Introduction
Observability is now a critical component of modern industry. In this article, we will delve into a crucial aspect of observability: the aggregation of webMethods Integration Server logs into a unified logging system using Loki and visualizing them in real-time with Grafana dashboards for monitoring and analysis. We will employ Promtail for log capturing.
Architecture
In the architecture diagram below, there are three webMethods Integration Server deployments. Each deployment incorporates a Promtail instance, which serves as a log collecting agent, running as a sidecar within the same pod as the Integration Server container. These Promtail instances collect logs from their respective Integration Server deployments. Subsequently, the collected logs are then forwarded to Loki, a log aggregation system. In the Grafana dashboard, Loki is configured as a data source, enabling further analysis of the logs.
Steps to Collect Logs from webMethods Integration Servers Running in a Kubernetes Environment
We will use Helm charts to deploy all the components—Grafana Loki, Grafana, Prometheus, and webMethods Integration Server—in a Kubernetes cluster. This deployment can be accomplished in two steps:
- Install the loki-Stack
- Create helm chart for IS with promtail running as a sidecar
Install Loki-Stack
- Add the helm-chart repo. The Loki-Stack Helm Chart is a package that allows you to deploy Grafana Loki, along with its dependencies, using Helm, which is a package manager for Kubernetes.
helm repo add grafana https://grafana.github.io/helm-charts
helm repo update
- By default, Grafana is disabled. To enable Grafana, edit the configuration file. You will also see configurations for Fluentd, Prometheus, and other components. Modify the file according to your requirements. An example of
loki-stack-values.yaml
is shown below.
helm show values grafana/loki-stack > loki-stack-values.yaml
loki:
enabled: true
isDefault: true
url: http://{{(include "loki.serviceName" .)}}:{{ .Values.loki.service.port }}
readinessProbe:
httpGet:
path: /ready
port: http-metrics
initialDelaySeconds: 45
livenessProbe:
httpGet:
path: /ready
port: http-metrics
initialDelaySeconds: 45
datasource:
jsonData: "{}"
uid: ""
promtail:
enabled: true
config:
logLevel: info
serverPort: 3101
clients:
- url: http://{{ .Release.Name }}:3100/loki/api/v1/push
grafana:
enabled: true
sidecar:
datasources:
label: ""
labelValue: ""
enabled: true
maxLines: 1000
image:
tag: 10.3.3
- Create a namespace and install the loki-stack in it.
kubectl create namespace <namespace name>
helm install loki-stack grafana/loki-stack --namespace <namespace> -f <stack-value>.yaml
- To log in to Grafana, you need to port-forward the Grafana port to access the Grafana dashboard from your localhost and retrieve the password from the secret. Follow the steps below:
# Port forward grafana :
kubectl -n <namespace> port-forward service/loki-stack-grafana 3000:80
# Get the password from the secret to login to grafana dashboard
kubectl -n <namespace> get secret loki-stack-grafana -o yaml
echo "<replace this with base64 encoded value from the above command>" | base64 -d
Create a Helm chart for the Integration Server (IS) with Promtail running as a sidecar.
- Now that the loki-stack in configured, its time to create a helm-chart for Integration Server.
helm create is-chart
- Create a
deployment.yaml
file with the Integration Server (IS) and Promtail running as a sidecar. Here is an example of thedeployment.yaml
file. In this configuration, the Integration server is pulled from the Docker registrysoftwareag/webmethods-microservicesruntime:10.15.0.10-slim
and mounts the IS logs folder/opt/softwareag/IntegrationServer/logs
, allowing Promtail to collect logs from IS. With-config.expand-env=true
enabled, Promtail dynamically replaces${POD_NAME}
with the actual value of thePOD_NAME
, enabling dynamic configuration when there are multiple IS deployments.
