Frequently Asked Questions on Observability

What is observability in simple terms?

This refers to the fact that it is possible to understand exactly what is happening within a system such as an app or a website by looking at the data being generated.

Why is observability important for IT teams?

It enables them detect and fix problems instantly before users are affected, by giving them a holistic view of all moving parts and technologies.

How is observability different from traditional monitoring?

Monitoring looks out for issues that are known while observability allows you to investigate and recognize unforeseen difficulties that were not expected.

What are the key types of data used for observability?

Logs (event records), metrics (measurements over time), traces (a route through a request) and user experience data.

What are some challenges with observability in modern cloud environments?

These include too much information from multiple directions, manual configuration work involved, understanding connections between distributed components, and aligning information across teams/tools.

How can AI and automation help with observability?

AI can analyze huge data volumes to automatically expose problems and causes. Automation detects components and captures data without interruption.

Besides IT operations, how else is observability valuable?

It provides business insights by connecting technical data to customer experiences, conversions, and objectives – helping prioritize decisions.



What is Observability?

As technology systems become more complicated, the teams that manage them face growing challenges in keeping track of and addressing problems across different cloud environments. Due to this, the teams responsible for operations, development, and system reliability seek better visibility and understanding of these diverse and intricate computing setups. They need simpler ways to monitor and identify the issues within these complex systems.

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Table of Content

What is observability? Difference between monitoring and observability Why is observability important? Benefits of observability How do you make a system observable? Why the three pillars of observability aren’t enough What are the challenges of observability? The importance of the single source of truth Making observability actionable and scalable for the IT Department...

What is Observability?

Observability means we can understand how a system works based on the information it produces, like logs, measurements, and traces. As cloud systems have become more complicated, observability has become more important. It’s harder to find why something goes wrong or doesn’t work as expected....

How Observability Works?

Observability relies on the information collected from various parts of your cloud and infrastructure. Each component like hardware, software, cloud, containers and tools generate logs of what they do. Observability helps you understand what happens within these systems, so you can locate issues and keep your systems running and customers satisfied....

Implementing Observability

Most organizations implement observability using tools or services like Open Telemetry which is open source. Organizations also use observability platforms to detect and analyze incidents that impact their operations, software, security, or user experiences. As teams get familiar with observability data, they realize this advantage extends beyond IT into the entire company....

Difference Between Monitoring and Observability

Monitoring...

Why is Observability Important?

Understanding Unknown Problems...

Benefits of Observability

1. Application Performance Monitoring...

How do you Make a System Observable?

1. Logs: Text records of events that happened at a given point in time....

Why are the three Pillars of Observability Aren’t Enough?

The Importance of Open Source Solutions...

What are the Challenges of Observability?

Data Silos: Understanding the interdependencies across applications clouds and digital channels like web, mobile and IoT is difficult due to multiple agents, different sources of data, siloed monitoring tools. Data Overload: It is almost impossible to make sense of the vast volumes of raw data collected from all components in dynamic cloud environments such as AWS, Azure and Google Cloud Platform (GCP) as well as Kubernetes and containers. Manual Instrumentation: IT resources dedicate the majority of their time to establishing observability rather than acting on insights when they need to manually instrument and modify code for every new component or agent. Lack of Pre-Production: Developers cannot see how actual users will impact applications and infrastructure before pushing code into production even with load testing. Troubleshooting Inefficiency: Telemetry data across multiple tools and vendors makes no sense; teams lose valuable time trying to identify root causes for problems. Multiple Tools: There are many systems that could impact performance so one single tool might not give full observability across all application systems....

The importance of the single source of truth

Organizations need a single source of truth to gain complete observability across their application infrastructure and accurately identify the root causes of performance issues. When organizations have a single platform that can handle cloud complexity, capture all relevant data, and analyze it with AI, teams can instantly identify the root cause of any problem, whether it’s in the application itself or the supporting architecture....

Making observability actionable and scalable for the IT Department

1. Understand Context and Topology...

Frequently Asked Questions on Observability – FAQs

What is observability in simple terms?...