can even set up automated alerts that notify you via email, Slack, or Webhook when a new issue occurs on your site.

Share LogRocket session replays and error reports with your development and support teams to facilitate collaboration and troubleshooting. The detailed session information helps reproduce issues and understand the context in which errors occurred, leading to faster resolution.

Utilize the insights gained from LogRocket to optimize your application’s performance. Analyze session replays and performance data to identify areas for improvement, optimize code, reduce latency, and enhance overall user experience.

Application performance monitoring (APM) is a vital tool for measuring the quality of your product’s applications. It provides key insights into user experience and generates data that can help identify areas for improvement. As a product manager, investing in a robust APM tool and integrating its data into your product management process is crucial.

APM tools like LogRocket empower you to optimize the user experience and deliver a high-quality product. These tools not only help in identifying potential issues but also guide you towards enhancing your product’s performance, scalability, and cost efficiency.

APM empowers you to make informed decisions that enhance overall user satisfaction and ultimately boost your bottom line.

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Application Performance Monitoring 101

A complete guide to what is apm and how it works, table of contents.

In today's digital market, modern apps have to not only bring value but provide around-the-clock availability, fast responses, and real-time problem-solving. Because all businesses rely on software applications their performance is one of every organization's main concerns and biggest headaches, especially if their applications are not just a part of their business, but the business itself. This is where APM comes into play.

In this guide, we are going to dive deep into what is application performance monitoring, how it works, and why and how to use it to help you troubleshoot performance issues faster and ensure peak app performance and flawless user experience.

Definition: What Is Application Performance Monitoring

Application Performance Monitoring (APM) is the strategy and practice of continuously monitoring and tracking application performance and availability, as well as end-user experience. Using APM solutions, IT and DevOps teams can detect anomalies, understand trends, optimize resource usage, and troubleshoot performance issues before they impact end users. Such tools enable you to gather insights that help ensure customer satisfaction and drive business growth.

Application Performance Monitoring shouldn't be confused with Application Performance Management as they are often used interchangeably as ‘APM.'

How Is Application Performance Management Different

Application Performance Management is the broader strategy of managing the overall performance, starting with code, application dependencies, transaction times, and user experience. Monitoring is a small – but critical – part of it. It points out, typically via alert notifications, that there is a problem.

On the other hand, performance management takes it a step further. By using the alerts sent out by your monitoring tool, it allows you to see when and where along their journey, users encountered problems and why these problems occurred. For example, monitoring will alert you that your app or website is slow or down, but management will help you understand the causes and make changes that could potentially address the problem.

Such a complete strategy ensures full visibility into app performance, helping DevOps teams spot trends and be better prepared to respond to similar issues in the future.

Why Do You Need Application Performance Monitoring

When it comes to the digital economy, avoiding downtime and measuring the availability, response time, and behavior of every business transaction is crucial.

Detect Why Applications Are Running Slow

When you're facing application slowness, you need to determine why your app is slow, since when it's been running slowly, and what is causing slowness. That would be easy if it were not for how modern software applications look today – highly distributed, multi-tier, multi-element architectures based on app development frameworks. However, while that helps build better software applications, it makes performance management and monitoring increasingly difficult if you were to stick to traditional monitoring techniques such as performing ping tests or measuring server-level metrics (network activity, memory, CPU, and disk usage, etc.).

These techniques can't help you analyze the interdependencies between components when you work with a distributed application. Logs , metrics , events are everywhere – in the cloud, across clouds, in hybrid clouds – sometimes hard to locate and manage, thus hard to find out why your app is running slow.

Ensure End-to-End Visibility of Your Application

There are other ways to work your way around application monitoring, with methods such as synthetic transactions , manual instrumentation of the code, or customer feedback. However, while these do have their own – important – role in a monitoring strategy, they need additional configuration until they can offer the same perks as an APM tool.

This would be both time- and money-consuming. Instead, a comprehensive APM solution gives you end-to-end visibility into how your application performs without needing extra effort from you.

How Does Application Performance Monitoring Work

Application performance monitoring works by:

• Tracking if your app is behaving as it should, within normal parameters.
• If not, sending alerts and collecting data regarding the source of the problem.
• Analyzing the data while considering the impact it has on business.
• Offering insight on how to adjust your app environment so that you can easily spot and fix similar issues in the future before they impact the end user. Thus, APM helps you take a proactive approach to troubleshooting.

What Does APM Measure: Metrics You Should Track

There are two types of metrics that APM tools measure: the ones that show how end-users experience app performance and those that monitor infrastructure resources. Below are the most critical application performance metrics you should monitor:

• User satisfaction/Apdex scores – provided by Real User Monitoring (aka User Experience Monitoring), Apdex is a measurement of your users' level of satisfaction based on the response time of request(s) when interacting with your website or application.
• Response time – the time it takes for a user of an application to receive a response from an application.
• Error rates – the number of application errors in some period of time.
• Number of application instances – the number of instances of some application. In today's dynamic deployments this number typically varies with traffic, application usage, etc.
• Request rates – the number of requests in some period of time. The higher the rate, the busier the application.
• Application and server, virtual machine, or container CPU usag e – the CPU usage of the underlying infrastructure.
• Application availability/uptime (SLAs) – the extent to which an application is operational, functional, and usable for fulfilling user requests.
• Garbage Collection (GC) – for Java Virtual Machine, Node.js Virtual Machine, and other runtimes that perform garbage collection.

Application Performance Monitoring Strategy Requirements:

That sounds simple enough, but in reality, you need a non-trivial setup to reap the full benefits of application monitoring. Here's what your application performance monitoring strategy should include:

1. Digital Experience Monitoring

Also known as end-user experience monitoring (EUEM), digital experience monitoring (DEM) tracks how a software application behaves from a user's point of view, looking for the times when they experience slowness, downtime, or errors. You can monitor end user experience proactively with synthetic monitoring solutions like Sematext Synthetics , or passively with real-user monitoring , meaning tools such as Sematext Experience .

Learn about the difference between these two methods in our blog post about real user monitoring vs. synthetic monitoring and see where RUM fits into the APM strategy in RUM vs. APM .

2. Dynamic Application Architecture Display (Service Map)

This is a map of how all the components of your application communicate with each other. APM tools automatically discover these dependencies and interactions and update them in real-time. Having the data available in a visual form makes problem detection easier.

3. Code Profiling

Transaction profiling, also known as transaction tracing or code-level performance profiling, analyzes the flow of every user transaction and isolates specific interactions where performance issues are detected. Tracing allows you to follow the user's journey from frontend to backend. That way, you can find the exact line of code, database query, or third-party call that affects application performance.

4. Transaction Tracing

Many performance issues are caused by memory leaks in the server, slow network connectivity, virtualization bottlenecks, etc., making infrastructure monitoring a must for ensuring peak app performance.

An application performance monitoring tool enables deep-dive analysis by collecting performance metrics in the form of transaction traces from all the components in your infrastructure. More specifically, it performs distributed transaction tracing, as it tracks transactions across tier boundaries providing end-to-end performance visibility along with the information you need (app and server metrics) to connect application infrastructure and performance with the user journey. Such solutions help keep an eye on the health of every business transaction as they happen so that you can easily understand when, where and why app slowness happened and user experience was affected.

5. IT Operations Analytics

IT operations analytics refers to analyzing data to identify usage patterns, trends, and performance issues that you can leverage to build a better plan on how to deal with similar situations before they occur and affect end-users.

Application Performance Monitoring Tools

A complete application monitoring solution consists of one or more tools that allow you to monitor all three core elements we mentioned earlier – digital experience monitoring, application discovery, tracing and diagnostics, and artificial intelligence for IT operations.

