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    you want to create alerts on your google cloud resources, such as when health checks fail. which is the best google cloud product to use?

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    [QUIZ] 5. Developing, Deploying, and Monitoring in the Cloud Flashcards

    Study with Quizlet and memorize flashcards containing terms like Why might a GCP customer choose to use Cloud Source Repositories?, Why might a GCP customer choose to use Cloud Functions?, Why might a GCP customer choose to use Deployment Manager? and more.

    [QUIZ] 5. Developing, Deploying, and Monitoring in the Cloud

    3.3 (6 reviews) Term 1 / 5

    Why might a GCP customer choose to use Cloud Source Repositories?

    Click the card to flip 👆

    Definition 1 / 5

    They don't want to host their own git instance, and they want to integrate with IAM permissions.

    Click the card to flip 👆

    Created by Eltonoliram

    Terms in this set (5)

    Why might a GCP customer choose to use Cloud Source Repositories?

    They don't want to host their own git instance, and they want to integrate with IAM permissions.

    Why might a GCP customer choose to use Cloud Functions?

    Their application contains event-driven code that they don't want to have to provision compute resources for.

    Why might a GCP customer choose to use Deployment Manager?

    Deployment Manager is an infrastructure management system for GCP resources.

    You want to define alerts on your GCP resources, such as when health checks fail. Which is the best GCP product to use?

    Stackdriver Monitoring

    Which statements are true about Stackdriver Logging? Choose all that are true (2 statements)

    1) Stackdriver Logging lets you view logs from your applications, and filter and search on them.

    2) Stackdriver Logging lets you define metrics based on your logs.

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    Computer Science

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    Introduction to alerting

    Operations Suite Monitoring Documentation Guides Was this helpful?

    Introduction to alerting

    Alerting gives timely awareness to problems in your cloud applications so you can resolve the problems quickly.

    In Cloud Monitoring, an alerting policy describes the circumstances under which you want to be alerted and how you want to be notified. This page provides an overview of alerting policies.

    Alerting policies that are used to track metric data collected by Cloud Monitoring are called metric-based alerting policies. Most of the Cloud Monitoring documentation about alerting policies assumes that you are using metric-based alerting policies. To learn how to set up a metric-based alerting policy, try the Quickstart for Compute Engine.

    You can also create log-based alerting policies, which notify you when a particular message appears in your logs. These policies are not based on metrics. This content does not apply to log-based alerting policies. For information about log-based alerting policies, see Monitoring your logs.

    How alerting works

    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.

    For example, you might configure a condition as follows:

    The HTTP response latency is higher than two seconds for at least five minutes.

    In this example, the condition monitors the metric HTTP response latency and specifies when the values of the metric require you to respond. The condition is met when the resource, or the group of resources, is in a state that requires you to respond.

    Notification channels that describe who is to be notified when action is required. You can include multiple notification channels in an alerting policy. Cloud Monitoring supports Cloud Mobile App and Pub/Sub in addition to common notification channels. For a complete list of supported channels and information about how to configure these channels, see Notification options.

    For example, you can configure an alerting policy to email [email protected] and to post a Slack message to the channel #my-support-team.

    Documentation that you want included in a notification. The documentation field supports plain text, Markdown, and variables.

    For example, you could include in your alerting policy the following documentation:

    ## HTTP latency responses

    This alert originated from the project ${project}, using

    the variable $${project}.

    After a metric-based alerting policy is configured, Monitoring continuously monitors the conditions of that policy. You can't configure the conditions to be monitored only for certain time periods.

    When the conditions of that policy are met, Monitoring creates an incident and sends a notification about the incident creation. This notification includes summary information about the incident, a link to the Policy details page so that you can investigate the incident, and any documentation that you specified.

    If an incident is open and Monitoring determines that the conditions of the metric-based policy are no longer met, then Monitoring automatically closes the incident and sends a notification about the closure.

    Example

    You deploy a web application onto a Compute Engine virtual machine (VM) instance that's running a web application. While you expect the HTTP response latency to fluctuate, you want your support team to respond when the application has high latency for a significant time period.

    To ensure that your support team is notified when your application experiences high latencies, you create the following alerting policy:

    If the HTTP response latency is higher than two seconds for at least five

    minutes, then open an incident and send an email to your support team.

    In this alerting policy, the condition is monitoring the HTTP response latency. If this latency is higher than two seconds continuously for five minutes, then the condition is met and an incident is created. A transient spike in latency doesn't cause the condition to be met or an incident to be created.

    Your web application turns out to be popular, and the response latency grows beyond two seconds. Here's how your alerting policy responds:

    Monitoring starts a five-minute timer when it receives an HTTP latency measurement higher than two seconds.

    If each latency measure received during the next five minutes is higher than two seconds, then the timer expires. When the timer expires, Monitoring marks the condition as met, it opens an incident, and it sends an email to your support team.

