Anomaly Detection Model in Observability Data
Budget: $250 – $750 USD
I am seeking a proficient data scientist, well versed in Python, to develop an anomaly detection model for my project. The model should have the ability to:
- Detect unusual behavior patterns
- Identify potential failures
Your task will involve utilizing logs and traces from our microservice observability data. It is imperative that your expertise in Python contributes to developing a robust and efficient model. This project requires a balance of critical thinking and technical skills to effectively identify system anomalies and potential issues. Your keen understanding of microservice observability data will be crucial in the success of this project.
I have some ideas and reference papers on what techniques can work but we would like your expertise to filter, implement and build a usable model which is generic and unsupervised.
Project Milestones:
1. Plan - 5%
2. Data cleanup (not much) & feature engineering - 20%
3. Model development - 50%
4. Test A - 70%
5. Test B - 85%
6. Test C - 100%
- Detect unusual behavior patterns
- Identify potential failures
Your task will involve utilizing logs and traces from our microservice observability data. It is imperative that your expertise in Python contributes to developing a robust and efficient model. This project requires a balance of critical thinking and technical skills to effectively identify system anomalies and potential issues. Your keen understanding of microservice observability data will be crucial in the success of this project.
I have some ideas and reference papers on what techniques can work but we would like your expertise to filter, implement and build a usable model which is generic and unsupervised.
Project Milestones:
1. Plan - 5%
2. Data cleanup (not much) & feature engineering - 20%
3. Model development - 50%
4. Test A - 70%
5. Test B - 85%
6. Test C - 100%