Logging

OpenSearch Operator

Step by step instructions: How to deploy OpenSearch Operator inside Kubernetes Cluster (EKS)

Prerequirements

Install Helm

brew install helm
brew install helmfile
brew install kubectl

Add Plugin Helm

helm plugin install https://github.com/databus23/helm-diff
helm plugin install https://github.com/hypnoglow/helm-s3.git

Add Helm Repository S3 Bucket

### LAB ### helm s3 init s3://devopscorner-helm-chart/lab AWS_REGION=ap-southeast-1 helm repo add devopscorner-lab s3://devopscorner-helm-chart/lab ### STAGING ### helm s3 init s3://devopscorner-helm-chart/staging AWS_REGION=ap-southeast-1 helm repo add devopscorner-staging s3://devopscorner-helm-chart/staging ### PRODUCTION ### helm s3 init s3://devopscorner-helm-chart/prod AWS_REGION=ap-southeast-1 helm repo add devopscorner s3://devopscorner-helm-chart/prod helm repo update

Update Repository

helm repo add stable https://charts.helm.sh/stable
helm repo add opensearch-operator https://opster.github.io/opensearch-k8s-operator/ helm repo update helm repo list

NAME URL
opensearch-operator https://opster.github.io/opensearch-k8s-operator/ stable https://charts.helm.sh/stable

Create Namespace

kubectl create namespace observability

Install OpenSearch Operator

helm install opsearch opensearch-operator/opensearch-operator --create-namespace -n observability

NAME: opsearch LAST DEPLOYED: Sat Nov 4 09:08:25 2023 NAMESPACE: observability STATUS: deployed REVISION: 1 TEST SUITE: None

Install Cluster OpenSearch

Change this default OpenSearch-Cluster.yaml

apiVersion: opensearch.opster.io/v1
kind: OpenSearchCluster
metadata:
  name: my-cluster
  namespace: default
spec:
  general:
    version: "1.3.0"
    httpPort: 9200
    vendor: opensearch
    serviceName: my-cluster
    monitoring:
      enable: true
    pluginsList: ["repository-s3"]
  dashboards:
    version: "1.3.0"
    enable: true
    replicas: 2
    resources:
      requests:
        memory: "1Gi"
        cpu: "500m"
      limits:
        memory: "1Gi"
        cpu: "500m"
  confMgmt:
    smartScaler: true
  nodePools:
    - component: masters
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "master"
        - "data"
    - component: nodes
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "data"
    - component: coordinators
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "ingest"

LAB Configuration (Simple Cluster)

apiVersion: opensearch.opster.io/v1
kind: OpenSearchCluster
metadata:
  name: opsearch
  namespace: observability
spec:
  general:
    version: "1.3.0"
    httpPort: 9200
    vendor: opensearch
    serviceName: opsearch
    monitoring:
      enable: true
    pluginsList: ["repository-s3"]
  dashboards:
    version: "1.3.0"
    enable: true
    replicas: 1
    nodeSelector:
      node: devopscorner-monitoring
    resources:
      requests:
        memory: "200Mi"
        cpu: "500m"
      limits:
        memory: "512Mi"
        cpu: "500m"
  confMgmt:
    smartScaler: true
  nodePools:
    - component: masters
      replicas: 2
      diskSize: "10Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "master"
        - "data"

LAB Configuration (HA Cluster)

apiVersion: opensearch.opster.io/v1
kind: OpenSearchCluster
metadata:
  name: opsearch
  namespace: observability
spec:
  general:
    version: "1.3.0"
    httpPort: 9200
    vendor: opensearch
    serviceName: opsearch
    monitoring:
      enable: true
    pluginsList: ["repository-s3"]
  dashboards:
    version: "1.3.0"
    enable: true
    replicas: 1
    nodeSelector:
      node: devopscorner-monitoring
    resources:
      requests:
        memory: "200Mi"
        cpu: "500m"
      limits:
        memory: "512Mi"
        cpu: "500m"
  confMgmt:
    smartScaler: true
  nodePools:
    - component: masters
      replicas: 2
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "master"
        - "data"
    - component: nodes
      replicas: 2
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "data"
    - component: coordinators
      replicas: 2
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "ingest"

