Challenges in a Microservices Age: Monitoring, Logging and Tracing on Red Hat OpenShift
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Transcript of Challenges in a Microservices Age: Monitoring, Logging and Tracing on Red Hat OpenShift
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CHALLENGES IN A MICROSERVICES AGE:MONITORING, LOGGING AND TRACING ON OPENSHIFT
Martin EtmajerTechnology Lead @DynatraceMay 4, 2017
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WHY A CHALLENGE?
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Microservice A Microservice B Microservice C
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Microservice B
Runtime Environment Runtime Environment Runtime Environment
Microservice A Microservice C
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Microservice B DataStore
Runtime Environment Runtime Environment Runtime Environment
Microservice A DataStore
Microservice C DataStore
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Microservice A DataStore
Microservice B DataStore
Microservice C DataStore
Runtime Environment Runtime Environment Runtime Environment
3 6
+3+2
5 9
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Microservice A Microservice B Microservice C
Runtime Environment Runtime Environment Runtime Environment
-3-2
DataStore
3
DataStore
6
DataStore
5 9
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Microservice A
Load Balancing
Microservice B
Load Balancing
Microservice C
Runtime Environment Runtime Environment Runtime Environment
Load Balancing
DataStore
DataStore
DataStore
3 6
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Microservice A
Load Balancing
Microservice B
Load Balancing
Microservice C
Runtime Environment Runtime Environment Runtime Environment
Load Balancing
DataStore
DataStore
DataStore
3 6
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Microservice A
Load Balancing
Microservice B
Load Balancing
Microservice C
Runtime Environment Runtime Environment Runtime Environment
Load Balancing
DataStore
DataStore
DataStore
Messaging System
3 6
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Microservice A
Load Balancing
Microservice B
Load Balancing
Microservice C
Runtime Environment Runtime Environment Runtime Environment
Load Balancing
Messaging System
API Gateways
DataStore
DataStore
DataStore
3 6
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Microservice A
Load Balancing
Microservice B
Load Balancing
Microservice C
Runtime Environment Runtime Environment Runtime Environment
Load Balancing
Messaging System
API Gateways
DataStore
DataStore
DataStore
languages
application servers,container runtimes,…
load balancing
discovery & routing
security
messaging
storage3 6
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Red Hat „Hello World“ MSA
Demo
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MONITORING
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Monitoringcontainer health checks with OpenShift Liveness Probes
What?
● a liveness probe periodically checks if a container is able to handle requests
● when a condition has not been met within a given timeout, the probe fails
● if a probe fails, the container is killed and subjected to its restart policy
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Monitoringcontainer health checks with OpenShift Liveness Probes
How?
…
1 livenessProbe:
2 httpGet:
3 path: /health
4 port: 8080
5 initialDelaySeconds: 15
6 timeoutSeconds: 1
…
set in spec.containers.livenessProbe of Pod config
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Monitoringcontainer health checks with OpenShift Liveness Probes
How?
…
1 livenessProbe:
2 httpGet:
3 path: /health
4 port: 8080
5 initialDelaySeconds: 15
6 timeoutSeconds: 1
…
supports HTTP Get, Container Command and TCP Socket types
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Monitoringcontainer health checks with OpenShift Liveness Probes
How?
Demo
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MonitoringWhere are the fancy dashboards?
Source: d3js.org - Data-Driven Documents
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Heapster Hawkular Metrics
Monitoringcontainer, pod and node metrics with Heapster and Hawkular Metrics
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collects resource usage data, etc.
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exposes metrics via REST
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supports variousstorage backends
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Heapster
gathers metrics
runs in a Pod
exposes metrics
influxdb
GCL
elasticsearch
GCM
graphite
kafka
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e.g. Hawkular
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HawkularA collection of open source monitoring components by Red Hat
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HawkularA collection of open source monitoring components by Red Hat
metrics storage engine
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HawkularA collection of open source monitoring components by Red Hat
distributed tracing andapplication performance management
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HawkularA collection of open source monitoring components by Red Hat
alerting
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HawkularA collection of open source monitoring components by Red Hat
feed for Jolokia and Prometheus metrics
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a metrics storage engine
with a REST interface
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Monitoringcontainer, pod and node metrics with Heapster and Hawkular Metrics
! ! ! ! !
gathers metricssends metricsvisualizes metrics
Demo
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Hawkular OpenShift Agent Jolokia Prometheus
Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
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feeds Jolokia/Prometheus metrics data into Hawkular
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
! ! ! ! !
is deployed via a DaemonSet
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
! ! ! ! !HOSA HOSA HOSA HOSA HOSA
runs
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
! ! ! ! !HOSA HOSA HOSA HOSA HOSA
gathers metricssends metrics
applications
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
! ! ! ! !HOSA HOSA HOSA HOSA HOSA
gathers metrics
application containers
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
How?
