Code360 powered by Coding Ninjas X Naukri.com. Code360 powered by Coding Ninjas X Naukri.com
Table of contents
1.
Introduction
2.
Using API in Cloud Monitoring
2.1.
Alerting policies in the Monitoring API 
2.1.1.
Structure of an alerting policy
2.1.2.
Types of conditions in the API
2.1.3.
Filter-based metric conditions
2.1.4.
MQL-based metric conditions
2.1.5.
Conditions for alerting on ratios
2.1.6.
Condition for Log-Based Alerting Policies
2.2.
Managing alerting policies by API
2.2.1.
Prerequisites
2.3.
About Alerting Policies
2.3.1.
Creating Policies
2.3.2.
Deleting Policies
2.3.3.
Retrieving Policies
2.4.
Managing Notification Channels by the API
2.5.
Channel Descriptors
3.
Notification channels
3.1.
Creating Channels
4.
Frequently Asked Questions
4.1.
When creating an alerting policy what can be specified?
4.2.
What is monitoring alerting?
4.3.
What is KPI in API?
5.
Conclusion
Last Updated: Mar 27, 2024

Using API in Cloud Monitoring

Author Shivam Sinha
0 upvote
Master Python: Predicting weather forecasts
Speaker
Ashwin Goyal
Product Manager @

Introduction

In this article, we will discuss the use of API in Cloud Monitoring. We will see the alerting policies in the monitoring API in detail, and how to manage them. We will also see how to manage notification channels by API.

Using API in Cloud Monitoring

We can use the Monitoring API to access over 1,500 cloud monitoring metrics from Google Cloud and Amazon Web Services. We can create our own custom metrics and use groups to organize our cloud resources.

Alerting policies in the Monitoring API 

Alert policies are represented by the AlertPolicy object in the Cloud Monitoring API. This object describes a set of conditions that indicate a potentially abnormal state of the system. This article describes how the Monitoring API presents alert policies and the types of conditions that the Monitoring API exposes to alert policies.

Structure of an alerting policy

The AlertPolicy structure describes the components of an alerting policy. When we create a policy, either by using the Google Cloud console or the Monitoring API, we specify values for the below AlertPolicy fields:

  • displayName: It is a descriptive label for the policies.
  • documentation: Any information or messages given here to help responders.
  • userLabels: Any user-defined or custom labels attached to the policy. Visit here to know more about using labels.
  • Conditions []: It is an array of Condition structures.
  • combiner: A logical operator, we can handle multiple situations through it.
  • notificationChannels[]: A notification channel array.
  • alert strategy: It describes how fastly monitoring closes the incidents when the arrival of data stops.

 

We might use other fields, depending on the conditions we create.

Notification policies created using the Monitoring API send notifications when the conditions that trigger the policy are met and when the conditions are no longer met. This is the default case, and we can't change this behavior using the Monitoring API, but we can disable close incident notifications by editing the policy in Google Cloud Console. To disable notifications about closing an incident, in the Notifications section, clear the Notify me when an incident closes check box and save the edited policy.

When we create or modify a notification policy, monitoring also sets other fields, including the name field. The value in the name field is the alert policy resource name that identifies the policy. The format of the resource name is as follows:

projects/PROJECT_ID/alertPolicies/POLICY_ID

Alerting policy conditions is the most variable part of an alerting policy.

Types of conditions in the API

The Cloud Monitoring API supports different condition types in Condition structures. There are different condition types for metric-based alerting policies, and there is only one condition for log-based alerting policies. 

The coming sections describe the present condition types.

Conditions for metric-based alerting policies

We can use the following condition types to create an alerting policy that can monitor metric data along with log-based metrics:

Filter-based metric conditions

The MetricAbsence and MetricThreshold conditions use a monitoring filter to select the time series data to monitor. The other fields in the conditional structure show how the data is filtered, grouped, and aggregated. For more information, visit Filtering and aggregation: manipulating time series

If we use the MetricAbsence condition type, we can use aggregates to aggregate time series into a single time series to create conditions triggered only if all time series are missing. See the Metric absence condition reference in the API documentation.