Production Configuration (HA Cluster)

apiVersion: opensearch.opster.io/v1
kind: OpenSearchCluster
metadata:
  name: opsearch
  namespace: observability
spec:
  general:
    version: "1.3.0"
    httpPort: 9200
    vendor: opensearch
    serviceName: opsearch
    monitoring:
      enable: true
    pluginsList: ["repository-s3"]
  dashboards:
    version: "1.3.0"
    enable: true
    replicas: 2
    nodeSelector:
      node: devopscorner-monitoring
    resources:
      requests:
        memory: "200Mi"
        cpu: "500m"
      limits:
        memory: "1Gi"
        cpu: "500m"
  confMgmt:
    smartScaler: true
  nodePools:
    - component: masters
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "master"
        - "data"
    - component: nodes
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "data"
    - component: coordinators
      replicas: 3
      diskSize: "30Gi"
      nodeSelector:
        node: devopscorner-monitoring
      resources:
        requests:
          memory: "2Gi"
          cpu: "500m"
        limits:
          memory: "2Gi"
          cpu: "500m"
      roles:
        - "ingest"

Apply manifest

kubectl create -f opensearch-cluster.yaml -n observability

Access Portforward

kubectl get po -n observability  

NAME READY STATUS RESTARTS AGE alertmanager-prometheus-kube-prometheus-alertmanager-0 2/2 Running 0 40m opsearch-coordinators-0 1/1 Running 0 9m57s opsearch-coordinators-1 1/1 Running 0 10m opsearch-dashboards-7fcc5595c7-fhf28 1/1 Running 0 22m opsearch-masters-0 1/1 Running 0 10m opsearch-masters-1 1/1 Running 0 13m opsearch-nodes-0 1/1 Running 0 9m59s opsearch-nodes-1 1/1 Running 0 13m opsearch-opensearch-operator-controller-manager-7cc6dd6fd8qx5xd 2/2 Running 0 37m

kubectl get po opsearch-dashboards-7fcc5595c7-fhf28 -n observability

NAME READY STATUS RESTARTS AGE opsearch-dashboards-7fcc5595c7-fhf28 1/1 Running 0 23m

kubectl get po opsearch-dashboards-7fcc5595c7-fhf28 -n observability

... Containers: dashboards:
Container ID: containerd://02966406e8e5d2c9cef7c1e139b74887537386111374e29cf5c50ab3cbda19ae
Image: docker.io/opensearchproject/opensearch-dashboards:1.3.0
Image ID: docker.io/opensearchproject/opensearch-dashboards@sha256:7dcc706ab6c71ab00013e341246e7a701c11c61a7668e4dbecd298d6d7aef758
Port: 5601/TCP
Host Port: 0/TCP ...

kubectl port-forward opsearch-dashboards-7fcc5595c7-fhf28 5601:8080 -n observability

Forwarding from 127.0.0.1:5601 -> 8080 Forwarding from [::1]:5601 -> 8080

UserName: admin Password: admin

Setup Pattern

Goto Stack Management

Create Index Pattern

Select Index Pattern

Setup Timestamp for sorting Index Pattern

Discover Logs

Using Network LoadBalancer (NLB) via NGINX Controller

Get Deployment Manifest

wget https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/static/provider/aws/deploy.yaml

Change Manifest

sed -i 's/externalTrafficPolicy: Local/externalTrafficPolicy: Cluster/g' deploy.yaml

Deploy Manifest

kubectl create -f deploy.yaml

Expose LB for OpenSearch Dashboard

kubectl expose deployment opsearch-dashboards --name=opensearch-lb --type=LoadBalancer --port=80 --target-port=5601 --protocol=TCP --namespace=observability

Helm Release Version

helm list --all-namespaces helm list --namespace=observability

[RFC] Rate Limits API Requests

This documentation refer to rate limits of AWS and Datadog API.

