As software delivery systems race to reap the benefits of digital transformation with cloud migration, they're fraught with crippling complexity, new challenges, and overwhelming data noise. When the number of applications or services - in these sprawling multi-cloud environments - reach a certain tipping point, you lose track of what runs where and how well these perform. It's critical to continuously examine these massive volumes of high-velocity data streams to identify known and unknown issues in production. This is exactly when observability and monitoring come into the picture. 

To start with, let us define the two terms before delving into the nitty gritty. Simply put, monitoring is the task of finding problems by collecting and analyzing data, whereas observability is achieved by resolving these problems. Observability helps teams understand the internal state of systems across multi-cloud environments using metrics, logs, and traces. Monitoring and observability offer a two-pronged approach, which helps in maintaining the performance and reliability of software environments. 

When it comes to running software in production, monitoring and observability provide the necessary information to:

• Improve the customer experience.
• Reduce Mean Time to Repair (MTTR).
• Improve Mean Time Between Failures (MTBF).
• Provide the reliability and availability that customers expect.

As per Gartner’s predictions about the pace of change in the software delivery world, “By 2024, 30% of enterprises implementing distributed system architectures will have adopted observability techniques to improve digital business service performance, up from less than 10% in 2020.” 

But what does monitoring really mean? And what can observability actually provide? 

To gain a better understanding of observability / monitoring, let’s dive in to explore each term in detail. This will give you enough info that you should be able to start building these practices.

What's Observability in DevOps?

Complex modern infrastructure involves distributed systems like cloud, containers, microservices, serverless, and a lot more combinations of these technologies. As the usability and complexity of your system increases with too many parts interacting, it becomes difficult to analyze the problems and predict future ones. 

Enter observability. Observability is the ability to understand a system’s internal states from external outputs such as logs, metrics, and traces. As per control theory, observability is a mathematical dual to controllability. It is a technical solution that uses instrumentation to gather insights, and explore patterns and properties not defined in advance. Actionable insights obtained by evaluating the outputs generated by software systems enable you to reach meaningful conclusions into your system’s health. 

Observability focuses on three telemetry types, widely known as the pillars of observability:

• Metrics: These are numeric values measured over an interval of time with attributes like granular, timestamped, and immutable records of application events. System metrics are easier to query and can be retained for longer periods.
• Logs: These are time-stamped text records of events that occurred at a particular time. They come in three formats: plain text, structured, and binary. Error logs are basically the first thing you look for when something goes mayhem in a system.
• Traces: These represent the end-to-end 'journey' of a user request through the entire distributed architecture and back to the user. Using distributed tracing, you can track the course of requests through your system and identify the cause of any breakdown.

In short, observability focuses on assessing how a system works without interfering or even interacting with it. When done correctly, observability offers a series of benefits:

• Enhanced visibility of system performance and health.
• Discover and address unknown issues with accurate insights.
• Fewer problems and blackouts as a result of optimized workflows.
• Predict issues based on system behavior / outs by combining observability with AIOps machine learning and automation capabilities.
• Catch and resolve issues in the early phases of the software development process.
• Deep-dive into logs and inspect stack trace errors.

You need an observable system to spot problems as they arise before they disrupt the customer experience. Early recognition and preemptive resolution enable better decision-making and a faster feedback loop.

What Are Good Observability Tools?

Observability systems enable developers to understand the internal state of a system at any point in time. Let us take a look at what good observability solutions offer:

• User-friendly: Good observability platforms will provide an at-a-glance overview of multiple areas of the business, which makes even the most complex data easy to read and interpret. 
• Total visibility of your system: You'll know exactly what’s going on in your business at all times with insights in easily digestible formats, such as dashboards for example, that you can comprehend quickly. This way, your business is better positioned to adapt to changing market conditions.
• Delivers business value: When you can collect data and analyze key metrics important to your business quickly and meticulously, you get to know where to focus your time to increase results.
• Real-time, actionable data: With real-time insights about an issue, its impact on ‌customers, and how it can be resolved, you have a good chance of achieving higher retention rates and increased revenue.
• Support modern techniques: Effective tools collect observability data from across your operating environments, stacks, and technologies, and offer the required context for teams to respond.