    Your support team receives the email, signs into the Google Cloud console, and acknowledges receipt of the notification.

    Following the documentation in the notification email, your support team is able to address the cause of the latency. Within a few minutes, the HTTP response latency drops to less than two seconds.

    When Monitoring receives an HTTP latency measurement less than two seconds, it closes the incident and sends a notification to your support team that the incident is closed.

    If the latency rises higher than two seconds and stays higher than that threshold for five minutes, then a new incident is opened and a notification is sent.

    स्रोत : cloud.google.com

    Google Cloud Service Health

    Google Cloud Service Health

    Incidents

    We are experiencing an issue with Google Cloud Networking at us-central1 across multiple products, beginning at Tuesday, 2022-06-14 06:00 US/Pacific.

    Service Health

    This page provides status information on the services that are part of Google Cloud. Check back here to view the current status of the services listed below. If you are experiencing an issue not listed here, please contact Support. Learn more about what's posted on the dashboard in this FAQ. For additional information on these services, please visit https://cloud.google.com/.

    Incident affecting Google Kubernetes Engine, Google Cloud Networking, Cloud Load Balancing, Cloud Filestore

    We are experiencing an issue with Google Cloud Networking at us-central1 across multiple products, beginning at Tuesday, 2022-06-14 06:00 US/Pacific.

    Incident began at 2022-06-14 06:56 and ended at 2022-06-14 17:43 (all times are US/Pacific).

    Previously affected location(s)

    Iowa (us-central1)

    DATE TIME DESCRIPTION

    28 Jun 2022 11:27 PDT

    Incident Report

    Summary:

    On Tuesday, 14 June 2022, at approximately 06:00 US/Pacific, Google Cloud Networking in us-central1 began experiencing increased delays in applying administrative operations, impacting several downstream services. Customers performing administrative actions on resources in us-central1 experienced delays, connectivity issues, and elevated rates of failure.

    To our customers that were impacted during this outage, we sincerely apologize. We are conducting an internal investigation and are taking steps to improve our service.

    Background:

    Google’s Cloud Load Balancer (GCLB) is a collection of software and services that load balances HTTP traffic across customer services. A key component of GCLB is the Google Front End (GFE), which load balances traffic over customer backend instances. GCLB also includes a health checking service to determine whether backends such as customer virtual machines, are responding to traffic as expected, or are unhealthy and should be removed from service.

    Root Cause:

    The health checking service and GFE share a common resource pool. For a period of time, GCLB traffic was directed away from certain clusters, and, independently, during this time, health checking load in these clusters increased significantly.

    The incident was triggered when Google engineers rerouted traffic to these clusters as part of a standard maintenance activity. This rerouted traffic increased load in those clusters, and this slowed the performance of the health checking service, resulting in an increasing rate of health check failures. This in turn led to a general networking control plane slowdown, as the service struggled to keep up with erroneous and rapid health status changes of load balancer backends. The slowdown in the networking control plane resulted in the impact on administrative operations for other resource types which involve network configuration. Customers may have experienced this as slowness or timeouts in administrative operations for the resource types listed in the Impact section, or delays in new resources (like VM instances) connecting to networks.

    Remediation and Prevention:

    On Monday, 13 June 2022, at 16:30 US/Pacific, Google engineers rerouted traffic to additional compute resources in the us-central1 region as part of a standard maintenance activity.

    Google engineers were alerted to control plane slowness on Tuesday, 14 June 2022, at 09:17 and started an investigation. Initially, Google engineers were unable to determine the severity of the latency, due to insufficient monitoring. After attempts to mitigate by adding resources were unsuccessful, the incident was escalated at 15:50. A cross team effort of Google engineers was launched and at 17:39 mitigated the incident by removing the earlier reroute. This reduced the load on the health check system, and subsequently the networking control plane recovered at 17:43.

    Google is committed to improving our service in the future and will be completing the following actions:

    Prevent similar incidents by improving the capacity modeling of our health checking service, and implementing improved resource isolation in our health checking service.

    Detect similar incidents more rapidly by improving alerting related to the health checking process to notify responsible teams earlier and speed time to mitigate.

    Add defense in depth: protect the downstream networking control plane from high rates of load balancing health reports, thus avoiding this type of incident in future.

    Detailed Description of Impact:

    On 13 June 16:30 to 14 June 17:43 2022 US/Pacific:

    Google Kubernetes Engine (GKE)

    Affected customers would have observed latency and up to ~40% elevated errors or timeouts during GKE Private Service Connect cluster operations including creation, deletion, and updates for a subset of clusters in us-central1.

    Google Cloud Load Balancing (GCLB)

    Customers with resources in us-central1-c and us-central1-f would have observed increased latency or timeouts and connection errors from the Load Balancer service for resources in us-central1. Customers would have seen up to a 4.5% overall error rate, with up to 23% of requests timing out.

    स्रोत : status.cloud.google.com

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