A. AWS Throttle API Requests

References:
https://docs.aws.amazon.com/apigateway/latest/developerguide/api-gateway-request-throttling.html

Account-level throttling per Region

By default, API Gateway limits the steady-state requests per second (rps) across all APIs within an AWS account, per Region. It also limits the burst (that is, the maximum bucket size) across all APIs within an AWS account, per Region. In API Gateway, the burst limit corresponds to the maximum number of concurrent request submissions that API Gateway can fulfill at any moment without returning 429 Too Many Requests error responses. For more information on throttling quotas, see Amazon API Gateway quotas and important notes.

To help understand these throttling limits, here are a few examples, given a burst limit of 5,000 and an account-level rate limit of 10,000 requests per second in the Region:

If a caller submits 10,000 requests in a one-second period evenly (for example, 10 requests every millisecond), API Gateway processes all requests without dropping any.
If the caller sends 10,000 requests in the first millisecond, API Gateway serves 5,000 of those requests and throttles the rest in the one-second period.
If the caller submits 5,000 requests in the first millisecond and then evenly spreads another 5,000 requests through the remaining 999 milliseconds (for example, about 5 requests every millisecond), API Gateway processes all 10,000 requests in the one-second period without returning 429 Too Many Requests error responses.
If the caller submits 5,000 requests in the first millisecond and waits until the 101st millisecond to submit another 5,000 requests, API Gateway processes 6,000 requests and throttles the rest in the one-second period. This is because at the rate of 10,000 rps, API Gateway has served 1,000 requests after the first 100 milliseconds and thus emptied the bucket by the same amount. Of the next spike of 5,000 requests, 1,000 fill the bucket and are queued to be processed. The other 4,000 exceed the bucket capacity and are discarded.
If the caller submits 5,000 requests in the first millisecond, submits 1,000 requests at the 101st millisecond, and then evenly spreads another 4,000 requests through the remaining 899 milliseconds, API Gateway processes all 10,000 requests in the one-second period without throttling.

B. Datadog API

References:
https://docs.datadoghq.com/api/latest/rate-limits/

Rate Limits

All of the API endpoints are rate limited. Once you exceed a certain number of requests in a specific period, Datadog returns an error.

If you are rate limited, you will see a 429 in the response code. Datadog recommends to either wait the time designated by the X-RateLimit-Limit before making calls again, or you should switch to making calls at a frequency slightly longer than the X-RateLimit-Limit / X-RateLimit-Period.

Rate limits can be increased from the defaults by contacting the Datadog support team.

Regarding the API rate limit policy:

Datadog does not rate limit on data point/metric submission (see metrics section for more info on how the metric submission rate is handled). Limits encounter is dependent on the quantity of custom metrics based on your agreement.
The rate limit for metric retrieval is 100 per hour per organization.
The rate limit for event submission is 500,000 events per hour per organization.
The rate limit for event aggregation is 1000 per aggregate per day per organization. An aggregate is a group of similar events.
The rate limit for the Query a Timeseries API call is 1600 per hour per organization. This can be extended on demand.
The rate limit for the Log Query API call is 300 per hour per organization. This can be extended on demand.
The rate limit for the Graph a Snapshot API call is 60 per hour per organization. This can be extended on demand.
The rate limit for the Log Configuration API is 6000 per minute per organization. This can be extended on demand.

Rate Limit Headers	Description
`X-RateLimit-Limit`	number of requests allowed in a time period.
`X-RateLimit-Period`	length of time in seconds for resets (calendar aligned).
`X-RateLimit-Remaining`	number of allowed requests left in the current time period.
`X-RateLimit-Reset`	time in seconds until next reset.

