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WHAT IS OBSERVABILITY?

Try New Relic for free Try New Relic for free
Learn more Learn more
In this article
 * What is observability?
 * Why is observability important?
 * Observability vs monitoring
 * What are the components of observability? 
 * What are the benefits of observability?
 * Who uses observability?
 * Observability and DevOps
 * Get started with observability. Try New Relic.


WHAT IS OBSERVABILITY?

Observability is proactively collecting, visualizing, and applying intelligence
to all of your metrics, events, logs, and traces—so you can understand the
behavior of your complex digital system.

A simple way of describing observability is how well you can understand the
system from the work it does. In control theory, observability is defined as how
engineers can infer the internal states of a system from knowledge of that
system's external outputs. Expanded to IT, software, and cloud computing,
observability is how engineers can understand the current state of a system from
the data it generates. To fully understand, you’ve got to proactively collect
the right data, and then visualize it and apply intelligence.

A common abbreviation for observability is o11y, which replaces the 11 letters
between o and y with the number 11. (Fun fact: That’s why we get k8s for
Kubernetes!)

Observability gives engineers a proactive approach to optimizing their systems.
It provides a connected real-time view of all the operational data in your
software system, as well as the flexibility to ask questions on the fly about
your applications and infrastructure to get the answers you need.




WHY IS OBSERVABILITY IMPORTANT?

Modern-day systems are transforming into complex, open source, cloud-native
microservices running on Kubernetes clusters. They’re being developed and
deployed faster than ever—by distributed teams. With DevOps, continuous
delivery, and agile development, the whole software delivery process is faster
than ever before, which can make it more difficult to detect issues when they
arise.

When things went wrong in the days of mainframes and static operations, it was
pretty easy to understand why, and pre-configured static dashboards alerted an
operator of an issue. These systems failed in similar ways over and over again.

As systems became more complex, monitoring tools attempted to shed light on what
was happening with software performance. You could trace application performance
with monitoring data and time-series analytics. It was a manageable process.

IDC WHITE PAPER

The Business Value of the New Relic Observability Platform
Learn More Learn More

Today, the possible causes of failure are abundant—and can feel infinite when
you are staring at a screen, frustrated. Is a server down? Is your cloud
provider having an outage? Did someone push new code that's impacting end-user
behavior?

When working on these complex, distributed systems, identifying a broken link in
the chain can be nearly impossible without an observability solution. Now that
microservices architectures are commonplace, responsibilities are distributed
across teams. There’s not a discrete app owner, and many teams need to be
involved. Teams need to understand, analyze, and troubleshoot application areas
they don’t necessarily own. You need distributed tracing, which allows you to
trace requests—and bottlenecks—through all parts of a distributed system.


OBSERVABILITY VS MONITORING

Conventional monitoring won’t help you succeed in the complex world of
microservices and distributed systems. It can only track known unknowns. These
are the things you know to ask about in advance (for example: “What’s my
application’s throughput?”, “What does compute capacity look like?”, “Alert me
when I exceed a certain error budget.”) Observability gives you the power to not
just know that something is wrong…but to also understand why. It gives you the
flexibility to understand patterns you hadn’t even thought about before, the
unknown unknowns.

Think of it this way: Observability (a noun) is the approach to how well you can
understand your complex system. Monitoring (a verb) is an action you take to
help in that approach. Observability doesn't eliminate the need for monitoring.
Monitoring just becomes one of the techniques used to achieve observability. 

Application performance monitoring (APM) is one of the steps in a well-rounded
observability practice that uses dashboards and alerts for known or expected
failures. To learn why it's important to have APM as part of your observability
practice, see APM vs. observability.


WHAT ARE THE COMPONENTS OF OBSERVABILITY? 

