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Observability ‐ Logging & Metrics
When working with a small website that runs on a few servers, logging, metrics, and automation support are good practices but not a necessity. However, now that your site has grown to serve a large business, investing in those tools is essential.
Logging: Monitoring error logs is important because it helps to identify errors and problems in the system. You can monitor error logs at per server level or use tools to aggregate them to a centralized service for easy search and viewing.
Metrics: Collecting different types of metrics help us to gain business insights and understand the health status of the system. Some of the following metrics are useful:
Host level metrics: CPU, Memory, disk I/O, etc.
Aggregated level metrics: for example, the performance of the entire database tier, cache tier, etc.
Key business metrics: daily active users, retention, revenue, etc.
Automation: When a system gets big and complex, we need to build or leverage automation tools to improve productivity. Continuous integration is a good practice, in which each code check-in is verified through automation, allowing teams to detect problems early. Besides, automating your build, test, deploy process, etc. could improve developer productivity significantly.
What is Observe?
Observe, Inc. is a cloud-based Observability platform designed to help organizations monitor, analyze, and troubleshoot their logs, metrics, and traces in one unified system. It’s often used as an alternative to traditional observability tools like Datadog, Splunk, and New Relic but with a data-first approach.
Key Features of Observe:
✅ Unified Data Model – Converts logs, metrics, and traces into structured data for better insights. ✅ Powerful Querying (LQL - Log Query Language) – Allows for deep analysis of system behavior. ✅ Scalability & Cost Efficiency – Stores observability data in cloud object storage (e.g., S3), reducing costs. ✅ Event Correlation – Helps connect different system events for better debugging and root cause analysis. ✅ Integrations – Works with AWS, Kubernetes, and common DevOps tools.
How Observe Differs from Other Observability Tools
Unlike Splunk, which is primarily log-focused, Observe structures logs as relational data for better queryability.
Compared to Datadog, Observe offers cheaper storage by leveraging object storage instead of hot databases.
Unlike Prometheus, which is mainly for metrics, Observe supports logs, traces, and events in one place.
Do You Need Help With Anything Specific in Observe?