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A Beginner's Guide To Prometheus APM

When it comes to monitoring applications, ensuring their optimal performance is key. Picture this: you've launched a new app that's gaining traction. User complaints about slow response times are flooding in, causing a spike in bounce rates. Consider how a reliable Application Performance Monitoring (APM) solution like Prometheus could help you promptly identify and address these issues. This blog shows Prometheus APM can significantly impact your app's performance.

Alerty's free APM solution presents a valuable learning opportunity about Prometheus monitoring. Its user-friendly interface and robust functionalities let you monitor performance seamlessly. Ready to optimize your application's performance with insightful data? Let's explore more.

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Table of Contents

What Is Prometheus?

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Prometheus is an open-source system monitoring and alerting toolkit created at SoundCloud in 2012. Over the years, it has been adopted by numerous companies and organizations, boasting a vibrant and engaged developer and user community. 

Independent Foundation

Prometheus operates as a standalone open-source project free from the influence of any one corporation. In 2016, to illustrate its independence and governance structure, the project aligned with the Cloud Native Computing Foundation, becoming the second hosted project after Kubernetes. 

Time Series Data

This open-source toolkit excels at collecting and storing metrics as time series data, where information is recorded with corresponding timestamps and optional key-value pairs known as labels.

Open Source Success

The software's repository on GitHub, which showcases ongoing development and community engagement, is a testament to its widespread adoption and success.

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10 Best Features Of Prometheus

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Prometheus is a powerful open-source monitoring and alerting toolkit for reliability and scalability. Here’s an overview of its key features:

1. Multi-Dimensional Data Model

Prometheus uses a multidimensional data model in which time series data is identified by a metric name and a set of key-value pairs (labels). This allows for flexible and detailed querying.

2. Powerful Query Language (PromQL)

Prometheus Query Language (PromQL) is a flexible query language that allows users to extract and aggregate time series data in various ways. It:

  • Supports complex queries
  • Can generate detailed visualizations

3. Data Collection

Prometheus pulls metrics from configured endpoints at specified intervals. Unlike many other systems, it uses a pull model:

  • Simplifying data collection 
  • Reducing the need for agents on each monitored system

4. Built-in Storage

Prometheus includes its own time-series database optimized for storing and querying time-series data. This storage is designed to be:

  • Efficient 
  • Scalable

5. High Availability and Fault Tolerance

Prometheus supports high availability by enabling federation, which allows multiple Prometheus servers to work together. This setup helps in achieving the following:

6. Alerting and Notifications

Prometheus integrates with Alertmanager to handle alerts and notifications. Users can set up complex alerting rules based on PromQL queries and receive notifications via various channels like: 

  • Email
  • Slack
  • PagerDuty)

7. Service Discovery

 Prometheus can automatically discover services and instances through various service discovery mechanisms. These include integration with cloud providers and container orchestration systems like Kubernetes.

8. Visualization

Prometheus is often used with other tools, like Grafana (an open-source analytics and monitoring platform). Grafana allows users to create visually appealing dashboards and reports based on the data collected by Prometheus.

Prometheus integrates seamlessly with Kubernetes, making it a preferred choice for monitoring containerized environments.

9. Scraping and Exporters

Prometheus supports scraping metrics from a wide variety of sources through exporters. Many pre-built exporters are available for popular applications and systems.

10. Data Retention and Aggregation

Prometheus allows users to configure data retention policies and perform aggregation on time-series data, helping to:

  • Manage storage 
  • Focus on relevant metrics

Alerty’s Core Features

Alerty is a cloud monitoring service for developers and early-stage startups, offering:

  • Application performance monitoring
  • Database monitoring
  • Incident management

Tech Support

It supports technologies like:

  • NextJS
  • React
  • Vue
  • Node.js

Database Focus

These technologies help developers identify and fix issues. Alerty monitors databases such as:

  • Supabase
  • PostgreSQL
  • RDS

Key Metrics

Alerty also tracks key metrics like:

  • CPU usage
  • Memory consumption

Incident & UX

It features quick incident management and Real User Monitoring (RUM) to optimize user experience. Its Universal Service Monitoring covers dependencies like:

  • Stripe API
  • OpenAI
  • Vercel

AI & Value

Alerty uses AI to simplify setup, providing a cost-effective solution compared to competitors. It is designed for ease of use, allowing quick setup, and integrates with tools like Sentry, making it ideal for developers and small teams needing efficient, affordable monitoring.