What’s Monitoring in DevOps?

When propelling forward with new releases, proactive monitoring is a way to discover issues that were missed when running monitors in the background. Of course, system failures can occur in organizations from time to time, owing to unforeseen events. However, monitoring focuses on minimizing the frequency of such failures by a significant proportion. 

Simply put, a good monitoring system aids DevOps teams in identifying issues and receiving alerts about them. Monitoring tools enable you to initiate rapid responses to such issues, avoid unplanned outages, and achieve strategic business objectives and performance targets, in addition to improving visibility of the production environment.

Although monitoring may appear ‌outdated, this technology is critical to DevOps teams’ success. Gaining a comprehensive and real-time perspective of the product is crucial, with enterprises embracing DevOps to accelerate the application development process. Monitoring tools provide visibility into application health, performance, and usage patterns as well as input from production. 

Throughout the entire software development lifecycle, from planning to development, integration and testing, deployment, and operations, monitoring tools help with automation and expanded measurement and visibility. This, in turn, lets you fortify security measures - threat assessment, root cause analysis, incident response, computers, and database forensics. In short, the dreaded and expensive downtime of development teams can be minimized if you are able to respond and resolve them in a timely manner. 

What Are Good Monitoring Tools?

Constant monitoring helps gain insights on your IT infrastructure, which helps you offer top-notch services to your customers. Let us take a look at what a good monitoring tool offers:

• Early detection: Regular and up-to-date scanning and monitoring enables you to rectify any sort of anomalies or discrepancies in the system beforehand. A clear picture of how your applications and infrastructure are performing helps detection of problems before they become a major issue.
• Real-time alerts: Live warnings not only alert teams about performance issues, but also enables them to resolve reliability issues quickly.
• Identify threats: Continuously monitoring your systems is very crucial to identify security threats, which could otherwise lead to data loss, security breaches, or other vulnerabilities.
• Improve reliability: Monitoring offers you a better idea of which elements in your system might need an upgrade or even replacement.
• Cost effectiveness: With monitoring done right, you can anticipate upcoming issues and predict downtime in your business. Detecting and fixing issues beforehand prevents unhappy customers and saves your reputation.

Observability vs Monitoring

Observability and monitoring might sound vaguely similar, but aren't the same thing. Although observability and monitoring are typically used interchangeably, they aren't one and the same. Monitoring notifies you when something is not operating well, and observability helps you figure out why. 

Monitoring and observability exist in a symbiotic relationship in which both are inextricably linked. It is a fact that achieving visibility to spot anomalies and identifying their effect on your services is well beyond human ability. It's possible to monitor without observing, but that would significantly diminish your ability to analyze and resolve ‌problems quickly. 

As you make more changes to your system it's more likely that something might go mayhem. Monitoring and Observability tools ensure that you can maintain ‌operational stability as ‌development velocity increases. The observability of a system depends on:

• Simplicity of a system
•  Representation of the performance metrics
• Ability of a monitoring tool to identify the correct metrics

These insights help determine the internal states of a system despite a system’s inherent complexity. Monitoring tools make use of these insights and help you understand what’s not working. Although it is a common notion to speak in terms of observability vs monitoring, the truth is that you can’t have observability without monitoring.

Conclusion

The ultimate goal of any business is to build resilient systems and modern applications that are available with high uptime. Unlike the situation in the monolith architecture days, complex distributed systems make it harder to achieve full visibility into an application. 

Finding anomalies and identifying their ultimate effects when running production software can be a task well beyond human ability. Observability and monitoring go hand in hand, so you need both if you want to build reliable systems. The two-pronged approach offered by observability and monitoring lets you grab the bull by the horns. This combination provides accurate insights about the internal states of a system despite its complexity.

We'd like you to continue your reading journey with this piece on dashboarding. It could give you good ideas about what to collect data for.