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Prometheus Sample Alert Rules

Apr 17, 2023
Last Updated:
June 20, 2024
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Prometheus Sample Alert Rules
Table of Contents:

    Prometheus is a robust monitoring and alerting system widely used in cloud-native and Kubernetes environments. One of the critical features of Prometheus is its ability to create and trigger alerts based on metrics it collects from various sources. Additionally, you can analyze and filter the metrics to develop:

    • Complex incident response algorithms
    • Service Level Objectives
    • Error budget calculations
    • Post-mortem analysis or retrospectives 
    • Runbooks to resolve common failures.

    In this article, we look at Prometheus alert rules in detail. We cover alert template fields, the proper syntax for writing a rule, and several Prometheus sample alert rules you can use as is. Additionally, we also cover some challenges and best practices in Prometheus alert rule management and response. 

    Summary of key Prometheus alert rules concepts

    Before we go into more detail on writing Prometheus alert rules, let's quickly summarize the concepts that this article will cover.

    Concept Description
    Alert Template Fields Prometheus has a number of required and optional fields for generating rules.
    Alert Expression Syntax YAML is the format used to build rules.
    Prometheus sample alert rules A list of examples of commonly-used Prometheus alert rules.
    Limitations of Prometheus Inability to suppress alerts and increasing complexity at scale may pose some challenges.
    Best Practices You should follow best practices around rule descriptions, testing, and deployment.
    Incident Response Handling Prometheus can be used to facilitate the handling of incidents from detection to resolution.

    Alert template fields

    Prometheus alert templates provide a way to define standard fields and behavior for multiple alerts. You can define these templates in the Prometheus configuration file. You can reuse templates across multiple alerts to keep your alert configuration clean, maintainable, and understandable.

     The following are the main fields available in Prometheus alert templates:

    Alert

    This field specifies the alert's name. It identifies the alert and must be unique within a Prometheus instance.

    Expr

    This field specifies the Prometheus query expression that evaluates the alert condition. It is the most important field in an alert template, and you must specify it.

    Labels

    This field adds additional information to the alert. You can use it to specify the severity of the alert, the affected service or component, and any other relevant information.

    Annotations

    This field provides additional context and human-readable information about the alert. You can include a summary of the alert, a description of the issue, or any other relevant information.

    For

    This field specifies the duration for which the alert condition must be true before Prometheus triggers the alert.

    Groups

    This field groups multiple alerts together. A single alert condition in a group triggers all alerts in the same group.

    Alert expression syntax

    Prometheus uses the PromQL (Prometheus Query Language) to create alerting rules. The alert expression is the core of a Prometheus alert. You use PromQL to define the condition that triggers an alert. For example, the following expression triggers an alert if the average CPU utilization on a host exceeds 80% for 5 minutes:

    avg(node_cpu{mode="system"}) > 80

    Basic alert syntax

    The basic syntax of an alert expression is as follows:

    <metric_name>{<label_name>="<label_value>", ...} <operator> <value>
    
    • The <metric_name> is the name of the metric being queried. 
    • The {<label_name>="<label_value>", ...} is an optional part of the query that  specifies the labels that should be used to filter the metric. 
    • The <operator> is a mathematical operator, such as >, <, ==, etc. 
    • The <value> is the value that the metric must be compared against using the specified operator.

    Advanced alert queries

    For more complex scenarios, you can use functions, like avg, sum, min, max, etc., in the expression to aggregate the metrics and make more complex comparisons. For instance, the below query triggers an alert if the average rate of HTTP requests per second to the "api" service exceeds 50 for a 5-minute period.

    avg(rate(http_requests_total{service="api"}[5m])) > 50
    

    Other advanced features include:

    Integrated full stack reliability management platform
    Try for free
    Drive better business outcomes with incident analytics, reliability insights, SLO tracking, and error budgets
    Manage incidents on the go with native iOS and Android mobile apps
    Seamlessly integrated alert routing, on-call, and incident response
    Try for free

    Prometheus sample alert rules

    We present examples that cover a variety of situations where you may want to produce alerts based on environment metrics. You can use them as-is, or adapted to fit your specific needs.

    High CPU utilization alert

    
     groups:
        - name: example_alerts
          rules:
          - alert: HighCPUUtilization
            expr: avg(node_cpu{mode="system"}) > 80
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: High CPU utilization on host {{ $labels.instance 
              }}
              description: The CPU utilization on host {{
              $labels.instance }} has exceeded 80% for 5 minutes.
    