Catch issues before they affect your users with Alerty's free APM solution today!

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How Does Prometheus Work?

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Prometheus, an open-source monitoring and alerting toolkit originally built at SoundCloud, has gained widespread popularity in DevOps.

This tool's unique architecture sets it apart in application performance monitoring.

Prometheus follows a pull-based model to collect and store metrics, making it indispensable for organizations that must monitor their applications effectively.

Data Collection and Retrieval

Prometheus supports a pull-based model that periodically scrapes data from the targets: the applications, services, or infrastructure components instrumented with Prometheus client libraries.

Data Collection Targets

By exposing metrics and endpoints, these targets allow Prometheus to pull and gather the correct information. This mechanism ensures that Prometheus collects data efficiently, ensuring that many elements of your infrastructure are accurately monitored.

Data Storage

Prometheus's data is stored in a time-series database, providing a historical record of system performance over time.

Data Storage Model

The multidimensional model used in this database enables Prometheus to store data in a way that is easy to query and access. 

Performance Analysis

This feature is crucial for organizations that must analyze performance data over time and compare it with current metrics.

Service Discovery

Traditionally, service discovery is a significant challenge in application monitoring. Prometheus effectively addresses this issue through discovery mechanisms that automatically detect new instances in your infrastructure and ensure they are promptly monitored. 

Dynamic Monitoring

This feature is vital for organizations with dynamic environments, ensuring that monitoring remains up-to-date without manual intervention. 

Unique Approach

Prometheus' unique approach to monitoring and alerting makes it a standout tool in the application performance monitoring space. 

Effortless Monitoring

This tool provides organizations a valuable way to monitor their applications without significant manual effort, enabling them to scale their monitoring activities effectively. 

User Satisfaction

With Prometheus, you can ensure that your applications run smoothly and that performance issues are detected early, keeping your users always satisfied.

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What Is PromQL?

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PromQL, short for Prometheus Query Language, is a functional tool for selecting and aggregating time series data. 

Powerful Language

It is a highly flexible and powerful language that enables you to manipulate your data as needed.

Versatile Queries

PromQL is incredibly versatile and can be used in various cases. You can use instant vectors to query data from a single point in time or use range vectors to query data over a specified time range. 

Metric Filtering

Furthermore, you can query basic metrics like `http_requests_total` and filter your metrics further through key-value pairs with regular expression matches.

Invaluable Tool

For users operating within the Prometheus APM, PromQL is an invaluable tool for accessing and analyzing time series data. 

Data Insights

By leveraging PromQL, users can gain deep insights into system performance and identify potential areas for optimization and enhancement. 

Data-Driven Decisions

PromQL truly shines in enabling users to make data-driven decisions based on real-time analysis:

  • Streamlining operational efficiency
  • Ensuring optimal system performance

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What Is Prometheus Monitoring And What Can You Monitor?

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Frontend Monitoring with Prometheus

Frontend monitoring is crucial for tracking application performance metrics and ensuring a seamless user experience. 

Performance Monitoring

Prometheus allows users to effectively monitor metrics such as throughput (TPS) and response times. It provides the black box exporter feature to enable uptime checks and accurate monitoring of website statuses. This capability:

  • Allows for comprehensive tracking of frontend performance indicators 
  • Ensures optimal user experience behavior

Backend Monitoring with Prometheus

Monitoring applications' backend infrastructure ensures smooth operations and identifies potential bottlenecks. Prometheus offers the ability to monitor effectively:

  • Databases
  • APIs
  • HTTP request statuses 

API Monitoring

Users can track REST API metrics such as:

  • Request latency
  • Log events
  • Error rates to ensure optimal backend performance

JVM Monitoring

Prometheus's JMX Exporter enables users to monitor JVM-based applications accurately. This feature:

  • Enhances overall backend monitoring capabilities 
  • Enables detailed tracking of key performance metrics

Server Monitoring with Prometheus

Monitoring server performance is essential to ensure optimal resource utilization and avoid potential failures. 