The metric alert policy is missing, and some data needs to be written in advance. 

MQL-based metric conditions

The MonitoringQueryLanguageCondition condition uses the Monitoring Query Language (MQL) to select and manipulate the time series data to be monitored. We can use this condition type to create alerting policies that compare values ​​to thresholds and test for missing values. If we use the MonitoringQueryLanguageCondition condition, this should be the only condition of the alerting policy. For more information, visit Alerting policies with MQL.

Conditions for alerting on ratios

We can create a metric threshold alerting policy to monitor the ratio of the two metrics. These policies can be created using either the MetricThreshold or MonitoringQueryLanguageCondition condition types. We can also use MQL directly in the Google Cloud Console. We cannot create or manage ratio-based conditions by using the graphical interface to create threshold conditions.

It is recommended that we should use MQL to create a ratio-based alerting policy. MQL allows us to create more powerful and flexible queries than we can create using the MetricTheshold condition type and monitoring filters. For example, we can use the MonitoringQueryLanguageCondition to calculate the gauge and delta metrics ratio. To see more examples, visit MQL alerting-policy examples.

When using the MetricThreshold condition, the numerator and denominator of the ratio must be the same MetricKind. 

It is generally best to use label values ​​to calculate ratios based on the time series collected for a single metric type. Ratios calculated across two different metric types can be anomalous due to different sampling periods and alignment windows.

Suppose we have two different metric types, total RPC count and error RPC count, and we want to calculate the ratio of error count RPC to total RPC. Failed RPCs are counted in time series for both metric types. Therefore, we may not see failed RPCs in both time series with the same alignment interval when aligning time series.

There are several possible reasons for this difference:

  • Since there are two different time series that record the same event, two basic counter values implement the recording, and they are not updated atomically.
  • Sampling rates may vary. If the time series are aligned in a common time series, the count for a single event may appear in adjacent alignment intervals in time series with different metrics.

 

Differences in the number of corresponding alignment interval values ​​can result in nonsensical error / total ratio values ​​such as 1/0 and 2/1. The higher the ratio, the less likely it is that a nonsensical value will be generated. We can get more numbers by aggregation by using an alignment window that is longer than the sampling period or by grouping the data for a particular label. These techniques minimize the impact of slight differences in the number of points within a particular interval. A 2-point discrepancy is more pronounced when the expected number of points in the interval is three than when the expected number is 300.

When using the built-in metric types, we may have no choice but to calculate the ratio between the metric types to get the required value.

If we are designing a custom metric that allows two different metrics to count the same (such as an RPC that returns error status), consider a single metric that contains each count only once instead. Suppose we are counting RPCs and want to keep track of the ratio of failed RPCs to all RPCs. To resolve this issue, we need to create a single metric type that counts RPCs, and we need to use a label to record the status of the call, including the OK status. Then each status value, error, or "OK" is recorded by updating a single counter in that case.

Condition for Log-Based Alerting Policies

Use the LogMatch condition type to create a log-based alerting policy that notifies us when a message that matches the filter appears in a log entry. If we use the LogMatch condition, this should be the only condition in your notification policy.

We cannot use the LogMatch condition type with log-based metrics. Alerting policies that monitor log-based metrics are metric-based. The alerting policy used in the document example is a metric-based alerting policy, but the principles of a log-based alerting policy are the same. For specific information on log-based alerting policies, see "Create a log-based alert (Monitoring API)" in the Cloud Logging documentation.

Managing alerting policies by API

In this section, we use the Cloud Monitoring API to create and manage metric-based alerting policies programmatically. We will also illustrate the use of the Google Cloud CLI for managing alerting policies. This content does not apply to log-based alerting policies. For information about log-based alerting policies, see Monitoring your logs.

