Cabot an Opensource Tool for Monitoring and Alerting
Monitoring and Alerting are the most important words in DevOps world. Today we …
Monitoring and Alerting are the most important words in DevOps world. Today we are going to see how to install Cabot tool for monitoring and alerting.
Requirements:
1. docker and docker-compose
2.Git tool
3.Graphite server
Steps 1: Clone Cabot repository in local.
git clone https://github.com/cabotapp/docker-cabot
Steps 2: Update the settings based on our needs.
cd docker-cabot/conf
mv production.env.example production.env
Step 3: Install Cabot via docker-compose
cd docker-cabot
docker-compose up -d
Wait for few minutes until the containers are comes up
Step 4: Login to Cabot portal
URL : http://localhost:5000/
Initially it will ask to setup username and login details.
Step 5: Setup a simple service and checks.
There are three options to Monitor in Cabot, they are instance, check and service.
"Check" is some particular task you want to run to check something. Checks can be of some predefined types, like:
ping: a ping to a host
HTTP: call an URL and check the HTTP status.
"Instance" is an actual instance of a machine that will have some service running. It will have a IP/hostname.
"Service" is the macro stuff you want to monitor.
Am running a nginx webserver locally, will enable check for that.
After login go to checks Tab and click the "+" icon and rest add similar like below,
After saved the configuration,
Step 6: Test the Alert
Lets stop the nginx webserver and see if we are getting an email.
Successfully received an email.
Ref: https://github.com/cabotapp/docker-cabot
What is Hypertrace: It is a cloud-native distributed tracing based observability platform that gives visibility into any environment distributed system. It converts distributed trace data into relevant insight for everyone.
Hypertrace supports all standard instrumentation libraries and agents. If your application is already instrumented with OpenTelemetry, Jaeger or Zipkin, Hypertrace will work out of the box with your application telemetry data.
Requirements:
- Docker engine & Docker compose
Step 1: Clone and Install hypertrace,
# git clone https://github.com/hypertrace/hypertrace.git
# cd hypertrace/docker
# docker-compose pull
# docker-compose up --force-recreate
Step 2: Access Hypertrace Dashboard
Once step 1 is completed successfully, We can access the Hypertrace dashboard from the browser.
URL: http://IP of the VM:2020
Step 3: Sample Application test with Hypertrace
The above-cloned repo is having a sample application which is having frontend and backend APIs and it sends data to Zipkin. Let's check that.
# cd hypertrace/docker
# docker-compose -f docker-compose-zipkin-example.yml up
Once the containers are up, we can check the frontend in the browser by,
URL: http://IP of the VM:8081
Step 4: View the metrics in Hypertrace
Hit the frontend URL multiple times and see Hypertrace dashboard to see the data.
We can see the list of APIs, Errors, latency, etc. Here are few screenshots.
Ref. : https://github.com/hypertrace/hypertrace
https://docs.hypertrace.org/
As a DevOps/SRE, We used to write terraform code, Kubernetes Yaml, Dockerfile, etc. In order to make sure our code is healthy, we need to have a tool to get a visibility of any security issues and vulnerabilities.
In this blog, We will see how to use the "checkov" tool to identify vulnerability and issues in terraform script, Dockerfile, and K8s deployment manifest.
For more details about checkov : https://github.com/bridgecrewio/checkov
Requirements:
OS : Linux
Python >= 3.7
Terraform >= 0.12
Checkov Installation:
# pip install checkov
To find the installed version,
# checkov --version
All the list of checks can be view by below command,
# checkov --list
Next, we will experiment with checkov with Terraform Code, K8s Yaml file and Dockerfile.
Check Terraform code with checkov:
Cmd:
# checkov -d path-of-the-Tf-scripts
eg :
# checkov -d /root/terraform-code
Under this terraform-code directory, I have multiple scripts.
In the checkov result, we can see what action needs to take. In the below result we can see 26 checks are failed, so we can validate one by one and fix it.
Check Dockerfile with checkov:
Cmd:
# checkov -f dockerfile-path
eg :
# checkov -f /root/Dockerfile
In the above screenshot result, we can see 2 checks are failed, so we can validate one by one and fix it.
Check Kubernetes deployment file with checkov:
Cmd:
# checkov -f Yaml-file-path
eg :
# checkov -f /root/pod.yaml
In the above screenshot result, we can see 20 checks are failed, so we can validate one by one and fix it.
