AI Predictive Splunk Log Agent
Budget: ₹1,500 – ₹12,500 INR
Our Splunk deployment needs an AI-driven agent that performs predictive analysis on two main feeds—system and application logs. The goal is to spot impending issues before they surface, act on them instantly, and keep stakeholders informed without manual intervention.
Scope of work
• Ingest and normalize existing system and application log streams inside Splunk.
• Train or import a machine-learning model that forecasts anomalies and performance degradations ahead of time.
• On every anomaly, automatically
– send alerts (email, Slack, or Splunk alert action),
– generate concise PDF/CSV reports, and
– trigger automated responses through playbooks or scripted REST calls.
Technical expectations
Python (ideally within the Splunk Machine Learning Toolkit), SPL searches, and familiarity with modular inputs or custom apps will streamline integration. REST API use is encouraged so the solution remains portable when we add network logs later.
Deliverables
1. Packaged Splunk app/add-on containing the predictive model, searches, and alert actions.
2. Documented setup guide covering installation, model retraining, and response workflows.
3. Sample reports plus a short test run that proves:
• prediction precision ≥ 85 % on supplied validation data,
• alert latency under one minute, and
• automated response execution verified in Splunk logs.
Hand-over is complete once the app is installed in our staging environment and passes the above acceptance criteria.
Scope of work
• Ingest and normalize existing system and application log streams inside Splunk.
• Train or import a machine-learning model that forecasts anomalies and performance degradations ahead of time.
• On every anomaly, automatically
– send alerts (email, Slack, or Splunk alert action),
– generate concise PDF/CSV reports, and
– trigger automated responses through playbooks or scripted REST calls.
Technical expectations
Python (ideally within the Splunk Machine Learning Toolkit), SPL searches, and familiarity with modular inputs or custom apps will streamline integration. REST API use is encouraged so the solution remains portable when we add network logs later.
Deliverables
1. Packaged Splunk app/add-on containing the predictive model, searches, and alert actions.
2. Documented setup guide covering installation, model retraining, and response workflows.
3. Sample reports plus a short test run that proves:
• prediction precision ≥ 85 % on supplied validation data,
• alert latency under one minute, and
• automated response execution verified in Splunk logs.
Hand-over is complete once the app is installed in our staging environment and passes the above acceptance criteria.