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Observability Pillars: Exploring Logs, Metrics and Traces

Observability Pillars: Exploring Logs, Metrics and Traces

September 29, 2023
Observability Pillars: Exploring Logs, Metrics and Traces
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The ability to measure the internal states of a system by examining its outputs is called Observability. A system becomes 'observable' when it is possible to estimate the current state using only information from outputs, namely sensor data. You can use the data from Observability to identify and troubleshoot problems, optimize performance, and improve security.

In the next few sections, we'll take a closer look at the three pillars of Observability: Metrics, Logs, and Traces.

What is the difference between Observability & Monitoring?

‘Observability wouldn’t be possible without monitoring.’ 

Monitoring is another term that closely relates to observability. The major difference between Monitoring and Observability is that the latter refers to the ability to gain insights into the internal workings of a system, while the former refers to the act of collecting data on system performance and behavior.

What is monitoring

In addition to that, Monitoring doesn't really think about the end goal. It focuses on predefined metrics and thresholds to detect deviations from expected behavior. Observability aims to provide a deep understanding of system behavior, allowing exploration and discovery of unexpected issues.

In terms of perspective & mindset, Monitoring adopts a "top-down" approach with predefined alerts based on known criteria. Whereas, Observability takes a "bottom-up" approach, encouraging open-ended exploration and adaptability to changing requirements.

Observability Monitoring
Tells you why a system is at fault. Notifies that you have a system at fault.
Acts as a knowledge base to define what needs monitoring. Focuses only on monitoring systems and detecting faults across them.
Focuses on giving context to data. Data collection focused.
Give a more complete assessment of the overall environment. Keeping track of monitoring KPIs.
Observability is a traversable map. Monitoring is a single plane.
It gives you complete information. It gives you limited information.
Observability creates the potential to monitor different events. Monitoring is the process of using Observability.

Monitoring detects anomalies and alerts you to potential problems. However, Observability not only detects issues but also helps you to understand their root causes and underlying dynamics.

👀 Cover more on this article: O11y (Observability): Tutorial, Best Practices & Examples

3 pillars of Observability 

Observability, built on the Three Pillars (Metrics, Logs, Traces), revolves around the core concept of "Events." Events are the fundamental units of monitoring and telemetry, each time stamped and quantifiable. What distinguishes events is their context, especially in user interactions. For example, when a user clicks "Pay Now" on an eCommerce site, this action is an event, expected within seconds.

In monitoring tools, "Significant Events" are key. They trigger:

  1. Automated Alerts: Notifying SREs or operations teams.
  2. Diagnostic Tools: Enabling root-cause analysis.

Imagine a server's disk nearing 99% capacity; it's significant, but understanding which applications and users cause this is vital for effective action.

Metrics

Metrics serve as numeric indicators, offering insights into a system's health. While some metrics like CPU, memory, and disk usage are obvious system health indicators, numerous other critical metrics can uncover underlying issues. For instance, a gradual increase in OS handles can lead to a system slowdown, eventually necessitating a reboot for accessibility. Similar valuable metrics exist throughout the various layers of the modern IT infrastructure.

Careful consideration is crucial when determining which metrics to continuously collect and how to analyze them effectively. This is where domain expertise plays a pivotal role. While most monitoring tools can detect evident issues, the best ones go further by providing insights into detecting and alerting complex problems. It's also essential to identify the subset of metrics that serve as proactive indicators of impending system problems. For instance, an OS handle leak rarely occurs abruptly. 

Tracking the gradual increase in the number of handles in use over time makes it possible to predict when the system might become unresponsive, allowing for proactive intervention.

Advantages of Metrics Challenges of Metrics
  • Quantitative and intuitive for setting alert thresholds
  • Lightweight and cost-effective for storage
  • Excellent for tracking trends and system changes
  • Provides real-time component state data
  • Constant overhead cost; not affected by data surges
  • Limited insight into the "why" behind issues
  • Lack context of individual interactions or events
  • Risk of data loss in case of collection/storage failure
  • Fixed interval collection may miss critical details
  • Excessive sampling can impact performance and costs
  • Read More: Integrate APImetrics with Squadcast to streamline alert routing.

    Logs  

    Logs frequently contain intricate details about how an application processes requests. Unusual occurrences, such as exceptions, within these logs can signal potential issues within the application. It's a vital aspect of any observability solution to monitor these errors and exceptions in logs. Parsing logs can also reveal valuable insights into the application's performance.