Many of these tasks can also be performed by using the Cloud Monitoring console; see Using Alerting Policies for an introduction to creating and managing alerting policies with the Cloud Monitoring console.

Now let's see how to use the Cloud Monitoring API to programmatically create and manage metric-based alerting policies. It also describes how to manage alerting policies using the Google Cloud CLI. This content does not apply to log-based notification policies. 

Many of these tasks can also be performed using the Cloud Monitoring Console. For an overview of creating and managing alerting policies using the Cloud Monitoring Console.

Prerequisites

Before writing the code for the API, we need to do the following:

  • Familiar with the general concepts and terminology used in alert policies. See Introduction to Alerting.
  • Make sure that the use of Cloud Monitoring API is enabled. For more information, see Enabling the API.
  • Install the client library for our language. See Client Libraries for more information. Currently, API support for alerting is only available in C #, Go, Java, Node.js, and Python.

 

Install Google Cloud CLI, which can also perform these tasks. If we are using Cloud Shell, use Cloud Shell instead of installing the Google Cloud CLI. An example using the gcloud interface is also provided here. All gcloud examples assume that the current project is already set as a target (gcloud config set project [PROJECT_ID]), so the explicit --project flag is omitted in the call. We need to be careful. The current project ID in the example is a-gcp-project.
 

Make sure we have the appropriate permissions for our Google Cloud project. See Permissions. for more information.

About Alerting Policies

Alert policies are represented by AlertPolicy objects that describe a set of conditions that indicate a potentially abnormal state of the system. Alerting policies refer to notification channels. You can use the notification channel to specify how to notify that an alerting policy has been triggered.

Each alerting policy belongs to the metric scope project. Each project can contain up to 500 policies. For API calls, you need to specify the "project ID". Use the ID of the metric-scoped scoping project as the value. In these examples, the scope project ID for the metric scope is a-gcp-project.

The AlertPolicy resource supports the following operations:

  • Create new policy
  • Delete existing policy
  • Retrieve specific or all policies
  • Modify existing policy

 

Alerting policies can be expressed in YAML or JSON, so you can record the policy to a file and use the file to back up and restore the policy. You can use the Google Cloud CLI to create policies from files in either format. You can use the REST API to create a policy from a JSON file.

Creating Policies

To create an alerting policy in a project, use the alertPolicies.create method.

You can create policies from JSON or YAML files. The Google Cloud CLI accepts these files as arguments, and you can programmatically read JSON files, convert them to AlertPolicy objects, and create policies from them by using the alertPolicies.create method.

For general information about monitoring ratios of metrics, see Ratios of metrics.

The following examples illustrate the creation of alerting policies. 

C#:

static void RestorePolicy(string projectId, string filePath)
{
    var policyClient = AlertPolicyServiceClient.Create();
    var channelClient = NotificationChannelServiceClient.Create();
    List<Exception> exceptions = new List<Exception>();
    var backup = JsonConvert.DeserializeObject<BackupRecord>(
        File.ReadAllText(filePath), new ProtoMessageConverter());
    var projectName = new ProjectName(projectId);
    bool isSameProject = projectId == backup.ProjectId;

    var channelNameMap = new Dictionary<string, string>();
    foreach (NotificationChannel channel in backup.Channels)
    {
    }
    foreach (AlertPolicy policy in backup.Policies)
    {
        string policyName = policy.Name;
        policy.CreationRecord = null;
        policy.MutationRecord = null;
    