We can skip the checks in the command,
eg : checkov -f /root/Dockerfile --skip-check CKV_AWS_28
That's all, we have installed checkov and tested with some terraform code, dockerfile and K8s yaml file.
Nowadays every organization is using Kubernetes orchestration for Dev, QA, Prod, etc. environments. Today we are going to see a tool called "Octant" which helps all the users to understand their cluster status, view the logs, update the meta data, see the resources utilization, etc. In this blog will cover how to do the installation.
Requirements:
1.K8s cluster
2.Local desktop
Step 1: Installation of Octant,
The installation will be on the local machine not on the cluster.
OS : Linux (Installer are available for Windows and Mac as well)
Octant package to download : https://github.com/vmware-tanzu/octant/releases
Download the linux package in you local and extract it.
https://github.com/vmware-tanzu/octant/releases/download/v0.24.0/octant_0.24.0_Linux-64bit.tar.gz
Step 2: K8s cluster config
Keep your kubernetes cluster config at below path.
/root/.kube/config
By default octant will search the cluster configuration from above path.
Step 3: Start Octant
Go to the extracted path and start it,
cd octant_0.24.0_Linux-64bit
./octant
At the end you will get a message as "Dashboard is available at http://127.0.0.1:7777" it means its successfully started and we can access the dashboard.
Step 4: Access Octant dashboard
Go to browser and enter, http://localhost:7777
You can see your cluster name at the top right and you can select the namespace near to the cluster name to show the entire details. Through this we can view the Metadata, Logs, Update the deployments, etc.
Thats all we have successfuly installed the Octant dashboard and view the status of the cluster.
Do you want to apply any policy to avoid any changes happen in Kubernetes cluster? Kyverno is the right tool to achieve it.
Kyverno - Its a policy engine for kubernetes, define and enforce policies so that cluster users can maintain standard mechanism.
In this blog, we will see how to install Kyverno in Kubernetes and define policy.
Requirements:
Kubernetes cluster greater than v1.14
Step 1: Install Kyverno on kubernetes using manifest.
# kubectl create -f https://raw.githubusercontent.com/kyverno/kyverno/master/definitions/release/install.yaml
Validate the installation,Step 2:
Create a policy that without label "app" in pod it should not deploy in cluster.
#cat policy.yaml
# kubectl apply -f policy.yaml
Now policy is created, Hereafter if any deployment without label "app" it will not deploy in the cluster.
For more Policies : https://github.com/kyverno/policies/tree/main/best-practices
Step 3:
Create a sample pod deployment without label "app"
In this blog we will see step by step to install Cadvisor, NodeExporter, Prometheus, Grafana to monitor docker containers and its hosts.
Note : We are going to use only docker images for all the tools.
Requirements:
Docker running Linux server : 1
Step 1:
Deploy Cadvisor in docker:
Cadvisor : It provides container resource usage and performance characteristics of their running containers.
Execute the below docker command in linux server,
# docker run -d -p 8080:8080 -v /:/rootfs:ro -v /var/run:/var/run:rw -v /sys:/sys:ro -v /var/lib/docker/:/var/lib/docker:ro --name=cadvisor google/cadvisor:latest
We can access Cadvisor in browser by http://server-IP:8080
Step 2:
Deploy Node-Exporter in docker:
Node-Exporter : It helps to measure various machine resources like as CPU, memory, disk and network utilization.
Execute the below docker command in linux server,
# docker run -d -p 9100:9100 --name=node-exporter prom/node-exporter
We can access Node-Exporter metrics in browser by http://server-IP:9100/metrics
Step 3:
Deploy Prometheus in docker:
To deploy Prometheus, we need to create configuration file for prometheus like below,
#vi /root/config/prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['Host-IP:9090']
labels:
alias: 'prometheus'
- job_name: 'cadvisor'
static_configs:
- targets: ['Host-IP:8080']
labels:
alias: 'cadvisor'
- job_name: 'node-exporter'
static_configs:
- targets: ['Host-IP:9100']
labels:
alias: 'node-exporter'
Save the file.
Here Cadvisor, Node-exporter metrics details are given.
Now run the Prometheus docker command,
# docker run -d -p 9090:9090 -v /root/config/prometheus.yml:/etc/prometheus/prometheus.yml --name=prometheus prom/prometheus
We can access Prometheus metrics in browser by http://server-IP:9090/metrics
Monitoring and Alerting are the most important words in DevOps world. Today we are going to see how to install Cabot tool for monitoring and alerting.