    Logs often hold insights that may remain elusive when using APIs (Application Programming Interfaces) or querying application databases. Many Independent Software Vendors (ISVs) don't offer alternative methods to access the data available in logs. Therefore, an effective observability solution should enable log analysis and facilitate the capture of log data and its correlation with metric and trace data.

    Advantages of Logs Challenges of Logs
  • Easy to generate, typically timestamp + plain text
  • Often require minimal integration by developers
  • Most platforms offer standardized logging frameworks
  • Human-readable, making them accessible
  • Provide granular insights for retrospective analysis
  • Can generate large data volumes, leading to costs
  • Impact on application performance, especially without asynchronous logging
  • Retrospective use, not proactive
  • Persistence challenges in modern architectures
  • Risk of log loss in containers and auto-scaling environments
  • Do you know the tool combination for centralized logging, log analysis, and real-time data visualization? Read our blog on ELK Stack for introduction.

    Traces

    Tracing is a relatively recent development, especially suited to the complex nature of contemporary applications.  It works by collecting information from different parts of the application and putting it together to show how a request moves through the system.

    Traces as a function of span
    A trace represented as spans: span A is the root span, span B is a child of span A. Source.

    The primary advantage of tracing lies in its ability to deconstruct end-to-end latency and attribute it to specific tiers or components. While it can't tell you exactly why there's a problem, it's great for figuring out where to look.

    Advantages of Traces Challenges of Traces
  • Ideal for pinpointing issues within a service
  • Offers end-to-end visibility across multiple services
  • Identifies performance bottlenecks effectively
  • Aids debugging by recording request/response flows
  • Provides contextual insights into system behavior
  • Limited ability to reveal long-term trends
  • Complex systems may yield diverse trace paths
  • Doesn't explain the cause of slow or failing spans (steps)
  • Adds overhead, potentially impacting system performance
  • Integrating tracing used to be difficult, but with service meshes, it's now effortless. Service meshes handle tracing and stats collection at the proxy level, providing seamless observability across the entire mesh without requiring extra instrumentation from applications within it.

    Each above discussed component has its pros & cons even though one might want to use them all. 🧑‍💻

    Observability Tools

    Observability tools in devops gather and analyze data related to user experience, infrastructure, and network telemetry to proactively address potential issues, preventing any negative impact on critical business key performance indicators (KPIs).

    Observability Survey Report 2023 - key findings
    Observability Survey Report 2023 - key findings

    Some popular observability tooling options include:

    1. Prometheus: A leading open-source monitoring and alerting toolkit known for its scalability and support for multi-dimensional data collection.
    2. Grafana: A visualization and dashboarding platform often used with Prometheus, providing rich insights into system performance.
    3. Jaeger: An open-source distributed tracing system for monitoring and troubleshooting microservices-based architectures.
    4. Elasticsearch: A search and analytics engine that, when paired with Kibana and Beats, forms the ELK Stack for log management and analysis.
    5. Honeycomb: An event-driven observability tool that offers real-time insights into application behavior and performance.
    6. Datadog: A cloud-based observability platform that integrates logs, metrics, and traces, providing end-to-end visibility.
    7. New Relic: Offers application performance monitoring (APM) and infrastructure monitoring solutions to track and optimize application performance.
    8. Sysdig: Focused on container monitoring and security, Sysdig provides deep visibility into containerized applications.
    9. Zipkin: An open-source distributed tracing system for monitoring request flows and identifying latency bottlenecks.
    10. Squadcast: An incident management platform that integrates with various observability tools, streamlining incident response and resolution.

    Conclusion

    Logs, metrics, and traces are essential Observability pillars that work together to provide a complete view of distributed systems. Incorporating them strategically, such as placing counters and logs at entry and exit points and using traces at decision junctures, enables effective debugging. Correlating these signals enhances our ability to navigate metrics, inspect request flows, and troubleshoot complex issues in distributed systems.

    Observability and Incident Management are also closely related domains. By combining both, you can create a more efficient and effective way to respond to incidents. 

    In essence, Squadcast can help you to minimize the impact of incidents on your business and improve the overall reliability of your systems. Start your free trial of Squadcast incident platform today, which seamlessly integrates with a wide range of observability tools including Honeycomb, Datadog, New Relic, Prometheus, and Grafana. In addition to these integrations, Squadcast also has a public API that you can use to integrate with other tools. This means that you can integrate Squadcast with any observability tool that has an API. Here’s where you can book a Demo today.

