Definition of Application performance monitoring(APM) and providing advice on choosing the appropriate tool

As part of my responsibilities at Tietoevry, I have developed an APM product to be sold to our clients. I am a Certified Scrum Product Owner (CSPO®)

This article is dedicated to explaining the definition of APM and providing advice on choosing the appropriate tool.

Nowadays, software is indispensable in the corporate landscape, and it is crucial to ensure the peak performance of crucial applications.

The market offers a plethora of application performance management and monitoring tools that cater to developers, DevOps teams, and traditional IT operations.

Defining Application Performance Management (APM)

The concept of APM and its beneficiaries within an organization are often subject to ambiguity. APM, or application performance monitoring, is a critical component of ensuring that your business applications are running smoothly and providing the best possible experience for end-users.

The sustained accessibility and optimal functionality of an application are imperative for a company’s capacity to uphold uninterrupted business operations. This precludes unwarranted business interruptions and augments customer contentment.

A proficient APM platform endows an organization with the capability to correlate its application performance with its business objectives, identify and rectify glitches prior to their impact on the end user, and curtail the average time required for repairs.

In order to effectively manage and monitor the performance of an application, it is necessary to gather and monitor various types of data.

An APM solution can be likened to the black box of an aeroplane, as it ensures that developers are not operating blindly. The components of a comprehensive application performance management solution include:

Monitoring the performance of individual web requests or transactions.
Tracking the usage and performance of all application dependencies, such as databases, web services, caching, and others.
Providing detailed transaction traces that can be traced back to specific lines of code.
Conducting code-level performance profiling.
Collecting basic server metrics, such as CPU usage and memory consumption.
Monitoring application framework metrics, such as performance counters and JMX mBeans.
Incorporating custom application metrics that are created by the development team or business.
Analyzing application log data.
Identifying and addressing application errors.
Implementing real user monitoring to gain insights into user experience.

What is the purpose of Application Performance Monitoring (APM)?

The purpose of APM is to ensure the continuous availability and optimal performance of an application, which is crucial for a company to maintain uninterrupted business processes.

By preventing unnecessary disruptions and enhancing customer satisfaction, an effective APM platform enables an organization to connect its application performance to its business outcomes. It allows them to identify and resolve errors before they impact the end user, as well as reduce the mean repair time.
APM tools gather and analyze data from various sources that contribute to an application’s performance. At the foundational level, these tools examine the application’s hosting platform, collecting information on process utilization, memory demands, and disk read/write speeds.
They also monitor processor utilization, which measures the number of operations per second performed by the CPU server. High memory usage can lead to application performance issues, and APM tracks the amount of short-term data stored by the CPU to address this.
Additionally, at the software level, APM tools monitor error rates, indicating how frequently an application encounters problems or fails. For instance, an error may occur when there is insufficient memory for the application to access.
Furthermore, application performance monitoring tools track code execution to identify potential bottlenecks during memory-intensive processes, such as database searches.

How does Application Performance Monitoring (APM) work?

APM tools or platforms operate by observing the performance of applications and assessing their behaviour. If any inappropriate behaviour is detected, data is collected to identify the source of the issue.

This gathered data is then analyzed in the context of its impact on the business, and necessary corrections are made to the application environment to prevent similar problems from occurring in the future.

When configuring an APM platform, it is important to consider three categories of data:

Metrics: Metrics are quantified measures that provide insights into the status of specific processes. These metrics are often compared to a defined baseline to analyze the overall system or process status. Any changes in metrics can indicate underlying issues.
Traces: Traces represent the complete processing of a request, illustrating its journey through all the components and services of the network. Traces consist of numerous data points that can help identify errors, diagnose security threats, and detect and isolate network issues.
Log files: Log files are automatically generated by applications or operating systems and contain information about user behaviour and events within the application. These files are used for root cause analysis, understanding changes in metrics, and identifying the origin of specific events.

It is important to note that while performance monitoring is a part of the broader performance management topic, relying solely on monitored data and analytics may not guarantee an optimal user experience.

Performance management systems often integrate monitoring data with automation and orchestration to enable autonomous problem remediation.

What are the components of APM?

The components of APM encompass various aspects that are crucial for monitoring and assessing the performance of an application.

There exist various kinds of Application Performance Monitoring (APM) methodologies, which include

Agent-based
Agentless
Network-based
Synthetic monitoring.

Agent-based APM employs software installed on the application server to collect pertinent data, whereas agentless APM utilizes external tools to monitor the performance of the application.