       for (int ctr = 0; ctr < policy.NotificationChannels.Count; ++ctr)
        {
            if (channelNameMap.ContainsKey(policy.NotificationChannels[ctr]))
            {
                policy.NotificationChannels[ctr] =
                    channelNameMap[policy.NotificationChannels[ctr]];/6
            }
        }
        try
        {
            Console.WriteLine("Update the policy.\n{0}",
                policy.DisplayName);
            bool update = false;
            if (isSameProject)
                try
                {
                    policyClient.UpdateAlertPolicy(null, policy);
                    update = true;
                }
                catch (Grpc.Core.RpcException e)
                when (e.Status.StatusCode == StatusCode.NotFound)
                { }
            if (!update)
            {
                // The policy no longer exists.  Recreate it.
                policy.Name = null;
                foreach (var condition in policy.Conditions)
                {
                    condition.Name = null;
                }
                policyClient.CreateAlertPolicy(projectName, policy);
            }
            Console.WriteLine("Restored {0}.", policyName);
        }
        catch (Exception e)
        {
            // Trying to update others, if one failed
            exceptions.Add(e);
        }
    }
    if (exceptions.Count > 0)
    {
        throw new AggregateException(exceptions);
    }
}

 

Java:

private static void restoreRevisedPolicies(
    String projectId, boolean isSameProject, List<AlertPolicy> policies) throws IOException {
  try (AlertPolicyServiceClient client = AlertPolicyServiceClient.create()) {
    for (AlertPolicy policy : policies) {
      if (!isSameProject) {
        policy = client.createAlertPolicy(ProjectName.of(projectId), policy);
      } else {
        try {
          client.updateAlertPolicy(null, policy);
        } catch (Exception e) {
          policy =
              client.createAlertPolicy(
                  ProjectName.of(projectId), policy.toBuilder().clearName().build());
        }
      }
      System.out.println(String.format("Restored %s", policy.getName()));
    }
  }
}

 

Python:

def restore(project_name, backup_filename):
    print(
        "Loading alert policies and notification channels from {}.".format(
            backup_filename
        )
    )
    record = json.load(open(backup_filename, "rt"))
    is_same_project = project_name == record["project_name"]
    policies_json = [json.dumps(policy) for policy in record["policies"]]
    policies = [
        monitoring_v3.AlertPolicy.from_json(policy_json)
        for policy_json in policies_json
    ]
    channels_json = [json.dumps(channel) for channel in record["channels"]]
    channels = [
        monitoring_v3.NotificationChannel.from_json(channel_json)
        for channel_json in channels_json
    ]

    # Restore the channels.
    channel_client = monitoring_v3.NotificationChannelServiceClient()
    channel_name_map = {}

    for channel in channels:
        update = False
        print("Updating channel", channel.display_name)
        channel.verification_status = (
            monitoring_v3.NotificationChannel.VerificationStatus.VERIFICATION_STATUS_UNSPECIFIED
        )

        if is_same_project:
            try:
                channel_client.update_notification_channel(notification_channel=channel)
                update = True
            except google.api_core.exceptions.NotFound:
                pass  # The channel was deleted.  Create it below.

        if not updated:
            # The channel no longer exists.  Recreate it.
            old_name = channel.name
            del channel.name
            new_channel = channel_client.create_notification_channel(
                name=project_name, notification_channel=channel
            )
            channel_name_map[old_name] = new_channel.name

    # Restore the alerts
    alert_client = monitoring_v3.AlertPolicyServiceClient()

    for policy in policies:
        print("Updating policy", policy.display_name)
        del policy.creation_record
        del policy.mutation_record

        for counter, channel in enumerate(policy.notification_channels):
            new_channel = channel_name_map.get(channel)
            if new_channel:
                policy.notification_channels[counter] = new_channel

        update = False

        if is_same_project:
            try:
                alert_client.update_alert_policy(alert_policy=policy)
                update = True
            except google.api_core.exceptions.NotFound:
                pass  
            except google.api_core.exceptions.InvalidArgument:
                 pass

        if not updated:
            # The policy no longer exists.  Recreate it.
            old_name = policy.name
            del policy.name
            for condition in policy.conditions:
                del condition.name
            policy = alert_client.create_alert_policy(
                name=project_name, alert_policy=policy
            )
        print("Updated", policy.name)

The AlertPolicy object created has additional fields. The policy itself contains name, creationRecord, and mutationRecord fields. In addition, each condition of the policy is also named. These fields cannot be changed externally and do not need to be set when creating the policy. The JSON samples used to create the policies do not include them, but the fields are present when the policies created from them are retrieved after creation.