    Read more on: Best 19 Observability tools in Devops

    Written By:
    September 29, 2023
    Chitra Bisht
    Chitra Bisht
    September 29, 2023
    Observability
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    Squadcast is a leader in Incident Management on G2 Squadcast is a leader in Mid-Market IT Service Management (ITSM) Tools on G2 Squadcast is a leader in Americas IT Alerting on G2 Best IT Management Products 2024 Squadcast is a leader in Europe IT Alerting on G2 Squadcast is a leader in Enterprise Incident Management on G2 Users love Squadcast on G2
    Squadcast is a leader in Incident Management on G2 Squadcast is a leader in Mid-Market IT Service Management (ITSM) Tools on G2 Squadcast is a leader in Americas IT Alerting on G2
    Best IT Management Products 2024 Squadcast is a leader in Europe IT Alerting on G2 Squadcast is a leader in Enterprise Incident Management on G2
    Users love Squadcast on G2
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    Observability Pillars: Exploring Logs, Metrics and Traces

    Sep 29, 2023
    Last Updated:
    September 13, 2024
    Share this post:
    Observability Pillars: Exploring Logs, Metrics and Traces
    Table of Contents:

      The ability to measure the internal states of a system by examining its outputs is called Observability. A system becomes 'observable' when it is possible to estimate the current state using only information from outputs, namely sensor data. You can use the data from Observability to identify and troubleshoot problems, optimize performance, and improve security.

      In the next few sections, we'll take a closer look at the three pillars of Observability: Metrics, Logs, and Traces.

      What is the difference between Observability & Monitoring?

      ‘Observability wouldn’t be possible without monitoring.’ 

      Monitoring is another term that closely relates to observability. The major difference between Monitoring and Observability is that the latter refers to the ability to gain insights into the internal workings of a system, while the former refers to the act of collecting data on system performance and behavior.

      What is monitoring

      In addition to that, Monitoring doesn't really think about the end goal. It focuses on predefined metrics and thresholds to detect deviations from expected behavior. Observability aims to provide a deep understanding of system behavior, allowing exploration and discovery of unexpected issues.

      In terms of perspective & mindset, Monitoring adopts a "top-down" approach with predefined alerts based on known criteria. Whereas, Observability takes a "bottom-up" approach, encouraging open-ended exploration and adaptability to changing requirements.

      Observability Monitoring
      Tells you why a system is at fault. Notifies that you have a system at fault.
      Acts as a knowledge base to define what needs monitoring. Focuses only on monitoring systems and detecting faults across them.
      Focuses on giving context to data. Data collection focused.
      Give a more complete assessment of the overall environment. Keeping track of monitoring KPIs.
      Observability is a traversable map. Monitoring is a single plane.
      It gives you complete information. It gives you limited information.
      Observability creates the potential to monitor different events. Monitoring is the process of using Observability.

      Monitoring detects anomalies and alerts you to potential problems. However, Observability not only detects issues but also helps you to understand their root causes and underlying dynamics.

      👀 Cover more on this article: O11y (Observability): Tutorial, Best Practices & Examples

      3 pillars of Observability 

      Observability, built on the Three Pillars (Metrics, Logs, Traces), revolves around the core concept of "Events." Events are the fundamental units of monitoring and telemetry, each time stamped and quantifiable. What distinguishes events is their context, especially in user interactions. For example, when a user clicks "Pay Now" on an eCommerce site, this action is an event, expected within seconds.

      In monitoring tools, "Significant Events" are key. They trigger:

      1. Automated Alerts: Notifying SREs or operations teams.
      2. Diagnostic Tools: Enabling root-cause analysis.

      Imagine a server's disk nearing 99% capacity; it's significant, but understanding which applications and users cause this is vital for effective action.

      Metrics

      Metrics serve as numeric indicators, offering insights into a system's health. While some metrics like CPU, memory, and disk usage are obvious system health indicators, numerous other critical metrics can uncover underlying issues. For instance, a gradual increase in OS handles can lead to a system slowdown, eventually necessitating a reboot for accessibility. Similar valuable metrics exist throughout the various layers of the modern IT infrastructure.