In contrast, network-based APM utilizes traffic analysis to identify and resolve performance issues, while synthetic monitoring simulates user activity to detect potential problems.

Runtime application architecture.

These components include runtime application architecture, real user monitoring, business transactions, component monitoring, and analytics and reporting.

Runtime application architecture involves the analysis of both hardware and software components utilized in the execution of the application, as well as the communication pathways employed by these components.
By employing pattern recognition and identifying performance issues, IT professionals can proactively anticipate potential problems and effectively plan for necessary upgrades, such as increased application storage capacity, in a timely manner.

Real user monitoring.

Real user monitoring, also referred to as end-user experience monitoring, is a crucial component that collects performance data based on user interactions.

Its purpose is to assess the application’s performance for users and identify potential performance issues. For instance, application performance management (APM) can track the response time of a critical website and notify stakeholders if response times exceed an acceptable threshold, indicating lag or application response problems.
Real user monitoring allows organizations to promptly address faults and comprehend their impact. There are two methods for monitoring end-user experience:
Synthetic monitoring: This monitoring technique employs probes and bots to simulate end users and identify issues before the application is accessed. Synthetic monitoring is also utilized to monitor service-level agreements (SLAs) associated with the application.
Agentless monitoring: This approach utilizes data probes to analyze network traffic passing through load balancers and switches. Agentless monitoring provides insights into performance across the entire infrastructure and offers details about the analyzed client, such as their location, operating system, and browser.

Component monitoring,

Component monitoring, also referred to as application component deep dive, encompasses the meticulous tracking of all components within the IT infrastructure.

A comprehensive and thorough monitoring process is conducted on all utilized resources and encountered events within the application performance infrastructure.
This encompasses an analysis of all servers, operating systems, middleware, application components, and network components.
Component monitoring facilitates a more profound comprehension of the diverse elements and pathways identified in preceding procedures.

IoT monitoring

By utilizing IoT monitoring, complex systems can be efficiently analyzed and a significant amount of events and alerts can be handled.

Furthermore, IoT monitoring enables the connection of devices to business by gathering and analyzing a diverse range of IoT data across multiple devices, customers, and applications.
This ultimately results in improved performance across various applications, networks, APIs, and protocols.
By obtaining actionable insights, customer experience can be enhanced, issues can be resolved, and IoT opportunities can be maximized.
End-to-end IoT monitoring system allows you to effortlessly monitor performance, process billions of events and alerts, and bridge the gap between devices and business processes.
Gain actionable insights to improve customer experiences, remedy issues, and maximize IoT opportunities beyond your imagination.
The system optimizes performance across multiple applications, APIs, networks, and protocols, due to powerful IoT features like publish/subscribe and MQTT messaging.
Incorporate continuous testing to identify and resolve performance and security issues before IoT deployments and boost your IoT development beyond your expectations.

Infrastructure monitoring

To ensure that servers, virtual machines, containers, databases, and other backend components in a tech stack are working optimally, infrastructure monitoring is employed.

When backend systems encounter issues, engineers may utilize an infrastructure monitoring tool to identify, examine, and notify on vital metrics.
Infrastructure monitoring traces the performance, resource usage, and availability of various backend components involving hosts and containers.
To analyze and visualize the data, engineers install an agent on their hosts, which gathers infrastructure metrics and transmits them to a monitoring platform.
This offers visibility into the health of backend components that run applications, enabling engineers to ensure that critical services are accessible and performing as expected.
With the adoption of cloud infrastructure, engineers can deploy or substitute servers on demand. As a result, monitoring ephemeral infrastructure components becomes necessary in such dynamic environments.
Engineers require insight into specific subsets of their infrastructure, such as hosts in a specific region. In the past, organizations handled their own physical servers with fixed IP addresses.
However, infrastructure monitoring has been developed to accommodate the changing requirements of cloud infrastructure.

Server monitoring

Monitoring servers involves keeping track of the system resources associated with relevant servers to detect any specific states and changes.

This process can provide valuable insight into the hardware and processes required to maintain server functionality and ensure optimal system performance.
Moreover, beyond detecting performance issues before they affect users, server monitoring can improve application and server performance, thereby increasing efficiency and enhancing the end-user experience.
It is crucial to monitor servers because it enables administrators to identify and troubleshoot system issues before they impact users, thereby saving time and effort.
Although manual monitoring efforts can be helpful, utilizing server monitoring and reporting tools can save time by quickly identifying the root cause of problems, allowing for faster resolution.
Repeatedly using an effective server monitoring solution can help pinpoint where issues originated, streamlining the troubleshooting process and allowing for more efficient problem-solving.