Requirements:
1. docker and docker-compose
2.Git tool
3.Graphite server
Steps 1: Clone Cabot repository in local.
git clone https://github.com/cabotapp/docker-cabot
Steps 2: Update the settings based on our needs.
cd docker-cabot/conf
mv production.env.example production.env
Step 3: Install Cabot via docker-compose
cd docker-cabot
docker-compose up -d
Wait for few minutes until the containers are comes up
Step 4: Login to Cabot portal
URL : http://localhost:5000/
Initially it will ask to setup username and login details.
Step 5: Setup a simple service and checks.
There are three options to Monitor in Cabot, they are instance, check and service.
"Check" is some particular task you want to run to check something. Checks can be of some predefined types, like:
ping: a ping to a host
HTTP: call an URL and check the HTTP status.
"Instance" is an actual instance of a machine that will have some service running. It will have a IP/hostname.
"Service" is the macro stuff you want to monitor.
Am running a nginx webserver locally, will enable check for that.
After login go to checks Tab and click the "+" icon and rest add similar like below,
After saved the configuration,
Step 6: Test the Alert
Lets stop the nginx webserver and see if we are getting an email.
Successfully received an email.
Ref: https://github.com/cabotapp/docker-cabot
What is Hypertrace: It is a cloud-native distributed tracing based observability platform that gives visibility into any environment distributed system. It converts distributed trace data into relevant insight for everyone.
Hypertrace supports all standard instrumentation libraries and agents. If your application is already instrumented with OpenTelemetry, Jaeger or Zipkin, Hypertrace will work out of the box with your application telemetry data.
Requirements:
- Docker engine & Docker compose
Step 1: Clone and Install hypertrace,
# git clone https://github.com/hypertrace/hypertrace.git
# cd hypertrace/docker
# docker-compose pull
# docker-compose up --force-recreate
Step 2: Access Hypertrace Dashboard
Once step 1 is completed successfully, We can access the Hypertrace dashboard from the browser.
URL: http://IP of the VM:2020
Step 3: Sample Application test with Hypertrace
The above-cloned repo is having a sample application which is having frontend and backend APIs and it sends data to Zipkin. Let's check that.
# cd hypertrace/docker
# docker-compose -f docker-compose-zipkin-example.yml up
Once the containers are up, we can check the frontend in the browser by,
URL: http://IP of the VM:8081
Step 4: View the metrics in Hypertrace
Hit the frontend URL multiple times and see Hypertrace dashboard to see the data.
We can see the list of APIs, Errors, latency, etc. Here are few screenshots.
Ref. : https://github.com/hypertrace/hypertrace
https://docs.hypertrace.org/
As a DevOps/SRE, We used to write terraform code, Kubernetes Yaml, Dockerfile, etc. In order to make sure our code is healthy, we need to have a tool to get a visibility of any security issues and vulnerabilities.
In this blog, We will see how to use the "checkov" tool to identify vulnerability and issues in terraform script, Dockerfile, and K8s deployment manifest.
For more details about checkov : https://github.com/bridgecrewio/checkov
Requirements:
OS : Linux
Python >= 3.7
Terraform >= 0.12
Checkov Installation:
# pip install checkov
To find the installed version,
# checkov --version
All the list of checks can be view by below command,
# checkov --list
Next, we will experiment with checkov with Terraform Code, K8s Yaml file and Dockerfile.
Check Terraform code with checkov:
Cmd:
# checkov -d path-of-the-Tf-scripts
eg :
# checkov -d /root/terraform-code
Under this terraform-code directory, I have multiple scripts.
In the checkov result, we can see what action needs to take. In the below result we can see 26 checks are failed, so we can validate one by one and fix it.
Check Dockerfile with checkov:
Cmd:
# checkov -f dockerfile-path
eg :
# checkov -f /root/Dockerfile
In the above screenshot result, we can see 2 checks are failed, so we can validate one by one and fix it.
Check Kubernetes deployment file with checkov:
Cmd:
# checkov -f Yaml-file-path
eg :
# checkov -f /root/pod.yaml
In the above screenshot result, we can see 20 checks are failed, so we can validate one by one and fix it.
We can skip the checks in the command,
eg : checkov -f /root/Dockerfile --skip-check CKV_AWS_28
That's all, we have installed checkov and tested with some terraform code, dockerfile and K8s yaml file.