      Careful consideration is crucial when determining which metrics to continuously collect and how to analyze them effectively. This is where domain expertise plays a pivotal role. While most monitoring tools can detect evident issues, the best ones go further by providing insights into detecting and alerting complex problems. It's also essential to identify the subset of metrics that serve as proactive indicators of impending system problems. For instance, an OS handle leak rarely occurs abruptly. 

      Tracking the gradual increase in the number of handles in use over time makes it possible to predict when the system might become unresponsive, allowing for proactive intervention.

      Advantages of Metrics Challenges of Metrics
    • Quantitative and intuitive for setting alert thresholds
    • Lightweight and cost-effective for storage
    • Excellent for tracking trends and system changes
    • Provides real-time component state data
    • Constant overhead cost; not affected by data surges
    • Limited insight into the "why" behind issues
    • Lack context of individual interactions or events
    • Risk of data loss in case of collection/storage failure
    • Fixed interval collection may miss critical details
    • Excessive sampling can impact performance and costs
    • Read More: Integrate APImetrics with Squadcast to streamline alert routing.

      Logs  

      Logs frequently contain intricate details about how an application processes requests. Unusual occurrences, such as exceptions, within these logs can signal potential issues within the application. It's a vital aspect of any observability solution to monitor these errors and exceptions in logs. Parsing logs can also reveal valuable insights into the application's performance.

      Logs often hold insights that may remain elusive when using APIs (Application Programming Interfaces) or querying application databases. Many Independent Software Vendors (ISVs) don't offer alternative methods to access the data available in logs. Therefore, an effective observability solution should enable log analysis and facilitate the capture of log data and its correlation with metric and trace data.

      Advantages of Logs Challenges of Logs
    • Easy to generate, typically timestamp + plain text
    • Often require minimal integration by developers
    • Most platforms offer standardized logging frameworks
    • Human-readable, making them accessible
    • Provide granular insights for retrospective analysis
    • Can generate large data volumes, leading to costs
    • Impact on application performance, especially without asynchronous logging
    • Retrospective use, not proactive
    • Persistence challenges in modern architectures
    • Risk of log loss in containers and auto-scaling environments
    • Do you know the tool combination for centralized logging, log analysis, and real-time data visualization? Read our blog on ELK Stack for introduction.

      Traces

      Tracing is a relatively recent development, especially suited to the complex nature of contemporary applications.  It works by collecting information from different parts of the application and putting it together to show how a request moves through the system.

      Traces as a function of span
      A trace represented as spans: span A is the root span, span B is a child of span A. Source.

      The primary advantage of tracing lies in its ability to deconstruct end-to-end latency and attribute it to specific tiers or components. While it can't tell you exactly why there's a problem, it's great for figuring out where to look.

      Advantages of Traces Challenges of Traces
    • Ideal for pinpointing issues within a service
    • Offers end-to-end visibility across multiple services
    • Identifies performance bottlenecks effectively
    • Aids debugging by recording request/response flows
    • Provides contextual insights into system behavior
    • Limited ability to reveal long-term trends
    • Complex systems may yield diverse trace paths
    • Doesn't explain the cause of slow or failing spans (steps)
    • Adds overhead, potentially impacting system performance
    • Integrating tracing used to be difficult, but with service meshes, it's now effortless. Service meshes handle tracing and stats collection at the proxy level, providing seamless observability across the entire mesh without requiring extra instrumentation from applications within it.

      Each above discussed component has its pros & cons even though one might want to use them all. 🧑‍💻

      Observability Tools

      Observability tools in devops gather and analyze data related to user experience, infrastructure, and network telemetry to proactively address potential issues, preventing any negative impact on critical business key performance indicators (KPIs).

      Observability Survey Report 2023 - key findings
      Observability Survey Report 2023 - key findings

      Some popular observability tooling options include:

      1. Prometheus: A leading open-source monitoring and alerting toolkit known for its scalability and support for multi-dimensional data collection.
      2. Grafana: A visualization and dashboarding platform often used with Prometheus, providing rich insights into system performance.
      3. Jaeger: An open-source distributed tracing system for monitoring and troubleshooting microservices-based architectures.
      4. Elasticsearch: A search and analytics engine that, when paired with Kibana and Beats, forms the ELK Stack for log management and analysis.
      5. Honeycomb: An event-driven observability tool that offers real-time insights into application behavior and performance.
      6. Datadog: A cloud-based observability platform that integrates logs, metrics, and traces, providing end-to-end visibility.
      7. New Relic: Offers application performance monitoring (APM) and infrastructure monitoring solutions to track and optimize application performance.
      8. Sysdig: Focused on container monitoring and security, Sysdig provides deep visibility into containerized applications.
      9. Zipkin: An open-source distributed tracing system for monitoring request flows and identifying latency bottlenecks.
      10. Squadcast: An incident management platform that integrates with various observability tools, streamlining incident response and resolution.