    Low disk space alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: LowDiskSpace
            expr: node_filesystem_free{fstype="ext4"} < 1e9
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: Low disk space on host {{ $labels.instance 
              }}
              description: The free disk space on host {{
              $labels.instance }} has dropped below 1G
    

    High request error rate alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighRequestErrorRate
            expr: (sum(rate(http_requests_total{status="500"}[5m])) /
            sum(rate(http_requests_total[5m]))) > 0.05
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: High request error rate
              description: The error rate for HTTP requests has exceeded
              5% for 5 minutes.
    

    Node down alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: NodeDown
            expr: up == 0
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: Node {{ $labels.instance }} is down
              description: Node {{ $labels.instance }} has been down for
              5 minutes.
    

    High memory utilization alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighMemoryUtilization
            expr: node_memory_MemTotal - node_memory_MemFree < 0.8 *
            node_memory_MemTotal
            for: 5m
            labels:
              severity: warning
            annotations:
              summary: High memory utilization on host {{
              $labels.instance }}
              description: The memory utilization on host {{
              $labels.instance }} has exceeded 80% for 5 minutes.
    

    High network traffic alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighNetworkTraffic
            expr: node_network_receive_bytes > 100e6
            for: 5m
            labels:
              severity: warning
            annotations:
              summary: High network traffic on host {{
              $labels.instance }}
              description: The inbound network traffic on host {{
              $labels.instance }} has exceeded 100 MB/s for 5 minutes.
    

    Limitations of Prometheus

    Like any tool, Prometheus has its own set of challenges and limitations.

    Excessive alerts for noisy metrics 

    Prometheus alerts are based on metrics, and sometimes metrics can be noisy and difficult to interpret. This may lead to false positives or false negatives, which can be difficult to troubleshoot.

    Scaling challenges

    As the number of metrics and alerting rules increases, Prometheus becomes resource-intensive and may require additional scaling or optimization. Too many complex alerting rules can also become challenging to understand and troubleshoot. Additionally, Prometheus does not have built-in dashboards, so you have to use external dashboarding tools, like Grafana, for metric visualization. 

    Inability to detect dependent services

    Prometheus alerts are based on metrics, but in some scenarios, a particular service metric depends on a different service behavior. In such cases, inaccuracy increases, and alerts become difficult to action.

    No alert suppression

    Prometheus does not have built-in alert suppression or deduplication. Depending on your configuration, you could have a high volume of alerts for non-critical issues. To mitigate this, users can use an additional component, such as Alertmanager, to group, deduplicate, and route alerts to the appropriate channel.

    Limited integration with other tools

    While you can integrate Prometheus with various notification channels, it does present limited integration opportunities with other monitoring and alerting tools. You may already have existing monitoring infrastructure that is incompatible with Prometheus. 

    Best practices for Prometheus alerts configuration

    Despite some challenges, you can customize Prometheus to meet your organization's needs. Proper planning and configuration proactively identify and resolve issues before they become critical.

    Here are some best practices to follow when using Prometheus alerting rules:

    Create meaningful alert templates

    Write alert templates and configurations that even new team members can understand. For example:

    • Choose alert names that clearly describe the metric and scenario they monitor. 
    • Write descriptive annotations for each alert. 
    • Assign appropriate severity levels to your alerts, such as critical, warning, or info.
    • Group related alerts together in a single alert group to improve manageability.

    These best practices provide more context about the alert and improve response and troubleshooting time.

    Set the appropriate alert frequency

    Make sure the time window specified in the for clause of an alert is appropriate for the metric you are monitoring. A short time window may result in too many false positive alerts, while a long time window may delay detecting real issues. For example, some user actions may cause your application's CPU usage to spike quickly before subsiding again. You may not want to action every small spike. 

    Test Prometheus before deployment 

    Test your alert rules in a test environment before deploying them to production. This helps to ensure that the rules are working as expected and eliminates the risk of unintended consequences. Additionally, you can:

    • Monitor the Prometheus Alertmanager to ensure it functions properly and handles alerts as expected. 
    • Regularly review and update your alert rules to ensure that they continue to accurately reflect your system state and incorporate environment changes.
    • Use alert templates to reduce the amount of duplication in your alert rules, as duplication increases management complexity.

    Use incident response systems

    Automate alert handling where possible to reduce the time required to respond to alerts and to minimize human error. You can also use your Prometheus metrics and alerts for productive incident retrospectives or build runbooks to handle similar issues.

    You can use tools like Squadcast to route alerts to applicable teams. Squadcast extends beyond basic incident response functionality to provide many other features like documenting retrospectives, tracking service level objectives (SLO), and error budgets. 