[RFC] Postmortem Report

This is sample postmortem reporting to review chronologies, provide the mitigation from the issue and solving the problem during period time

Title

YYYY-MM-DD Issue Name.
eg:
2020-09-01 Failed to Replicate Database Slave in Node-2.

Issue Summary

Summary of issue that describe all chronologies.
eg:
We had issue in replication slave server database in node-2. This issue running at 07:00 due to can’t connect the slave server DNS to DNS server master. Impacted to unable connected for some of microservices that using slave server as pointing reading / query read to database.

List of microservices impacted:
- Microservices 1: Auth
- Microservices 2: OTP

Impact

List of microservices or other infrastructure resources impacted for this issue.
eg:
Impacted microservices:
- Microservices 1: Auth
- Microservices 2: OTP

Impacted infra:
DNS slave

Trigger

List of trigger issue.
eg:
- Cloud provider running on maintenance starting at 2020-09-01 02:00 GMT+7 and end at 2020-09-01 03:00.
- Some of DNS changed as the impacted of maintenance.

Detection

List of detection issue.
eg:
- Detect on Metrics for failed replication (with snapshot picture)
- Detect on Log for dns changes (with snapshot picture)

Root Cause

List of root cause for the issue.
eg:
- Slave server database in node-2 can’t running due to can’t connect to DNS server master.
- DNS server master had been moved to other pointing address due to cloud provider maintenance.

Timeline

List timeline issue from beginning until end (resolved).
eg:
2020-09-01 07:00 Metrics show failed to replicate the slave server database in node-2
2020-09-01 07:10 Raise the alert on P3 Escalation
2020-09-01 07:12 Oncall ack the issue
2020-09-01 07:15 Taking action for manual replication slave server
2020-09-01 07:30 All Replication had been restored
2020-09-01 07:35 Monitoring phase replication (for about 10-15 minutes)
2020-09-01 08:00 Operation slave server database in node-2 is back to normal

Resolution & Recovery

List of resolution & recovery action
eg:
- Manual replication for slave server
- Repointing DNS slave node-2 to new DNS master

Corrective and Preventive Measurements

List of action item / procedure to make correction & prevention (as mitigation)
eg:
- Update threshold metrics for alerting, raise to P2 for escalation level.
- Raise open ticket for cloud provider dns issue moving impact.

Financial Impact

Product Impacted	Start DateTime – End DateTime	Impact Type (Outage, Error Rates, Latency Spike)	Monitoring Links	Log Links

Detail of Financial Impact

Division / Team Name

List of division / team which impacted for this postmortem

Related documentation for this issue (JIRA / Confluences)

[RFC] Performance Testing K6

Monitoring Dashboard

Monitoring Dashboard URL

Logging Dashboard URL

Operations (Executors)

PIC Name	Department
DevOps Engineer – 1	DevOps
DevOps Engineer – 2	DevOps
QA Engineer – 1	QA
QA Engineer – 2	QA
Software Engineer – 1	Engineering
Software Engineer – 2	Engineering

Supervisors

Supervisor Name	Department	Remark
@zeroc0d3-devops	DevOps
@zeroc0d3-engineer	Engineering
@zeroc0d3-iot	IoT
@zeroc0d3-data	Data

HelmChart

Deployments	Request		Limit
Deployments	CPI (mi)	Mem (mb)	CPU (mi)	Mem (mb)

Performance Test Report

Cycle

Virtual User (vus)

Duration (seconds)

Date / Time

Service

Component

Before

Inprogress

After

Jenkins
Link

Monitoring Link

Remark (Logs)

Start

End

CPU (mi)

Mem (mb)

CPU (mi)

Mem (mb)

CPU (mi)

Mem (mb)

Performance Test Process

After Performance Test Process

EKS

<deployment-name>

RDS

<rds-name>/<db-name>

N/A

References:

K6 Website:    https://k6.io/
K6 SourceCode: https://github.com/grafana/k6

[RFC] Logging

A. Concepts

Standardization export log path and name

eg:
----
/var/log/[microservice-name]/[microservice-name]-error.log   # error only
/var/log/[microservice-name]/[microservice-name].log         # info, warning & debug

Log using JSON formatted

Severity logs & formatting logs

eg: INFO
---
{
  "datetime": "2020-10-10 20:01:59TZ+0700"
  "severity": "info",
  "message": "yes, this is info"
}

eg: WARNING
---
{
  "datetime": "2020-10-10 20:01:59TZ+0700"
  "severity": "warning",
  "message": "this is warning"
}

eg: ERROR
---
{
  "datetime": "2020-10-10 20:01:59TZ+0700"
  "severity": "error",
  "code": 404
  "message": "not found"
}

eg: DEBUG (optional)
---
{
  "datetime": "2020-10-10 20:01:59TZ+0700"
  "severity": "debug",
  "code": 100
  "message": "describe debug information (criteria by number) "
}

Logrotation & compression

# /etc/logrotate.d/[microservice-name]
---
/var/log/[microservice-name]/[microservice-name].log {
        rotate 12
        weekly
        missingok
        notifempty
        compress
        delaycompress
        size 50M
        notifempty
        sharedscripts
        postrotate
           /usr/bin/killall -HUP [microservice-name]
        endscript
}

/var/log/[microservice-name]/[microservice-name]-error.log {
        rotate 12
        weekly
        missingok
        notifempty
        compress
        delaycompress
        size 50M
        notifempty
        sharedscripts
        postrotate
           /usr/bin/killall -HUP [microservice-name]
        endscript
}

Log4j (JAVA)

# log4j.properties
---
log4j.rootLogger=INFO, fileLogger
log4j.appender.fileLogger=org.apache.log4j.RollingFileAppender
log4j.appender.fileLogger.layout=org.apache.log4j.PatternLayout
log4j.appender.fileLogger.layout.ConversionPattern=%d [%t] %-5p (%F:%L) - %m%n
log4j.appender.fileLogger.File=example.log
log4j.appender.fileLogger.MaxFileSize=50MB
log4j.appender.fileLogger.MaxBackupIndex=12

Schedule logging (log exporter)

Schedule with cron (crontab)

/etc/cron.d/[microservice-name]

Schedule with systemd

/etc/systemd/system/[microservice-name].service
/etc/systemd/system/[microservice-name].timer

B. Tools

https://github.com/sirupsen/logrus

Python

from datetime import datetime
import logging
import time
import json
       
def main():
    print("--- Staring Log Exporter Agent ---")
    logging.basicConfig(level=logging.INFO, filename="/var/log/[microservice-name]/[microservice-name].log", format="%(message)s")

if __name__ == '__main__':
    main()

Prerequirements

Install Helm

Add Plugin Helm

Add Helm Repository S3 Bucket

Update Repository

Create Namespace

Install OpenSearch Operator

Install Cluster OpenSearch

LAB Configuration (Simple Cluster)

LAB Configuration (HA Cluster)

Production Configuration (HA Cluster)

Apply manifest

Access Portforward

Setup Pattern

Goto Stack Management

Create Index Pattern

Select Index Pattern

Setup Timestamp for sorting Index Pattern

Discover Logs

Using Network LoadBalancer (NLB) via NGINX Controller

Helm Release Version

A. AWS Throttle API Requests

Account-level throttling per Region

B. Datadog API

Rate Limits

Title

Issue Summary

Impact

Trigger

Detection

Root Cause

Timeline

Resolution & Recovery

Corrective and Preventive Measurements

Financial Impact

Division / Team Name

Related Documents

Monitoring Dashboard

Logging

Operations (Executors)

Supervisors

HelmChart

Performance Test Report

References:

A. Concepts

Standardization export log path and name

Log using JSON formatted

Severity logs & formatting logs

Logrotation & compression

Log4j (JAVA)

Schedule logging (log exporter)

B. Tools