A server monitoring solution offers a plethora of features beyond mere asset inventory.

It includes hardware health monitoring, monitoring capabilities beyond different environments and vendors, and real-time tracking.
Creating an accurate inventory entails collating data from multiple nodes on the software at scheduled times. Hardware health monitoring allows you to gather beyond what is normally available from server operating systems.
By using a server monitoring tool, you can monitor multiple nodes, including cloud and on-premises servers, client servers, application servers, mail servers, FTP servers, proxy servers, and web servers.
These tools can also collect key metrics for applications and servers, providing analytic tools to help you understand their significance.
Real-time tracking allows you to receive performance metrics, including memory load, CPU load, disk queue, response time, and network throughput. Administrators can set thresholds and alerts to stay on top of performance problems beyond what repeatedly occurs.

Network Monitoring

Monitoring a network is a crucial aspect of maintaining its proper functioning, both in terms of hardware and software layers. Network engineers rely heavily on this process to prevent and troubleshoot issues that could lead to network outages or failures.

Networks allow the exchange of information between two systems, such as computers or applications.

The Open Systems Interconnection (OSI) Model outlines the various functions that computer systems depend on to send and receive data.
Data passes through each component of the OSI, utilizing different protocols, starting at the physical layer and ending at the application layer, to be transmitted across a network.
Network monitoring provides engineers with visibility into all these components, enabling them to identify and resolve issues at any layer.
The Simple Network Management Protocol (SNMP) standard is supported by most network devices, enabling engineers to monitor inbound and outbound network traffic and other vital network telemetry.
The Internet Protocol (IP) is a standard used on almost all networks to provide an address and routing system for devices, facilitating the routing of information to the correct destination over large networks.
To collect various metrics from network devices, such as uptime, CPU utilization, bandwidth usage, throughput, interface errors/discards, and IP metrics such as time delay and hop count, network engineers typically use monitoring tools.
These metrics are essential for ensuring the health and performance of on-premise equipment.
It’s important to note that cloud environments involve companies purchasing compute and network resources from cloud vendors who are responsible for maintaining the physical infrastructure for running their services or applications, shifting the burden of managing the hardware to the cloud vendor.

Database monitoring

Monitoring databases in real time is commonly referred to as database monitoring or database performance monitoring.

This practice involves the constant tracking of specific metrics to comprehend the health and behaviour of database systems, which allows teams to troubleshoot and optimize performance.
Database monitoring is a crucial aspect of database management as databases power critical apps and services for organizations.
Slow queries or too many open connections can significantly impact end-users experience, thus making monitoring beyond essential.
By providing insight into software and database server hardware health, teams can identify and rectify performance issues before they negatively affect users.
Furthermore, the data from database monitoring can repeatedly assist developers in upgrading their application infrastructure and ensuring high performance.

Database performance can be influenced by a variety of factors. However, there are five main factors to consider: workload, throughput, resources, optimization, and contention.

Workload refers to the total number of requests made by users and applications. It can be unpredictable and fluctuate over time.
Throughput, on the other hand, measures the amount of work done by the database within a given period. If it’s lower than the incoming queries, slower response times can occur.
Resources, such as hardware and software tools, also have a significant impact on database performance.
Optimization techniques, like proper indexing and data types, are crucial for increasing information retrieval efficiency and speed.
Contention arises when multiple processes attempt to access the same data at the same time, which results in decreased throughput.

Database administrators must optimize these factors to ensure the best possible performance for the largest workload.

Cloud monitoring

To efficiently manage the workflow of an IT infrastructure and detect possible security threats, monitoring plays a critical role.

Cloud monitoring, on the other hand, evaluates the performance of cloud-based infrastructures, including websites, servers, applications, and other cloud resources.
The assessment encompasses factors such as resource levels, server response times, and the ability to identify threats and vulnerabilities promptly.
Automated tools are employed in cloud monitoring to check uptime, speed, and errors when users interact with applications.
This helps to ensure that beyond the smooth operations of cloud-based infrastructures, potential risks are identified and mitigated repeatedly.

Cloud monitoring is a crucial aspect for a variety of reasons.