Unfortunately, there are no free open-source projects that cover all three aspects of APM as a package. Usually, they offer only one, be it infrastructure monitoring , RUM , or tracing , which you can combine if you want to go open-source all the way. Among the best, we can name Jaeger , Zipkin , Stagemonitor , Pinpoint , Weave Scope , Scouter , and Apache Skywalking. They've gathered large communities around them that are driven to innovate and help by coming with new features that meet users' needs.

On the other hand, there are a lot of vendors that offer both standalone monitoring tools and the whole package. We, at Sematext , are one of them.

Why Use Sematext as an APM Tool

Sematext Cloud is an APM solution . It provides end-to-end visibility into your web application's performance. It traces requests across multiple applications, tiers, servers, microservices, and processes, all the way down to databases, to detect the slowest and under-performing parts of your stack.

Sematext uses this data along with error rates and failed transactions to build a dynamic map of your complete app architecture – including connections to external services and databases – that shows how all components interact with each other. The AppMap makes it easier for you to track application health and performance.

How to Choose the Right APM Software

Besides being easy to use and able to provide actionable insights, your application performance monitoring tools should be able to:

• manage applications in language(s) your applications use
• monitor performance at code-level
• track end-user experience
• use artificial intelligence
• allow you to monitor the entire infrastructure
• offer information that helps you connect app performance metrics with business outcomes.

As businesses go through digital transformations such as cloud migration and container orchestration the risk of app downtime goes up, making application performance management and monitoring more important than ever.

APM is essential to ensure software application availability, making using such a tool a must, especially if you're running a SaaS business. APM tools help DevOps understand how application releases affect service performance, security, and reliability. They enable teams to set up alerts to detect and solve issues before they impact user experience and set up automated actions based on specific events, patterns, and trends.

Hopefully, this tutorial helped you understand better what APM means, why you need it as part of your monitoring and alerting strategy, and how to use it to deliver enhanced app performance, improved digital user experience, and, ultimately, to drive business growth.

Now all you have to do is pick the right APM tool and you're good to go!

Application performance management (APM) software helps an organization ensure that critical applications meet established expectations for performance, availability and customer or user experience. It enables organizations to predict and prevent performance issues before they impact users or the business.

APM does this by measuring application performance, alerting administrators when performance baselines aren’t met, providing visibility into root causes of performance issues and automatically resolving many performance issues before they impact users or the business.

APM is also an abbreviation for application performance monitoring . The terms are often used interchangeably, but application performance monitoring is actually a component of application performance management because after all, you must monitor performance to manage it. 

Increasingly, application performance management solutions are evolving from relying on traditional application performance monitoring tools to incorporating observability , a performance data collection and analysis technology better suited to the complexity of modern, distributed cloud-native applications.

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Register for the guide on observability

Again, APM gathers software application performance data, analyzes it to detect potential performance problems, and provides information or accelerates resolution of those problems. The chief difference in how they gather and analyze the data is the difference between application performance monitoring and observability.

Application performance monitoring

In application performance monitoring , agents are deployed throughout the application environment and supporting infrastructure to 'monitor' performance by sampling performance and performance-related metrics (sometimes called telemetry) as frequently as once every minute. Types of monitoring these agents perform include:

• Digital experience monitoring gathers performance metrics - such as load time, response time, uptime, downtime - from the user interface on the user device. (This used to be called user experience monitoring, but was broadened to acknowledge that non-human entities, such as robots or other software components, also interact with the application and have performance expectations of their own). Digital experience monitoring usually supports real-user monitoring, which monitors the experience of an actual user on the system, and synthetic monitoring for performance testing in production and non-production environments.
• Application monitoring  includes monitoring of the entire application stack - application framework (for example, Java or .NET), operating system, database, APIs, middleware, web application server, UI - as well as IT infrastructure monitoring   that samples factors such as CPU utilization, disk space and network performance. Stack monitoring typically includes code-level tracing, which can help spot portions of code that might be causing a performance bottleneck.
• Database monitoring   samples performance of SQL queries or procedures, in addition to the database monitoring provided by application monitoring agents.
• Availability monitoring  monitors the actual availability of application and hardware components   (because applications can generate performance data even when they aren't accessible to the user).

In addition to collecting performance data, these agents perform user-defined transaction profiling, tracing each transaction from the user UI or device through every application component or resource involved in the transaction. This information is used to determine application dependencies, and to create a topology map - a visualization of the dependencies between application and infrastructure components, ideally across on-premises, private cloud, public cloud (including any software-as-a-service or SaaS solutions) and or hybrid cloud environments. 

APM solutions typically provide a controller and centralized dashboard where the collected performance metrics are aggregated, analyzed and compared to established baselines. The dashboard alerts system administrators to deviations from baselines that indicate actual or potential performance issues; it also provides contextual information and actionable insights administrators can use to troubleshoot and resolve the issues.

Observability

Periodic sampling is effective enough for monitoring and troubleshooting monolithic applications or traditional distributed applications, where new code is released periodically and workflows and dependencies between application components, servers and related resources are well-known or easy to trace.

But today, as organizations are adopting modern development practices and cloud-native technologies—Agile and DevOps methodologies, microservices , Docker containers, Kubernetes and serverless functions—they're deploying new application components so often, in so many places, in so many languages and for such widely varying periods of time that the once-a-minute data sampling of traditional monitoring solutions can't keep up.

Observability swaps traditional monitoring agents with instrumentation that collects performance and contextual data non-stop, and uses machine-learning techniques to correlate and analyze the data in real-time. With an observability solution, development, IT operations and site reliability engineering (SRE) teams can:

• Discover and address 'unknown unknowns.' Traditional monitoring looks only for known deviations from known baselines. An observability platform's machine-learning functionality can detect patterns in performance telemetry to identify new deviations that correlate with performance problems.
• Catch and resolve issues early in development.  Observability lets DevOps teams bake monitoring into the early phases of the software development process, so that they can test, identify and fix issues in new code before they impact the customer experience or service level agreements (SLAs).
• Scale observability automatically.  For example, developers can specify observability instrumentation as part of a Kubernetes cluster configuration, so that any new cluster starts gathering telemetry from the moment it spins up, until it spins down.

Observability doesn’t replace monitoring; it enables better monitoring, and better APM.

Today APM tools are using observability and AI in varying degrees. Some are combining traditional application performance monitoring with AI to automate the discovery of changing transaction paths and application dependencies. Others are combining observability with AI to automatically determine performance baselines, and to sift signals, or actionable insights, from the 'noise' of IT operations management (ITOM) data. Industry analyst Gartner finds that organizations can realize a "60% noise reduction in ITOM through use of AI-augmented tools."

The ultimate goal—and the future of APM and IT operations—is to combine observability with artificial intelligence for IT operations, or AIOps, to create self-healing, self-optimizing infrastructure. Together, the steady stream of real-time observability telemetry and AIOps machine learning and automation can predict application performance issues based on system outputs, resolve them before they impact the user experience or operations and even take actions to optimize application performance - all without management intervention.

Innovate faster, reduce operational cost and transform IT operations (ITOps) with an AIOps platform that delivers visibility into performance data and dependencies across environments.

Discover the leading enterprise observability platform for hybrid clouds. Improve application performance management and accelerate CI/CD pipelines no matter where the applications reside.

Leverage observability to proactively optimize application resourcing, ensure performance and save money.

Learn how AI for IT improves business outcomes, leads to increased revenue and lowers both cost and risk for organizations.

Achieve new levels of efficiency and resiliency in your IT operations.

SRE uses software engineering to automate IT operations tasks that would otherwise be performed manually by systems administrators.

Gain full visibility into your application and infrastructure resource allocation which contribute to user response time and any resource congestion.

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What is Application Performance Monitoring?

Application performance monitoring meaning.

APM, application performance monitoring , is the process for organizations to quickly identify and resolve any performance issues in their application and code.

APM solutions collect, monitor, and analyze telemetry data from websites, software applications, and services. Teams get end-to-end visibility across their applications so they can understand application and service dependencies and address any errors or slowdowns. APM solutions also store and utilize historical data to surface trends and detect outliers for key performance indicators, such as latency and throughput, as well as business KPIs.