1 kind: ConfigMap
2 apiVersion: v1
3 metadata:
4 name: my-hosa-config
5 data:
6 hawkular-openshift-agent: |
7 endpoints:
8 - type: jolokia 15 - type: prometheus
9 protocol: http 16 protocol: http
10 port: 8778 17 port: 8080
11 path: /jolokia/ 18 path: /metrics/
12 metrics 19 metrics:
13 - name: java.lang:type=Memory 20 - name: process_start_time_seconds
14 type: gauge 21 type: gauge
ConfigMap defines agent configuration
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
How?
…
1 spec:
2 volumes:
3 - name: hawkular-openshift-agent
4 configMap:
5 name: my-hosa-config
…
a volume named „hawkular-openshift-agent“ tells HOSA to monitor this Pod
Demo
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
How?
1 kind: ConfigMap
2 apiVersion: v1
3 metadata:
4 name: my-hosa-config
5 data:
6 hawkular-openshift-agent: |
7 endpoints:
8 - type: jolokia 15 - type: prometheus
9 protocol: http 16 protocol: http
10 port: 8778 17 port: 8080
11 path: /jolokia/ 18 path: /metrics/
12 metrics 19 metrics:
13 - name: java.lang:type=Memory 20 - name: process_start_time_seconds
14 type: gauge 21 type: gauge
Jolokia ?
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JolokiaJMX on Capsaicin
access JMX MBeans remotely via REST
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$ mv $JOLOKIA_HOME/agents/jolokia.war $TOMCAT_HOME/webapps$ $TOMCAT_HOME/bin/catalina.sh start
JolokiaJMX on Capsaicin installs a Jolokia WAR agent into Apache Tomcat
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Monitoringapplication level metrics with Hawkular OpenShift Agent (HOSA)
How?
1 kind: ConfigMap
2 apiVersion: v1
3 metadata:
4 name: my-hosa-config
5 data:
6 hawkular-openshift-agent: |
7 endpoints:
8 - type: jolokia 15 - type: prometheus
9 protocol: http 16 protocol: http
10 port: 8778 17 port: 8080
11 path: /jolokia/ 18 path: /metrics/
12 metrics 19 metrics:
13 - name: java.lang:type=Memory 20 - name: process_start_time_seconds
14 type: gauge 21 type: gauge
Prometheus ?
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PrometheusA monitoring system for metrics data
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PrometheusA monitoring system for metrics data
metrics storage engine
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PrometheusA monitoring system for metrics data
various exporters expose metrics fromnodes, database engines and cloud componentry
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PrometheusA monitoring system for metrics data
alerting
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# build.gradle # Application.java
1 dependencies { 1 public void registerMetricServlet() {
2 compile 'io.prometheus.simpleclient.0.0.21' 2 // Expose Promtheus metrics.
3 compile 'io.prometheus.simpleclient_hotspot.0.0.21' 3 context.addServlet(new ServletHolder(new MetricsServlet()), "/metrics");
4 compile 'io.prometheus.simpleclient_servlet.0.0.21' 4 // Add metrics about CPU, JVM memory etc.
5 } 5 DefaultExports.initialize();
6 }
PrometheusA monitoring system for metrics data
exposes default JMX metrics: CPU, Memory, Garbage Collection, etc.
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Where to start?
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LOGGING
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how to process all these data?
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Loggingapplication events with Elasticsearch, Fluentd and Kibana (EFK)
FluentdElasticsearch Kibana
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unifies your logging infrastructure; supports almost 200 plugins
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! ! ! ! !
is deployed via a DaemonSet
Loggingapplication events with Elasticsearch, Fluentd and Kibana (EFK)
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! ! ! ! !
deploys
Fluentd Fluentd Fluentd Fluentd Fluentd
Loggingapplication events with Elasticsearch, Fluentd and Kibana (EFK)
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application events with Elasticsearch, Fluentd and Kibana (EFK)
! ! ! ! !
watches container logs
Fluentd Fluentd Fluentd Fluentd Fluentd
ingests log datavia configuration
Logging
query
ElasticsearchKibana Application
Demo
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DISTRIBUTED TRACING
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design goals
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Google Dappertrace
(transaction)
initiator
processes
remote calls
Source: Google Dapper Paper
spans(timed operations)
annotations,event data
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ZipKinA distributed tracing system timescale
spans
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a standard API for reporting distributed traces
with various client libraries
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OpenTracingA vendor-neutral open standard for distributed tracing
The problem?
● instrumentation is challenging: tracing context must propagate within and between processes
● unreasonable to ask all vendor and FOSS software to be intrumented by a single tracing vendor
The solution?
● allow developers to instrument their own code using OpenTracing client libraries
● have the application maintainer choose the tracing technology via configuration change
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Hawkular APMDistributed Tracing and Application Performance Management
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JaegerA distributed tracing system
Source: Jaeger Architecture – jaeger.readthedocs.io
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SOLVES THE CHALLENGE?
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DynatraceAll-in-one monitoring, now!
! ! ! ! !
dynatrace/oneagent
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DynatraceAll-in-one monitoring, now!
! ! ! ! !
deploys
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