Observability for Cloud Applications: A Quick Guide

Observability for Cloud Applications: A Quick Guide

By Contributing Writer
Gilad David Maayan
  |  April 24, 2023

A cloud application is a software application that runs on a cloud computing infrastructure, rather than on a local computer or on-premises server. Cloud applications are designed to be accessed over the Internet and typically rely on a web browser or mobile app to provide users with access to the software.

Cloud infrastructure provides the necessary resources and services for the application to run, such as servers, storage, and databases. This allows for scalability and flexibility, as well as the ability for users to access the application from anywhere with an Internet connection. Examples of cloud applications include email services, customer relationship management (CRM) systems, and big data systems.

While cloud environments promote innovation and agility, they also introduce complexity. A cloud environment has many moving parts, many of which are ephemeral (can be destroyed and recreated at short notice), and is often distributed across multiple physical locations. Technologies like SD-WAN make it possible to dynamically reconfigure networks, which means that services must be able to discover each other and cannot communicate via static IPs.

This makes it difficult to understand how a cloud application is functioning, whether there are performance, functional, or availability issues, and how to solve them. This is where observability comes in.

What Is Observability and Why Is It Important?

Observability is the ability to understand the internal state of a system by monitoring and analyzing its external outputs. It allows developers and operations teams to understand how a system is behaving, troubleshoot issues, and make informed decisions about how to improve its performance.

There are three main components of observability:

  • Metrics: quantitative measurements of various aspects of the system, such as CPU utilization, memory usage, and network traffic.
  • Logs: records of events and transactions that occur within the system, such as error messages and performance data.
  • Traces: a detailed view of the sequence of events that occurred within the system, including the timing and duration of each event.

Observability is important because it allows teams to quickly identify and diagnose issues within a system, and to gain a deeper understanding of how the system is behaving. This can help teams improve the performance and reliability of the system, and make better decisions about scaling and deploying the system.

Additionally, observability allows teams to detect and prevent issues before they occur, which can help to minimize downtime and improve the overall user experience. It helps in various development, security, and operational tasks, including debugging and troubleshooting, monitoring and alerting, root cause analysis, and business intelligence (BI).

Observability for Cloud Applications: 3 Key Aspects

There are three ways in which observability can have a critical impact on cloud applications.

Cloud Migration

Observability is an important aspect of cloud migration because it allows teams to monitor and understand the behavior of their systems as they move to a cloud environment. This can help teams to identify and troubleshoot any issues that may arise during the migration process, and to ensure that the systems are performing as expected in the new environment.

When migrating to the cloud, teams need to be able to monitor and understand the behavior of their systems in the new environment, in order to ensure that they are meeting the performance, scalability, and availability requirements. Observability can help teams to identify and troubleshoot issues related to network connectivity, resource allocation, and application performance. It can also be used to monitor the usage of cloud resources and to identify potential cost savings.

It is important to implement monitoring and observability solutions that are cloud-native, or that are compatible with the cloud platform being used. This will allow teams to gain visibility into the system’s behavior and performance, even as it scales and changes. Additionally, teams should have a plan in place for how to collect, store, and analyze observability data to gain meaningful insights for troubleshooting and performance optimization.

Application Dependency Management

Observability can help with application dependency management for cloud applications by providing visibility into the interactions and dependencies between different components of the application. This can include monitoring the communication between microservices, tracking the performance of external APIs and services, and identifying any issues or delays in the flow of data between different parts of the system.

In addition, observability can also help with identifying the impact of changes in the application dependencies, for example, if you are planning to upgrade an external service, you can check the metrics and logs to see the impact of that change on your application performance, and take the necessary actions before it's too late.

Moreover, observability can also help with identifying potential security issues or misconfigurations related to dependencies, such as exposed sensitive data or open ports, by monitoring the network and infrastructure logs.

Logging and Tracing

Applying observability for cloud applications involves collecting and analyzing data about the performance and behavior of the application. This can include metrics such as request and response times, error rates, and resource usage. Logging can also be used to track events and actions within the application, such as user actions, system messages, and errors. Tracing can be used to understand the flow of a request through the application and identify any bottlenecks or issues.

To apply observability in cloud environments, you can use dedicated tools such as Prometheus, Grafana, Elasticsearch and Kibana. Additionally, cloud providers such as AWS, GCP, and Azure offer their own observability tools that integrate with their services.

6 Cloud Observability Best Practices

Here are some best practices for implementing observability for cloud applications:

  1. Centralize your data: Collect and store all of your observability data in a central location, such as a data lake or a monitoring platform. This will make it easier to access and analyze the data, and will also make it easier to integrate with other tools and services.
  2. Use automated alerts: Set up automated alerts to notify you of any issues or anomalies in your application. This can help you quickly identify and respond to problems before they become critical.
  3. Use distributed tracing: Use distributed tracing to understand the flow of a request through your application, and to identify any bottlenecks or issues caused by dependencies.
  4. Monitor the infrastructure: In addition to monitoring your application, also monitor the underlying infrastructure, including your network and operating systems. This can help you identify issues that may be caused by problems with the infrastructure rather than the application itself.
  5. Have a proper logging strategy: Use structured logging and have a centralized logging system in place, this will help you to easily search, filter, and analyze the logs, and it also can help in troubleshooting and debugging.
  6. Continuously validate your observability: Continuously validate your observability strategy by running tests and simulations to ensure that you are collecting and analyzing the data that you need to effectively monitor your application.

By following these best practices, you can implement effective observability for your cloud applications, providing valuable insights into the performance and behavior of your application, and helping to identify and troubleshoot issues quickly and efficiently.


In conclusion, observability is a critical aspect of managing cloud applications. It allows teams to monitor and understand the behavior of their systems in real-time, identify and troubleshoot issues, and make informed decisions about how to improve performance and scalability.

By implementing observability best practices, such as centralizing and standardizing data collection and using cloud native monitoring tools, teams can gain the visibility and understanding they need to effectively migrate and manage their cloud applications.

Author Bio: Gilad David Maayan

Gilad David Maayan is a technology writer who has worked with over 150 technology companies including SAP (News - Alert), Imperva, Samsung NEXT, NetApp and Check Point, producing technical and thought leadership content that elucidates technical solutions for developers and IT leadership. Today he heads Agile SEO, the leading marketing agency in the technology industry.

LinkedIn (News - Alert): https://www.linkedin.com/in/giladdavidmaayan/

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