What does application performance monitoring do?

Application performance monitoring provides continuous and detailed insight into how applications are performing. Teams can leverage these insights to be more proactive, rather than waiting for customer complaints. APM has several uses. For example, teams can set up alerts for degradations in user experience, gauge the impact of the latest release, and make informed decisions on where to make improvements. It can also be used to help with root-cause analysis and drive down mean time to detection (MTTD) and mean time to resolution (MTTR) .

Why is APM important?

Applications are the lifeblood for modern organizations. They are the gateway to the products, services, and tools people use every day, and they are also becoming increasingly complex. With the rise of distributed applications — cloud-native technologies and microservices — teams simply cannot keep up with the volume of telemetry data streaming in. They need a way to monitor everything in order to deliver exceptional user experiences.

APM ensures that applications perform as expected. To maintain customer confidence, APM tools can alert teams to potential issues so they are resolved fast.

History of APM

Since its founding in the 1990s, APM has given IT teams visibility into applications where previously they were blind. Throughout the years, several companies have experimented with distributed tracing . But it wasn’t until the 2010s that more robust APM solutions entered the market. These platform solutions offer more high-level tracking and end-to-end monitoring capabilities.

APM vs. Observability

On the surface, observability and APM are similar. They both use telemetry to gather data and deliver insights on performance. While APM is more application-focused — tracking and monitoring transactions — observability covers both application and infrastructure performance. Observability enables deep dives into the technical details for improved understanding of systems. It can help teams understand the context and root cause behind a performance issue by correlating across logs, metrics, and traces.

How does application performance monitoring work?

APM uses a set of tools and methodologies to monitor and manage the performance of software applications. APM tools typically include monitoring of key metrics such as response time, throughput, and error rate to identify and diagnose performance bottlenecks and issues.

APM tools can also provide detailed tracing and debugging information to help developers understand and fix issues in the code. This often includes alerting and reporting functionality to keep stakeholders informed of the performance of the application.

An agent is a piece of software that is usually instrumented in the application. It monitors and transmits trace and telemetry data to the APM server and/or other monitoring tools. Agents can be used to monitor a wide range of systems and applications. They can be configured to collect data about specific aspects of performance.

APM instrumentation

Instrumentation is the process of adding monitoring code to an application to collect performance data. It can be used to collect metrics for response times, error rates, resource utilization, logs, and other key indicators of an application's health and performance.

Instrumentation can be done manually using a vendor specific APM SDK (software development kit) or with open standards, like OpenTelemetry , where traces are started and stopped using spans .

Alternatively it can be done by using agents that auto instrument the code. After installing the agents, teams can instrument specific parts of an application or transaction for analysis and then send the data to an endpoint — usually an APM platform. Instrumentation is usually set up in a tool’s UI or via an API. Examples of configurations include environment names, sampling rates, and other metrics.

APM analysis and alerting

Once performance data is collected, it can be analyzed. It is important when selecting a tool that it includes dashboards and views that make it easy to track a user’s experience and identify errors and issues at-a-glance. Most teams start investigations around reported issues, and then work to identify the root cause. Having a platform approach to APM avoids tool switching at this stage. Alerts can also be set up moving forward to avoid future issues.

What does APM measure?

APM tools can measure:

• Server health: Monitor server CPU usage, memory demands, and read/write speeds
• Error rates: Track performance degradation and identify issues
• Response time: Determine whether app performance is being impacted
• Instances: Understand how many server or app instances are running to scale efficiently and manage overall costs. This metric is critical for cloud-based applications.
• Request rates: Evaluate user traffic to understand why there are spikes or users are inactive
• Availability: Track uptime for the application

What are the benefits of APM?

When applications stop working, it is better to know ahead of time before creating a negative experience for users. APM allows teams to identify and resolve issues quickly, and even prevent them in the future. With a comprehensive APM tool, teams can:

• Increase stability and uptime
• Reduce incidents
• Resolve issues faster
• Release high-quality software
• Identify infrastructure improvements
• Improve productivity
• Create better user experiences
• Drive revenue

What are the challenges of APM?

APM tools do not come without challenges. Teams are dealing with massive amounts of data streaming in real time. Complex, distributed applications — especially those using cloud-native technologies — can make APM instrumentation a challenge. If there are issues across an environment or complex root cause analysis cases, many tools can struggle.

APM solutions need to monitor end-to-end transactions, applications, and code-level performance to give organizations comprehensive coverage. Having a single platform provides the most comprehensive coverage, and can simplify workflows and speed issue resolution. It is important to choose the right APM solution that can use a combination of monitoring methods to meet business goals.

Key features of APM tools

What should you look for when selecting the right APM tool? While there are several different APM solutions that can monitor end-to-end transactions, applications, and code-level performance, it is important to select one that matches your technical needs now and in the future.

Technical capabilities

Create a checklist for your organization. Then you can compare tool features to your needs. Some examples of APM technical capabilities include:

• Track website and/or application performance
• Map and manage application and service dependencies
• Collect distributed traces for end-to-end visibility
• Provide real-time user monitoring (client and server)
• Connect app performance to business goals
• Leverage machine learning and AI-based analytics
• Support for a variety of data types, data sources, and languages

End-to-end visibility

APM data has the ability to inform organizations about what is actually happening in their application. But you need to be able to monitor everything well to get a clear vision into how it is working.

Because individual traces only show part of this story, your APM tool should go one step further and monitor transactions all the way through their journey. Then, traces can be linked together to go from a bird's-eye view into code-level concerns.

End-to-end visibility is also a critical element for AIOps .

Integrations with third-party services and applications is what allows your APM tool to seamlessly fit into your organization’s larger ecosystem. From authentication to CI/CD frameworks, it is important to investigate these integrations up front.

Ease of Use

There are various people within your organization that will need access to APM features. Cater to their needs with an intuitive UI. Also, verify how easy it is to deploy, manage, and scale your APM solution.

Deployment options

If you are looking to reduce operating and administrative costs, you may want to consider a cloud-based SaaS option . But, there are other deployment options to consider. While some APM tools can support multi-cloud or hybrid strategies, others could have limitations based on your preferred cloud provider.

Support for open standards/open data

The observability space is constantly evolving. As new tools and standards enter the market, you need a flexible platform that can adapt. Using open standards and technologies like OpenTelemetry can also help to future-proof your toolset.

Learn more about telemetry data building blocks

When evaluating your tools, consider the vendor’s commitment to security . How the APM tool is built and delivered could either enhance or weaken your existing security framework. Traffic between components should be encrypted. Third-party extensions could also represent a security concern . Also, make sure that your APM tool supports your existing identity access management solution with granular permissions.

Application performance monitoring with Elastic

In 2023, Elastic was named a visionary (for the third consecutive year) in the Gartner® Magic Quadrant™ for APM and Observability . Elastic offers companies a full-stack approach to observability with APM monitoring built-in . Teams do not need to work with multiple tools to get 360 degree views into their product. Elastic offers teams:

• Visibility across hybrid and multi-cloud: Accelerate your digital transformation with observability for cloud-native technologies, such as Kubernetes and serverless . Elastic also offers native support for OpenTelemetry .
• Improved troubleshooting and efficiency: Break down silos across your organization and consolidate metrics, logs, and traces with a single view into your environment.
• Powerful machine learning and analytics: Automate root cause analysis for your teams with innovative AIOps capabilities, such as APM correlations and anomaly detection .
• User experience monitoring: Get a detailed view of how your users interact with your site with real user monitoring (RUM) . Proactively catch web performance issues before your customers do with synthetic monitoring .

Learn more about Elastic and APM

APM glossary

Application performance monitoring resources.

