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Why Application Monitoring Matters?

SRE

Why Application Monitoring Matters?

Fedir Kompaniiets

DevOps and Cloud Architecture Expert Co-founder of Gart

September 10, 2024

Table of contents

Key Challenges in Application Monitoring
Types of Application Monitoring
Key Metrics for Application Monitoring
Tools for Application Monitoring
Best Practices in Application Monitoring
Optimize Your Application Performance with Expert Monitoring

Application monitoring is watching apps to make sure they work well.

Application monitoring is the process of observing, tracking, and analyzing the performance, availability, and overall health of software applications. It plays a crucial role in ensuring the smooth functioning of modern digital systems and services.

The key objectives of application monitoring are to:

Ensure optimal application performance
Maintain high availability and reliability
Identify and resolve issues quickly

Application monitoring has become increasingly vital in the era of DevOps, Agile, and Continuous Integration/Continuous Deployment (CI/CD) methodologies. These practices demand a heightened focus on monitoring to support rapid development cycles, continuous deployment, and the ability to quickly identify and address problems.

Key Challenges in Application Monitoring

One of the major challenges in modern application monitoring is managing the complexity that comes with microservices. Applications today are built using a multitude of microservices that interact with one another, often spanning across different cloud environments. Finding and monitoring all these services can be a daunting task.

A useful analogy can be drawn from early aviation. Pilots in the past had to rely on their intuition and limited manual tools to interpret multiple signals coming from various instruments simultaneously, making it difficult to ensure safe operations. Similarly, application operators are often flooded with a vast amount of performance signals and data, which can be overwhelming to process. This data overload is compounded by the fact that microservices are highly distributed and can have many dependencies that require monitoring.

Without the right tools, managing all this information can be a bottleneck, just like early pilots struggled with too many signals.

SRE (Site Reliability Engineering) principles streamline the monitoring of complex systems by focusing on the most critical aspects of application performance. Rather than tracking every possible metric, SRE emphasizes the Golden Signals (latency, errors, traffic, and saturation). This approach reduces the complexity of analyzing multiple services, allowing engineers to identify root causes faster, even in microservice topologies where each service could be based on different technologies. The key advantage is faster detection and resolution of issues, minimizing downtime and enhancing the user experience.

Streamlining Application Monitoring with SRE Principles

Types of Application Monitoring

Application monitoring encompasses a range of techniques and tools to provide comprehensive visibility into the performance, availability, and overall health of software systems. Some of the key types of application monitoring include:

Infrastructure Monitoring

This involves monitoring the underlying hardware, virtual machines, and cloud resources that support the application, such as CPU, memory, storage, and network utilization. Infrastructure monitoring helps ensure the reliable operation of the application’s foundation.

Application Performance Monitoring (APM)

APM focuses on tracking the performance and behavior of the application itself, including response times, error rates, transaction tracing, and resource consumption. This allows teams to identify performance bottlenecks and optimize the application’s codebase.

User Experience Monitoring

This approach tracks how end-users interact with the application, measuring metrics like page load times, user clicks, and session duration. User experience monitoring helps ensure the application meets or exceeds customer expectations.

Log and Event Monitoring

Monitoring the application’s logs and event data can provide valuable insights into system behavior, errors, and security incidents. This information can be used to troubleshoot problems and ensure regulatory compliance.

Synthetic Monitoring

Synthetic monitoring uses automated scripts to simulate user interactions and measure the application’s responsiveness, availability, and functionality from various geographic locations. This proactive approach helps detect issues before they impact real users.

Real-User Monitoring (RUM)

RUM tracks the actual experience of end-users by collecting performance data directly from the user’s browser or mobile device. This provides a more accurate representation of the user experience compared to synthetic monitoring.