To see code in more languages click here

Deleting Policies

Use the alertPolicies.delete method to delete a policy from a project, and also supply the name of the alerting policy that needs to be deleted.

gcloud

Use gcloud alpha monitoring policies to delete an alerting policy and specify the name of the policy that needs to be deleted. For example, this command deletes the “High CPU rate of change” policy:

gcloud alpha monitoring policies delete projects/a-gcp-project/alertPolicies/12669073143329903307

Retrieving Policies

Use the alertPolicies.list method to retrieve a list of the policies in a project. We can also use this method to retrieve policies and apply some action to each of them, for example, backing them up. This method also supports orderBy and filter options to restrict and sort the results; see Sorting and Filtering.

You can use the alertPolicies.get a method to retrieve only that policy that you are looking for and you know its name. The name of a policy is the value of the name field in the AlertPolicy object. The name of a policy has the format projects/[PROJECT_ID]/alertPolicies/[POLICY_ID], for example:

projects/a-gcp-project/alertPolicies/12669073143329903307

C#:

static void ListAlertPolicies(string projectId)
{
    var client = AlertPolicyServiceClient.Create();
    var response = client.ListAlertPolicies(new ProjectName(projectId));
    foreach (AlertPolicy policy in response)
    {
        Console.WriteLine(policy.Name);
        if (policy.DisplayName != null)
        {
            Console.WriteLine(policy.DisplayName);
        }
        if (policy.Documentation?.Content != null)
        {
            Console.WriteLine(policy.Documentation.Content);
        }
        Console.WriteLine();
    }
}

Java:

private static void listAlertPolicies(String projectId) throws IOException {
  try (AlertPolicyServiceClient client = AlertPolicyServiceClient.create()) {
    ListAlertPoliciesPagedResponse response = client.listAlertPolicies(ProjectName.of(projectId));

    System.out.println("Alert Policies:");
    for (AlertPolicy policy : response.iterateAll()) {
      System.out.println(
          String.format("\nPolicy %s\nalert-id: %s", policy.getDisplayName(), policy.getName()));
      int channels = policy.getNotificationChannelsCount();
      if (channels > 0) {
        System.out.println("notification-channels:");
        for (int i = 0; i < channels; i++) {
          System.out.println("\t" + policy.getNotificationChannels(i));
        }
      }
      if (policy.hasDocumentation() && policy.getDocumentation().getContent() != null) {
        System.out.println(policy.getDocumentation().getContent());
      }
    }
  }
}

Python

def list_alert_policies(project_name):
    client = monitoring_v3.AlertPolicyServiceClient()
    policies = client.list_alert_policies(name=project_name)
    print(
        str(
            tabulate.tabulate(
                [(policy.name, policy.display_name) for policy in policies],
                ("name", "display_name"),
            )
        )
    )

To know more about other operations, please click here

Managing Notification Channels by the API

Alerting policies usually have a way to notify us when triggered. These "notification means" are called notification channels. There are several channel types available. Each type is described in a notification channel descriptor. A particular type of notification channel is an instance of that type of descriptor. The alerting policy contains a reference to the notification channel used as the notification path.

A notification channel must exist to be used in the notification policy. A notification channel descriptor is provided, but you must create the channel before using it.

Channel Descriptors

Monitoring has several built-in notification channel types. Each of these types is described in NotificationChannelDescriptor. These descriptors have a type field, and the value of this field is used as an identifier when creating an instance of that channel type. You can use the following command to get the available channel types that are more commonly described in Notification Options.

