I have done the analysis of the operating margin with the financial results from three major companies in Japan.
Rakuten Inc: The company shows a consistent positive operating margin for the Year 2018 & 2019. However, the company’s operating income was reduced due to heavy investment in the telecom sector.
Z-Holdings Inc: Z-holdings is an outperformer for competition in the eCommerce and digital payment industry. It holds digital payments as PayPay in Japan and as well Yahoo! Japan eCommerce business.
Mercari Inc: A startup company based in the US and majorly operates in the US & Japan. Its business is in eCommerce and digital payment in Japan. After losses in operating income for 2018 & 2019 Mercari Inc has shown a positive outcome in the Year 2020.
In shared linux server environment it is important to track the usage of high CPU consuming processes.
If you are administrator then following command is useful to check top 10 CPU consuming processes on linux:
$ ps aux | sort -nrk 3,3 | head -n 10
It will give you result of the top 10 cpu consuming process.
This is 1m read article written by Kuberneteslab. In this article we will discuss about the keep action for keeping certain metrics in Prometheus and dropping everything else.
Prometheus provides rich features like dropping the metrics and keeping the metrics which can specified under job configuration.
To keep the specific metric:
__name__ indicates the metric name by default. With the config above for job-1 it will scrape only metrics which are matching regex provided in configuration.
Metric relabeling is applied to samples as the last step before ingestion. Make sure the configuration uses “metric_relabel_configs”.
This is 1m read article written by Kuberneteslab. In this article we will discuss about the disk statistics and how to view it through terminal ?
As a linux administrator or devops engineer it is important to know disk usage of the servers. Due to heavy write disk usage might go up and eventually server can run out of disk.
To check the usage of the disk we can use the df command on terminal.
Just df command:
For human readable form “-h” option is useful. It will show data in units(Gi,Ki,Mi,Bi):
To view statistics only for local…
In this article we will look into some commands to get resources from Kubernetes cluster using Kubectl.
To get the resource of the objects within Kubernetes Cluster:
To get pod from namespace kuberneteslab:
$ kubectl get pod -n kuberneteslab
If you do not specify the namespace then you will get the result from “default” namespace.
To get deployment from namespace kuberneteslab:
$ kubectl get deployment -n kuberneteslab
To get replicasets from namespace kuberneteslab:
$ kubectl get replicaset -n kuberneteslab
To get service from namespace kuberneteslab:
$ kubectl get service -n kuberneteslab
To get persistent volume from namespace kuberneteslab:
Prometheus does provide many configs for service discovery. It’s very easy to discover the targets from consul, kubernetes & mesos, etc.However, there are certain use cases where we maybe need to add static configs. With growing infrastructure and monitoring targets, it may be possible that the static configs will become hard to maintain. Because of this file-based discovery is a convenient way to manage such configs.
Its very simple and only three-step is needed to configure this:
Maintenance or abnormal node requires the graceful termination of the pods running on the node. Graceful termination is the operation where pods on the node will complete all running activities (for example serving HTTP requests) before the termination. But however, it’s required to run that pod somewhere else at the same time(evicting the pod).
Kubernetes supports the Node draining functionality through its API. It will evict/ delete the pods except for the mirror pods. Mirror pods are created by a kubelet in the kube-api server for each static pod kubelet created. Static pods are really important in terms of deploying…
We are running the Prometheus as our white-box monitoring solution for the last 1 and a half years. Following are the point’s to be noted:
1. For capacity sample size should be observed with time. Prometheus metrics for Prometheus itself should be exposed. For reliability cross data center/cross-environment of monitoring should be enabled for Prometheus. Metrics(Prometheus metrics)should be collected with cross data center / cross environment.
2. Recording rules must be added. For the most expensive CPU based queries all queries must be optimized. Recording rules should be added to all the expensive queries.
Typhoon Faxai is approaching Japan. Already the emergency alert is received for the people living in Tokyo, Kawasaki, Chiba and Yokohama area.
It will be good if people will stay indoors. The storm information is available on https://google.org/crisismap/google.com/2019-faxai
According to forecast typhoon Faxai will reach Tokyo at 9.00 PM JST.
Credit (images) : Japan Meteorological Agency
Prometheus is an excellent tool for collecting the metrics. In the previous article, I have explained the different data type of Prometheus. If you missed it please view this article here.
Sometimes we need to implement the custom exporter for Prometheus. For example, if I am having metrics already present in another system then I just need to export it. In such cases you might to SET the value for the counter. However, the counter is not designed for setting up the value. Gauge type will do that for you. There are numerous exporters are already available in Prometheus.