Monitoring & Observability
Log Aggregation Implementation
When something goes wrong at 2am, you need to search logs across all services in one place — not SSH into 15 different servers. Centralized log aggregation collects logs from every container, VM, and managed service into a searchable system. We implement log aggregation using the tool that fits your scale and budget.
Need this done for your project?
We implement, you ship. Async, documented, done in days.
What We Deliver
Centralized log aggregation with agents on all hosts, log parsing and enrichment pipelines, structured logging standards for your team, retention and archival policies, search and query interfaces, dashboards for log volume and error monitoring, and integration with your alerting system for log-based alerts.
Tool Selection
Grafana Loki for cost-effective logging with Grafana integration. Elasticsearch/OpenSearch for full-text search at scale. CloudWatch Logs or Cloud Logging for AWS/GCP native simplicity. Vector or Fluent Bit for high-performance log routing. We recommend based on your log volume (GB/day), search requirements, and existing monitoring stack.
Structured Logging Standards
We help your team adopt structured logging (JSON log format) with consistent fields: timestamp, level, service, requestId, userId, message, and error details. Structured logs are trivially parseable by any log system. We provide logging library configurations for your stack (pino for Node.js, structlog for Python, zerolog for Go) and middleware for automatic request context injection.
Log Pipeline Architecture
Agents (Fluent Bit, Filebeat, or Vector) collect logs from containers and files. Pipeline stages parse multi-line logs (stack traces), extract structured fields from unstructured logs, enrich with metadata (Kubernetes namespace, pod, deployment), filter noisy logs (health checks, debug in production), and route to appropriate destinations (hot storage for search, cold storage for archives).
Retention & Cost Management
Log storage is the biggest cost driver. We implement tiered retention: 7–30 days in searchable hot storage, 90 days in warm storage with slower queries, 1+ years in cold archives (compressed in object storage). Log sampling reduces volume for high-frequency, low-value logs (health checks, static assets). Index lifecycle policies automate the progression.
How It Works
Purchase the engagement, submit your async brief with your current logging situation and requirements, and receive a complete log aggregation implementation within 5–7 business days.
Why Anubiz Engineering
100% async — no calls, no meetings
Delivered in days, not weeks
Full documentation included
Production-grade from day one
Security-first approach
Post-delivery support included
Ready to get started?
Skip the research. Tell us what you need, and we'll scope it, implement it, and hand it back — fully documented and production-ready.