Firstly, it allows for cost optimization by identifying and eliminating unused resources, thereby reducing unnecessary expenses.
Secondly, it provides real-time insights into cloud performance, enabling the detection and resolution of performance issues.
Thirdly, it enhances security by detecting and mitigating potential security threats, ensuring a safe environment for the application.
Fourthly, cloud monitoring allows for scalability as resources can be scaled as per demand, making it easier to handle increased demand.
Fifthly, it improves operational efficiency by identifying underutilized resources and automating monitoring tasks, reducing manual effort.
Lastly, it enhances user experience by ensuring the smooth functioning of cloud-based applications and meeting service level objectives (SLOs).

Through these benefits, cloud monitoring becomes a vital tool for any organization looking to optimize its cloud-based operations.

When considering cloud monitoring, there exist three types: public, private, and hybrid. Each has its own distinct features and benefits.

Public cloud monitoring is provided by third-party providers such as Azure or AWS and is available to any company that purchases the service. It is a cost-effective option as the cost is based on the resources used. However, application data control is less due to shared resources. According to 70% of users, public cloud monitoring can be more challenging than private cloud monitoring.
Private cloud monitoring, on the other hand, is controlled by a single organization. This makes it more secure and provides more accurate and detailed reporting. It monitors system performance, uptime or availability, CPU and memory utilization, requests per minute, disk utilization, resource levels, server response times, speed of data transfer, and cluster health.
Hybrid cloud monitoring combines the benefits of both public and private cloud monitoring, allowing for greater flexibility and control beyond what is available with either public or private cloud monitoring.

Full Stack Monitoring

Are you seeking to streamline your monitoring strategy without completely overhauling your current tools and methods? Look no further than full-stack monitoring.

Full-stack monitoring breaks down silos in monitoring workflows, enabling comprehensive end-to-end monitoring of all your resources.

This method encompasses all resource types, including applications, infrastructure, and cloud services.
Additionally, it integrates all monitoring techniques, such as synthetic and real-user monitoring, into a single process.

In essence, full-stack monitoring enables you to monitor every facet of your IT estate through a united, multi-pronged approach. It is the antithesis of solely focusing on one monitoring technique or resource type.

Full-stack monitoring bears similarities to full-stack software development, which has gained traction in recent years.

This term pertains to software engineering strategies that encompass all facets of development, such as server programming, application programming, database programming, and beyond.
Similarly, full-stack monitoring treats monitoring as a comprehensive undertaking.

Full-stack monitoring has advantages beyond separate monitoring processes.

It increases efficiency and consolidates monitoring into one tool and team.
Monitoring all resources together, it offers better context on performance issues and can detect how an application issue may be related to an infrastructure problem.
Full-stack monitoring is also conducive to shift-left monitoring, which emphasizes techniques that assess application performance earlier in the CI/CD pipeline.
It allows comprehensive data collection and enhances your ability to detect performance risks early.

Therefore, full-stack monitoring is a valuable tool for IT infrastructure management.

APM tools and top vendors

Organizations are presented with a plethora of APM tools, which may either be dedicated to APM tasks or possess APM functionality integrated into a broader range of features.

Among the most popular tools for APM are third-party and cloud-based offerings, including

Dynatrace
AppDynamics
Datadog
Azure Application Insights,
DX Application Performance Monitoring
Site24x7
SolarWinds AppOptics
Splunk
Stackify
Dell Foglight
eG Innovations
Google Cloud Console
Grafana, LogicMonitor
ManageEngine Applications Manager
Microsoft System Center
Nagios
New Relic
Pulse Secure Virtual Traffic Manager
Red Hat OpenShift Container Platform
Sematext APM
Sensu
Retrace
Zenoss.

By implementing powerful APM tools, businesses can achieve optimal performance and enhance the overall user experience.

Recommendations for Choosing Application Monitoring Tools

Historically, application performance management tools were only accessible to larger enterprises and were utilized by IT operations to oversee critical applications.

These tools were primarily used for business transaction monitoring. However, in recent years, APM tools have become more affordable and are now considered essential for all businesses.

Additionally, developers are increasingly using APM tools for application performance monitoring, not just IT operations.

APM plays a significant role in the DevOps movement. When selecting APM tools, there are several key factors to consider.

These include:

Programming language support
Cloud support (e.g., Azure, AWS, Heroku)
SaaS vs on-premise options
Pricing
Ease of use

Dynatrace and AppDynamics.

These two platforms offer businesses application performance monitoring (APM) solutions that help to enhance the performance and availability of their applications.