Key Metrics for Application Monitoring

Effective application monitoring relies on a comprehensive set of metrics that provide insights into the performance, availability, and overall health of the system. Some of the key metrics to track include:

Performance Metrics

Response time: The time it takes for the application to respond to user requests

Throughput: The number of requests or transactions processed per unit of time

Resource utilization: CPU, memory, and network usage by the application and its underlying infrastructure

Availability Metrics

Uptime/Downtime: The percentage of time the application is available and functioning as expected

Error rate: The number of errors or exceptions occurring within the application

Latency: The time it takes for the application to respond to requests

User Experience Metrics

Page load time: The time it takes for pages to load and become interactive

User sessions: The number of active user sessions and their duration

Bounce rate: The percentage of users who leave the application without interacting further

Business Metrics

▪️ Revenue: The financial impact of the application, such as sales, subscriptions, or in-app purchases

▪️ Conversion rate: The percentage of users who complete a desired action, such as making a purchase or signing up for a service

▪️ Customer satisfaction: Measures like Net Promoter Score (NPS) or user reviews

Tools for Application Monitoring

Effective application monitoring requires the use of specialized tools and platforms. Some of the popular options include:

Application Performance Monitoring (APM) Tools

New Relic: Provides comprehensive APM, infrastructure, and user experience monitoring
Datadog: Offers a suite of monitoring and analytics tools for applications, infrastructure, and cloud environments
AppDynamics: Focuses on transaction tracing, root cause analysis, and application performance optimization

Open-Source Monitoring Tools

Prometheus: A powerful time-series database and monitoring system for cloud-native applications
Grafana: A highly customizable data visualization and dashboard platform, often used in conjunction with Prometheus
Nagios: A widely-adopted open-source tool for monitoring systems, networks, and applications

Log Management Tools

ELK Stack (Elasticsearch, Logstash, Kibana): A popular open-source solution for log aggregation, analysis, and visualization
Splunk: A commercial platform for collecting, indexing, and analyzing machine data, including application logs

Real Time Monitoring and Analytics tools.

When choosing application monitoring tools, organizations should consider factors such as:

Scalability: The ability to handle increasing volumes of data and support growing infrastructure

Budget: Both the initial cost of the tool and the ongoing operational expenses

Integration: The ease of integrating the monitoring solution with the existing software stack and tools

Best Practices in Application Monitoring

Effective application monitoring requires a strategic approach and the adoption of best practices. Some key recommendations include:

Comprehensive Application Monitoring Strategies

Set Realistic Thresholds and Baselines

Establish meaningful performance thresholds and baseline metrics for your application, taking into account factors such as user expectations, industry standards, and historical trends.

This helps ensure that monitoring alerts are triggered only for significant deviations from normal operation.

Automate Monitoring and Alerting Workflows

Leverage automation to streamline the monitoring and alerting processes. This includes automatically configuring monitoring tools, setting up alert triggers, and integrating monitoring data with incident management and collaboration tools.

Leverage AI/ML for Anomaly Detection and Predictive Analysis

Utilize advanced analytics and machine learning techniques to identify anomalies, predict performance issues, and proactively address problems before they impact users.

Implement Continuous Monitoring in the CI/CD Pipeline

Integrate monitoring into the continuous integration and continuous deployment (CI/CD) process, ensuring that application performance and reliability are validated at every stage of the software delivery lifecycle.

Balance Between Too Many Alerts and Meaningful Signals

Carefully design your monitoring and alerting strategy to strike a balance between overwhelming the team with too many alerts and ensuring that the most critical issues are surfaced promptly.

Monitor Across Different Environments

Extend your monitoring capabilities to cover the application across different environments, including development, staging, and production. This provides a holistic view of the application’s performance and helps identify inconsistencies or regressions.

Optimize Your Application Performance with Expert Monitoring

Is your application running at its best? At Gart Solutions, we specialize in setting up robust monitoring systems tailored to your needs. Whether you’re looking to enhance performance, minimize downtime, or gain deeper insights into your application’s health, our team can help you configure and implement comprehensive monitoring solutions.

