Applications whose foundation is laid on Reactive Manifesto accounts for being Reactive Applications. But can any monitoring pipeline ensure that its worthy enough to monitor your reactive fleet? With years of experience in Reactive stack; Knoldus compiles all its learning into a Premonition based Reactive Monitoring and Alerting Platform i.e PremonR which is a single solution for all your enterprise monitoring needs.

1. A Reactive Platform to monitor
Reactive Application
Sahil Sawhney
Sr. DevOps Consultant
+91-9871211045
www.knoldus.com

2. Agenda
What Is Reactive Monitoring
Reactive Monitoring Challenges
PremonR: The Solution
Demonstration
Monitoring Needs Of The Hour

3. Monitoring Needs Of The Hour
“Traditional metrics of cpu and memory usage don’t matter to your customers. How ’bout measuring what really matters
to your customers?”
“No matter how careful or good you are, sh!t will happen.”
“If it isn’t monitored, it isn’t production!”
“Application up, monitoring applied, alerting all set. Now relax until things go down”

4. What is Reactive Monitoring?
❑ Applications whose foundation is laid on Reactive Manifesto accounts for being Reactive
Applications.
❑ But can any monitoring pipeline ensure that its worthy enough to monitor your reactive
fleet?

5. Challenges
Moving and
decentralized
component
Lack of visibility
across the
enterprise
Lack of democracy in
monitoring, due to cost of
acquiring commercial tools
Insufficient,
unmanaged
alerting rules
Alerting of the
mishaps after they
have occured.
Lack of persistence of
custom visualizations
& alert rules
Dedicated environment (prod,
beta) based classification of
visualization + dashboard
Keeping up with
evolving
applications & tools

6. In comes PreMonR
With years of experience in Reactive stack; Knoldus compiles all its learning into a Premonition based
Reactive Monitoring and Alerting Platform.
The fabrication of such a tool was based on three driving forces:
Driving
Forces
Monitor the
reactive applications
The monitoring platform
must itself be Reactive
Containing the mishaps
before they turn into reality

7. Features of PreMonR
Based on a
reactive
monitoring
pipeline.
Highly available
monitoring
platform.
One Subscription
all solution
Centralized
insights of your
distributed
platform
Prebuilt fleet of dashboards
& alerting rules as per the
project stack.
Customize as
per your
appetite
Specialized for distributed
environments like
Kubernetes and DCOS
Real time
monitoring and
premonition
based alerting

8. PreMonR Architecture
1. Extractor extracts metrics from
the underlying infrastructure.
2. Collector collects logs of the
application as well as
infrastructure.
3. Shipper exports the extracted
metrics to transformer in case
there are some transformations
that must be applied to collected
data.
4. Transformer transforms the input
logs and metrics as per the use
case.
5. Data Backend stores the metrics
and logs aggregated by
Extractore and Collectors
6. Premonition engine apply
Machine Learning algorithm to
detect anomalies and facilitate
proactive alerting.
7. Visualizer is the UI where all logs
and Dashboards could be
visualized.
8. Alerter fires alerts in case of
threshold breaches.
Metrics
Extractor
Data
Backend
Alerter
Visualizer
Logs
Collector
PagerDuty
Email
Slack
System logs(syslog, journald)
Application logs(log4j, log4net)
Server Logs(Apache, Nginx)
Platform Logs(AWS, Baremetal)
Cluster Logs(K8S, Mesos)
System metrics
(CPU, memory, disk)
Infrastructure metrics
(AWS, Gcloud,
Baremetal)
Application Agents
(APM, error tracking)
TransformerShipper
PreMonition
Analytics
Engine

9. ● Lagom Metrics
● Spring-Boot Metrics
● Akka Metrics
● Play Metrics
● Application Logs
● System Resource Metrics
● Cassandra metrics
● Dgraph metrics
● Elasticsearch Metrics
● Kafka Metrics
● Anything That Gives Metrics
Monitoring
Application
Monitoring
Infrastructure
Monitoring
What Can I Monitor ?

10. The PremonR Effect
Centralized monitoring and alerting tool for
cluster health, log analysis.
High availability, persistence of
Dashboards and alert rules.
Clean and convenient setup procedure
Automatically discover, configure and
customize all relevant metrics.
Easily Adaptable/customizable solution
based on BELK
Visualize the health and topology of their
distributed applications in real-time
Data science-driven anomaly detection quickly detects
the tentative problems.
Optimized thresholds ensuring real time
alerting.

11. Demo Architecture
PreMonR Engine
Kubernetes
Visualization &
Alerting

12. www.knoldus.com
+(91) 987-121-1045
sahil.sawhney@knoldus.in
@Knolspea
k
Thank You
(Great Work Sachin)
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