What is observability?

Observability is the combination of modern application performance monitoring (APM) and analytics. Observability is a consistently expanding practice in the world of software development and IT operations management.

Control theory, considered the root of observability, is a field of mathematics for dynamic engineering and mechanical systems. If the right controls are in place a system can be optimized, and those controls can work only if there is confirmation the system is performing.

The History of Observability

Rudolf Kálmán was an expert mathematician who coined observability in the 1960s to describe how well a system can be measured by its outputs. He employed a mathematical technique commonly used in the digital computers of navigation and control systems, avionics, and outer-space vehicles to extract signals from long sequences of incomplete measurements. Considered routine amongst engineers working in process and aerospace industries, the actual term “observability” only entered the lexicon of IT practitioners 30 years afterward.

The advent of observability can be traced back to a blog in 2013, where engineers from Twitter wrote about the “observability stack” they created to monitor the health and performance of the “diverse service topology” that came from the shift from a monolithic to a distributed IT architecture. The move meant an overall more complex system and the interactions between those two systems. They defined their observability solution as an efficient tool for swiftly determining the root cause of issues and increasing the overall reliability and efficiency of the organization. Then in 2018, the three pillars (logs, metrics, traces) entered the conversation and became the standard. COVID-19 acted as a catalyst that fueled a trend that was already in motion. Now two decades later from the start of observability, the practice in 2022 is now mainstream and considered a best practice for organizations.

What are the objectives of observability?

Observability assures IT stacks for enterprises are available and that they are performing reliably. Achieving these goals leads to increased levels of:

• Business success
• Security and compliance
• Optimized marketing efforts

What is unified observability?

Observability gives IT teams a holistic view of their application and infrastructure health by unifying the data from metrics, logs, and traces, hence why it’s called unified observability. Unified observability packages infrastructure monitoring (ITIM), logs, application performance monitoring (APM), and SaaS monitoring together into a single platform to provide organizations with complete visibility. It helps corporations build a world-class customer experience while boosting employee productivity. Three pillars that matter most when it comes to unified observability are: customer experience, employee productivity, and the digital infrastructure. 

To be a successful business today, you not only need total visibility across these pillars but also need to be able to map the relationships between these pillars to achieve common outcomes and economies of scale. When these three pillars work in synergy, only then will your business be able to achieve unified observability that clearly depicts the performance and health of your business in real-time. Achieving business-centric visibility with unified observability will enable your organization to answer questions like:

• How is the customer experience?
• Do our employees feel empowered to do their jobs?
• What are potential threats to our infrastructure?

Why is observability important?

The reason observability platforms are important is that they give businesses opportunities to learn more about vital aspects of there IT environments without having a backlog of questions you need to ask. This process seeks to answer how much you can understand about a system by looking at it from the outside.

Shifting the focus to the actual states of a system rather than the elements or components, observability provides an enhanced view of a system’s functionality, overall health, and ability to serve its mission.

The focus of visibility in observability is to only view what’s important as opposed to seeing everything. Visibility is the ability to view different layers of a system or infrastructure and garner context or a form of meaning from the data. The choice of monitoring tools deployed, and specific data gathered, depends on the goals of the business and how data will be used for observability.

What is Applied Observability?

Applied observability, or data observability, is the process of using observable data across business functions, application teams, and infrastructure teams in a way that is well-coordinated and works well together. Gartner expects that by 2026, 70% of organizations successfully applying observability will achieve shorter latency for decision-making, enabling competitive advantages for IT processes.  

The overarching concept of applied observability is that the future success of businesses is dependent on carefully planning using actual data as opposed to predicting the future. To gain actual value and insights from applied observability, your organization needs to shift from reactive to proactive. The key to getting a competitive edge is for IT leaders to be able to use the actual actions of stakeholders instead of their intentions or educated guesses. This allows for the shortest latency from action to reaction, as well as proactive planning of business decisions. When planned strategically and executed successfully, applied observability has shown itself to be a powerful approach to data-driven decision-making. 