Take a look at these two recent cases that illustrate our expertise in this area:

Centralized Monitoring for a B2C SaaS Music Platform:
We developed a real-time infrastructure and application monitoring solution using AWS CloudWatch and Grafana for a global music platform. This solution provided scalable monitoring across multiple regions, enhanced system visibility, reduced downtime, and improved operational efficiency. The result was a cost-effective, user-friendly monitoring system that ensured future growth and expansion.

Monitoring Solutions for Scaling a Digital Landfill Platform:
We created a universal monitoring system for the elandfill.io platform, successfully scaling it across countries like Iceland, France, Sweden, and Turkey. This solution improved methane emission predictions, optimized landfill management, and simplified compliance with regulatory requirements. The cloud-agnostic approach also ensured flexibility in cloud provider selection for the client.

Ready to elevate your app’s performance? Contact Gart Solutions today to get started with personalized application monitoring that ensures your system runs smoothly and efficiently. Let us help you stay ahead of issues before they impact your users.

Let’s work together!

See how we can help to overcome your challenges

FAQ

What is application monitoring?

Application monitoring is the process of continuously tracking and analyzing the performance, availability, and behavior of software applications. It helps developers and IT teams identify and resolve issues, optimize application performance, and ensure a positive user experience.

What are the key metrics to monitor in an application?

Some of the most important metrics to monitor include:

Response time: The time it takes for an application to respond to a user request.
Throughput: The number of requests an application can handle per unit of time.
Error rate: The percentage of failed requests or errors encountered by users.
Resource utilization: CPU, memory, and disk usage of the underlying infrastructure.
User activity: Tracking user interactions and behavior within the application.

How do I get started with application monitoring?

To get started with application monitoring, follow these steps:

Identify your monitoring goals: Determine what you want to achieve with monitoring (e.g., faster issue resolution, improved performance).
Select the right tools: Choose monitoring tools that align with your goals and the technologies used in your application.
Instrument your application: Integrate monitoring agents or libraries into your application code to collect relevant data.
Set up alerting and dashboards: Configure alerts to notify you of issues and create dashboards to visualize monitoring data.
Continuously optimize: Regularly review your monitoring data and adjust your approach to ensure you're getting the most value.

