What is APM?
As its name suggests, application performance monitoring (APM) is a tool to
locate the source of application performance issues. Even so, APM goes well
beyond what might be expected from basic performance monitoring offerings.
APM is often used with a modern application as a way of assessing the user
experience. At a general level this might mean tracking an application's load,
along with KPIs. Doing so not only enables an organization to monitor the user
experience; it also provides visibility into how that experience changes as an
application's workload increases.
What is use of APM?
What makes APM so powerful are the abilities to:
•See exactly what your applications are doing while interacting with real users
•Discover problems that may be limiting sales, keeping customers from using
your product successfully, or damaging your brand experience
•Identify when your applications are struggling and why
•Identify where applications are wasting resources so you can tune to reduce
expenses and increase availability
•See historical trends and proactively prevent service outages
Benefits of APM?
1.Understand how your applications are being used: how many
users are using the system at once? for how long? where are they having
problems? are specific subsets of users poorly served? what is causing a
problem for a specific customer?
2.Understand your requests: how much traffic are you receiving? from
where? how fast are you responding? which aspects of the application are
slow?
3.Understand your resource usage: how much CPU are you using? is
your application leaking memory? are processes bloated because of poor code
execution? are you running unnecessary database queries? will your
application scale gracefully with growth?
4.Track how things are changing: what are the impacts of new
deploys? are you introducing new problems? are you fixing the problems you
think you are?
5.Know what isn't working: is your application experiencing errors?
What is observability?
Like APM, observability is a method used to determine the overall health of
complex systems and IT workloads. While APM collects data for KPIs, observability
aggregates data from various sources to paint a picture of the system's overall
health. Observability data sources :
1.Metrics. These generally refer to raw performance data. Metrics might represent
anything from the number of CPU cycles being consumed at a given moment to the
amount of time an e-commerce application takes to complete a credit card
transaction.
2.Traces. These help to monitor the interaction between the components making
up a complex system. A network trace, for instance, can track the path packets take
to their destination. An application trace can also track how the application's
components are used.
3.Logs. Coming in many forms, logs can be informational or contain errors or
warnings. An informational log entry might be generated, for example, when a
process is created, while an error event might be added to a log if that process
were to terminate unexpectedly.
What are the differences between APM and observability?
APM and observability tools can ensure a good user experience, but
they work toward that goal in different ways. Observability takes the
data that exists in logs, metrics and traces, and then uses that
information to form an overall health assessment. Even though the goal
is to ensure a good user experience, observability doesn't directly focus
on gauging the user experience. Instead, observability applies the
principles of control theory, which essentially state that it's possible to
understand what's going on with a system by examining its inputs and
outputs. Examining logs, metrics and traces collectively enables a tool
to assess the application's health, which can then be used to determine
if users are having a good experience.
What are the differences between APM and observability?
APM works by actively collecting internal state data and data
related to application response time. This data correlates
directly to the user experience. Some APM tools are designed
to monitor the underlying infrastructure in addition to the
application itself, which enables the tool to perform root cause
analysis when problems occur.
Monitoring vs Observability
The bottom line in the observability vs monitoring debate is that they’re both vital
when managing microservice-based applications. While monitoring tracks the
system’s health of your application, observability tells you why it’s performing a
certain way. It could be argued that monitoring is simply a subset of observability or
a part of the process.
The issue with starting with monitoring alone is that without observability, you won’t
be able to gain the data needed for contextualized analysis. Observability
encompasses monitoring and allows DevOps professionals to understand the root
cause of an error and how it is affecting your system. Thankfully, there are tools like
Instana that collect and evaluate this data to make sense of your multicloud
environment.
Monitoring vs Observability
Monitoring is tooling or a technical solution that allows teams to watch
and understand the state of their systems. Monitoring is done by
gathering predefined sets of metrics or logs.
Observability is tooling or a technical solution that allows teams to
debug their system actively. Observability is exploring properties and
patterns not defined in advance
Monitoring vs Observability
Monitoring focuses on a set of predefined system health metrics and how they
change with time. Logging provides separate data but is viewed in isolation
generally. Monitoring helps one understand "WHAT" is changing. This is helpful
when the points of failure of a system are well understood, and there are fewer
unknowns.
Observability is the ability to understand a system's internal state by analyzing the
data it generates, such as logs, metrics, and traces. Observability takes monitoring
to the next level, by not only highlighting "WHAT" is changing, but analyzing the
related data sets to answer "WHY" did some metrics change and identify the root
cause. Observability becomes especially important in distributed systems, where
there could be many failures, and it's impossible to foresee the point of failures in
advance.
Similarities between Observability and Monitoring
• Fix Issues
By locating and resolving problems, observability and monitoring both contribute
contribute to the system's continued functionality and dependability.
• Rely on Data
Both use data to identify the problem, which is another characteristic they share. A
share. A deeper exploration of both of these locations reveals differences.
• Demand a Deeper Understanding
Furthermore, whether you try to implement monitoring or observability, a
comprehensive understanding of the system is required. Particularly in the case of
case of monitoring because, in contrast to observability, it does not assist you in
you in establishing connections between various system occurrences.