What is application observability?

No matter how well prepared or skilled your engineers are at maintaining your critical services, unforeseen technical issues are inevitable. Any downtime can severely impact customer satisfaction and lead to significant revenue losses, potentially costing your business hundreds of thousands of dollars per hour.

Application observability offers a robust framework to address these challenges. This approach can dramatically reduce downtime expenses, with some businesses seeing up to a 90% decrease in related costs. Even companies with basic initial implementations have reported annual savings from $23.8 million to $2.5 million.

Read on to learn about application observability and discover how it can help your programs run smoothly, meet customer expectations, and ultimately protect your bottom line.

What is application observability?

Application observability is a comprehensive approach to understanding and managing the performance of your software systems by collecting, correlating, and analyzing telemetry data from various components of your applications. This practice provides deep insights into the internal states and behaviors of your software, allowing you to quickly identify and resolve issues, optimize performance, and enhance user experience.

By leveraging application observability, your team gains a holistic view of your entire software ecosystem, including how different components interact and affect each other. This visibility enables proactive problem-solving and informed decision-making, ultimately leading to more reliable and efficient applications that better serve your customers' needs.

The three pillars of observability

Application observability relies on three foundational elements that work together to provide comprehensive insights into your applications' performance and operations. These pillars offer a thorough understanding of issues that may impact essential services for your customers:

1. Logs

Logs serve as a historical record of events and errors within your applications. They capture crucial information such as HTTP requests, SQL queries, and error stacks. By maintaining effective logging practices, such as implementing different logging levels and filtering sensitive data, your engineering team can quickly pinpoint issues affecting customer experience.

2. Metrics

Metrics measure key performance indicators (KPIs) that directly influence how smoothly your services operate. These include response times and resource usage. By collecting appropriate metrics at the right level, your teams can detect performance changes before they negatively impact customers. Common types of metrics include:

• System metrics: These monitor infrastructure performance through indicators such as CPU usage, memory consumption, disk I/O, and network throughput.

• Business metrics: KPIs such as transaction volumes, revenue, user engagement, and conversion rates offer insights into your overall business health and success.

• Custom metrics: These focus on performance indicators specific to your unique business needs and applications.

3. Traces

Traces track requests as they move across multiple services in complex business systems. Distributed tracing correlates these traces from each service, providing a clear picture of end-to-end request flows. This capability helps identify bottlenecks or failures, such as issues between a customer registration service and payment processing, allowing your teams to efficiently debug and resolve problems.

Observability vs. monitoring

When evaluating solutions to manage and optimize your business systems, two key concepts frequently arise: observability and monitoring. Understanding the distinction between these approaches is valuable for selecting the most effective solution for your operations.

Monitoring solutions play a vital role in maintaining service level objectives and alerting your team to known issues. They typically focus on predefined metrics and thresholds, providing valuable insights into system performance and health. However, monitoring alone may not offer the comprehensive visibility required to address complex, interconnected systems.

Application observability, on the other hand, takes a more holistic approach. It goes beyond simple threshold monitoring to provide deep insights into your system's behavior and performance. Observability platforms help uncover unknown issues and relationships, such as how third-party services might impact your own performance without triggering traditional alerts.

While monitoring answers the question "Is there a problem?", observability helps answer "Why is there a problem?" This deeper level of insight enables your team to:

• Proactively identify potential issues before they affect users

• Quickly diagnose and resolve complex problems

• Understand the root causes of performance bottlenecks

• Gain insights into user behavior and system interactions

By combining monitoring and observability practices, you can create a robust strategy for managing your systems, ensuring optimal performance, and delivering exceptional user experiences.

The benefits of application observability for your business

If you aim to maximize efficiency and meet customer needs, application observability is the right solution. It provides numerous benefits for your organization by offering deep insights into your internal system states and strengthening key aspects of your operations:

• Enhances troubleshooting capabilities: Observability equips your engineers with comprehensive logs, metrics, and traces, enabling them to quickly diagnose complex, multi-system issues that impact your services.

• Improves system performance: Metrics from observability help identify bottlenecks and anomalies that could slow performance if left unaddressed.

• Enhances user experience: A faster resolution of problems translates to fewer disruptions and outages that frustrate customers.

• Enables proactive issue detection: Observability supports monitoring trends and patterns to surface potential issues before they impact end users.

• Reduces Mean Time to Resolution (MTTR): Deep insights enable faster problem identification and resolution, minimizing downtime and ensuring systems return to service quickly.

• Supports informed decision-making: Data from an observability platform empowers you to make evidence-based choices around capacity, features and upgrades.

• Increases development velocity: The context provided by logs, metrics, and traces accelerates the development and testing of new features, ultimately improving overall system performance.

