Draft:Observability Tools
Submission declined on 21 December 2023 by KylieTastic (talk). This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources. This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
| ![]() |
Observability tools are integral in the realm of software engineering, offering insights into system performance, health, and reliability. These tools monitor, diagnose, and understand the behaviors of applications and infrastructure. Observability is based on logs, metrics, and traces.
Definition
[edit]Observability is the capacity to understand a system's internal states from its external outputs. Observability tools collect, aggregate, and analyze data, offering a comprehensive view of system performance and health.
Importance
[edit]With the rise of microservices, distributed systems, and cloud-native technologies, understanding system behavior has become more challenging and critical. Observability tools are vital for maintaining system reliability and ensuring a seamless user experience.
Types of Observability Data
[edit]- Logs: Records of events within applications or infrastructure.
- Metrics: Numerical data representing system aspects at specific times.
- Traces: Depictions of a request's journey through the system.
Key Features of Observability Tools
[edit]- Data Collection: Gathering logs, metrics, and traces.
- Data Aggregation: Combining data for a comprehensive view.
- Visualization: Displaying data in formats like dashboards.
- Alerting: Notifying of anomalies or issues.
- Analysis: Providing insights from the data.
Prominent Observability Tools
[edit]- Cribl Stream: Known for routing, reducing, and redacting data, optimizing observability pipelines.
- Prometheus (software): An open-source monitoring and alerting toolkit for metric collection and querying.
- Grafana: Provides advanced visualization features, creating detailed dashboards from various data sources.
- Elastic Stack (ELK): Comprises Elasticsearch, Logstash, and Kibana for searching, analyzing, and visualizing data.
- Jaeger (software) and Zipkin (software): Distributed tracing systems for microservice architectures.
Challenges and Future Directions
[edit]Observability tools face challenges like vast data volumes, maintaining data quality, and adapting to evolving technology. Future trends point toward intelligent, automated solutions for predictive issue detection and deeper system insights.