DevOps

SRE

SRE Monitoring: Golden Signals as a Key Metrics for System Reliability

Fedir Kompaniiets

September 9, 2024

Site Reliability Engineering (SRE) focuses on keeping services reliable and scalable. A crucial part of this discipline is monitoring, which is where the concept of Golden Signals comes into play. Golden Signals help teams quickly identify and diagnose issues within a system. This article breaks down what these signals are, why they're important, and how they can be used to maintain healthy systems. The Four Golden Signals SRE principles streamline monitoring by focusing on four key metrics—latency, errors, traffic, and saturation—collectively known as Golden Signals. Instead of tracking numerous metrics across different technologies, focusing on these four metrics helps in quickly identifying and resolving issues. Latency:Latency is the time it takes for a request to travel from the client to the server and back. High latency can cause a poor user experience, making it critical to keep this metric in check. For example, in web applications, latency might typically range from 200 to 400 milliseconds. Latency monitoring helps detect slowdowns early, allowing for quick corrective action. Errors:Errors refer to the rate of failed requests. Monitoring errors is essential because not all errors have the same impact. For instance, a 500 error (server error) is more severe than a 400 error (client error) because the former often requires immediate intervention. Identifying error spikes can alert teams to underlying issues before they escalate into major problems. Traffic:Traffic measures the volume of requests coming into the system. Understanding traffic patterns helps teams prepare for expected loads and identify anomalies that might indicate issues such as DDoS attacks or unplanned spikes in user activity. For example, if your system is built to handle 1,000 requests per second and suddenly receives 10,000, this surge might overwhelm your infrastructure if not properly managed. Saturation:Saturation is about resource utilization; it shows how close your system is to reaching its full capacity. Monitoring saturation helps avoid performance bottlenecks caused by overuse of resources like CPU, memory, or network bandwidth. Think of it like a car's tachometer: once it redlines, you're pushing the engine too hard, risking a breakdown. Challenges associated with monitoring saturation in microservices: Complexity of Microservice Architectures:In microservice environments, various services are often built on different technologies (e.g., Node.js, databases, Swift). Each service may handle resource usage differently, making it challenging to monitor and understand overall system saturation accurately. Saturation occurs when resources such as CPU, memory, or network bandwidth are fully utilized, leading to degraded performance. Resource Utilization Visibility:Since each microservice can have its unique metrics, gaining a clear view of overall saturation is difficult. Teams need to aggregate and standardize data from multiple services to accurately assess saturation levels. This can be time-consuming and requires expertise across different technology stacks. Identification of Bottlenecks:Saturation often results in bottlenecks where some services are overloaded while others are underutilized. Pinpointing which service is causing the bottleneck in a complex system can be difficult without a cohesive monitoring approach like the one provided by SRE Golden Signals. Dynamic and Variable Loads:In microservice architectures, traffic and resource demands can fluctuate rapidly, making it essential to monitor saturation in real-time. Services must adapt to changes in load, but without proper monitoring, it's easy to miss critical saturation points that can impact overall system performance. Why Golden Signals Matter Golden Signals provide a comprehensive overview of a system's health, enabling SREs and DevOps teams to be proactive rather than reactive. By continuously monitoring these metrics, teams can spot trends and anomalies, address potential issues before they affect end-users, and maintain a high level of service reliability. SRE Golden Signals help in proactive system monitoring SRE Golden Signals are crucial for proactive system monitoring because they simplify the identification of root causes in complex applications. Instead of getting overwhelmed by numerous metrics from various technologies, SRE Golden Signals focus on four key indicators: latency, errors, traffic, and saturation. By continuously monitoring these signals, teams can detect anomalies early and address potential issues before they affect the end-user. For instance, if there is an increase in latency or a spike in error rates, it signals that something is wrong, prompting immediate investigation. What are the key benefits of using "golden signals" in a microservices environment? The "golden signals" approach is especially beneficial in a microservices environment because it provides a simplified yet powerful framework to monitor essential metrics across complex service architectures. Here’s why this approach is effective: ▪️Focuses on Key Performance Indicators (KPIs) By concentrating on latency, errors, traffic, and saturation, the golden signals let teams avoid the overwhelming and often unmanageable task of tracking every metric across diverse microservices. This strategic focus means that only the most crucial metrics impacting user experience are monitored. ▪️Enhances Cross-Technology Clarity In a microservices ecosystem where services might be built on different technologies (e.g., Node.js, DB2, Swift), using universal metrics minimizes the need for specific expertise. Teams can identify issues without having to fully understand the intricacies of every service’s technology stack. ▪️Speeds Up Troubleshooting Golden signals quickly highlight root causes by filtering out non-essential metrics, allowing the team to narrow down potential problem areas in a large web of interdependent services. This is