So what’s the difference between Monitoring and Observability?
IT Monitoring and IT Observability are two approaches used in the field of information technology (IT) to gain insights into the health, performance, and behaviour of systems, applications, and infrastructure. While both concepts aim to provide visibility into IT environments, they differ in their focus and methodologies.
IT Monitoring refers to the practice of collecting data from various components within an IT system and using that data to track the performance and availability of those components. It typically involves setting up monitoring tools, agents, or sensors that gather metrics such as CPU usage, memory utilisation, network traffic, and response times. These metrics are often stored in a time-series database and displayed through dashboards or alerting systems.
The key characteristics of IT Monitoring are:
1. Metrics-driven: Monitoring relies on predefined metrics and thresholds to determine the state and health of the system.
2. Proactive approach: Monitoring is focused on identifying potential issues and deviations from normal behaviour.
3. Limited context: Monitoring primarily provides visibility into specific metrics and predefined areas of interest, making it suitable for known problems and scenarios.
4. Data-centric: Monitoring focuses on collecting and analysing quantitative data for performance and availability metrics.
IT Observability, on the other hand, is a holistic and proactive approach that aims to understand complex systems by leveraging diverse sources of data, including logs, metrics, traces, and events. It involves capturing and analysing not only the metrics but also the contextual information necessary to gain a deep understanding of system behaviour and diagnose complex issues.
The key characteristics of IT Observability are:
1. Context-rich: Observability goes beyond metrics and captures qualitative data, such as logs and traces, to provide a more complete understanding of the system.
2. Event-driven: Observability emphasises capturing events and traces that can help reconstruct the system’s behaviour during specific events or incidents.
3. Adaptable and flexible: Observability is designed to handle unknown and unexpected issues, making it suitable for complex and distributed systems.
4. Root-cause analysis: Observability facilitates deep investigation and root-cause analysis by providing comprehensive visibility into the system’s internal workings.
In summary, IT Monitoring focuses on collecting predefined metrics to track the performance and availability of specific components, while IT Observability takes a more comprehensive approach by leveraging various data sources and contextual information to gain a deeper understanding of complex systems and diagnose issues. Observability provides a more flexible and adaptable framework for understanding and troubleshooting IT environments.
The main issue I see in the IT market today is that companies are jumping on the observability bandwagon much like they jumped on the cloud phenomenon over the past few years…
As Microfocus said in a recent webinar, migrating to the cloud won’t solve all of your problems, in some ways it’s just another datacenter, and needs to be managed and monitored accordingly. Many clients have been caught out byy this it seems.
The same goes for observability tools.
They won’t magically fix all of your issues – if anything they will highlight where your underlying tools and systems and deficient and not working as effectively as they could be. I’ve seen this to be the case 1st hand in a number of blue-chip organisations.
It’s therefore essential before you deploy observability tools into your environment that you ensure all data feeds are reviewed, improved, cleaned-up and are doing the job they were intended to do.
Only then can you start to reap the proactive features and benefits that observability tools can provide.
You won’t see anything of use if the (data) lake is polluted.