Benefits of Applied Observability

How does applied observability address challenges for enterprises posed by digital transformation? Here are some benefits that result from applying observability: 

• Enhances the usefulness, quality, and comprehensiveness of the data for more precise decisions with full context;  
• Guarantees data is timely delivered to the concerned department;  
• Assists in delivering higher trust in data. The result is that enterprises can make more informed data-driven actions;  
• Data observability also helps improve the responsiveness of the data operations team to bolster the enterprise to meet organizational goals; 
• Plays a significant role in SLA tracking, assessing the pipeline data and data quality against predefined benchmarks; and 

• Data observability goes beyond alerting and monitoring, enabling businesses to understand their data systems, helping them fix data issues, and proactively preventing them. 

What is full-stack observability? 

Full stack observability can be defined as observing the real-time status of each technology stack component distributed in an IT environment. This means holistically viewing your cloud-hosted applications, services, infrastructure, on-premises servers, Kubernetes infrastructure, and other cloud-native assets.  

Through full-stack observability, IT teams can develop a thorough understanding of their highly distributed application topologies and dependencies across domains. This enables ITOps teams to easily access and manage a vast amount of data, and then correlate application performance to business outcomes. 

Why is full-stack observability necessary for my business?

Full-stack observability gives teams comprehensive, real-time insight into the behavior, performance, and health of applications and their underlying infrastructure. Benefits associated with full-stack observability include: 

• Pinpoints precise root cause and prioritizes issues based on business impact; 
• Enables end-to-end visibility across your multi-cloud ecosystem; 
• Removes operational silos and better connects IT teams; 
• Proactively identifies and resolves incidents prior to affecting performance; 
• Uses precise analytics to best align tech decisions with the needs of your business; 
• Aligns run time application security with DevSecOps; 
• Accelerates and automates the CI/CD pipeline; and 
• Optimizes your infrastructure cost and performance. 

What are the benefits of observability?

Organizations are requiring more technology to support the shift to a hybrid workforce, as a result of the COVID-19 pandemic—exacerbating monitoring challenges for ITOps teams.

There are many benefits associated with an effective observability strategy.

Those benefits include:

• Enables organizations to determine the cause of performance issues at an accelerated rate;
• Uses observable data in the software delivery life cycle to build optimally secure, resilient applications;
• Improves application uptime and brings confidence to complex infrastructure, cloud, and Kubernetes monitoring;
• Resolves issues prior to the user encountering the issue boosts customer satisfaction and retention; and
• Understands real-time business impact, improves conversion optimization, and ensures software releases will be on time and meet expected business goals.

Who benefits from observability?

Software engineers, developers, project teams, and the business, in general, all greatly benefit once an observability strategy is implemented properly into an organization. The developers and engineers benefit from gaining visibility into their entire architecture, from third-party apps and services to their own. Having this at their fingertips enables them to fix and be proactive in managing problems. There is also an improved understanding of system performance and how it shapes a better customer experience. This frees up time for developers and engineers who then have more time for strategic initiatives that benefit the business.

Observability allows a variety of teams and members across the organization to access the same insights about services, customers, and other system elements. Observability leads to post-incident reviews with the highest levels of accuracy because both parties examined official records of real-time system behavior as opposed to relying on siloed data sources. Having a reliable data source is the best way to understand why incidents occurred in the first place. This type of data source allows you to identify the root of the incident to prevent and handle future problems.

While the developers, engineers, and project teams all benefit from an observability strategy, the business ultimately gets the most value. Having observability implemented within a business allows for the ability to be agile with changes to apps and services without compromising the stability of your systems. Businesses now have the most insight into what’s working and what isn’t and are able to address any issues that occur and quickly remediate them. Innovative features mixed with less downtime translate to improved customer experiences and a direct positive impact on your organization’s bottom line.

What are the three pillars of observability?