• APM solutions
• APM technical guide
• [WEBINAR] Using the Elastic Stack for Application Performance Monitoring
• Elastic named a Visionary in the 2023 Gartner® Magic Quadrant™ for APM and Observability

Why Monitoring Applications (APM) is Important and How to Monitor Applications Effectively

What is Application Performance Monitoring (APM)

Application Performance Monitoring (APM) is a critical practice for businesses seeking to ensure optimal performance and user experiences. APM involves monitoring and analyzing various performance metrics and key indicators to gain insights into an application’s behavior and identify areas for improvement. By implementing APM, organizations can proactively detect and address performance issues, minimize downtime, and enhance overall application performance.

Effective application performance monitoring entails tracking metrics such as response time, throughput, error rates, and resource utilization. By continuously monitoring these metrics, businesses can identify bottlenecks, pinpoint performance degradation, and optimize resource allocation.

Application monitoring tools like  Azure Monitor,  AppDynamics, and New Relic show how well an app is working. APM tools organizations find and fix problems quickly, so users have a good experience and business runs smoothly. This proactive approach helps to create a full stack, minimize disruptions, improve customer satisfaction, and boost productivity.

APM also plays a crucial role in capacity planning and scalability. By monitoring resource utilization and performance trends, businesses can accurately predict their application’s resource needs and plan for scalability accordingly. This ensures that the application can handle increased user loads and transaction volumes without compromising performance. Additionally, APM enables organizations to conduct performance testing, analyze results, and fine-tune their application to achieve optimal performance levels.

Why is Monitoring your applications important?

1. maintaining business continuity.

Applications are susceptible to various issues that can disrupt business operations. Downtime, slow response times, and system failures can lead to frustrated customers, lost sales opportunities, and  damaged brand reputation . By implementing robust application monitoring practices, businesses can identify and rectify issues promptly, minimizing downtime and ensuring uninterrupted service delivery. Proactive monitoring helps in early detection of anomalies, allowing for swift remediation before they snowball into larger problems.

2. Enhancing User Experience  

User experience is a key differentiator in today’s competitive market. Slow-loading pages, frequent errors, and unresponsive applications can drive users away, negatively impacting customer satisfaction and loyalty.  

Through application monitoring, businesses can gain insights into performance metrics such as response times, page load times, and error rates. This data enables them to optimize application performance, streamline user interactions, and deliver a seamless experience. Monitoring also aids in identifying and addressing bottlenecks, optimizing resource utilization, and improving overall user satisfaction.  

3. Operational Efficiency  

Monitoring applications not only helps in maintaining their performance but also enables businesses to identify opportunities for optimization. Businesses can use metrics to make decisions about infrastructure scaling, load balancing, and resource allocation. This proactive approach prevents system overload, enhances scalability, and optimizes resource utilization, leading to improved operational efficiency and cost savings.  

4.Proactive Issue Resolution  

Traditional troubleshooting methods often involve reacting to customer complaints or system failures. However, application monitoring allows businesses to proactively identify and resolve issues before they impact end-users. With real-time monitoring and automated alerts, businesses can quickly pinpoint performance bottlenecks, errors, or security threats. Finding problems early helps IT teams fix them quickly, avoiding issues for users and the business.  

5. Ensuring Security and Compliance  

In an era of increasing cyber threats and stringent data privacy regulations, monitoring applications for security vulnerabilities and compliance violations is of paramount importance. Application monitoring helps detect unauthorized access attempts, abnormal user behavior, and other security breaches. It also aids in monitoring compliance with industry regulations and internal policies. Businesses can protect sensitive information and meet regulations by constantly watching apps. They can do this by applying security updates, controlling access, and following data protection rules.  

How to monitor application performance  

Monitoring applications effectively involves a systematic. Here are ten steps to help you establish an efficient application monitoring process:  

1. Define Monitoring Objectives:

Clearly define your application monitoring goals and objectives. Identify the most important metrics for your business, such as response time, uptime, error rates, and user engagement.  

2. Select Appropriate Monitoring Tools:    

Research and select monitoring tools that align with your monitoring objectives. Look for solutions that offer comprehensive monitoring capabilities, including real-time performance monitoring, error tracking, log analysis, and security monitoring.  

3. Establish Baseline Performance:  

Before implementing monitoring, establish a baseline for your application’s performance. This baseline will serve as a reference point for identifying deviations and anomalies in the future. Measure and document the normal behavior of your application under different conditions.  

4. Set Up Real-Time Monitoring:  

Configure real-time monitoring for critical application components and performance metrics. Use monitoring tools to track parameters such as server response time, database performance, network latency, and user interactions. Set thresholds and alerts to notify you when performance falls below acceptable levels.  

5. Monitor User Experience:  

Implement user experience monitoring to gain insights into how users interact with your application. Track metrics like page load times, click-through rates, conversion rates, and user journey flows. User experience monitoring helps identify areas for improvement and prioritize enhancements.    

6. Monitor Application Logs  

Log analysis plays a crucial role in identifying errors, exceptions, and potential security breaches. Set up log monitoring and analysis tools to track application logs and detect anomalies. Regularly review logs to identify patterns, troubleshoot issues, and proactively address potential risks.  

7. Implement Security Monitoring:    

Protecting your application from security threats is paramount. Employ security monitoring tools to detect and respond to unauthorized access attempts, abnormal user behavior, and potential vulnerabilities. Monitor logs, network traffic, and user activities to identify security incidents promptly.  

8. Leverage Performance Testing:    

Conduct regular performance tests to assess how your application performs under different loads and stress levels. Use load testing tools to simulate real-world scenarios and analyze performance metrics. These tests help you identify scalability issues and optimize resource allocation.  

9. Establish Incident Response Processes:  

Define clear incident response processes to handle alerts and issues detected through monitoring. Establish roles and responsibilities, escalation procedures, and communication protocols to ensure timely response and resolution. Document incident response steps and update them as necessary.  

10. Continuously Review and Optimize:  

Application monitoring is an iterative process. Regularly review monitoring data, analyze trends, and identify areas for improvement. Use the insights gained from monitoring to optimize performance, enhance security measures, and refine user experiences.  

Conclusion  

In conclusion, effective application monitoring is crucial for businesses that rely on digital applications to drive their operations and deliver exceptional user experiences. By monitoring application performance, organizations can proactively detect and resolve issues, maintain business continuity, and optimize operational efficiency. Additionally, application monitoring helps businesses enhance user satisfaction, ensure security and compliance, and make informed decisions about scalability and resource allocation.  

To monitor applications effectively, organizations should define their monitoring objectives, select appropriate monitoring tools, and establish a baseline for performance. Real-time monitoring, user experience monitoring, and security monitoring are essential components of a comprehensive monitoring strategy. Performance testing, incident response processes, and continuous review and optimization are key steps to ensure the effectiveness of the monitoring process.    

By investing in robust application monitoring practices and leveraging the right tools, businesses can gain valuable insights, prevent potential disruptions, and continuously improve the performance and reliability of their applications. In a competitive digital landscape, proactive application monitoring is a crucial practice that enables organizations to deliver seamless user experiences, maintain a competitive edge, and drive business success.  

CONTACT US TO LEARN MORE ABOUT APPLICATION MONITORING

Andrew Reade

Andrew is our Digital Marketing Manager and oversees web-based marketing strategies and content creation for the organization. As a marketing veteran, Andrew has worked with organizations of all sizes in a diverse group of industries, from Risk Management to Transportation. Joining the organization in 2021, Andrew is based in Mobile Mentor’s Nashville, TN office.

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What is APM? Application performance monitoring in a cloud-native world

Application performance monitoring (APM) for modern, cloud-native environments extends observability beyond system availability and service performance and response times. Automatic and intelligent observability helps organizations improve user experiences at the scale of modern computing.

What is APM?

Application performance monitoring (APM) is the practice of tracking key software application performance metrics using monitoring software and telemetry data. Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences.

Mobile apps, websites, and business applications are typical use cases for monitoring. However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and end-users that access these applications — including a company’s customers and employees.