Observability in digital systems has four fundamental pieces:

 1. Open instrumentation. Instrumentation is using code (agents) to track and
    measure data flowing through your software application. Open instrumentation
    means gathering telemetry data from open source or vendor-specific entities
    that produce that data. Examples of telemetry data include metrics, events,
    logs, and traces, often referred to as MELT. Examples of entities include
    services, hosts, applications, and containers.
 2. Correlation and context.  Understanding the bigger picture is vital,
    especially for large enterprise applications with enormous amounts of raw
    telemetry data. The telemetry data collected must be analyzed for
    correlations and context, so humans can make sense of any patterns and
    anomalies that arise.
 3. Programmability. Organizations need the flexibility to create their own
    context and curation with custom applications based on their unique business
    objectives.
 4. AIOps tools. To ensure that your modern infrastructure is always available,
    you need to accelerate incident response. AIOps solutions use machine
    learning models to automate IT operations processes such as correlating,
    aggregating, and prioritizing incident data. These tools help you eliminate
    false alarms, proactively detect issues, and accelerate mean time to
    resolution (MTTR).


WHAT ARE THE BENEFITS OF OBSERVABILITY?

Observability tools empower engineers and developers to create better customer
experiences despite the increasing complexity of the digital enterprise. With
observability, you can collect, explore, alert, and correlate all telemetry data
types.

Observability makes it easier to drive operating efficiencies and fuel
innovation and growth. For example, a team can use an observability platform to
understand critical incidents that occurred and proactively prevent them from
recurring. This decreases downtime and improves MTTR.

When a new build is pushed out, they can see into the application performance
and then drill down into the reasons why an error rate spikes or application
latency rises. They can see which particular node has the problem. For more
examples, organized into 10 principles of observability, see Observability: A
21st Century Manifesto.

Other benefits of observability include:

 * A single source of truth for operational data.
 * Verified uptime and performance. 
 * An understanding of the real-time fluctuations of your digital business
   performance.
 * Better cross-team collaboration to troubleshoot and resolve issues faster.
 * A culture of innovation.
 * Greater operating efficiency to produce high-quality software at scale,
   accelerating time to market.
 * Specific details to make better data-driven business decisions, and
   optimizing investments.

The 2021 Observability Forecast found that 90% of respondents believe
observability is important and strategic to their business, but only 26% said
their observability practice was mature. Only half of the nearly 1,300 software
engineers, developers, and IT leaders surveyed said their business was in the
process of implementing observability.

Observability is essential, but there's a lot of room for most businesses to
improve.


WHO USES OBSERVABILITY?

SREs and IT Operations teams are in charge of keeping complex systems—the apps
that people rely on every day—up and running. But observability is everyone’s
concern throughout the software development lifecycle. 

Software engineering teams use observability to understand the health,
performance, and status of software systems, including when and why errors
occur. By looking at a system's outputs, such as events, metrics, logs, and
traces, engineers can determine how well that system is performing.


OBSERVABILITY AND DEVOPS

Deployment frequency has increased dramatically with microservices. Too much is
changing to realistically expect teams to predefine each and every possible
failure mode in their environments. It's not just application code, but the
infrastructure that supports it, and consumer behavior and demand. 

Observability gives DevOps teams the flexibility they need to test their systems
in production, ask questions, and investigate issues that they couldn’t
originally predict.

Observability helps DevOps teams:

 * Establish clear service-level objectives (SLOs) and put instrumentation in
   place to prepare and join forces toward measurable success.
 * Rally around team dashboards, orchestrate responses, and measure the effects
   of every change to enhance DevOps practices.
 * Review progress, analyze application dependencies and infrastructure
   resources, and find ways to continually improve the experience for the users
   of their software.

For DevOps best practices, check out the DevOps Done Right ebook.


GET STARTED WITH OBSERVABILITY. TRY NEW RELIC.

Modern observability empowers software engineers and developers with a
data-driven approach across the entire software lifecycle. It brings all
telemetry—events, metrics, logs and traces—into a unified data platform with
powerful full-stack analysis tools that enable them to plan, build, deploy and
run great software to deliver great digital experiences that fuel innovation and
growth.

The best way to learn more about observability is to get hands-on experience
with a modern, unified observability platform.

Get started with New Relic Get started with New Relic
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