    Incident response handling

    Your organization's incident response algorithms could be as simple as sending an email to your team letting them know that a failure is imminent.  More complex alerts may trigger runbooks to automate the resolution process. For example, your ruleset could be defined to automatically scale services if a particular error budget exceeds a predefined threshold. Should the error rate continue to climb, a tool like Squadcast contacts the on-call administrator to step in and handle the incident. 

    Runbooks

    It is crucial to build out proper runbooks for handling some of the more common issues. Administrators use runbooks to facilitate incident resolution or convert them into scripts to automate the process. For example, you may write a runbook on handling an issue where a specific web server starts to segfault randomly, causing a high rate of HTTP failures. The runbook includes information on where to look for the errors, and specifically what services you need to restart as a result.

    The best time to develop these runbooks is during the post-mortem of the incident, also known as a retrospective. This is the time when incident managers determine what went well, what did not go well, and what action items the team can take to correct issues in the future.

    Conclusion

    As you can see, Prometheus is an excellent tool to alert on key metrics in cloud-native environments. Prometheus's flexible query language and integration capabilities make it a versatile solution for efficient monitoring and alerting at scale. Our Prometheus sample alert rules and best practices will surely assist you in fully utilizing the most comprehensive Kubernetes alerting tools available today. 

    Integrated full stack reliability management platform
    Platform
    Blameless
    Lightstep
    Squadcast
    Incident Retrospectives
    Seamless Third-Party Integrations
    Built-In Status Page
    On Call Rotations
    Incident
    Notes
    Advanced Error Budget Tracking
    Try For free
    Platform
    Incident Retrospectives
    Seamless Third-Party Integrations
    Incident
    Notes
    Built-In Status Page
    On Call Rotations
    Advanced Error Budget Tracking
    Blameless
    FireHydrant
    Squadcast
    Try For free
    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.
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    Prometheus Sample Alert Rules

    Prometheus Sample Alert Rules
    Apr 17, 2023
    Last Updated:
    Apr 17, 2023

    Prometheus is a robust monitoring and alerting system widely used in cloud-native and Kubernetes environments. One of the critical features of Prometheus is its ability to create and trigger alerts based on metrics it collects from various sources. Additionally, you can analyze and filter the metrics to develop:

    • Complex incident response algorithms
    • Service Level Objectives
    • Error budget calculations
    • Post-mortem analysis or retrospectives 
    • Runbooks to resolve common failures.

    In this article, we look at Prometheus alert rules in detail. We cover alert template fields, the proper syntax for writing a rule, and several Prometheus sample alert rules you can use as is. Additionally, we also cover some challenges and best practices in Prometheus alert rule management and response. 

    Summary of key Prometheus alert rules concepts

    Before we go into more detail on writing Prometheus alert rules, let's quickly summarize the concepts that this article will cover.

    Concept Description
    Alert Template Fields Prometheus has a number of required and optional fields for generating rules.
    Alert Expression Syntax YAML is the format used to build rules.
    Prometheus sample alert rules A list of examples of commonly-used Prometheus alert rules.
    Limitations of Prometheus Inability to suppress alerts and increasing complexity at scale may pose some challenges.
    Best Practices You should follow best practices around rule descriptions, testing, and deployment.
    Incident Response Handling Prometheus can be used to facilitate the handling of incidents from detection to resolution.

    Alert template fields

    Prometheus alert templates provide a way to define standard fields and behavior for multiple alerts. You can define these templates in the Prometheus configuration file. You can reuse templates across multiple alerts to keep your alert configuration clean, maintainable, and understandable.

     The following are the main fields available in Prometheus alert templates:

    Alert

    This field specifies the alert's name. It identifies the alert and must be unique within a Prometheus instance.

    Expr

    This field specifies the Prometheus query expression that evaluates the alert condition. It is the most important field in an alert template, and you must specify it.

    Labels

    This field adds additional information to the alert. You can use it to specify the severity of the alert, the affected service or component, and any other relevant information.

    Annotations

    This field provides additional context and human-readable information about the alert. You can include a summary of the alert, a description of the issue, or any other relevant information.

    For

    This field specifies the duration for which the alert condition must be true before Prometheus triggers the alert.

    Groups

    This field groups multiple alerts together. A single alert condition in a group triggers all alerts in the same group.