crucial for maintaining service uptime and a seamless user experience. By applying these golden signals, SRE teams can efficiently diagnose and address issues, keeping complex applications stable and responsive. How can the "one-hop dependency view" assist in troubleshooting? The "one-hop dependency view" in application performance monitoring (APM) simplifies troubleshooting by focusing only on the services that directly impact the affected service. Here’s how it helps: ▪️Reduces Investigation Scope Rather than analyzing the entire microservices topology, the one-hop view narrows the scope to immediate dependencies. This selective approach allows engineers to focus on the most likely sources of issues, saving time in identifying the root cause. ▪️Streamlines Root-Cause Analysis By examining only the services one level away, the team can apply the golden signals (latency, errors, traffic, saturation) to detect any anomalies quickly. If a direct dependency is experiencing problems, it becomes immediately apparent without unnecessary complexity. ▪️Decreases Mean-Time-to-Recovery (MTTR) With fewer services to investigate, the MTTR is significantly reduced. Engineers can identify and address the root issue faster, minimizing downtime and maintaining the application’s reliability. Using the one-hop dependency view helps SRE teams keep the troubleshooting process efficient, especially in complex, interdependent service ecosystems Practical Application: Using APM Dashboards Application Performance Management (APM) dashboards integrate Golden Signals into a single view, allowing teams to monitor all critical metrics at once. For example, the operations team can use APM dashboards to get insights into latency, errors, traffic, and saturation. This holistic view simplifies troubleshooting and reduces the mean time to resolution (MTTR). Here's how they work together: ▪️Centralized Monitoring with APM Dashboards:APM tools provide dashboards that centralize the key Golden Signals—latency, errors, traffic, and saturation. This centralized view allows operations and development teams to monitor the health of their applications in real-time. By displaying these critical metrics in one place, APM tools simplify the identification of performance issues, making it easier to spot trends and anomalies that need attention. ▪️"One Hop" Dependency Views:APM tools often support a "one hop" dependency view, which shows only the immediate downstream services connected to a problematic service. This feature is particularly useful in complex microservice environments where pinpointing the root cause of an issue can be daunting. By focusing on immediate dependencies, teams can quickly assess which services are functioning within normal parameters and which are experiencing issues, thereby speeding up the troubleshooting process. ▪️Proactive Issue Detection and Resolution:Integrating Golden Signals into APM tools allows for proactive monitoring, where issues can be identified before they escalate into more serious problems. For example, if a service’s saturation levels begin trending upwards, the APM tool can alert the team before users experience degraded performance. This proactive approach helps reduce the mean time to resolution (MTTR) and improves overall service reliability. ▪️ Customization for Different Teams:The video also mentions that APM tools can be customized for different stakeholders within the organization. While the operations team may focus on all four Golden Signals, development teams might create specialized dashboards that prioritize the signals most relevant to their services. This tailored approach ensures that both dev and ops teams are aligned and can address issues quickly, often even before they impact the end-users. In essence, the integration of SRE Golden Signals with APM tools empowers teams to maintain high levels of service performance and reliability by providing clear, actionable insights into the most critical aspects of their systems. What is the significance of distinguishing 500 vs. 400 errors in SRE monitoring? The distinction between 500 and 400 errors in SRE monitoring is crucial because it impacts how issues are prioritized and addressed. Here’s a breakdown: 500 Errors (Server Errors) These indicate serious problems on the server side, such as downtime or crashes. They require immediate attention because they prevent users from accessing the service entirely, often resulting in significant disruptions. For instance, a 500 error signals that something is failing within the server's infrastructure, meaning end-users can’t receive a response at all. Therefore, these errors are more critical in incident response and may trigger alerts for the SRE team. 400 Errors (Client Errors) These typically indicate client-side issues, where a request is invalid or needs adjustment, like when the requested resource doesn’t exist or is restricted. Such errors might be resolved simply by retrying or by the client correcting the request, so they’re usually less urgent. Monitoring 400 errors can still reveal trends or user behavior that may require attention, but they don't indicate systemic issues. In summary, recognizing the difference allows SREs to prioritize resources on issues that directly affect the system’s reliability and availability (like 500 errors) versus issues that may just need minor adjustments or retries. Conclusion Ready to take your system's reliability and performance to the next level? Gart Solutions offers top-tier SRE Monitoring services to ensure your systems are always running smoothly and efficiently. Our experts can help you identify and address potential issues before they impact your business, ensuring minimal downtime and optimal performance. Discover how Gart Solutions can enhance your system's reliability today! Learn from our IT Monitoring case studies (Monitoring Solution for a B2C SaaS Music Platform and Advanced Monitoring for Digital Landfill Management) to learn more about our SRE Monitoring expertise. https://youtu.be/BqPXUxhshTM?si=EWFFu0JNYgJCj7g0