6 best practices for application observability

To maximize the benefits of application observability for your organization, follow these proven practices during implementation. By strategically focusing on objectives, tools, and instrumentation, your observability initiatives can significantly enhance operations. Here are some essential practices for effective implementation: 

1. Define clear objectives

Collaborate with your development and operations teams to identify two or three key goals for your observability efforts. This focused approach ensures everyone directs their energy towards areas that will deliver tangible results for your business and customers.

1. Choose the right tools

Conduct thorough research to select observability tools that integrate seamlessly with your existing technologies. Consider your application architecture, current monitoring needs, and budget constraints. Test potential solutions to assess how easily you can instrument relevant components like databases and services to generate useful telemetry data.

1. Implement comprehensive instrumentation

Task your development teams with configuring all microservices, databases, client-side code, and other relevant components to collect essential metrics, logs, and traces. This holistic approach ensures you capture a complete picture of your system's performance.

1. Establish baselines and thresholds

Measure typical metrics such as error rates, response times, and resource usage over time to define standard performance levels. Use these results as baselines and set appropriate alerts to quickly identify concerning deviations that may indicate issues requiring attention.

1. Promote a culture of observability

Establish an environment where employees understand how to proactively use data from observability tools to continuously improve reliability, security, and customer outcomes. Encourage data-driven decision-making across your organization.

1. Continuously refine and improve

As your needs evolve and tools update, regularly audit your instrumentation and re-evaluate monitored metrics. This ongoing refinement ensures your observability strategies remain optimized to support your business and customers in the long term.

Challenges in implementing observability

While implementing observability practices offers many benefits for organizations like your business, various challenges must be addressed to adopt these solutions successfully. Understanding these hurdles is key to overcoming them. Let's have a look:

• Data volume and management

The sheer volume of telemetry data generated from monitoring applications and infrastructure can overwhelm teams if not properly managed. Careful planning is required to store and analyze large datasets while balancing data retention with actionable insights.

• Tool selection and integration

With a wide array of observability tools available, selecting options that suit your specific needs and integrate with existing technologies can be complex. This process requires thorough evaluation and testing to ensure optimal compatibility and functionality.

• Skill gaps and training requirements

Observability practices often demand specialized knowledge that your existing employees may lack. Addressing these skill gaps through targeted training and development programs requires investment in time and resources, but is essential for long-term operational success.

• Privacy and security concerns

Collecting and storing vast amounts of data raises compliance challenges, particularly with regulations such as CCPA, EU-US DPF, and GDPR that protect customer information. Implementing robust data protection measures is crucial to maintain compliance and customer trust.

• Cost considerations

Implementing observability solutions can strain budgets due to expenses related to tool licensing, infrastructure for data collection and analysis, and potential additional personnel or training costs. Careful financial planning and ROI analysis are necessary to justify these investments.

• Cultural resistance

Shifting from traditional monitoring to new observability practices may face resistance within the organization. Effective change management strategies are essential to gain acceptance and promote adoption across teams.

• Noise and alert fatigue

Without careful tuning, excessive alerts can overwhelm teams and lead to critical issues being overlooked. Diligent setting of proper thresholds and filters is necessary to maintain an effective alert system that highlights truly important issues.

• Complexity in distributed systems

Tracing issues across microservices and serverless components in modern distributed systems presents unique challenges. Advanced techniques are required to effectively correlate data from various sources and gain a comprehensive understanding of system behavior.

Why Fastly is the best solution for real-time application monitoring

While observability provides crucial insights that enhance troubleshooting capabilities and improve system performance and user experience, implementing it can be fraught with difficulties. Fastly's real-time approach effectively addresses these challenges, offering a comprehensive solution for modern application monitoring.

Traditional observability solutions often fall short in providing visibility into edge computing and real user experiences. Fastly overcomes this limitation by offering extensive data on your entire delivery infrastructure, from the network to the applications. This holistic approach ensures you have a complete picture of your system's performance.

Key features of Fastly's observability solutions include:

• Real-time logging: Fastly captures up-to-the-minute data across regions and edge locations, enabling quick troubleshooting of issues that impact distributed user bases. This real-time insight allows for rapid problem resolution and minimizes downtime.

• Domain Inspector: This tool provides clarity into your DNS infrastructure, offering valuable insights that help optimize and secure domain performance. By understanding your domain's behavior, you can proactively address potential issues before they affect users.

• Origin Inspector: It offers transparency into the origin infrastructure, allowing you to monitor and manage the health and performance of your origin servers. This feature ensures that your core systems are operating efficiently and reliably.

• Edge Observer: Fastly collects insights at the edge globally, giving you a comprehensive view of edge server performance. This capability enables you to leverage the benefits of edge computing effectively, improving response times and reducing latency for your users.

Learn more about how you can use Datadog and Fastly to improve user experiences, accelerate development, and take advantage of edge computing.