Full
Stack Monitoring
In a complex enterprise application world, investing in a
good full stack monitoring platform becomes a necessity. Getting timely
actionable insight into anomalous behaviors of the application could save
millions of dollars, a company's brand image and their customer relationships.
A good full stack monitoring platform should provide across-the-board,
high-level actionable metrics as well as the ability to drill down granular details
with full context. A good platform delivers all these capabilities, easily
moving between high-level and lower-level views
What to Monitor?
How should you choose data metrics so
that you can receive meaningful, automated alerts for potential problems and
quickly investigate and get to the bottom of the issues? Instrument and collect
as many metrics, events and logs as you reasonably can, Since the monitoring of
complex systems demands comprehensive measurements. Collect metrics with
sufficient granularity to make important information visible.
Server
Uptime
Processor Utilization
Memory Utilization
Reads & Writes
Network in & out
Disk Space Utilization
Error logs
|
Middleware
Uptime
Connections
Messages Count
JVM Memory
Error Logs
|
Database
Connection Check
Active / Total Sessions
Table Space Usage %
Full Table Scans
Error Logs
|
Application
Login Status Check
Key services Status
Batch Job Status
Job Completion Time
Key Transaction Counts
Users Logged-in
Error Logs
|
Monitoring
Technology
I got a chance to work hands-on with two leading providers
of Monitoring platform for a cloud-based Lending and Leasing system: AWS
CloudWatch and Data Dog. Both these are leaders in the monitoring platforms,
and they enable full system visibility by bringing all the data about full
stack application performance and customer experience into one platform.
Investing in full stack monitoring gave us access to all the data for an entire
infrastructure and applications, so teams can visualize the connections between
services and components and quickly identify the source of the issues.
Dashboards
and Visualizations
Both AWS
CloudWatch and Data Dog have
modern visualization capabilities using dashboards that enable you to create
re-usable graphs and visualize your infrastructure resources and applications
in a cohesive view. You can graph metrics and logs data side by side in a dashboard
to quickly get the context and go from diagnosing the problem to understanding
the root cause. You can visualize key metrics, like CPU utilization and memory,
and compare them to capacity. You can also correlate the log pattern of a
specific metric and set alarms to be proactively alerted about performance and
operational issues. With a single source of truth, our organization was able to
track the interactions between separate components and effectively troubleshoot
issues that involve multiple teams and their interdependent services.
About the Author:
Vinay Bhatia is an experienced product leader, passionate about
building financial products that delight customers. He has an extensive
background in technology, cloud and agile software development.
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