$ gcloud beta monitoring channel-descriptors list --format='value(type)'
campfire
email
hipchat
pagerduty
pubsub
slack
sms
webhook_basicauth
webhook_tokenauth

We need to use notificationChannelDescriptors.list method to retrieve all the channel descriptors in a project.

Similarly, we can use the notificationChannelDescriptors.get method, if you are looking for a particular descriptor and you know its names, it will retrieve only that channel descriptor. The name of a channel descriptor has the format projects/[PROJECT_ID]/notificationChannelDescriptors/[CHANNEL_TYPE] [CHANNEL_TYPE] must be one of the types listed above, for example:

projects/[PROJECT_ID]/notificationChannelDescriptors/email


To list all the notification-channel descriptors in a project, use the gcloud beta monitoring channel-descriptors list command:

gcloud beta monitoring channel-descriptors list

 

If successful, the list command provides a listing of all the channel descriptors in the specified project. For example, the email channel descriptor appears in the list like this:

---
    description: A channel that sends notifications via email.
    displayName: Email
    labels:
      - description: An address to send email.
        key: email_address
    name: projects/[PROJECT_ID]/notificationChannelDescriptors/email
    type: email
---


All channel descriptors include these fields:

  • name: The fully qualified resource name of the channel descriptor
  • type: The part of the name that indicates the type of channel
  • displayName: A description of the type field, for display purposes
  • description: A brief description of the channel
  • labels: A set of fields specific to a channel type. Each channel type has its own set of labels.

When a channel is created, it also gets an enabled field, with the value true by default.

To list a single channel descriptor, use gcloud beta monitoring channel-descriptors describe, instead, and specify the name of the channel descriptor. You don't need to specify the fully qualified name. For example, both of these commands return the listing above:

gcloud beta monitoring channel-descriptors describe email

gcloud beta monitoring channel-descriptors describe projects/[PROJECT_ID]/notificationChannelDescriptors/email

See the gcloud beta monitoring channel-descriptors list and describe references for more information. The describe command corresponds to the notificationChannelDescriptors.get method in the API.

Get the tech career you deserve, faster!
Connect with our expert counsellors to understand how to hack your way to success
User rating 4.7/5
1:1 doubt support
95% placement record
Akash Pal
Senior Software Engineer
326% Hike After Job Bootcamp
Himanshu Gusain
Programmer Analyst
32 LPA After Job Bootcamp
After Job
Bootcamp

Notification channels

A notification channel is an instance of one of the notification-channel descriptors that is discussed in Channel descriptors.

The NotificationChannel resource supports five operations:

  • Create new channels
  • Delete existing channels
  • Retrieve a specific channel or all channels
  • Modify existing channels

There are three other operations that are related to managing the verificationStatus field of a channel:

  • Send a verification code
  • Generate a code for copying the verification status of a verified channel to other identical channels in the same or a new project
  • Verify the channel using the code created by the previous two operations

In the coming section, we will be discussing only creating new channels. For other operations, please visit the official documentation.

Creating Channels

You can create notification channels from YAML or JSON files using the Google Cloud Command Line Interface, and you can create them programmatically.

You need to supply values for the fields in its descriptor to create a notification channel, Most of these are common across all notification-channel descriptors.

Each descriptor also has a set of labels, and this set varies across the descriptors. To see the set of labels for a particular descriptor, retrieve the descriptor using the gcloud beta monitoring channel-descriptors describe command described in Channel descriptors. For example, retrieving the email channel descriptor shows a single label:

    labels:   
       - description: An address to send email.
          key: email_address

       

Retrieving the webhook_basicauth channel descriptor shows several labels:

         labels:   
              - description: The password. The field is obfuscated when the channel is fetched.
                key: password
              - description: The public URL to which to publish the webhook.
                key: url    
              - description: The username. 
                key: username

Whether you create a new channel from the command line or programmatically, the specification type value must match the type field in the corresponding notification channel descriptor. The required label key must also match the key in the channel descriptor.
Some labels correspond to the credentials used to authenticate with your provider. When you create a channel, you need to get the values ​​for these labels from your provider. Obtaining credentials may include using the API key generation page on the provider's website or performing an OAuth login flow with the provider. The details of how to obtain such credentials vary from provider to provider.
For example, the following example shows the specifications for a new pubsub notification channel in JSON.