Check out this session from Perform 2023 conference “Improve application performance with AI-powered exploratory analytics”

What does APM stand for?

APM stands for Application Performance Monitoring .

Though that meaning is specific to the topic discussed in this article, APM has additional meanings and can be referred to as all the below:

• Application monitoring
• Application performance monitoring
• Application performance management
• Application performance
• Performance monitoring

The focus of application performance monitoring is on specific metrics and measurements; application performance management is the wider discipline of developing and managing an application performance strategy. All these terms refer to related technology and practices.

Why do we need APM?

Digital teams use APM tools to view and address the many variables that can impact an application’s performance. Without these tools, teams struggle to resolve the numerous problems that can arise — raising the likelihood of customers becoming frustrated by the poor experience and abandoning the app altogether.

Every day, customers use apps to shop, stream TV shows and movies, connect to social media, manage finances, and work. In the age of working from home, customers rely more than ever on these apps to conduct their daily lives. When an app crashes, is slow to load, or doesn’t load at all, users become frustrated, which can cause the business to suffer brand damage or lose revenue. When an internal business application begins to falter, the company may also see reduced employee productivity.

However, digital teams often find it difficult to find the root cause of an application performance problem. Causes can run the gamut — from coding errors to database slowdowns to hosting or network performance issues. Even a conflict with the operating system or the specific device being used to access the app can degrade an application’s performance.

Modern applications such as mobile apps, websites, and business apps may seem simple on the surface, but they are actually highly complex. Millions of lines of code comprise these apps, and they include hundreds of interconnected digital services and open-source solutions , and run in containerized environments hosted across multiple cloud services.

What does APM do?

APM has rapidly expanded to encompass a broad range of technologies and use cases. According to Gartner , “Application performance monitoring is a suite of monitoring software comprising digital experience monitoring (DEM), application discovery, tracing and diagnostics, and purpose-built artificial intelligence for IT operations.”

APM core features

The Gartner® Magic Quadrant™ for APM and Observability , a leading industry report on APM, provides a clear definition of APM’s core capabilities as they have matured. These capabilities set the bar for modern APM solutions .

• Automatic discovery and mapping of application and its infrastructure components to maintain real-time awareness in dynamic environments
• End-to-end observability of an application’s complete HTTP/S transactional behavior to understand the effect on business outcomes and user experience
• Mobile and desktop application monitoring on mobile and desktop browsers to track user experience across platforms
• Root-cause and impact analysis of application performance problems and business outcomes for faster, more reliable incident resolution
• Integration and automation with service management tools and third-party sources to keep pace with an expanding and evolving infrastructure
• Business KPIs and user journey analysis (for example, login to check out) to optimize user experiences and provide transparency into how changes impact KPIs
• Endpoint monitoring to understand how mobile applications impact endpoint devices and identify issues with those devices
• Virtual desktop infrastructure (VDI) monitoring to maximize the productivity of employees using VDI

These capabilities extend into many areas. Here are a few of the most common ones:

• API monitoring to understand how application performance is impacted by third party services
• Application architecture to gain insights into how application architecture changes impact performance and user experience
• Service monitoring to understand how individual services interact and their impact on overall application performance
• Container monitoring to help understand the context and performance impact of individual containers
• End-user experience monitoring to help you understand how changes to applications affect your end users

What are the benefits of APM?

APM gives businesses increased visibility and intelligence into the performance of applications and their dependencies to detect and pinpoint application performance issues before real users are impacted. APM delivers an impressive and expanding list of technical benefits and business benefits.

Technical benefits

Business, operations, application, and development teams can expect to enjoy several practical benefits from adopting APM practices and tools, such as:

• Increased application stability and uptime
• Reduced number of performance incidents
• Faster resolution of performance problems
• Faster and higher-quality software releases
• Improved infrastructure utilization

Concrete business benefits

Those in the boardroom have just as much to gain from adopting APM solutions as those on the front lines of DevOps efforts. Business benefits include:

• Improved developer and operational productivity
• Increased time spent on innovation
• Better user experiences
• Increasing revenue
• Reduced operational costs
• Increasing conversion rates

Soft business benefits

Long-time APM users also report that APM has given their organizations some unexpected but impactful advantages.

Why cloud-native applications make APM challenging

Even though the benefits of APM are well established, the rise of cloud-native applications has made it more challenging to do well. For example, cloud-native apps generate far greater quantities of telemetry data because they are made up of a myriad microservices that dynamically spin up and spin down in the background. Each of these microservices exists for a short period and generates its own telemetry data, adding to the overall signal noise. When this happens, it becomes more difficult to find the most important events taking place within your application infrastructure.

Cloud-native apps also produce many kinds of data. Telemetry data from a serverless environment is quite different from a database or a virtual machine (VM), for example, but a business still needs to normalize and centrally manage all the information as it comes in. The velocity at which this data is created is another problem. When a cloud-native app includes many smaller microservices, data comes in at a much faster rate than with a monolithic application. All these factors have added new challenges that make traditional APM more difficult in a cloud-native application environment.

APM tools vs. APM platforms

What are apm tools.

APM tools are often designed to look at one specific aspect of application performance. These point solutions can help identify specialized issues. Over time, organizations often find themselves using multiple APM tools that don’t necessarily integrate with one another or provide comprehensive insight into the application environment.

What are APM platforms?

An APM platform provide a single integrated platform using AI and automation to deliver a precise, context-aware analysis of the application environment. Organizations can continuously monitor the full stack for system degradation and performance anomalies by utilizing an APM platform.

With the deluge of telemetry data that comes with cloud-native apps comes a profusion of performance monitoring tools and platforms.

Organizations can take one of two approaches when picking APM tools. By default, or by design, different teams may deploy a combination of point solutions. Or, they may choose a single platform that more fully encompasses the many layers and use cases within the application environment. Point solutions can pose benefits at a local level and challenges at a macro level, while a platform approach embraces a modern vision of APM that demonstrates clear advantages at the local and macro levels.

Benefits of point solutions

Point solutions are specialized to monitor specific components and provide advantages for those specific use cases. For example, some companies use Grafana to consolidate their metrics visualizations in a single dashboard while others use Jaeger for its distributed tracing capabilities to gain better observability into their systems and troubleshoot performance issues. Both these tools are highly specialized for the environments they’re applied to.

Teams focused on solving a specific, specialized issue, such as implementing a service mesh to help manage orchestration in their Kubernetes environment, turn to point solutions because they’re cost-effective and easy to implement.

Challenges of point solutions

Point solutions only provide a limited view of a company’s application architecture. This limited visibility makes it harder to identify root causes of application performance issues, resulting in longer downtimes when problems arise. Further, they only provide a single view of the application architecture, often missing the “cause and effect” of performance problems — for example, increased CPU usage caused by a microservice failure. This may result in unnecessary troubleshooting exercises and finger-pointing, not to mention wasted time and money.

Because the scope of these solutions is limited by their nature, they also tend to create silos in which teams can disagree on service-level objectives (SLOs) and metrics. This silo effect can lead to more inefficiency and blame as teams rely on separate tools and different information.

Advantages of a platform approach to APM

Because APM has its roots in the era of monolithic applications before the rise of microservices, open-source technologies, and cloud-native environments, some industry observers have argued that APM platforms lack the innovation and deep-dive capabilities required to keep up with bespoke point solutions. This may be true for many traditional APM platforms.

However, a platform that is purpose-built for cloud-native environments and uses a simple, automated deployment model, like Dynatrace, can offer broad technological coverage across the full stack, including those bespoke point solutions. By leveraging “ agentless ” data capture (for application use cases that cannot support an agent-based deployment model) and APIs to ingest data, a cloud-native platform like Dynatrace can broaden its coverage to the entire hybrid-multicloud network. This broad-spectrum observability provides a macro-level view across multiple environments to provide continuous discovery, and the applications that run on them, and proactive anomaly detection prioritized by business impact.