      Conclusion

      Logs, metrics, and traces are essential Observability pillars that work together to provide a complete view of distributed systems. Incorporating them strategically, such as placing counters and logs at entry and exit points and using traces at decision junctures, enables effective debugging. Correlating these signals enhances our ability to navigate metrics, inspect request flows, and troubleshoot complex issues in distributed systems.

      Observability and Incident Management are also closely related domains. By combining both, you can create a more efficient and effective way to respond to incidents. 

      In essence, Squadcast can help you to minimize the impact of incidents on your business and improve the overall reliability of your systems. Start your free trial of Squadcast incident platform today, which seamlessly integrates with a wide range of observability tools including Honeycomb, Datadog, New Relic, Prometheus, and Grafana. In addition to these integrations, Squadcast also has a public API that you can use to integrate with other tools. This means that you can integrate Squadcast with any observability tool that has an API. Here’s where you can book a Demo today.

      Read more on: Best 19 Observability tools in Devops

      What you should do now
      • Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
      • Curious about how Squadcast can assist you in implementing SRE best practices? Discover the platform's capabilities through our Interactive Demo.
      • Enjoyed the article? Explore further insights on the best SRE practices.
      • Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
      • Curious about how Squadcast can assist you in implementing SRE best practices? Discover the platform's capabilities through our Interactive Demo.
      • Enjoyed the article? Explore further insights on the best SRE practices.
      • Get a walkthrough of our platform through this Interactive Demo and see how it can solve your specific challenges.
      • See how Charter Leveraged Squadcast to Drive Client Success With Robust Incident Management.
      • Share this blog post with someone you think will find it useful. Share it on Facebook, Twitter, LinkedIn or Reddit
      • Get a walkthrough of our platform through this Interactive Demo and see how it can solve your specific challenges.
      • See how Charter Leveraged Squadcast to Drive Client Success With Robust Incident Management
      • Share this blog post with someone you think will find it useful. Share it on Facebook, Twitter, LinkedIn or Reddit
      • Get a walkthrough of our platform through this Interactive Demo and see how it can solve your specific challenges.
      • See how Charter Leveraged Squadcast to Drive Client Success With Robust Incident Management
      • Share this blog post with someone you think will find it useful. Share it on Facebook, Twitter, LinkedIn or Reddit
      What you should do now?
      Here are 3 ways you can continue your journey to learn more about Unified Incident Management
      Discover the platform's capabilities through our Interactive Demo.
      See how Charter Leveraged Squadcast to Drive Client Success With Robust Incident Management.
      Share the article
      Share this blog post on Facebook, Twitter, Reddit or LinkedIn.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Experience the benefits of Squadcast's Incident Management and On-Call solutions firsthand.
      Compare our plans and find the perfect fit for your business.
      See Redis' Journey to Efficient Incident Management through alert noise reduction With Squadcast.
      Discover the platform's capabilities through our Interactive Demo.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Experience the benefits of Squadcast's Incident Management and On-Call solutions firsthand.
      Compare Squadcast & PagerDuty / Opsgenie
      Compare and see if Squadcast is the right fit for your needs.
      Compare our plans and find the perfect fit for your business.
      Learn how Scoro created a solid foundation for better on-call practices with Squadcast.
      Discover the platform's capabilities through our Interactive Demo.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Experience the benefits of Squadcast's Incident Management and On-Call solutions firsthand.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Learn how Scoro created a solid foundation for better on-call practices with Squadcast.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Discover the platform's capabilities through our Interactive Demo.
      Enjoyed the article? Explore further insights on the best SRE practices.
      We’ll show you how Squadcast works and help you figure out if Squadcast is the right fit for you.
      Experience the benefits of Squadcast's Incident Management and On-Call solutions firsthand.
      Enjoyed the article? Explore further insights on the best SRE practices.
      Written By:
      September 29, 2023
      September 29, 2023
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