apiVersion: apps/v1
kind: Deployment
metadata:
name: is-deployment
spec:
replicas: 1
selector:
matchLabels:
app: is
template:
metadata:
labels:
app: is
spec:
containers:
- name: is-container
image: softwareag/webmethods-microservicesruntime:10.15.0.10-slim
imagePullPolicy: Always
ports:
- containerPort: 5555
- containerPort: 8091
securityContext:
runAsUser: 0 # Running as root
volumeMounts:
- name: is-logs
mountPath: /opt/softwareag/IntegrationServer/logs
# Sidecar container for Promtail
- name: promtail
image: grafana/promtail:2.9.3
args:
- -config.file=/etc/promtail/promtail-config.yaml
- -client.url=http://loki-stack:3100/loki/api/v1/push
- -config.expand-env=true
env:
- name: POD_NAME
value: "is-one"
volumeMounts:
- name: is-logs
mountPath: /opt/softwareag/IntegrationServer/logs
- name: config-volume
mountPath: /etc/promtail
readOnly: true
securityContext:
runAsUser: 0 # Running as root
volumes:
- name: is-logs
emptyDir: {}
- name: config-volume
configMap:
name: promtail-config
- If you have multiple applications, you can create another deployment based on the above example. For instance, below is the second deployment YAML for the second Integration server with Promtail running as a sidecar.
apiVersion: apps/v1
kind: Deployment
metadata:
name: is-deployment-two
spec:
replicas: 1
selector:
matchLabels:
app: is-two
template:
metadata:
labels:
app: is-two
spec:
containers:
- name: is-container-two
image: softwareag/webmethods-microservicesruntime:10.15.0.10-slim
imagePullPolicy: Always
ports:
- containerPort: 5555
- containerPort: 8091
securityContext:
runAsUser: 0 # Running as root
volumeMounts:
- name: is-logs-two
mountPath: /opt/softwareag/IntegrationServer/logs
# Sidecar container for Promtail
- name: promtail-two
image: grafana/promtail:2.9.3
args:
- -config.file=/etc/promtail/promtail-config.yaml
- -client.url=http://loki-stack:3100/loki/api/v1/push
- -config.expand-env=true
env:
- name: POD_NAME
value: "is-two"
volumeMounts:
- name: is-logs-two
mountPath: /opt/softwareag/IntegrationServer/logs
- name: config-volume
mountPath: /etc/promtail
readOnly: true
securityContext:
runAsUser: 0 # Running as root
volumes:
- name: is-logs-two
emptyDir: {}
- name: config-volume
configMap:
name: promtail-config
- Create a ConfigMap for
promtail-config.yaml
. In the following configuration map, we collect bothserver.log
andWMERROR.log
from the Integration Servers. If there are multiple deployments of Integration Servers, thepod: ${POD_NAME}
dynamically retrieves the value of the Integration server as defined in thedeployment.yaml
file above.
apiVersion: v1
kind: ConfigMap
metadata:
name: promtail-config
data:
promtail-config.yaml: |
scrape_configs:
- job_name: islog
static_configs:
- targets:
- localhost
labels:
job: serverlog
pod: ${POD_NAME}
__path__ : /opt/softwareag/IntegrationServer/logs/server.log
- targets:
- localhost
labels:
job: errorlog
pod: ${POD_NAME}
__path__ : /opt/softwareag/IntegrationServer/logs/WMERROR*.log
- Create a helm package and install the above deployment. Additionally, verify that all pods are running healthily.
helm package .
helm install <install-name> .\is-chart-0.1.0.tgz -n <namespace>
kubectl get all -n <namespace>
- To access the Grafana dashboard, log in and navigate to the “Explore” section. Here, you can execute queries based on the labels set in the Promtail configuration and view all your Integration Server (IS) deployment logs. You can filter logs by using the labels defined in the Promtail configuration. For instance, you can execute queries to filter logs based on “errorlog” or “serverlog” as defined in the above promtail-config.yaml file.
As we conclude, it’s crucial to recognize the significance of effective log management in troubleshooting and resolving issues within the webMethods Integration Server, particularly in complex customer environments. By using tools like Loki to organize and display logs, organizations can understand how their systems are working with webMethods Integration Servers. With a unified logging system in place, teams can promptly identify real-time events and expedite problem resolution, thereby enhancing the reliability and effectiveness of their systems.
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