Illustration of a magnifying glass depicting increased visibility across multiple components that are utilizing observability tools.

Observability

What is observability?

Observability is a process for modern applications that use software tools to detect issues before they become problems. This is done by observing tech stack inputs and outputs.  

Observability tools collect and analyze data, user experience, infrastructure, and network telemetry to resolve issues before they impact business KPIs.

Shifting to observability

Why are organizations shifting to observability?

Applications increasingly leverage components or services across on-premises, software as a service (SaaS), and public clouds. These distributed operating environments, introduce complexity and new challenges.

Observability tools give organizations insight into the end-user experience and their application's operational efficiency.

What is driving demand for observability solutions?

The demand for observability solutions is being driven by a proliferation of digital services and the increasing complexity of IT systems and applications.

These factors include:

  • The number of apps organizations need to manage are at an all—time high and continues to grow.
  • User expectations have never been greater, and customers expect quick updates—otherwise they abandon them due to bad experiences.
  • Development teams are constantly modernizing apps to reduce release and refresh cycles.
  • IT teams must now manage traditional and cloud-native apps.
  • Cloud services and third—party API utilization are growing.

 

This, in turn, increases the amount of data created across the technology stack—from the application and infrastructure to the network and security. Organizations are now dealing with complicated systems beyond human scale, including:

Lack of visibility

  • 75% of global technologists say they now face more IT complexity than they have ever before.
  • They also wrestle with overwhelming data noise without the resources and support they need to understand it.
  • 85% of technologists state it will continue to be a significant challenge to cut through noise caused by the increasing volumes of data to identify root causes of performance issues.

 

Inability to prioritize actions

  • 96% of technologists say there will be negative consequences unless they have genuine visibility and insight into the performance of the whole technology stack and how it impacts application performance.

Monitoring isn't enough

Why move beyond siloed domain monitoring?

Traditional monitoring solutions offer limited, siloed visibility across the managed and unmanaged distributed applications that impact the overall digital experience. For example, there can be limited visibility for application services, networks, infrastructure, clouds, databases, and logs.

Monitoring tools alert each team in their respective area when performance issues occur. However, these tools are limited when it comes to informing how performance in each domain impacts application transactions and business. In distributed native—cloud applications, the variety of processes and systems involved makes monitoring, alone, insufficient to achieve optimal system function.

These are the reasons that monitoring, by itself, isn't enough:

  • Meeting end—user demand and expectations for digital services means multiple teams; DevOps, AppOps, NetOps, InfraOps, and SecOps are all involved in optimizing the performance and security of every digital experience.
  • Traditional monitoring only gives IT teams visibility into defining what normal looks like by providing them with baselining, health rules, and alerts when issues arise in their domain.
  • Users don't see the ripple effect the issues have on the overall app experience or its impact to the business.
  • Technological expectations are higher than ever. Intolerance for technology breakdowns means IT needs tools that proactively prevent issues—not just react to them.
  • Teams need to manage performance and availability of modern applications across the entire technology stack, including the underlying infrastructure and the user experience.

Observability is proactive

Why should organizations use observability tools? 

In distributed cloud—native applications, the variety of processes and systems involved can create unexpected issues. Simply monitoring selected metrics is typically not sufficient to detect problems before they occur.

In these systems, requests that involve microservices can set off a chain reaction of messages to related services. This makes it difficult to use monitoring tools to precisely diagnose what has gone wrong when a system fault occurs.

Applications developed using agile methodologies, DevOps, microservices, containers, and other modern development techniques usually involve rapid deployment of application components, often using a variety of programming languages. By tracking a broad spectrum of events related to system function, observability tools can detect potential issues before they impact system deliverables.

The context provided by observability tools enables the appropriate team members to see any changes in system performance across time as well as how those changes are correlated with other changes. Often, this is done by using easily understood visual reports and dashboards. These tools can also report on links between the system elements involved in the problem, identifying interdependencies that should be examined to help resolve an issue.

The full stack observability difference 

Cisco defines full stack observability as a solution that enables teams to correlate application performance to the entire application technology stack—connecting performance back to their business metrics.

Full stack observability tools help IT teams deliver better application experiences by letting them know where application issues arise and why they happened. They also help them prioritize the actions you need to take based on the impact to your business.

Full stack observability monitors the inputs (application and infrastructure stacks) and outputs (business transactions, user experiences, application performance) and provides cross—domain correlations and dependency mapping. It provides teams with shared connected experience to break down siloes with application performance and business context. It also alerts them to issues that are impacting the business performance of the application. It includes cross-domain correlation and dependency to inform teams exactly which areas are causing performance issues and the reasons.

With the business context of the application observed, teams can prioritize which issues have the largest impact on business and experience so they can respond efficiently. Teams can then take full stack actions across the stack for performance, optimization, and security.

Why is full stack observability needed?

Modern application development cycles and system complexity make it difficult to understand the root causes behind application performance issues. Simply observing each domain isn't enough. Enterprises need full stack observability to properly manage the complexities and remove blind spots.
Full stack observability correlates the entire technology stack to the customer's application performance metrics, business transactions and, ultimately, the key performance indicators (KPIs) for their business.

This connection to business outcomes is key, as almost three quarters (73%) of survey participants fear that the inability to link IT performance with business performance will be detrimental to their business. The ability to connect full stack observability with real—time business outcomes is essential to delivering first–class digital experiences and accelerating digital transformation.

What are the benefits of full stack observability?
 

Full stack observability helps organizations:

  • Increase business impact and elevate business experience: Reduce mean times to identify issues and mean time to resolve issues to improve application uptime and performance and deliver a better end-user experience.
  • Optimize business operations and reduce costs: Map app—to—infrastructure dependencies to prevent over–provisioning and lower costs.
  • Reduce business risk: Strengthen application security from application development to runtime.

 

Full stack observability gives organizations:

  • Full stack observability visibility: Gather, unify and correlate data across multiple domains and multiple teams in real time to get a holistic understanding of system performance. Break down siloes, collaborate with multiple IT teams, and streamline workflows—backed by real—time information across your entire application infrastructure.
  • Full stack observability insights: Isolate the root causes of application performance faster, optimize resource allocation, and get a clearer picture of application costs versus performance and how they affect the end—user experience.

 

Full stack actions

  • Full stack observability actions: Get prioritized application recommendations based on data collected over time to better scale applications and accelerate application development cycles.

 

What use cases are enabled by full stack observability? 

 

Full stack observability enables the use cases across three pillars:

Performance

  • Hybrid application monitoring: Monitor performance of traditional and hybrid applications, often monolithic, hosted applications leveraging traditional infrastructure and hybrid cloud.
  • Modern cloud—native application monitoring: Monitor performance of cloud—native applications, often microservices—based, distributed applications leveraging cloud technologies hosted on public or private clouds.
  • Customer digital experience monitoring: Actionable, end—to—end insight into application experience, its underlying dependencies, and business impact.
  • Application dependency monitorin: Assure the performance of managed and unmanaged (third-party) application services and APIs, including Internet and cloud network performance to those services.

 

Optimization

  • Hybrid cost optimization: Lower costs by only paying for what you need in public cloud and by safely increasing utilization of on—premises assets.
  • Application resource optimization: Improve and assure application performance by taking the guesswork out of resource allocation for workloads on—premises and in the public cloud.

 

Security

  • Application security: Reduce business risk by actively identifying and blocking against vulnerabilities found in application run—times in production. 

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