    Alert expression syntax

    Prometheus uses the PromQL (Prometheus Query Language) to create alerting rules. The alert expression is the core of a Prometheus alert. You use PromQL to define the condition that triggers an alert. For example, the following expression triggers an alert if the average CPU utilization on a host exceeds 80% for 5 minutes:

    avg(node_cpu{mode="system"}) > 80

    Basic alert syntax

    The basic syntax of an alert expression is as follows:

    <metric_name>{<label_name>="<label_value>", ...} <operator> <value>
    
    • The <metric_name> is the name of the metric being queried. 
    • The {<label_name>="<label_value>", ...} is an optional part of the query that  specifies the labels that should be used to filter the metric. 
    • The <operator> is a mathematical operator, such as >, <, ==, etc. 
    • The <value> is the value that the metric must be compared against using the specified operator.

    Advanced alert queries

    For more complex scenarios, you can use functions, like avg, sum, min, max, etc., in the expression to aggregate the metrics and make more complex comparisons. For instance, the below query triggers an alert if the average rate of HTTP requests per second to the "api" service exceeds 50 for a 5-minute period.

    avg(rate(http_requests_total{service="api"}[5m])) > 50
    

    Other advanced features include:

    Integrated full stack reliability management platform
    Try for free
    Drive better business outcomes with incident analytics, reliability insights, SLO tracking, and error budgets
    Manage incidents on the go with native iOS and Android mobile apps
    Seamlessly integrated alert routing, on-call, and incident response
    Try for free

    Prometheus sample alert rules

    We present examples that cover a variety of situations where you may want to produce alerts based on environment metrics. You can use them as-is, or adapted to fit your specific needs.

    High CPU utilization alert

    
     groups:
        - name: example_alerts
          rules:
          - alert: HighCPUUtilization
            expr: avg(node_cpu{mode="system"}) > 80
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: High CPU utilization on host {{ $labels.instance 
              }}
              description: The CPU utilization on host {{
              $labels.instance }} has exceeded 80% for 5 minutes.
    

    Low disk space alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: LowDiskSpace
            expr: node_filesystem_free{fstype="ext4"} < 1e9
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: Low disk space on host {{ $labels.instance 
              }}
              description: The free disk space on host {{
              $labels.instance }} has dropped below 1G
    

    High request error rate alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighRequestErrorRate
            expr: (sum(rate(http_requests_total{status="500"}[5m])) /
            sum(rate(http_requests_total[5m]))) > 0.05
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: High request error rate
              description: The error rate for HTTP requests has exceeded
              5% for 5 minutes.
    

    Node down alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: NodeDown
            expr: up == 0
            for: 5m
            labels:
              severity: critical
            annotations:
              summary: Node {{ $labels.instance }} is down
              description: Node {{ $labels.instance }} has been down for
              5 minutes.
    

    High memory utilization alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighMemoryUtilization
            expr: node_memory_MemTotal - node_memory_MemFree < 0.8 *
            node_memory_MemTotal
            for: 5m
            labels:
              severity: warning
            annotations:
              summary: High memory utilization on host {{
              $labels.instance }}
              description: The memory utilization on host {{
              $labels.instance }} has exceeded 80% for 5 minutes.
    

    High network traffic alert

    
        groups:
        - name: example_alerts
          rules:
          - alert: HighNetworkTraffic
            expr: node_network_receive_bytes > 100e6
            for: 5m
            labels:
              severity: warning
            annotations:
              summary: High network traffic on host {{
              $labels.instance }}
              description: The inbound network traffic on host {{
              $labels.instance }} has exceeded 100 MB/s for 5 minutes.
    

    Limitations of Prometheus

    Like any tool, Prometheus has its own set of challenges and limitations.

    Excessive alerts for noisy metrics 

    Prometheus alerts are based on metrics, and sometimes metrics can be noisy and difficult to interpret. This may lead to false positives or false negatives, which can be difficult to troubleshoot.

    Scaling challenges

    As the number of metrics and alerting rules increases, Prometheus becomes resource-intensive and may require additional scaling or optimization. Too many complex alerting rules can also become challenging to understand and troubleshoot. Additionally, Prometheus does not have built-in dashboards, so you have to use external dashboarding tools, like Grafana, for metric visualization. 

    Inability to detect dependent services

    Prometheus alerts are based on metrics, but in some scenarios, a particular service metric depends on a different service behavior. In such cases, inaccuracy increases, and alerts become difficult to action.

    No alert suppression

    Prometheus does not have built-in alert suppression or deduplication. Depending on your configuration, you could have a high volume of alerts for non-critical issues. To mitigate this, users can use an additional component, such as Alertmanager, to group, deduplicate, and route alerts to the appropriate channel.

    Limited integration with other tools

    While you can integrate Prometheus with various notification channels, it does present limited integration opportunities with other monitoring and alerting tools. You may already have existing monitoring infrastructure that is incompatible with Prometheus. 