Nowadays every organization is using Kubernetes orchestration for Dev, QA, Prod, etc. environments. Today we are going to see a tool called "Octant" which helps all the users to understand their cluster status, view the logs, update the meta data, see the resources utilization, etc. In this blog will cover how to do the installation.
Requirements:
1.K8s cluster
2.Local desktop
Step 1: Installation of Octant,
The installation will be on the local machine not on the cluster.
OS : Linux (Installer are available for Windows and Mac as well)
Octant package to download : https://github.com/vmware-tanzu/octant/releases
Download the linux package in you local and extract it.
https://github.com/vmware-tanzu/octant/releases/download/v0.24.0/octant_0.24.0_Linux-64bit.tar.gz
Step 2: K8s cluster config
Keep your kubernetes cluster config at below path.
/root/.kube/config
By default octant will search the cluster configuration from above path.
Step 3: Start Octant
Go to the extracted path and start it,
cd octant_0.24.0_Linux-64bit
./octant
At the end you will get a message as "Dashboard is available at http://127.0.0.1:7777" it means its successfully started and we can access the dashboard.
Step 4: Access Octant dashboard
Go to browser and enter, http://localhost:7777
You can see your cluster name at the top right and you can select the namespace near to the cluster name to show the entire details. Through this we can view the Metadata, Logs, Update the deployments, etc.
Thats all we have successfuly installed the Octant dashboard and view the status of the cluster.
Do you want to apply any policy to avoid any changes happen in Kubernetes cluster? Kyverno is the right tool to achieve it.
Kyverno - Its a policy engine for kubernetes, define and enforce policies so that cluster users can maintain standard mechanism.
In this blog, we will see how to install Kyverno in Kubernetes and define policy.
Requirements:
Kubernetes cluster greater than v1.14
Step 1: Install Kyverno on kubernetes using manifest.
# kubectl create -f https://raw.githubusercontent.com/kyverno/kyverno/master/definitions/release/install.yaml
Validate the installation,Step 2:
Create a policy that without label "app" in pod it should not deploy in cluster.
#cat policy.yaml
# kubectl apply -f policy.yaml
Now policy is created, Hereafter if any deployment without label "app" it will not deploy in the cluster.
For more Policies : https://github.com/kyverno/policies/tree/main/best-practices
Step 3:
Create a sample pod deployment without label "app"
In this blog we will see step by step to install Cadvisor, NodeExporter, Prometheus, Grafana to monitor docker containers and its hosts.
Note : We are going to use only docker images for all the tools.
Requirements:
Docker running Linux server : 1
Step 1:
Deploy Cadvisor in docker:
Cadvisor : It provides container resource usage and performance characteristics of their running containers.
Execute the below docker command in linux server,
# docker run -d -p 8080:8080 -v /:/rootfs:ro -v /var/run:/var/run:rw -v /sys:/sys:ro -v /var/lib/docker/:/var/lib/docker:ro --name=cadvisor google/cadvisor:latest
We can access Cadvisor in browser by http://server-IP:8080
Step 2:
Deploy Node-Exporter in docker:
Node-Exporter : It helps to measure various machine resources like as CPU, memory, disk and network utilization.
Execute the below docker command in linux server,
# docker run -d -p 9100:9100 --name=node-exporter prom/node-exporter
We can access Node-Exporter metrics in browser by http://server-IP:9100/metrics
Step 3:
Deploy Prometheus in docker:
To deploy Prometheus, we need to create configuration file for prometheus like below,
#vi /root/config/prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['Host-IP:9090']
labels:
alias: 'prometheus'
- job_name: 'cadvisor'
static_configs:
- targets: ['Host-IP:8080']
labels:
alias: 'cadvisor'
- job_name: 'node-exporter'
static_configs:
- targets: ['Host-IP:9100']
labels:
alias: 'node-exporter'
Save the file.
Here Cadvisor, Node-exporter metrics details are given.
Now run the Prometheus docker command,
# docker run -d -p 9090:9090 -v /root/config/prometheus.yml:/etc/prometheus/prometheus.yml --name=prometheus prom/prometheus
We can access Prometheus metrics in browser by http://server-IP:9090/metrics
Monitoring and Alerting are the most important words in DevOps world. Today we are going to see how to install Cabot tool for monitoring and alerting.