Crucial capabilities of a modern APM platform include AI and continuous automation. With the explosion of observability data, a platform needs to automatically process billions of dependencies in real-time, continuously monitor the full stack for system degradation and performance anomalies and deliver precise answers with root-cause determination.

APM’s many forms

APM monitoring comes in many flavors, including infrastructure monitoring, network monitoring, database monitoring, log monitoring , container monitoring, cloud monitoring , synthetic monitoring , and end-user monitoring, among others. Companies often run dozens of individual monitoring tools at once, especially when they’re holding onto legacy applications and managing them using the tools they find most familiar. Although this may seem like the easiest approach, it frequently creates problems. A single APM solution that delivers full-stack observability can make monitoring all these use cases easy and more reliable.

Full-stack monitoring

As application infrastructures expand to encompass both on-premises and multicloud environments, organizations increasingly understand that only a full-stack monitoring approach can deliver comprehensive visibility into the root causes of issues, wherever they originate. Full-stack monitoring allows you to monitor your entire infrastructure from end to end — encompassing everything from infrastructure health to application performance and even the end-user experience. With this visibility, you can see all these components and understand the interdependencies between them, getting faster answers to all your questions.

Advantages of an advanced APM platform

The Dynatrace software intelligence platform provides all-in-one advanced observability for APM use cases that serve business, operations, application. AI assistance enables teams to automate operations, release software faster, and deliver better business outcomes. With the Davis® AI engine at its core, Dynatrace provides precise answers to complex questions in real time.

Advanced cloud observability

With the scale, diverse functionality, and dynamic nature of cloud platforms such as AWS, Azure, and GCP, APM solutions need to just work without configuration or model training. Dynatrace provides complete observability out-of-the-box for dynamic cloud environments, at scale and in context. It includes performance metrics, logs, traces, entity relationships, and user experience and behavior data, and data from the latest open-source standards, including OpenTelemetry , all in a single platform, automatically, with no configuration required.

Continuous automation

Trying to manually maintain, configure, script, and source data in a cloud-native environment is beyond human capabilities, which means organizations must continuously automate these tasks to ensure proper application performance. Dynatrace enables automation through automatic deployment, configuration, discovery, topology, performance, and updates. Davis® doesn’t need to learn because it already knows, and is continuously and automatically observing, analyzing, providing answers, and prioritizing what matters.

AI assistance

AI assistance empowers teams by reducing manual or redundant work, allowing them to be more productive in areas of critical importance to the business. Here, too, Davis® provides precise answers for proactive problem resolution and performance improvements in real time. Customers report that Davis® automatically multiplies the power and effectiveness of the entire team, supercharging the organization’s ability to quickly resolve application performance issues.

Cross-team collaboration

Dynatrace was built for enterprise-scale deployments. With its ease of use and an unlimited users, companies can eliminate silos and accelerate teamwork. Because Dynatrace combines a unified data platform with advanced analytics to provide a single source of truth for biz, ops, app and dev teams, they can go faster and deliver consistently better results with less friction.

User experience and business analytics

Experience and outcomes matter, whether the application is mobile app-to-user, IoT device-to-customers, or a web application behind the scenes. That’s why the Dynatrace platform encompasses the edge device and API. With intelligence into user sessions, including Real User Monitoring and Session Replay , teams can connect user experiences to business outcomes such as conversions, revenue, and KPIs. With data-backed decisions, answers at the ready, and real-time visibility into business KPIs, companies consistently and more efficiently deliver better digital business outcomes across all their channels.

Leading vendors in the APM market

Gartner names leading vendors in the APM market in its annual Magic Quadrant report, giving APM users valuable insight into which solutions are best suited to their unique needs. Gartner positions each vendor into various quadrants on a graph, rating them according to their leadership position within the market and their completeness of vision.

Deliver an exceptional user experience with APM

Customers increasingly demand a user experience that is as satisfying as reliable. Effective application performance monitoring gives organizations greater insight into underlying issues.

An APM solution that provides advanced observability through full-stack monitoring and enhanced root-cause analysis gives organizations even greater insight into application performance issues. It also solution provides digital teams with the full suite of capabilities needed to resolve priority issues faster and meet the growing customer demand for a stellar user experience.

To learn more about how Dynatrace delivers exceptional user experiences through APM, explore our interactive APM product tour .

What is distributed tracing, and why is it important?

How automated workflows and multicloud automation can reduce engineering toil

Critical app observability in government including ArcGIS

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Start a new discussion or ask for help in our Q&A forum.

15 Best Application Monitoring Tools (2024)

May 27, 2024 · 10 min read

As a software developer, your top priority is to guarantee your applications don't crash or slow down.

You know that application performance and reliability are critical for business success, but monitoring them can be complicated and time-consuming.

That's where application monitoring tools come in.

We've done the hard work for you by evaluating the best application monitoring tools to simplify the process so you can make sure that your applications run smoothly and efficiently to provide optimal user experience.

What is Application Performance Monitoring?

Application performance monitoring (APM) is the process of tracking and analyzing application performance and health using various metrics to verify that they function as intended without any issues.

Key performance metrics include:

• Response times.
• Error rates.
• Resource utilization.
• User experience monitoring.

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Benefits of Application Monitoring Tools

Application monitoring tools provide real-time insights into performance metrics so you can proactively identify and resolve issues before they impact users.

Here are some benefits of using APM tools:

• Identify performance bottlenecks and troubleshoot issues to improve app performance.
• Provide detailed logs and reports about app performance to guide future improvements and updates.
• Optimize response times and error rates to make your apps function as expected and provide a positive user experience.
• Monitor your application's resource needs so you can better allocate your resources.
• Quickly address issues to save time and reduce maintenance costs.

Best Application Monitoring Tools

Here's an overview of some of the best APM tools.

• New Relic:  Advanced analytics and monitoring.
• AppDynamics : End-to-end business transaction performance.
• Dynatrace:  Full-stack AI-powered monitoring.
• Datadog:  Best for unified monitoring.
• IBM Instana:  Automatic monitoring and incident management.
• Sumo Logic:  Unified log management.
• SolarWinds:  Dependencies mapping and management.
• Splunk:  Best for intelligent incident management and predictive analytics.

New Relic  is an all-in-one observability platform that allows developers and IT teams to monitor applications, infrastructure, and end-user experience.

It provides AI-powered insights into application performance and health so you can proactively monitor and resolve issues quickly.

Key Features:

• Full-stack performance monitoring.  New Relic APM is an ideal tool for code-level insights. You can view key metrics to detect the root cause at every stage of development quickly.
• Real-time insights.  It offers real-time data analytics and reporting, with log patterns and error user impact view for deep insights and faster troubleshooting.
• Real user monitoring.  The APM interface provides real-time monitoring of KPIs to identify issues before they impact users. You can simulate user interactions across browsers and mobile devices.
• Distributed tracing.  Get end-to-end visibility into the path of any service request and quickly spot missing alerts to pinpoint issues.
• Integrations.  It provides 750+ integrations with third-party tools, which improves versatility.
• Easy-to-use interface.
• Customizable dashboards.
• Error tracking with targeted alerts.
• Can be expensive for large-scale projects.
• Advanced features might be complex for new users.
• Free tier available.
• Pay-as-you-go pricing model starting from $0.30 per GB.

AppDynamics

AppDynamics  is an application performance management and analytics tool that provides unified business and performance insights.

It offers real-time monitoring of the performance of complex applications and end-to-end business transactions.

You can manage and monitor app performance across on-premises, cloud-native, or hybrid environments.