    Best practices for Prometheus alerts configuration

    Despite some challenges, you can customize Prometheus to meet your organization's needs. Proper planning and configuration proactively identify and resolve issues before they become critical.

    Here are some best practices to follow when using Prometheus alerting rules:

    Create meaningful alert templates

    Write alert templates and configurations that even new team members can understand. For example:

    • Choose alert names that clearly describe the metric and scenario they monitor. 
    • Write descriptive annotations for each alert. 
    • Assign appropriate severity levels to your alerts, such as critical, warning, or info.
    • Group related alerts together in a single alert group to improve manageability.

    These best practices provide more context about the alert and improve response and troubleshooting time.

    Set the appropriate alert frequency

    Make sure the time window specified in the for clause of an alert is appropriate for the metric you are monitoring. A short time window may result in too many false positive alerts, while a long time window may delay detecting real issues. For example, some user actions may cause your application's CPU usage to spike quickly before subsiding again. You may not want to action every small spike. 

    Test Prometheus before deployment 

    Test your alert rules in a test environment before deploying them to production. This helps to ensure that the rules are working as expected and eliminates the risk of unintended consequences. Additionally, you can:

    • Monitor the Prometheus Alertmanager to ensure it functions properly and handles alerts as expected. 
    • Regularly review and update your alert rules to ensure that they continue to accurately reflect your system state and incorporate environment changes.
    • Use alert templates to reduce the amount of duplication in your alert rules, as duplication increases management complexity.

    Use incident response systems

    Automate alert handling where possible to reduce the time required to respond to alerts and to minimize human error. You can also use your Prometheus metrics and alerts for productive incident retrospectives or build runbooks to handle similar issues.

    You can use tools like Squadcast to route alerts to applicable teams. Squadcast extends beyond basic incident response functionality to provide many other features like documenting retrospectives, tracking service level objectives (SLO), and error budgets. 

    Incident response handling

    Your organization's incident response algorithms could be as simple as sending an email to your team letting them know that a failure is imminent.  More complex alerts may trigger runbooks to automate the resolution process. For example, your ruleset could be defined to automatically scale services if a particular error budget exceeds a predefined threshold. Should the error rate continue to climb, a tool like Squadcast contacts the on-call administrator to step in and handle the incident. 

    Runbooks

    It is crucial to build out proper runbooks for handling some of the more common issues. Administrators use runbooks to facilitate incident resolution or convert them into scripts to automate the process. For example, you may write a runbook on handling an issue where a specific web server starts to segfault randomly, causing a high rate of HTTP failures. The runbook includes information on where to look for the errors, and specifically what services you need to restart as a result.

    The best time to develop these runbooks is during the post-mortem of the incident, also known as a retrospective. This is the time when incident managers determine what went well, what did not go well, and what action items the team can take to correct issues in the future.

    Conclusion

    As you can see, Prometheus is an excellent tool to alert on key metrics in cloud-native environments. Prometheus's flexible query language and integration capabilities make it a versatile solution for efficient monitoring and alerting at scale. Our Prometheus sample alert rules and best practices will surely assist you in fully utilizing the most comprehensive Kubernetes alerting tools available today. 

    Integrated full stack reliability management platform
    Platform
    Blameless
    Lightstep
    Squadcast
    Incident Retrospectives
    Seamless Third-Party Integrations
    Built-In Status Page
    On Call Rotations
    Incident
    Notes
    Advanced Error Budget Tracking
    Try For free
    Platform
    Incident Retrospectives
    Seamless Third-Party Integrations
    Incident
    Notes
    Built-In Status Page
    On Call Rotations
    Advanced Error Budget Tracking
    Blameless
    FireHydrant
    Squadcast
    Try For free
    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.
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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 2022 Squadcast is a leader in Europe IT Alerting on G2 Squadcast is a leader in Mid-Market Asia Pacific Incident Management on G2 Users love Squadcast on G2
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      mapgears
      "Mapgears simplified their complex On-call Alerting process with Squadcast.
      Squadcast has helped us aggregate alerts coming in from hundreds of services into one single platform. We no longer have hundreds of...
      Alexandre Lessard
      System Analyst
      bibam
      "Bibam found their best PagerDuty alternative in Squadcast.
      By moving to Squadcast from Pagerduty, we have seen a serious reduction in alert fatigue, allowing us to focus...
      Martin do Santos
      Platform and Architecture Tech Lead
      tanner
      "Squadcast helped Tanner gain system insights and boost team productivity.
      Squadcast has integrated seamlessly into our DevOps and on-call team's workflows. Thanks to their reliability metrics we have...
      Sandro Franchi
      CTO
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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
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