The accuracy of errors is much better with a record analysis

In contrast to local environments, the cloud is a developing world, where applications are differentiated, and the work burden is based as needed. The records are important in the context of service failure, performance failure or abnormal behavior. It provides developers with the ability to monitor orders in multiple containers in the cloud. Thus, the elaborate registry analysis plays a vital role in the current world, and in the long run, it also provides an accelerated defect and error solution.

Context

As a software engineer, one of the responsibilities is to solve the defect that has been raised as part of the system test, integration test, or version of the final users. During this process of solving defects, one of the most important steps is to conduct the radical causes analysis (RCA), which will help us to close the problem effectively and avoid the uncertainty coming from the defect that is reopened.

In the structure of small services, a result is achieved after a mixture of different microscopic services. Thus, it is a difficult task for anyone to easily discover the root of the problem and provide a solution immediately.

How do you face problems in Google Log Explorer?

Before entering Google Log Explorer, think about it as a complete new city. Records work as street brands indicating the error. But like circumventing an unknown city, it is necessary to have the right map and permissions to effectively explore it.

Make sure you have the right role Logging.viewaccessor. Otherwise, access to the login explorer is rejected. This permission is filled with the project, that is, it may only be able to reach container records scattered in this specified project.

Imagine that your project is to be the neighborhood where you start exploration. Log in to the Google Cloud console and select the project where the work burden is operating. Then go to “Work burdens“The menu, your guide to a crowded container pass. Look for the container you want to analyze, liquidate, and there you will find a place where all the records you need to walk and repair errors.

With this review list, continue; You now know how to locate Google Log Explorer and detect puzzles in records to explore and fix errors.

How did you master the registrar analysis in Google Cloud?

When I got to know Google Log Explorer for the first time, I felt the desire to walk in a huge library of data, each record provides an accurate hint of the questions I need to solve. When I discovered, I realized that mastery of the registry analysis requires identifying strategies, perseverance and good knowledge of what should be searched for.

Filter in history and time – Log Explorer is able to analyze dates and times in a specific time window. The date and time options available as shown below:

1. Fast shots: Whenever you solve modern problems, you have liquidated records to the last or 24 hours. Fast shots referred to abnormal cases in the actual time and allowed me to determine any difficult trends.

2. Wide directions: As for a problem that lasted or existed for some time, the inquiries on the previous week or the last 30 days revealed the trends that were not clear.

3. Windows the allocated timeHowever, sometimes you need to dig deeper. The time candidate that allowed me to change the timing of the system was enabled me to jump on the actual window in which an event occurred. Using the start and end dates, I can only detect important records.

4. Since then until now: For continuous investigations, the “date of starting date to the current” option was used to track events over time, and to capture all the information nuggets that lead to the present time.

Liquidation records by severity – You will be able to filter the records based on severity, such as error, alert, critical, information, correction, and other intensity. This is useful for narrowing attention to specific types of record related to what is under investigation.

Liquidation records via inquiries – Please use the following query sample to filter records. Customize and adapt it according to your needs to match your requirements.

resource.type="k8s_container"
resource.labels.project_id="e-caldron-448519-s5"
resource.labels.location="us-central1"
resource.labels.cluster_name="singh-deployment-cluster"
resource.labels.namespace_name="default"
labels.k8s-pod/app="singh-deployment"

Liquidation records via tracking – The query below is an example of how to use tracking to analyze requests via containers.

resource.type="k8s_container"
resource.labels.project_id="e-caldron-448519-s5"
resource.labels.location="us-central1"
resource.labels.cluster_name="singh-deployment-cluster"
resource.labels.namespace_name="default"
labels.k8s-pod/app="singh-deployment"
jsonPayload.trace_id = "1ab527ht67lkhjddg876nhdkd"

Lessons learned from the Google Register Explorer

Working with Google Cloud was a transformative experience, allowing me to master registration analysis techniques and gain valuable visions in the most common problems in Kubernetes.

1. Crashlooopbackoff One of the most prevalent problems, which causes the lack of pods, which leads to poor user experience due to the lack of service.
2. The image is not available Because of the organizational policy, old images are deleted and see the Crash episode.
3. Missing composition In rare cases, if a developer forgets to include some composition in order to provide it for the centuries, the centuries may be disrupted in a ring.
4. Cellar Personal definition information is kept to cloud cellars, and services cannot make a connection to the title, which leads to a crash ring.
5. Code problem – The crash ring occurs when developers pay an unreasonable symbol to Kubernetes and its application.
6. The certificate has expired – The rounded Google Keys Ring is broken due to a lack of renewal.
7. Continuous POD Restart Unusually, it continues to restart the pods of the application and this may be due to the Outofmemory error caused by the exhaustion of the system (i.e. resource shortages).
8. Network related problems – In small services structures, the service can participate in multiple communications between different services, where one of the services is broken, or as it denies the wall of protection for another communication service.

Can we reduce the risk of stopping work in the cloud?

However, problems cannot be avoided, however, proactive steps can be taken to reduce risks and improve the end user experience. Google monitors allows the construction of alerts, which they must inform developers and production support employees of the response well, immediately, proactively.

Let’s see how to create a cloud monitoring policy on Google

What are the Google Cloud notification channels that can be configured in the above policy.

It is not actually known tools that would distinguish you from others in the field of various and continuous cloud computing, but how these tools are already used to solve problems in the real world. My practical experience with Google Log Explorer brought me to realize that even the strongest tools require a personal touch to extract their real potential. I learned to discover patterns in repeated failures, isolate even the most accurate anomalies in the records, and to derive from them that can be implemented in order to prevent stopping. One of my largest fast food is how to convert initial data into an enforceable steps, whether it is refining formations or a proactive solution to resource restrictions. It is not just a solution to problems, but rather to predict these problems in advance.