Requirements:
1. docker and docker-compose
2.Git tool
3.Graphite server
Steps 1: Clone Cabot repository in local.
git clone https://github.com/cabotapp/docker-cabot
Steps 2: Update the settings based on our needs.
cd docker-cabot/conf
mv production.env.example production.env
Step 3: Install Cabot via docker-compose
cd docker-cabot
docker-compose up -d
Wait for few minutes until the containers are comes up
Step 4: Login to Cabot portal
URL : http://localhost:5000/
Initially it will ask to setup username and login details.
Step 5: Setup a simple service and checks.
There are three options to Monitor in Cabot, they are instance, check and service.
"Check" is some particular task you want to run to check something. Checks can be of some predefined types, like:
ping: a ping to a host
HTTP: call an URL and check the HTTP status.
"Instance" is an actual instance of a machine that will have some service running. It will have a IP/hostname.
"Service" is the macro stuff you want to monitor.
Am running a nginx webserver locally, will enable check for that.
After login go to checks Tab and click the "+" icon and rest add similar like below,
After saved the configuration,
Step 6: Test the Alert
Lets stop the nginx webserver and see if we are getting an email.
Successfully received an email.
Ref: https://github.com/cabotapp/docker-cabot
What is Hypertrace: It is a cloud-native distributed tracing based observability platform that gives visibility into any environment distributed system. It converts distributed trace data into relevant insight for everyone.
Hypertrace supports all standard instrumentation libraries and agents. If your application is already instrumented with OpenTelemetry, Jaeger or Zipkin, Hypertrace will work out of the box with your application telemetry data.
Requirements:
- Docker engine & Docker compose
Step 1: Clone and Install hypertrace,
# git clone https://github.com/hypertrace/hypertrace.git
# cd hypertrace/docker
# docker-compose pull
# docker-compose up --force-recreate
Step 2: Access Hypertrace Dashboard
Once step 1 is completed successfully, We can access the Hypertrace dashboard from the browser.
URL: http://IP of the VM:2020
Step 3: Sample Application test with Hypertrace
The above-cloned repo is having a sample application which is having frontend and backend APIs and it sends data to Zipkin. Let's check that.
# cd hypertrace/docker
# docker-compose -f docker-compose-zipkin-example.yml up
Once the containers are up, we can check the frontend in the browser by,
URL: http://IP of the VM:8081
Step 4: View the metrics in Hypertrace
Hit the frontend URL multiple times and see Hypertrace dashboard to see the data.
We can see the list of APIs, Errors, latency, etc. Here are few screenshots.
Ref. : https://github.com/hypertrace/hypertrace
https://docs.hypertrace.org/
As a DevOps/SRE, We used to write terraform code, Kubernetes Yaml, Dockerfile, etc. In order to make sure our code is healthy, we need to have a tool to get a visibility of any security issues and vulnerabilities.
In this blog, We will see how to use the "checkov" tool to identify vulnerability and issues in terraform script, Dockerfile, and K8s deployment manifest.
For more details about checkov : https://github.com/bridgecrewio/checkov
Requirements:
OS : Linux
Python >= 3.7
Terraform >= 0.12
Checkov Installation:
# pip install checkov
To find the installed version,
# checkov --version
All the list of checks can be view by below command,
# checkov --list
Next, we will experiment with checkov with Terraform Code, K8s Yaml file and Dockerfile.
Check Terraform code with checkov:
Cmd:
# checkov -d path-of-the-Tf-scripts
eg :
# checkov -d /root/terraform-code
Under this terraform-code directory, I have multiple scripts.
In the checkov result, we can see what action needs to take. In the below result we can see 26 checks are failed, so we can validate one by one and fix it.
Check Dockerfile with checkov:
Cmd:
# checkov -f dockerfile-path
eg :
# checkov -f /root/Dockerfile
In the above screenshot result, we can see 2 checks are failed, so we can validate one by one and fix it.
Check Kubernetes deployment file with checkov:
Cmd:
# checkov -f Yaml-file-path
eg :
# checkov -f /root/pod.yaml
In the above screenshot result, we can see 20 checks are failed, so we can validate one by one and fix it.
We can skip the checks in the command,
eg : checkov -f /root/Dockerfile --skip-check CKV_AWS_28
That's all, we have installed checkov and tested with some terraform code, dockerfile and K8s yaml file.
Nowadays every organization is using Kubernetes orchestration for Dev, QA, Prod, etc. environments. Today we are going to see a tool called "Octant" which helps all the users to understand their cluster status, view the logs, update the meta data, see the resources utilization, etc. In this blog will cover how to do the installation.