• Full-stack performance observability.  It monitors the entire application lifecycle and provides performance insights from code to production. You can monitor code-level transactions that affect the KPIs to improve performance.
• Automated root cause analysis.  It uses AI and machine learning to identify the most likely root cause and automatically analyze metrics across your application's code, storage, infrastructure, or network.
• Intelligent alerts.  You can get highly relevant and precise alerts intelligently triggered to reduce false positives and alert storms.
• Integrations.  It integrates with tools like AWS and Docker and supports popular programming languages and frameworks.
• AI-powered insights into business transactions.
• Analyze applications at the code level.
• Complex learning curve for advanced features.
• Pricing can be high for smaller businesses.

It starts from $33 per month.

Dynatrace  is a powerful software intelligence and observability platform for apps, microservices, and infrastructure.

It provides unified AIOps that automatically identifies problems and provides deep visibility and insights into complex environments.

• Automated full-stack observability.  It offers AI-powered end-to-end visibility across the entire technology stack, including applications, infrastructure, security, and cloud environments.
• AI-powered APM.  Leverage AI to automatically detect and analyze root causes using topology, transaction, and code-level information. It also provides predictive insights to prevent issues before they impact users.
• Multi-environment monitoring.  You can monitor ****private, public, and hybrid cloud environments, VMs, and containers, including AWS, Microsoft Azure, GCP, OpenStack, Kubernetes, and more.
• Data lakehouse architecture for causal data processing at scale.
• AI-powered analytics, insights, and automation.

It may be complex for beginners.

• Free trial available for 15 days.
• It starts from $0.08 per hour.

Datadog  is a modern monitoring and security platform designed for cloud-scale applications.

It provides an all-in-one solution to monitor apps, infrastructure, networks, databases, serverless apps, and containers.

• Distributed tracing.  It offers AI-powered code-level distributed tracing to view request flows across browsers, mobile apps, backend services, and databases.
• Interactive dashboards.  You can get a unified view of logs, metrics, database queries, network performance, and real user monitoring (RUM) data. You can also share dashboards with your team for collaboration.
• Highly precise alerts.  It uses machine learning to identify problems and provide actionable alerts, which helps minimize downtime and reduce false positives.
• Integrations.  It offers over 700 integrations, including AWS, Azure, CircleCI, Docker, GitHub, Java, Jira, Kubernetes, and more.
• Log management with audit trails and observability pipelines.
• Scalable for large, dynamic, and cloud-native environments.

Steep learning curve and complex setup.

• Free trial available.
• It starts from $15 per host per month.

IBM Instana

IBM Instana  is an automated application performance monitoring tool for full-stack observability.

It offers real-time visibility and AI-powered insights into the performance of browser and mobile apps, containers, databases, and user experiences.

• Automatic monitoring and discovery.  One of its best features is it automatically detects and logs changes in large-scale applications and starts monitoring without manual configuration.
• Distributed tracing.  It traces transactions across different components of an application and provides real-time alerts with insights into individual components performance and interaction.
• Automated root cause analysis.  It automatically detects changes, issues, and incidents with data analytics and reporting features to track application performance.
• Automatic incident management and issue resolution.
• Predictive alerting and recommendations.
• Complex configuration.
• Pricing can be high for large-scale monitoring.
• It starts from $75 per host per month.

Sumo Logic  is a cloud-native SaaS log analytics and integrated observability platform that provides continuous real-time intelligence across the application lifecycle.

• Unified application observability.  It covers all your application data, including logs, events, metrics, and distributed tracing.
• Automatic discovery.  It proactively discovers new apps, services, and infrastructure when deployed and provides automatically configured alerts.
• Dependencies visualization.  You can visualize the service dependencies and track issues faster with customizable dashboards.
• Comprehensive log management and advanced analytics.
• Real-time performance and security insights.

The steep learning curve for new users.

• It costs $3.14 per TB scanned.

SolarWinds  is a powerful monitoring, observability, and service management platform that provides a suite of products, including network and database management, server and application monitoring.

• Comprehensive monitoring.  It provides code-level monitoring with distributed tracing, live code profiling, and exception tracking.
• Dashboards and visualization.  A customizable dashboard that highlights performance metrics across the application stack provides end-to-end visibility to pinpoint the root cause quickly.
• Dependencies visualization.  With the visualization map, see the dependencies across services and proactively monitor distributed applications to visualize which microservice or database is the root cause.
• Integrations.  Pre-built integrations for third-party apps and frameworks.
• Supports cloud-native, hybrid, and on-premises environments.
• Dependencies mapping and management.
• Pricing can be high for large-scale projects.
• The installation process may be complicated.
• It starts from $24.99 for full-stack APM.

Splunk  is a unified security and observability platform widely used for log management, data analysis, and full-stack monitoring at scale.

• Distributed tracing.  It detects errors from any change and offers quick visualization with distributed tracing to scope the severity of a problem and the key components affected.
• AI-powered insights.  It uses machine learning to detect anomalies, predict trends, and automate root cause analysis with smart alerting.
• Code profiling.  It provides continuous code profiling to analyze code-level performance and help troubleshoot bottlenecks and performance issues.
• Service maps.  Get out-of-the-box visibility into all service interactions, microservices, dependencies, and performance.
• End-to-end tracing across distributed services.
• Powerful data analysis and incident management.

14-day free trial available.

Other Application Performance Monitoring Tools You Can Explore

• Google Cloud Observability:  APM for applications and systems running on Google Cloud, with integrated monitoring, logging, and tracing.
• LogRocket:  For front-end performance monitoring with session replays and AI error tracking.
• Grafana:  Open-source solution for data visualization, including metrics, logs, traces, and profiles.
• Site24x7:  All-in-one monitoring solution for websites, servers, applications, networks, and user experiences.
• Raygun:  For code-level diagnostics, server-side performance visibility, and real user monitoring.
• eG Innovations:  IT infrastructure and end-to-end application performance monitoring with proactive alerts.
• LogicMonitor:  SaaS-based automated monitoring and observability across hybrid and multi-cloud environments.

Final Words

We have carefully selected the best APM tools and platforms for your business and development needs.

Each tool offers a wide range of features, pricing options, and use cases, according to small businesses looking for an affordable solution and large enterprises requiring scalability.

Consider your requirements and evaluate the key features to choose the right tool for the smooth operation of your applications.

You can further explore our recent guides:

• 13  Best AI Platforms  for Developers
• 15 Best  Cloud Service Providers
• 8  Best Code Sharing Tools  for Developers

How do I choose a monitoring tool?

To choose a monitoring tool, consider factors such as scalability, ease of integration with your current infrastructure, the level of observability provided, and the specific metrics important to your operations.

What is the difference between application performance monitoring and infrastructure monitoring?

Application performance monitoring (APM) focuses on application performance and behavior, while infrastructure monitoring deals with the health and performance of the underlying technology stack supporting those applications.

How important is user experience tracking in an APM tool?

User experience tracking is critical in an APM tool as it provides valuable insights into how end-users interact with your applications. It helps you identify and resolve performance issues that may impact user satisfaction.

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APPLICATION MONITORING

Dec 15, 2012

560 likes | 942 Views

MGT302. APPLICATION MONITORING. Daniele Muscetta Program Manager Microsoft Corporation. KEY CAPABILITIES OF OM 12 APPLICATION MONITORING. Monitor Applications End-to-End . .NET Monitoring . Java Monitoring. User. Operations Manager. Application. Transaction. Performance.