    {   
   "type": "pubsub",
   "displayName": "Alert notifications",
    "description": "Pub/Sub channel for alert notifications",      
     "labels": {       
         "topic": "projects/[PROJECT_ID]/topics/notificationTopic"
      },
    }


The type value (pubsub) and the single label key (topic) match the type and labels.key fields in the corresponding channel descriptor.

Channels are enabled by default. If you want to create an inactive channel, you can include the field enabled with the value false.
 

C#:

static void RestorePolicies(string projectId, string filePath)
{
    var policyClient = AlertPolicyServiceClient.Create();
    var channelClient = NotificationChannelServiceClient.Create();
    List<Exception> exceptions = new List<Exception>();
    var backup = JsonConvert.DeserializeObject<BackupRecord>(
        File.ReadAllText(filePath), new ProtoMessageConverter());
    var projectName = new ProjectName(projectId);
    bool isSameProject = projectId == backup.ProjectId;
    var channelNameMap = new Dictionary<string, string>();
    foreach (NotificationChannel channel in backup.Channels)
    {
        try
        {
            bool update = false;
            Console.WriteLine("Updating channel.\n{0}",
                channel.DisplayName);
            channel.VerificationStatus = NotificationChannel.Types
                .VerificationStatus.Unspecified;
            if (isSameProject)
                try
                {
                    channelClient.UpdateNotificationChannel(
                        null, channel);
                    update = true;
                }
                catch (Grpc.Core.RpcException e)
                when (e.Status.StatusCode == StatusCode.NotFound)
                { }
            if (!update)
            {
                // Recreate the channel as it not exists
                string oldName = channel.Name;
                channel.Name = null;
                var response = channelClient.CreateNotificationChannel(
                    projectName, channel);
                channelNameMap.Add(oldName, response.Name);
            }
        }
        catch (Exception e)
        {
            // Update others if one failed
            exceptions.Add(e);
        }
    }
    foreach (AlertPolicy policy in backup.Policies)
    {
    }
    if (exceptions.Count > 0)
    {
        throw new AggregateException(exceptions);
    }
}


Java:

private static Map<String, String> restoreNotificationChannels(
    String projectId, List<NotificationChannel> channels, boolean isSameProject)
    throws IOException {
  Map<String, String> newChannelNames = Maps.newHashMap();
  try (NotificationChannelServiceClient client = NotificationChannelServiceClient.create()) {
    for (NotificationChannel channel : channels) {
      // Updating channel name if project ID is different.
      boolean channelUpdated = false;
      if (isSameProject) {
        try {
          NotificationChannel updatedChannel =
              client.updateNotificationChannel(NOTIFICATION_CHANNEL_UPDATE_MASK, channel);
          newChannelNames.put(channel.getName(), updatedChannel.getName());
          channelUpdated = true;
        } catch (Exception e) {
          channelUpdated = false;
        }
      }
      if (!channelUpdated) {
        NotificationChannel newChannel =
            client.createNotificationChannel(
                ProjectName.of(projectId),
                channel.toBuilder().clearName().clearVerificationStatus().build());
        newChannelNames.put(channel.getName(), newChannel.getName());
      }
    }
  }
  return newChannelNames;
}


Python:

def restore(project_name, backup_filename):
    print(
        "Loading alert policies and notification channels from {}.".format(
            backup_filename
        )
    )
    record = json.load(open(backup_filename, "rt"))
    is_same_project = project_name == record["project_name"]

    policies_json = [json.dumps(policy) for policy in record["policies"]]
    policies = [
        monitoring_v3.AlertPolicy.from_json(policy_json)
        for policy_json in policies_json
    ]
    channels_json = [json.dumps(channel) for channel in record["channels"]]
    channels = [
        monitoring_v3.NotificationChannel.from_json(channel_json)
        for channel_json in channels_json
    ]

