Software developments take place quickly as per the client’s requirements. The developments need to take place with safety and precautions. DevOps engineers can help into this matter; however, it is not possible without Observability.
What is Observability in DevOps?
There’s no mean of monitoring without having Observability in the first place. As per the definition, a system is only observable if you can estimate the system’s current state with the available output information. The DevOps team is supposed to communicate efficiently to improve the visibility across the CI/CD pipelines. Continuous improvement is what the DevOps team intends to achieve at any given moment.
Observability in DevOps is a technical solution that helps IT firms understand the ongoing processes in the application with the help of the application’s output. It makes firms understand the problems occurring in the applications and pinpoints how, what, why, and where the application is malfunctioning with rich insights.
The Observability can be helpful to SREs (Site Reliability Engineers) for the given points below.
- Offering high-quality applications and software with scale
- Accessibility across the performances and digital assets
- Building sustainable, innovative environments
- Maximizing the organizational investments into the cloud and other tools
- Investigating root causes faster and resolving in minimum time
The Observability Components
There are three essential components to Observability. With each element, your monitoring practice gets more robust and profound. They are like building blocks. Here’s a brief introduction to each and its importance.
- Event Logs: Event logs describe discrete events with time stamps. SREs pay their attention to Logs to know about the failures and issues. With historical data of the events and failures, SREs get the context, making it easy to resolve the problems.
- Metrics: A metric is data measurements over intervals of time. It has a set of traits like time stamp, name, value, and label. An SRE uses metrics to trigger an alert whenever a number rises above the set threshold. Metrics help you define the key areas, Service Level Agreements (SLAs), Service Level Objectives (SLOs), and Service Level Indicators (SLIs).
- Tracing: Traces represent a span of executed code with three attributes, name, ID, and time value. By combining traces from any distributed system, you can see an end-to-end flow and executed path. In addition, they discover the area where codes are taking more time to get completed.
How Observability Empowers DevOps and SRE Practices
The job of DevOps and SRE teams is to understand the production systems and reduce the complexity. Therefore, it is natural for them to care about the Observability of the systems they build and govern. Where SRE focuses on the idea of managing services as per their Service Level Objectives (SLOs) and Error Budgets, the DevOps team focuses on managing services with the help of cross-functional practices.
For example, rather than notifying a plethora of alerts that enumerate potential causes of outages, mature DevOps and SRE teams both try to measure if there are any visible symptoms of user pain—in that case, drilling down into understanding the outage with observability solutions.
This approach changes the way of monitoring. From cause-based monitoring to symptom-based monitoring. Rather than wasting the majority of time in attending to false alarms, teams can focus on actual system failures. The DevOps and SRE teams can use engineering techniques such as flagging, continuous verification, incident analysis, not just to fix or resolve issues.
Here are the ways to be helpful to SREs and DevOps engineers by adopting Observability.
- Reducing the labor associated with incident management. Particularly around cause analysis, resulting in better uptime and minimum MTTR
- Providing a platform to inspect and adapt as per SLOs ultimately improves teams’ ability to achieve them
- Relieving team cognitive load and burnout specially when the team is dealing with vast amounts of data
- Releasing teams from toil, resulting in better productivity, innovation, and the flow and delivery of value
- Achieving the value stream cycle by providing rich insights around value outcomes which can be fed back into the innovation phase
The practices of DevOps and SREs keep on changing each passing day, and as engineering grows, more innovative approaches will emerge. However, all the innovations will only matter if the teams have adopted Observability in the first place as it is essential to understand the modern complex infrastructures.
The rise of innovation in DevOps, SREs, and Cloud practices has created the need for Observability. And to adopt Observability, you need to adopt an observability solution. Motadata AIOps is a monitoring solution built with AI-ML abilities. The Deep Learning Framework makes it the most innovative and powerful observability solution for IT Operations. Motadata AIOps help SREs and DevOps team streamline their mundane IT operations and enhance efficiency. Reach out to us at email@example.com to know more.