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MGT302 APPLICATION MONITORING Daniele Muscetta Program Manager Microsoft Corporation

KEY CAPABILITIES OF OM 12 APPLICATION MONITORING • Monitor Applications End-to-End • .NET Monitoring • Java Monitoring User OperationsManager Application Transaction Performance Synthetic Transaction Reliability Availability Transaction • Where in the code caused the problem? • Which application is causing most problems? • Which problem is an application experiencing most? • Which Java app servers and apps are deployed in my environment? • Are they running? • How is my JVM performing? • Show me custom Java app metrics

KEY ADVANTAGES OF OM 12 APPLICATION MONITORING • Single tool for monitoring • Infrastructure and Applications • .Net and Java • No management pack authoring or code change • Easy to use • Express and advanced configuration • Consistent metrics • Problem categorization for .NET app • Always-on production monitoring with low overhead

.NET MONITORING

HOW TO SET UP .NET MONITORING? • Application monitoring agent and database are installed with OM, no additional installation steps needed Operations DB Data Warehouse DB Monitored Server OM Agent APM Agent CSM Collector OM Console OM Web Console App Diagnostics console App Advisor Console Management Server

CONFIGURE .NET MONITORING • IIS-Hosted Components • Import IIS management packs to discover apps • Microsoft.Windows.InternetInformationServices.2008.mp • Microsoft.SystemCenter.Apm.Web.IIS7.mp • Microsoft.Windows.InternetInformationServices.2012.mp – NEW (Out of Band Release) • Microsoft.SystemCenter.Apm.Web.IIS8.mp – NEW in SP1! • Discovery Overrides on http://technet.microsoft.com/en-us/library/hh916929.aspx • Windows Services Components - NEW in SP1! • Configure Windows Service Template first • Configure monitoring through APM template

DEMO CONFIGURING .NET MONITORING

CONFIGURE .NET MONITORING • Express configuration • Alert or not on events • Performance thresholds • Advanced configuration • Various levels of data collection • Component • Transaction • Namespace • Method • Limit end user IP range for browser side monitoring

HOW TO WORK WITH .NET MONITORING? • React to an application problem • Detect • Triage • Diagnose • Proactively reduce problems • Find the most problematic app • Find the biggest problem in the app • Provide info that developer needs to solve the problem

DEMO .NET MONITORING –DETECT, TRIAGE, DIAGNOSE

DEMO .NET MONITORING –ANALYZE

JAVA Monitoring

JAVA EE APPLICATION SERVER - OVERVIEW Windows, UNIX, Linux Java EE Application Server JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) Application Web Server Application Application Message Queues Connection Pools Naming Service Java Mgmt Extension (JMX) Transaction Service MBean Store …. …. …. AppServer Customer Microsoft

JAVA MONITORING - OVERVIEW Discover/Monitor App Servers Windows, UNIX, Linux Discover /Monitor Applications Java EE Application Server JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) Application Web Server Application Application Message Queues Connection Pools Naming Service Java Mgmt Extension (JMX) Transaction Service MBean Store …. …. …. AppServer Customer Microsoft

JAVA MONITORING – SUPPORTED PLATFORMS • Supported Java EE Application Servers • IBM WebSphere 6.1, 7.0 • Oracle WebLogic 11gRel1, 10gRel3 • RedhatJBoss 4.2, 5.1, 6 • Apache Tomcat 5.5, 6.0, 7 • Supported Operating Systems Matrix Tomcat JBoss WebSphere WebLogic     Windows RHEL     SLES     Solaris  AIX 

Java Monitoring - Windows Windows OS Java EE Application Server SCOM Agent JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) Application Web Server Application Java MP Application Message Queues HTTP Connection Pools BeanSpy HTTPS Naming Service Java Mgmt Extension (JMX) Transaction Service MBean Store …. …. …. AppServer Customer Microsoft

JAVA MONITORING – UNIX/LINUX UNIX/Linux Java EE Application Server SCX Agent JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) WSMAN Application Web Server Application Java Provider Application Message Queues HTTP Connection Pools BeanSpy HTTPS Naming Service Mgmt Server Java Mgmt Extension (JMX) Transaction Service MBean Store …. …. …. AppServer Customer Microsoft

JEE PACKAGE FOR OM 2012 • 16 MPs in one .msi • Download: http://www.microsoft.com/download/en/details.aspx?id=29270 • 4 MP Guides • 1 Readme (known issues & quick start guide)

WORKING WITH JAVA MONITORING Customer Actions Monitoring Scenarios 1. Import Java MPs • Which app servers are deployed? • Are they running?

TWO TYPES OF DISCOVERY • Automatic Discovery • By registry key on Windows • Different application server editions have different regkeys • Regkeys created under HKEY_USERS can be removed when user is not logged in • By command line option of running processes • Discoverable only when process is running • Process name can be changed • Command line option can be customized • Manual Discovery • By supplying a list of URLs to a Powershell script • Deep monitoring only • Agentless, management server (pool) must have access to application server URLs

WORKING WITH JAVA MONITORING Customer Actions Monitoring Scenarios 1. Import Java MPs • What app servers are deployed? • Are they running? 2. Deploy BeanSpy • Are my app servers responsive? • How’s my app server performing? • What apps are deployed in my app server? • Are my apps running?

JAVA MONITORING – HOW IT WORKS Windows, UNIX, Linux JEE Application Server JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) JEE Application Server (JBOSS, Tomcat, WebSphere, WebLogic) Application Web Server Application Application Message Queues HTTP Connection Pools BeanSpy HTTPS Naming Service Java Mgmt Extension (JMX) Transaction Service MBean Store …. …. …. AppServer Customer Microsoft

TWO TYPES OF DISCOVERY • Automatic Discovery • By registry key on Windows • Different application server editions have different regkeys • Regkeys created under HKEY_USERS can be removed when user is not logged in • By running process command line option • Discoverable only when process is running • Process name can be changed • Command line option can be customized • Manual Discovery • By supplying Java application server URLs to a Powershell script • Deep monitoring only • Agentless, management server (pool) must have access to application server URLs

WORKING WITH JAVA MONITORING Customer Actions Monitoring Scenarios 1. Import Java MPs • What app servers are deployed? • Are they running? 2. Deploy BeanSpy • Are my app servers responsive? • How’s my app server performing? • What apps are deployed in my app server? • Are my apps running? 3. Run Java Templates • What’s the status of my app component? • What’s the throughput of my app? • Should I change the size of my message queue, or connection pool?

DEMO JEE Monitoring

RETRIEVE MANAGEMENT INFO FROM BEANSPY • Application Server Info • /BeanSpy/Stats/Info • Application Server Performance Info • /BeanSpy/Stats • Custom Application Server and Application Info • Query Syntax is Java Standard • Query: /BeanSpy/MBeans?JMXQuery=WebSphere:name=PlantsByWebSphere,* • Invoke: /BeanSpy/MBeans/Invoke <Invoke>        <BeanObjectName>WebSphere:name=PLANTSDB,*</BeanObjectName>        <Method name=“getStatus“ /> </Invoke> • Need more? BeanSpy is open sourced on GitHub with test suit and build script included

360 - Bringing all together Daniele Muscetta Åke Pettersson

APPLICATION MONITORING PERSPECTIVES

360o VIEW OF APPLICATION HEALTH

DEMO 360 - Bringing all together

Related Content • MGT301 – Operations Manager 2012: Overview of What’s New • MGT306 - Tips & Tricks for Creating Custom Management Packs for Microsoft System Center Operations Manager • MGT307 - How to Have Microsoft System Center 2012 Operations Manager Work for You: Lessons Learned, Beyond the Install • MGT308 - Massively Multi-Instance: Building and Deploying Microsoft System Center Operations Manager Management Packs in the Enterprise • MGT31-HOL - Microsoft System Center 2012 Operations Manager: A Look at What’s New • MGT52-HOL - Microsoft System Center 2012 Application Performance Monitoring • MGT32-HOL - Microsoft System Center 2012 Operations Manager Java Monitoring • MGT33-HOL - Microsoft System Center 2012 Operations Manager Linux Monitoring Product Demo Stations (demo station title and location) Related Certification Exam Find Me Later At…

Resources Learning TechNet • Connect. Share. Discuss. • Microsoft Certification & Training Resources http://northamerica.msteched.com www.microsoft.com/learning • Resources for IT Professionals • Resources for Developers http://microsoft.com/technet http://microsoft.com/msdn

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© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

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by Deangelo Hunt

May 29, 2022

by Clark Ruiz