Compliance

Digital Transformation

Compliance Monitoring: Ensuring Businesses Stay on the Right Side of the Rules

Fedir Kompaniiets

August 29, 2024

Compliance monitoring is the ongoing process of checking that an organization is following all the rules, regulations, and standards that apply to its operations. In simple terms, it's about making sure a company is "playing by the rules" set by governments, industry bodies, or its own policies This practice is critical in several industries, including: Healthcare Finance and banking Pharmaceuticals Energy and utilities Food and beverage manufacturing Environmental services Compliance monitoring helps ensure that an organization follows laws and rules. It helps avoid legal problems and fines, and it builds the organization's reputation and trust with clients and partners. Key Components of Compliance Monitoring Effective compliance monitoring involves several important parts working together. At its core, there's a clear set of rules or standards that a company needs to follow. These could be laws, industry regulations, or even the company's own policies. Visit our compliance audits page to explore different compliance frameworks and regulations in detail. Next comes the crucial step of actually checking compliance. This involves regularly examining the company's activities and comparing them against established rules and regulations. It's essentially a health check-up for the business, ensuring everything is running according to plan. For companies looking to streamline this process, Gart Solutions offers specialized services to help assess regulatory compliance. Our expertise can be particularly valuable in navigating complex regulatory landscapes, providing businesses with peace of mind that they're meeting all necessary standards and requirements. Read more: Gart’s Expertise in ISO 27001 Compliance Empowers Spiral Technology for Seamless Audits and Cloud Migration Good record-keeping is another crucial piece. Companies need to keep detailed notes about what they're doing and how they're following the rules. This helps prove they're on track if anyone asks. There's also the tech side of things. Many companies use special software to help track and manage their compliance efforts. This can make the whole process smoother and more accurate. Read more about RMF (Resource Management Framework) a unified system for monitoring digital solutions for landfills that we developed for our client. Lastly, there's the response plan. This is what the company does if they find they're not following a rule. It might involve fixing the problem, reporting it to the right people, or changing how things are done to prevent it from happening again. Risk Assessment: Finding out where things might go wrong Policies and Procedures: Writing down clear rules for everyone to follow Training: Teaching employees about the rules and why they matter Regular Checks: Looking at work often to make sure rules are being followed Reporting: Keeping track of how well the company is following rules Technology: Using computers and software to help monitor things Updating: Changing the monitoring system when new rules come out Response Plan: Knowing what to do if a rule is broken Documentation: Keeping good records of all compliance activities Leadership Support: Making sure bosses take compliance seriously All these parts work together to create a strong compliance monitoring system, helping companies stay on the right side of the rules and avoid potential problems. Types of Compliance Monitoring Compliance monitoring comes in various forms, each serving a specific purpose in ensuring an organization adheres to relevant rules and regulations. One common type is regulatory compliance monitoring. This focuses on making sure a company follows laws and regulations set by government agencies. For example, a bank might monitor its practices to ensure it complies with anti-money laundering laws. Internal compliance monitoring is another important type. Here, companies check if their employees are following internal policies and procedures. This could involve reviewing expense reports to ensure they match company guidelines, or checking that proper safety protocols are being followed in a manufacturing plant. Industry-specific compliance monitoring is crucial for businesses operating in highly regulated sectors. For instance, healthcare providers must monitor their practices to ensure patient data privacy, while food manufacturers need to check that their production processes meet food safety standards. Environmental compliance monitoring has become increasingly important. Companies, especially those in manufacturing or energy sectors, must track their environmental impact to ensure they're meeting pollution control regulations. Financial compliance monitoring is critical for publicly traded companies. This involves ensuring accurate financial reporting and adhering to accounting standards to maintain investor trust and meet stock exchange requirements. Lastly, there's technology compliance monitoring. With the rise of data protection laws, companies must monitor how they collect, use, and store digital information to protect consumer privacy and prevent data breaches. Each type of compliance monitoring plays a vital role in helping organizations navigate the complex landscape of rules and regulations they face in today's business world. Challenges in Compliance Monitoring One of the biggest challenges is dealing with complex and ever-changing regulations. Laws and industry standards are often intricate, with many details to track. What's more, these rules frequently change, sometimes without much warning. This means companies must constantly update their knowledge and practices to stay compliant. Another major concern is balancing compliance with data privacy and security. In today's digital age, many compliance efforts involve handling sensitive information. Companies need to find ways to monitor and report on their activities without putting private data at risk. This can be especially tricky when dealing with customer information or confidential business data. Resource limitations also pose a significant challenge. Effective compliance monitoring often requires dedicated staff, sophisticated software, and ongoing training. For many businesses, especially smaller ones, finding the budget and personnel for these efforts can be difficult. They must find ways to meet regulatory requirements without breaking the bank or stretching their teams too thin. Need a Compliance Audit? Is your business fully aligned with the latest regulations and standards? At Gart Solutions, we specialize in comprehensive compliance monitoring to keep you on the right side of the rules. Our expert team offers tailored audits and monitoring services across various industries, including healthcare, finance, pharmaceuticals, and more. Ensure your business stays compliant and protected — contact Gart Solutions for a customized compliance audit today!

