Cloud Observability and Monitoring: Ensuring Optimal Performance and Reliability

By Muskan Rawat, Dinky Lakhani, Janvi Thakkar, Shaily shah / Mar 06,2023

Aggregating the internal state data of your system and wondering what to do with it? Well, that’s where Cloud Observability and Monitoring comes to your rescue. You might wonder what ‘Cloud Observability and Monitoring’ are? How do they both differ? What is their significance? What are the pillars of Observability? What are the Best Practices that one needs to follow?

Below, we have answered the above questions. Read on to find out and address your curiosities.

The challenges of the cloud:

Due to intricate billing structures and cost models offered by Cloud Services Provides (CSPs), it can be challenging to make a realistic cost-estimate of running a specific workload based on the actual cloud resource utilization. Overprovisioning of resources is another common challenge that IT department faces by planning months in advance and executing workloads round-the-clock. Employees tend to avoid IT approval to acquire instant access to new applications by dodging protocols which can then lead to data exposure.

To overcome these challenges of the cloud, FinOps came into existence in 2019. FinOps is a portmanteau of “Finance” and “DevOps”, stressing the communications and collaboration between business and engineering teams. [Reference: FinOps Foundation - What is FinOps?]

In the current scenario, FinOps is a regular exercise in the cloud industry whereas initially it was considered as a side-work. Let’s understand the core principles of Cloud FinOps.

Cloud Observability

Cloud Observability refers to the ability of a system to assess its internal state based on the data it produces. The Operations team can detect abnormalities & issues and troubleshoot them after an in-depth analysis of the health and status information of the system’s resources.

Cloud Observability tools understand the relationships between systems across a company’s diversified and multi-tiered infrastructure comprising of cloud environments, on-premises applications, and third-party software. Whenever the observability tool detects an abnormality, it pings the team and provides them with the necessary insights to troubleshoot and resolve the issue rapidly.

Key Components of Cloud Observability:

There are three pillars of cloud observability - Metrics, Logs, and Traces. Let us understand each of the pillars.

1. Metrics:Metrics are intended to provide observers with information about a part or system's health and operation.

2. Logs:The log data provides information about discrete events that occurred within a component. Log data is usually larger than metric data.

3. Traces:Trace is a key pillar of cloud observability, providing users with real-time monitoring and debugging tools. Trace ensures optimal performance by identifying and addressing any application issues quickly.

How can observability help identify and diagnose issues :

Observability is a tool that helps identify problems before they start, allowing developers to preemptively fix potential issues. There are a few methods that can be helpful when it comes to observability:

1. Logging & Monitoring:Logging & Monitoring can help detect errors or spikes in performance. In this way, the root cause of a problem can be identified.

2. Tracing:Tracing can identify bottlenecks and errors in a system by tracking requests as they move through it.

3. Metrics & Alerting:These tools are used to monitor the performance of a system. Metrics allow for the collection of data on the performance of a system. Alerting can then be used to notify administrators or other personnel of any changes in the system's performance.

4. Distributed Tracing:: Distributed Tracing can be used to monitor the performance of distributed systems. Performance issues, such as latency and throughput, can be identified & diagnosed through this process.

5. Application Performance Monitoring:This is useful in monitoring the performance of individual services and the entire system as a whole. Using this approach can contribute to the identification & diagnosis of performance, scalability, and availability issues.

Cloud Monitoring

Monitoring refers to the aggregation and analysis of data collected from the system. Often, the DevOps team creates dashboards using particular metrics to monitor. Monitoring can only help if one knows which metric to track. Untracked data could expose issues that go unobserved. The difference between Observability and Monitoring lies in the fact that Observability collects all data produced by the system, while Monitoring collects & analyzes a predetermined set of data from the system

Here are a few types of Cloud Monitoring

1. Website Monitoring:Website Monitoring is concerned with whether end users can interact with the website appropriately.

2. Virtual Machine Monitoring:Track the performance of virtual machines, including their availability and health status.

3. Database Monitoring:It monitors queries on the database, access requests, data integrity, and any connections that reflect real-time data usage.

4. Virtual Network Monitoring:It is primarily used in real-time to track the performance of routers, firewalls, and load balancers.

5. Cloud storage monitoring:It is used to track users, databases, processes, existing storage, and performance metrics.

Importance of Cloud Observability and Monitoring for Cloud Infrastructure

Cloud Observability and Monitoring play a crucial role in areas besides analyzing and mitigating known & unknown issues. They are:

Detects tricky problems.
Troubleshoot optimally by reducing MTTR, MTTI, and MTTA.
Improves end-user experience.
Optimizes cost.
Evolves with automation.
Saves time.
Boosts developer productivity.
Optimal resource utilization.
Detect latency issues.
Helps make informed decisions
Provides real-time monitoring & alerting.

Best Practices for Cloud Observability and Monitoring

Cloud observability and Monitoring plays a vital role in detecting and resolving issues in the cloud system. To ensure effective cloud observability and monitoring, it is important to follow best practices.

Set clear goals and metrics:Start with setting clear goals and metrics to measure the success of monitoring processes, including identifying key performance indicators (KPIs) and defining acceptable thresholds for each metric.
Select right tools:Selecting the right tools for monitoring and observability, such as logging, tracing, and metrics collection tools is equally essential. Ensure that the chosen tools are compatible with the cloud environment and provide real-time alerts for any potential issues.
Involve Stakeholders:Involving stakeholders, establishing clear communication channels, delivering relevant training, and integrating feedback to continuously improve the monitoring process is critical.

Tips for scaling observability and monitoring as your infrastructure grows:

When it comes to scaling observability and monitoring as your infrastructure grows, there are a few tips you can keep in mind.

Start with a solid foundation:Ensure that you have a robust monitoring infrastructure in place before you start scaling.
Invest in observability:Observability allows you to monitor your infrastructure and applications from a user perspective.
Automate everything:Automation allows you to scale your monitoring and observability with your infrastructure.
Keep it simple:When it comes to monitoring and observability, often, less is more. Avoid adding unnecessary complexity and stick to the basics.

Conclusion

In today's fast-paced digital world, where businesses rely heavily on cloud infrastructure, ensuring the reliability and performance of cloud systems is critical. Therefore, it is essential to invest in tools and technologies that enable effective cloud monitoring and observability. The importance of cloud monitoring and observability cannot be overemphasized. By adopting best practices, organizations can proactively detect and address issues, leading to improved uptime, enhanced user experience, and better business outcomes.