Requirements:
1.K8s cluster
2.Local desktop
Step 1: Installation of Octant,
The installation will be on the local machine not on the cluster.
OS : Linux (Installer are available for Windows and Mac as well)
Octant package to download : https://github.com/vmware-tanzu/octant/releases
Download the linux package in you local and extract it.
https://github.com/vmware-tanzu/octant/releases/download/v0.24.0/octant_0.24.0_Linux-64bit.tar.gz
Step 2: K8s cluster config
Keep your kubernetes cluster config at below path.
/root/.kube/config
By default octant will search the cluster configuration from above path.
Step 3: Start Octant
Go to the extracted path and start it,
cd octant_0.24.0_Linux-64bit
./octant
At the end you will get a message as "Dashboard is available at http://127.0.0.1:7777" it means its successfully started and we can access the dashboard.
Step 4: Access Octant dashboard
Go to browser and enter, http://localhost:7777
You can see your cluster name at the top right and you can select the namespace near to the cluster name to show the entire details. Through this we can view the Metadata, Logs, Update the deployments, etc.
Thats all we have successfuly installed the Octant dashboard and view the status of the cluster.
Do you want to apply any policy to avoid any changes happen in Kubernetes cluster? Kyverno is the right tool to achieve it.
Kyverno - Its a policy engine for kubernetes, define and enforce policies so that cluster users can maintain standard mechanism.
In this blog, we will see how to install Kyverno in Kubernetes and define policy.
Requirements:
Kubernetes cluster greater than v1.14
Step 1: Install Kyverno on kubernetes using manifest.
# kubectl create -f https://raw.githubusercontent.com/kyverno/kyverno/master/definitions/release/install.yaml
Validate the installation,Step 2:
Create a policy that without label "app" in pod it should not deploy in cluster.
#cat policy.yaml
# kubectl apply -f policy.yaml
Now policy is created, Hereafter if any deployment without label "app" it will not deploy in the cluster.
For more Policies : https://github.com/kyverno/policies/tree/main/best-practices
Step 3:
Create a sample pod deployment without label "app"
In this blog we will see step by step to install Cadvisor, NodeExporter, Prometheus, Grafana to monitor docker containers and its hosts.
Note : We are going to use only docker images for all the tools.
Requirements:
Docker running Linux server : 1
Step 1:
Deploy Cadvisor in docker:
Cadvisor : It provides container resource usage and performance characteristics of their running containers.
Execute the below docker command in linux server,
# docker run -d -p 8080:8080 -v /:/rootfs:ro -v /var/run:/var/run:rw -v /sys:/sys:ro -v /var/lib/docker/:/var/lib/docker:ro --name=cadvisor google/cadvisor:latest
We can access Cadvisor in browser by http://server-IP:8080
Step 2:
Deploy Node-Exporter in docker:
Node-Exporter : It helps to measure various machine resources like as CPU, memory, disk and network utilization.
Execute the below docker command in linux server,
# docker run -d -p 9100:9100 --name=node-exporter prom/node-exporter
We can access Node-Exporter metrics in browser by http://server-IP:9100/metrics
Step 3:
Deploy Prometheus in docker:
To deploy Prometheus, we need to create configuration file for prometheus like below,
#vi /root/config/prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['Host-IP:9090']
labels:
alias: 'prometheus'
- job_name: 'cadvisor'
static_configs:
- targets: ['Host-IP:8080']
labels:
alias: 'cadvisor'
- job_name: 'node-exporter'
static_configs:
- targets: ['Host-IP:9100']
labels:
alias: 'node-exporter'
Save the file.
Here Cadvisor, Node-exporter metrics details are given.
Now run the Prometheus docker command,
# docker run -d -p 9090:9090 -v /root/config/prometheus.yml:/etc/prometheus/prometheus.yml --name=prometheus prom/prometheus
We can access Prometheus metrics in browser by http://server-IP:9090/metrics
Monitoring and Alerting are the most important words in DevOps world. Today we …
In this blog, we will see how to install Hypertrace for the docker container ap…
As a DevOps/SRE, We used to write terraform code, Kubernetes Yaml, Dockerfile, …
Nowadays every organization is using Kubernetes orchestration for Dev, QA, Prod…
Do you want to apply any policy to avoid any changes happen in Kubernetes clust…
In this blog we will see step by step to install Cadvisor, NodeExporter, Prom…