Server Metrics

With Prometheus, users can accurately track server performance indicators like average response time. Additionally, users can easily monitor operating system metrics such as CPU utilization and disk usage. 

Apache Monitoring

The Apache Prometheus exporter feature provided by Prometheus enables detailed monitoring of Apache web servers, ensuring comprehensive tracking of server performance metrics.

Hardware Monitoring with Prometheus

Monitoring hardware performance metrics is crucial to ensure optimal resource utilization and avoid potential hardware failures.

Prometheus offers the Node Exporter feature to effectively track hardware and kernel metrics on Linux and Unix systems. 

Hardware Monitoring

This capability includes accurately tracking:

  • CPU usage
  • Disk utilization
  • Network bandwidth
  • Memory metrics

Hardware Health

With Prometheus, users can ensure the seamless performance of hardware components and identify potential performance issues promptly.

Infrastructure Monitoring with Prometheus

Monitoring various levels of infrastructure is essential for ensuring overall system performance and identifying potential bottlenecks. 

Comprehensive Monitoring

Prometheus enables users to monitor hosts, applications, and containers effectively. For instance, users can use the Prometheus MySQL exporter to track MySQL performance accurately. 

Kafka Monitoring

Monitoring Kafka load generators and consumers with Prometheus allows users to assess throughput and response times efficiently. 

Performance Optimization

This capability enables users to proactively:

  • Ensure optimal infrastructure performance 
  • Identify potential performance issues

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When is Prometheus the Right Fit?

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Prometheus is ideal for recording any purely numeric time series and is a great choice for both machine-centric monitoring and monitoring highly dynamic service-oriented architectures. 

Microservices Support

Its support for multidimensional data collection and querying makes it particularly beneficial in today's world of microservices.

High Reliability

One of Prometheus's standout features is its reliability. It is designed to be the go-to system during an outage, allowing users to diagnose problems quickly.

Each Prometheus server operates independently, without relying on network storage or other remote services.

Self-Sufficient Operation

This self-sufficiency ensures that you can depend on Prometheus even when other parts of your infrastructure are experiencing issues, and you don't need to set up extensive infrastructure to use it. 

​​Complex Environments

Prometheus is a powerful tool well-suited for monitoring and troubleshooting in complex environments. Its ability to handle multidimensional data and operate independently gives it an edge in ensuring system reliability and performance. 

Ideal Monitoring Tool

If you're looking for a monitoring solution that can effectively handle diverse time series data and provide critical insights during outages, Prometheus is an excellent choice.

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Why Not Prometheus?

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Although a powerful and widely used tool in the world of Application Performance Monitoring (APM), Prometheus comes with its limitations.

One major downside is that Prometheus cannot be used as a metric system to store event logs or events. It is not suitable for high-cardinal data like email addresses or usernames. 

Precision Limitation

This drawback makes it less than ideal for monitoring systems, such as financial applications, where impeccable precision is paramount.

Scaling Challenges

Prometheus may encounter difficulties as we scale up our systems in this era of highly distributed modern environments. 

Aggregation Complexity

Aggregating metrics from numerous instances is not straightforward for Prometheus, and solving this problem can result in additional complexity and engineering effort. 

Management Impact

This can impact Prometheus's effectiveness as a management tool, which is crucial for efficient incident response.

Data Retention Issue

Another limitation of Prometheus is its inability to store metrics data for an extended period. Historical data can provide valuable insights into system utilization and performance trends for organizations managing complex ecosystems. 

Long-Term Analysis

This long-term data analysis can help identify patterns and scale solutions when systems are pushed to their limits.