After you establish your goals and know what to measure, it’s time to figure out how to make sense of this data and turn it into insights. The three different types of observability data that are considered the three pillars are:

• Logs
• Metrics
• Traces

What are logs?

Logs are files within software environments that record events, warnings, and errors. Logs contain contextual annotations to improve efficiency. Data is aggregated from multiple log files and then collectively analyzed.

What are metrics?

Metrics are defined as quantifiable measurements reflecting the status and performance of infrastructure and applications. The main benefit of metrics is they provide real-time insight into the status of resources. Metrics are useful as they act as a visibility KPI and remain the optimal method to gauge if your application is responsive or to familiarize themselves with anomalies that could be early performance issues signals. Through the correlation of metrics with data from logs and traces, organizations gain the maximum visibility of system performance or potential availability issues with infrastructure or applications.

What are distributed traces?

A distributed trace is data that tracks an application request as it flows through the application. As the trace flows through, it records how long it takes each component of the application to process the request and pass along the result. Traces can pinpoint which parts of the application were the initial trigger causing the error to occur.

These pillars provide different views of an organization’s resources. When combined and analyzed, the organization gains a holistic understanding of its complex application environments.

Observability Best Practices

Making the decision to implement observability into your organization is an excellent start. To overcome challenges and obstacles, here are some best practices to ensure an effective observability strategy:

• Define observability goals and KPIs for your organization;
• Curate only relevant data for observability practices;
• Contextualize data to optimize for ingestion;
• Use meaningful data for actionable outputs;
• Automate outputs with reports, alerts, and dashboards; and
• Confirm outputs are being delivered to proper recipients.

These best practices are guidelines for your organization to follow when evaluating the potential value of adopting an observability tool in your enterprise.

Real-World Examples of Observability

Here are some examples of companies that have adopted observability into their organization:

• Twitter adopted an observability strategy to improve visibility across services within multiple data centers;
• Payment provider, Stripe, uses traces to find failures and latencies within a network. Stripe also has developed an early fraud detection capability that uses machine learning to improve security;
• Uber also uses a large scaled distributed tracing system; and
• Network monitoring comes with the ability to accurately identify network-related incidents. The software reveals if a particular problem originates at the ISP or third-party platform level. This insight will tremendously reduce internal conflict and result in a timely resolution.

What are the challenges of observability?

The capability of IT teams is often overestimated in current times. With heavy workloads and a lack of time or resources to act upon the data, this creates the main problem for organizations with observability. Cloud complexity has also caused many challenges due to the rapid pace of change causing organizations to address these issues. These are a few common, recurring challenges organizations have faced when dealing with observability:

• Lack of source data;
• Multiple information formats;
• Accidental invisibility of important events and data;
• Data silos;
• Overwhelming amounts of data;
• Manual efforts for configuration or instrumentation;
• Lack of pre-production; and
• Wasting time with troubleshooting when errors occur.

In order to successfully say you have achieved observability, you need to be able to use your telemetry data to improve user experience and achieve your business outcomes. There are two other options organizations can use to monitor their environment: OpenTelemetry and real user monitoring techniques.

What is OpenTelemetry?

OpenTelemetry method provides a de facto standard for collecting telemetry data in cloud settings. Open-source solutions enhance observability for cloud-native apps giving developers the chance to achieve a consistent understanding of application health across multiple environments across an enterprise.

What is Real User Monitoring (RUM)?

Organizations have the option to implement real user monitoring which assists in gaining real-time visibility into the user experience. The way this is achieved is it goes from a single request, gaining knowledge and context along the way. This process is also known as synthetic monitoring or can be viewed from a recording of the session. This empowers ITOps, DevSecOps, and SRE teams to have real-time insights into the accurate health of systems at a consistent rate.

What is observability in software?

Observability in DevOps empowers all developers to be proficient with monitoring which creates a culture of data-driven decision-making and improves overall system performance and reduces outages. Installing an observability tool has the ability and potential to assist with the objectives and achieve your business goals if implemented appropriately. Observability is gaining traction and popularity within the DevOps community as a process that is integral to the software lifecycle.