DevOps

Monitoring DevOps: Types, Practices, and Tools

Fedir Kompaniiets

July 8, 2024

Monitoring is one of the most important concepts in DevOps. It is a fundamental aspect that goes beyond just graphs showing the state of your product. Monitoring is a general term for collecting data about the behavior of a digital solution (platforms, infrastructure, applications). DevOps monitoring involves overseeing the entire development lifecycle, ensuring data protection, and quickly responding to and resolving errors. It encompasses various levels such as cloud services monitoring, infrastructure monitoring, abstraction level monitoring (e.g., containers), and application monitoring. Through monitoring, DevOps teams can ensure that their systems operate efficiently, stably, and securely, thereby delivering a high-quality end product. Monitoring in DevOps is like the dashboard of a plane; a cloud architect needs a clear view of every system's performance and potential issues. Just as a pilot relies on instruments to navigate safely, we rely on continuous monitoring to ensure smooth and efficient operations in the cloud. Roman Burdiuzha, Cloud Architect | Specializing in DevOps & Cloud Solutions Why Monitoring is Complex? Monitoring is the interpretation of information about your digital solution in the form you desire. The possibilities are limitless. This variability makes it a rather complex task. Determining what to monitor, what truly matters for the project, requires DevOps engineers to: Identify what to monitor, Determine what to display, Define how to execute these tasks. The most critical question is not how to monitor, but what to monitor. Types of Monitoring At each level, a system has its own set of metrics. For instance, at the cloud level such as AWS, there are metrics for account status, organizational structure—user counts, service instances, virtual machines, policies, and IP addresses—all meticulously recorded. Each service incurs charges, necessitating expense monitoring. Moving down a level to infrastructure—virtual machines, for example—they have processors, memory, disk usage, etc. This information is logged—how much memory is used, processor load, and network traffic. For instance, a network adapter might handle 1 gigabit per second, and its interface load is measured accordingly. Next is the abstraction level. Take Docker, where multiple instances of an operating system are launched to run a specific app. Docker provides virtual metrics for memory, CPU usage, and more. Then there's the application level. Consider an application running on Java. In Java, there's a Java Virtual Machine (JVM) that processes code. The JVM has its metrics—allocated memory, actual memory usage, worker threads, and so forth. There are also custom-based metrics; for example, an application might track errors occurring and log their frequency per second. In essence, monitoring involves tracking the state of a solution across these levels to ensure optimal performance, efficiency, and reliability. Cloud Level Monitoring ( AWS, Azure, Google Cloud, other) Observes and manages the performance, availability, and health of cloud resources and services provided by cloud platforms like AWS, Azure, and Google Cloud. Infrastructure Level Monitoring Server Monitoring Network Monitoring Database Monitoring Storage Monitoring Tracks the performance, availability, and health of physical and virtual infrastructure components, including servers, networks, databases, and storage systems. Abstraction Level Monitoring Monitors the performance and health of abstraction layers such as containers (e.g., Docker) and orchestration systems (e.g., Kubernetes), as well as virtual machines. Container Monitoring (e.g., Docker) Orchestration Monitoring (e.g., Kubernetes) Virtual Machine Monitoring Application Level Monitoring Focuses on tracking the performance, availability, and user interactions of applications, providing insights into response times, error rates, and transaction flows. Application Performance Monitoring (APM) Transaction Tracing User Experience Monitoring Three Pillars of Monitoring Logs - Logs record events with timestamps, creating a chronology of processes occurring within the system. Metrics - Metrics demonstrate resource usage levels or behaviors that can be collected in systems. Traces - Traces