Tool Integration

While Prometheus may have these limitations when used in isolation, integrating it with other tools like Grafana for visualization and Alerty for a comprehensive view of application health and performance can help address these shortcomings. 

Comprehensive Solution

By combining Prometheus with complementary tools, organizations can leverage their strengths while mitigating weaknesses to achieve a more robust APM solution.

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Best Practices For Prometheus Monitoring

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Understand Metrics and When to Use Them

Prometheus has four metric types that are essential for accurate monitoring. The counter metric type measures the quantity at the start of an event or counts several events. 

Gauge Metrics

Gauges measure positive and negative changes over time, making them particularly useful for tracking metrics like memory use or temperature. 

Histogram & Summary

Histograms help aggregate data by sampling and categorizing events with a sum of collected values. At the same time, summaries can be calculated using total event counts and sums of observed values over time.

Choose the Best Exporter

Exporters are essential tools for retrieving metrics from systems that Prometheus cannot easily scrape. Choosing the most relevant exporter for your needs is crucial for the success of your monitoring strategy.

By assessing exporters based on user reviews, recent updates, and security advisories, you can confidently select the one that best fits your requirements.

Label Carefully

Labeling your metrics is crucial to providing context and understanding your monitoring data effectively.

Consistent labeling across different monitoring targets is vital, but each label consumes resources. To avoid unnecessary resource costs, restrict your label use to around ten.

Set Actionable Alerts

Well-defined alerting strategies are vital for effective performance monitoring. You can proactively catch issues before they escalate by setting reasonable thresholds on critical metrics and events. 

Properly configured notifications that reach the right teams on time further enhance the security of your monitoring practices.

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Catch Issues Before They Affect Your Users with Alerty's Free APM Solution

Alerty is a cloud monitoring service designed for developers and early-stage startups. It offers a comprehensive suite of monitoring solutions, including application performance monitoring, database monitoring, and incident management.

Tech Compatibility

Alerty supports a range of popular technologies, such as:

  • NextJS
  • React
  • Vue
  • Node.js

These technologies make it versatile for various development environments. 

Database Monitoring and Incident Management: Keeping Your Systems Healthy

Alerty excels in monitoring databases such as:

  • Supabase
  • PostgreSQL
  • RDS

Alerty also tracks vital metrics like:

  • CPU usage
  • Memory consumption

By closely monitoring these key indicators, Alerty helps developers proactively identify and address potential issues before they impact users. The service also offers quick incident management, allowing developers to respond swiftly to any critical situations that may arise.

Real User Monitoring (RUM) for Enhanced User Experience

One highlight of Alerty is its Real User Monitoring (RUM) feature, which allows developers to gain insights into user behavior and optimize the user experience.

Developers can make informed adjustments to enhance performance and usability by closely monitoring user interactions with applications.

Universal Service Monitoring: Covering All Bases

Alerty’s Universal Service Monitoring covers many dependencies, including popular services like:

  • Stripe API
  • OpenAI
  • Vercel

By monitoring these dependencies, developers can ensure that all aspects of their applications are healthy and functioning optimally.

AI-Powered Simplified Setup: Making Monitoring Effortless

Alerty leverages artificial intelligence to simplify setup and configuration, making it easy for developers to start monitoring their applications quickly.

This streamlined approach saves time and ensures that developers can start benefiting from Alerty's monitoring capabilities without delay.

Integration with Tools like Sentry: Seamless and Efficient Monitoring

Alerty seamlessly integrates with tools like Sentry, providing developers with a comprehensive monitoring solution that covers a wide range of aspects.

This integration makes it easy for developers to consolidate their monitoring efforts and efficiently manage their applications.

Efficient and Affordable Monitoring for Small Teams: Empowering Developers

Alerty is designed to be cost-effective, offering a solution accessible to developers and small teams. By providing efficient monitoring capabilities at an affordable price point, Alerty empowers developers to manage their applications and proactively ensure a seamless user experience.

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