Observability in software has benefits that include:

• Improved development speed, quality, and agility;
• Cost-effectiveness;
• Optimized user experiences; and
• Increased engineer morale.

What goes into tracking and monitoring relates to the complicated interconnectivity between these systems and what is needed to triage outages is past the capabilities of traditional monitoring solutions. Observability fulfills this function by giving DevOps teams visibility across complex, multilayered architectures so they can identify the links in a process and quickly and efficiently locate the cause of a problem.

Observability and DevSecOps

DevSecOps teams can tap into observability to garner insights into the apps they develop and automate testing so they can release quality code at a faster rate. This results in organizations wasting less time in war rooms, and no more finger-pointing and playing the blame game. Not only is this a productivity improvement, but team relationships are also strengthened, which is imperative for quality collaboration among teams.

Observability is a solution for testing if applications are behaving properly through routine inspection of potential attacks or breaches by DevOps teams who can then make needed. The goal for organizations and developers is to get new code and features in the market as soon as possible which makes it important to mitigate risk while rolling out new features daily.

Containers & Microservices in Observability

Microservices and containers isolate applications in production environments so developer teams can be able to see when issues occur and are able to resolve those performance issues. Containers and microservices break applications down into independent services, allowing developers to modify and redeploy a particular service rather than the whole application. Observability addresses these challenges, providing visibility into systems and assisting developers with comprehension of application performance and availability. In the event of a failure, it provides the control needed to pinpoint and debug or fix the problem quickly.

What are the components of observability?

The following components are building blocks for observability:

• Open instrumentation: The process of open instrumentation involves agents of code tracking and measuring data flowing through your software. The term open instrumentation refers to the gathering of telemetry data from open source or vendor-specific entities that produce that data.
• Correlation and context: It is vital to understand the big picture (especially for large enterprises). Telemetry data collected must be reviewed for context, so humans can make sense of patterns and anomalies that may arise.
• Programmability: It is imperative for businesses to develop their personalized context and custom solutions based on each organization’s unique business objectives.
• AIOps tools: You need to accelerate incident response to guarantee that your modern infrastructure is consistently available. AIOps adds big data with machine learning to orchestrate predictive outcomes for faster root-cause analysis (RCA) and improved mean time to repair (MTTR). These insights drive higher levels of automation and collaboration, saving your organization time and money.

How do you implement observability?

Once organizations decide to pursue an observability strategy, they need to find a way to onboard the process to team members and leadership. Here are the necessary steps it takes to successfully complete an observability implementation:

1. Assign personnel to the observability team;
2. Define important metrics based on business goals;
3. Establish a pipeline based on OpenTelemetry standards across the organization;
4. Document organizational best practices for data management, security, and governance
5. Eliminate siloes by centralizing data sources;
6. Decide on which analytics tools your company will use;
7. Train and provide education for your team to empower proficiency in all development teams; and
8. Develop and nurture an overall culture of observability for your organization.

Success will look different with observability depending upon the overarching goals and KPIs of your business. To achieve observability once implemented into your organization, your enterprise must:

1. Thoroughly understand the various ways your IT systems impact the overarching goals of your organization;
2. Compile a list of questions about how your systems, applications, and network are operating to have these impacts;
3. Translate questions into measurable variables; and then
4. Decipher which measurements are acceptable and will play into your overall business goals and strategies.

Evaluating Observability Tools for Your Organization

If you decide to build your own tool, pursue a commercial, or choose an open-source tool, it’s paramount to ensure your observability tool meets the following criteria. By choosing a tool with these features, you are taking the first step towards setting your organization up for success and results.

• Ability to integrate with the current software in your organization;
• They have a seamless, user-friendly nature;
• They supply your organization with data in real time;
• Supports modern event-handling techniques;
• Visualizes aggregated data;
• Provides context for your IT environment and teams; and
• Makes use of machine learning to automate processes and curation.