    # Restore the channels.
    channel_client = monitoring_v3.NotificationChannelServiceClient()
    channel_name_map = {}

    for channel in channels:
        update = False
        print("Updating channel", channel.display_name)
        # This field is immutable and it is illegal to specify a
        # non-default value (VERIFIED or UNVERIFIED ) in the
        # Create() or Update() operations.
        channel.verification_status = (
            monitoring_v3.NotificationChannel.VerificationStatus.VERIFICATION_STATUS_UNSPECIFIED
        )

        if is_same_project:
            try:
                channel_client.update_notification_channel(notification_channel=channel)
                update= True
            except google.api_core.exceptions.NotFound:
                pass  # The channel was deleted.  Create it below.

        if not updated:
            # The channel no longer exists.  Recreate it.
            old_name = channel.name
            del channel.name
            new_channel = channel_client.create_notification_channel(
                name=project_name, notification_channel=channel
            )
            channel_name_map[old_name] = new_channel.name

    # Restore the alerts
    alert_client = monitoring_v3.AlertPolicyServiceClient()

    for policy in policies:
        print("Updating policy", policy.display_name)
        # These two fields cannot be set directly, so clear them.
        del policy.creation_record
        del policy.mutation_record

        # Updating old channels name
        for counter, channel in enumerate(policy.notification_channels):
            new_channel = channel_name_map.get(channel)
            if new_channel:
                policy.notification_channels[counter] = new_channel

        update = False

        if is_same_project:
            try:
                alert_client.update_alert_policy(alert_policy=policy)
                update = True
            except google.api_core.exceptions.NotFound:
                pass 
            except google.api_core.exceptions.InvalidArgument:
                pass  

        if not updated:
            # The policy no longer exists.  Recreate it.
            old_name = policy.name
            del policy.name
            for condition in policy.conditions:
                del condition.name
            policy = alert_client.create_alert_policy(
                name=project_name, alert_policy=policy
            )
        print("Updated", policy.name)

Frequently Asked Questions

When creating an alerting policy what can be specified?

Each alerting policy specifies the following: Conditions that describe when a resource, or a group of resources, is in a state that requires you to respond. An alerting policy must have at least one condition; however, you can configure a policy to contain multiple conditions.

What is monitoring alerting?

A set of software components used for data collection, processing, and presentation is called a monitoring system. Alerting is the capability of a monitoring system to detect and notify the operators about meaningful events that denote a grave change of state.

What is KPI in API?

Defining the key performance indicators (KPIs) for APIs being used is a critical part of understanding how they work and how well they can work and the impact they have on your services, users, or partners.

Conclusion

This article discusses Azure Advisor, the kinds of recommendations provided by Azure Advisor, how can we manage Azure Advisor, and many more things about it in detail.

To learn more, see Cloud ComputingMicrosoft Azure, C++ with Data StructureDBMSOperating System by Coding Ninjas, and keep practicing on our platform Coding Ninjas Studio.

If you think you are ready for the tech giants company, check out the mock test series on code studio.

You can also refer to our Guided Path on Coding Ninjas Studio to upskill yourself in domains like Data Structures and AlgorithmsCompetitive ProgrammingAptitude, and many more!. You can also prepare for tech giants companies like Amazon, Microsoft, Uber, etc., by looking for the questions asked by them in recent interviews. If you want to prepare for placements, refer to the interview bundle. If you are nervous about your interviews, you can see interview experiences to get ideas about questions that have been asked by these companies.

 Do upvote if you find this blog helpful!

Be a Ninja

Happy Coding!

 

ninjas logo

Previous article
Incidents in Cloud Monitoring
Next article
Amazon ec2 instance with cloud monitoring
Live masterclass