With Dynatrace’s real-time monitoring, intelligent analytics, and automation capabilities, businesses can quickly identify and resolve performance issues.
AppDynamics, on the other hand, provides end-to-end visibility into application performance across all layers of the technology stack, including code-level diagnostics and business transaction tracing.

Both solutions aim to optimize applications and improve the overall user experience.

These two valuable solutions offer businesses cutting-edge application performance monitoring (APM) capabilities that enable them to optimize the performance and availability of their applications.
Dynatrace’s real-time monitoring functionality, coupled with its advanced intelligent analytics and automation capabilities, empowers businesses to rapidly identify and resolve performance issues before they impact end-users.
Similarly, AppDynamics offers comprehensive end-to-end visibility into application performance across all layers of the technology stack, along with code-level diagnostics and business transaction tracing capabilities.
These features enable businesses to gain critical insights into the performance of their applications, identifying potential bottlenecks and other issues that could impact the overall user experience.

Overall, both Dynatrace and AppDynamics are powerful APM solutions that can help businesses achieve optimal application performance and improve the overall user experience.

APM Tools for Utilization During Code Development

APM tools were traditionally used on production servers. However, developers can also employ APM tools on their workstations while writing and testing their code.

Developers have the option to employ tools that offer thorough transaction tracing, utilizing lightweight code profilers or similar technologies.

This offers effortless access to crucial information and beyond. The selection of developer tools relies on the programming language utilized.

These tools offer diverse features and functions, with some necessitating extensive code modifications or configurations, while others require none. It may be necessary to use these tools repeatedly to ensure optimal performance.

Primarily designed to operate on workstations, some of these developer tools may also be compatible with servers.

The following APM tools are highly beneficial for developers, eventually becoming an integral part of their standard toolchain

Glimpse (.net) –
Miniprofiler (.net / ruby / go / node.js) –
XRebel (java, paid) –
Stackify Prefix (.net / java) – Scout Devtrace (ruby) –
Rack trace (ruby) –
Zend Z-Ray (php, paid)

Incorporating these types of APM tools into your development process can prove to be invaluable, enhancing efficiency and effectiveness.

Once integrated, they will undoubtedly become an indispensable component of your routine tool-set.

Key APM metrics or KPIs

In the realm of application performance monitoring (APM), a variety of metrics can be utilized to assess the state of an application.

Among the most crucial metrics for monitoring applications are the following:

Web performance monitoring: This metric evaluates the average response time for end-user interactions in order to determine if the speed is impacting the performance of the application.
Customer satisfaction: This metric provides insight into how customers perceive the application in comparison to a predetermined baseline.
Error rates: This metric observes the extent to which the application experiences degradation or failure at the software level.
Number of instances: This metric involves counting the number of server or application instances that are operational at any given time, which is particularly pertinent for cloud-based applications.
Response time: Similar to web performance monitoring, this metric measures the duration it takes for an application to fulfil a user’s request or query.
Resource usage: This metric monitors the utilization of the central processing unit (CPU), as well as the speed of disk read/write operations and memory requirements, to ascertain if resource usage is affecting the performance of the application.
Application availability and uptime: This metric assesses whether the application is accessible and accessible to users, and is frequently employed to assess compliance with an organization’s service level agreement (SLA).
Request rates: This metric quantifies the volume of traffic received by the application, enabling the identification of significant increases, decreases, or concurrent users.

Conclusion

In summary, Application Performance Management (APM) encompasses a range of tools and techniques that enable developers to effectively manage and monitor the performance of an application, ensuring optimal functionality and user experience.

APM might include overseeing projects, developing software, implementing agile methodology, monitoring performance, fostering team collaboration, and optimizing workflow.

Is there a particular aspect of APM that you would like me to concentrate on specifically? Let’s delve into a thoughtful and productive conversation about APM.

#ITinfrastructure, #CloudMonitoring, and #SecurityThreats today.#DatabaseMonitoring, #DatabaseManagement, #OptimizePerformance, #Troubleshooting, and #DatabaseHealth #DatabasePerformance, #OptimizationTechniques, #Efficiency, #DataRetrieval, and #Contention. #constructivedialogue #intellectualconversations #mindfuldebates #opencommunication #courteousinteraction. #shoebhakim #lawhak #APM #software #performance #optimization #monitoring #ITmonitoring, #FullStackMonitoring, #EndToEndMonitoring, #SyntheticMonitoring, and #RealUserMonitoring to stay on top of your IT game.

Adv. Shoeb Hakim

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