Monitoring and Observability play a crucial role in the health status monitoring of the deployed application. The responsibility of the operations team does not end with the deployment but it shifts to the role of the vigilant observer where the application is watched for performance. There is a subtle difference in the concept of Monitoring and observability.
Let’s take a quick dip into the concepts …
CI/CD approach in DevOps offers improved quality of the deliverables at reasonable costs. At the same time, it needs continuous application vigilance throughout the development life cycle. Monitoring helps assess the real-time status of the application in terms of functionality, performance as well as infrastructure in the production environment. It makes the system resilient that withstands unfavourable technical events.
What is Observability?
Observability refers to gauging the internal state of the system by examining the outputs. The Observable system provides the current state of the system by analyzing its output. There are various logs and traces that aid in detecting suspicious situations. This helps the team to dig down to the actual cause of the problem and take concrete action.
The Exact Difference
Monitoring and observability can be considered as two sides of the same coin. Both of them are used to trace out the problems underneath the deployed application. Monitoring alarms the signal when something goes wrong while observability helps in the identification of the failure, its possible cause, and the possible solutions. Output is the base of the investigation. It is being observed and the problem is traced out.
Observability- one step ahead of monitoring
Observability uses Logs, Matrices, and Traces in order to identify the underlying problems. Logs provide insight into the working of the application. Matrices provide statistical facts about the application’s health status. Traces focus on the application flow from one point to another. These are the tools that help investigate the root cause of the application failure.
Reactive Vs Proactive approach
Monitoring takes a reactive approach wherein you are been given an alert that something has gone wrong in the system and immediate action is required. Observability hinges on the proactive approach where the problems are anticipated prior and preventive measures can be taken to minimize the failure effect.
Both of them work hand in hand
Monitoring is carried out with the help of metrics, logs, and dashboards that alarm the signal of failure in the application. It also identifies the dependency among the different system components. Observability takes the investigation one step ahead and answers the questions related to the root cause of failure that aids DevOps teams in debugging, applying fixes, and retuning the application
Monitoring tools and Observability Tools
There are Monitoring and observability tools available in two flavors Saas and in-Premise. One can opt for the suitable one considering the exact requirements.
Some of the monitoring tools include -AppDynamics, Dynatrace, Grafana, etc.
AppDynamics and Dynatrace are available as Saas as well as in-premise monitoring tools. Grafana offers visual dashboards for logs, traces, and metrics.
DataDog, Lightstep, New Relic, and Splunk are some of the Saas observability tools available in the market.
When an organization is opting for a Monitoring or Observability tool, the following points need to be considered.
- One should opt for the solution considering present needs as well as future expansion demands.
- The observability/Monitoring platform should provide seamless integration with existing infrastructure and software components.
- The vendor should assist with continuous support.
- The tool should be reliable and scalable
- The platform should support Machine learning and AI capabilities for predictive insights.
Monitoring and Observability are equally important. One signals an alert on system failure while the next help investigates the problem and take necessary measures. Both phases need to be fine-tuned so as to achieve resilient and stable system performance after deployment.