illustrate the journey of a user through the entire application stack. Best Practices for Log Collection Ensure maximum standardization of logs. Avoid collecting confidential information to prevent data leaks. Configure real-time alerts. Optimize your log retention policy. Monitoring Tools Grafana and Prometheus are among the most widely used, free, and open-source solutions. These tools together create a solid foundation for a robust and reliable monitoring stack, ensuring high-quality analysis. Grafana: This powerful visualization tool displays data from various sources in customizable dashboards, making it easier to understand and act on complex metrics. Prometheus: A leading open-source monitoring and alerting toolkit, known for its reliability and scalability in gathering and querying metrics. Grafana Loki: A log aggregation system that integrates smoothly with Grafana, allowing for comprehensive log management and analysis. Other notable tools in the monitoring ecosystem include: Datadog: A comprehensive monitoring and analytics platform that provides visibility into your entire tech stack, from infrastructure to applications. New Relic: An observability platform that offers detailed insights into application performance, helping to quickly identify and resolve issues. The key to effective monitoring is not just in the tools used but in determining what to monitor. Identifying the critical metrics that matter most to your project is essential. This approach ensures that you are not overwhelmed with data but are focused on the information that will help you maintain and improve your systems' performance and reliability. By leveraging these tools and practices, you can create a monitoring setup that provides actionable insights, helping you to quickly respond to issues, optimize performance, and ensure the overall health of your digital solutions.Take a look at these Monitoring projects in the portfolio of Gart Solutions. Centralized Monitoring for a B2C SaaS Music Platform:We introduced a real-time monitoring framework for both infrastructure and applications by leveraging AWS CloudWatch and Grafana for a globally distributed music platform. This approach enabled seamless, region-wide scalability, improved system transparency, and reduced operational interruptions. The result was a cost-efficient, intuitive monitoring system designed to support the platform’s continuous growth and expansion efforts. To the case. Monitoring Solutions for Scaling a Digital Landfill Platform: for the elandfill.io platform, we engineered a robust monitoring system that was successfully scaled across several nations, including Iceland, France, Sweden, and Turkey. This solution enhanced the accuracy of methane emission forecasting, improved landfill management practices, and simplified adherence to regulatory standards. The cloud-agnostic architecture offered the client flexibility in selecting their preferred cloud service provider, ensuring adaptability and freedom of choice. To the case.

Key Challenges in Application Monitoring

Types of Application Monitoring

Infrastructure Monitoring

Application Performance Monitoring (APM)

User Experience Monitoring

Log and Event Monitoring

Synthetic Monitoring

Real-User Monitoring (RUM)

Key Metrics for Application Monitoring

Performance Metrics

Availability Metrics

User Experience Metrics

Business Metrics

Tools for Application Monitoring

Application Performance Monitoring (APM) Tools

Open-Source Monitoring Tools

Log Management Tools

Best Practices in Application Monitoring

Set Realistic Thresholds and Baselines

Automate Monitoring and Alerting Workflows

Leverage AI/ML for Anomaly Detection and Predictive Analysis

Implement Continuous Monitoring in the CI/CD Pipeline

Balance Between Too Many Alerts and Meaningful Signals

Monitor Across Different Environments

Optimize Your Application Performance with Expert Monitoring

FAQ

What is application monitoring?

What are the key metrics to monitor in an application?

How do I get started with application monitoring?

You might also like

SRE Monitoring: Golden Signals as a Key Metrics for System Reliability

Compliance Monitoring: Ensuring Businesses Stay on the Right Side of the Rules

Monitoring DevOps: Types, Practices, and Tools

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