Edge Optimizer
Cut log analytics and storage costs by over 50% by optimizing log/trace events at the edge before shipping them to output.
Cut Storage Costs
Reduce storage costs by 50-75% by forwarding compact events to object storage (e.g., AWS S3, Azure Blobs). Expand events on-the-fly using the Storage Streamer app to forward raw data to log analytics and metric outputs periodically or on-demand.
Cut Log Analytics Costs
Reduce ingestion and licensing costs by over 50% by forwarding compact events to Splunk and Elasticsearch. The open-source 10x for Splunk app and L1ES Elasticsearch plugin expand events in real-time, maintaining full querying, dashboard, and alerting capabilities without data loss.
Workflow
The Edge Optimizer app processes events from a variety of log forwarders, such as Fluentd, Fluent Bit, Filebeat, and Logstash. Configure the app to process all or a subset of the events, allowing for targeted analysis, regulation, and optimization.
graph LR
A["<div style='font-size: 14px;'>🚙 Forwarder</div><div style='font-size: 10px; text-align: center;'>Sidecar Process</div>"] --> B["<div style='font-size: 14px;'>📡 Receive</div><div style='font-size: 10px; text-align: center;'>Stream Events</div>"]
B --> C["<div style='font-size: 14px;'>🔄 Transform</div><div style='font-size: 10px; text-align: center;'>into TenXObjects</div>"]
C --> D["<div style='font-size: 14px;'>🎁 Enrich</div><div style='font-size: 10px; text-align: center;'>Add Context</div>"]
D --> E["<div style='font-size: 14px;'>🗜️ Optimize</div><div style='font-size: 10px; text-align: center;'>Encode Events</div>"]
E --> F["<div style='font-size: 14px;'>📤 Output</div><div style='font-size: 10px; text-align: center;'>Return to Forwarder</div>"]
classDef deploy fill:#7c3aed88,stroke:#6d28d9,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef receive fill:#9333ea88,stroke:#7c3aed,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef transform fill:#2563eb88,stroke:#1d4ed8,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef enrich fill:#059669,stroke:#047857,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef optimize fill:#f59e0b,stroke:#d97706,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef output fill:#ea580c88,stroke:#c2410c,color:#ffffff,stroke-width:2px,rx:8,ry:8
class A deploy
class B receive
class C transform
class D enrich
class E optimize
class F output
🚙 Forwarder: Runs 10x as a sidecar process to log forwarders for real-time event analysis
📡 Receive: Read events continuously from log forwarders via IPC
🔄 Transform: Structure raw events into well-defined TenXObjects
🎁 Enrich: Applies enrichment rules to augment TenXObjects with intelligent context
📈 Report: Publishes cost insight metrics for visualization and alerting
🚦 Regulate: Filters events using local or environment policies to prevent over-billing
🗜️ Optimize: Losslessly compacts events using templates the runtime engine builds from AOT compiler symbols
📤 Output: Returns optimized events to forwarder to ship to destination analyzers or storage
Architecture
Edge optimizers execute as a forwarder sidecar process to optimize events before they ship to log analyzer or Object Storage.
Forwarders ship verbose events containing repetitive elements such as JSON/KV field names, messages, severity levels and app-specific low-cardinality values, increasing cost of by over 50%.
Forward optimized events to low-cost storage (e.g., AWS S3, Azure Blobs). The Storage Streamer app expands and streams selected events to log analyzers and metric outputs.
Forward optimized events to Splunk. The open-source 10x for Splunk app expands events on-the-fly at search time, displaying them in full JSON/text form in dashboards and queries.
Forward optimized events to Elasticsearch or OpenSearch. The open-source L1ES plugin transparently rewrites standard queries and decodes _source at search time — Kibana dashboards, saved searches, and alerts work unchanged.
Safety & Reliability
The Edge Optimizer runs as a sidecar alongside your log forwarder with fail-open design — if the optimizer crashes or stops, your logs continue flowing normally to your analyzer.
Key topics:
- Sidecar failure behavior & fail-open design — Logs continue flowing if 10x goes down
- Handling traffic spikes with backpressure — Disk buffering prevents data loss
- Per-node resource requirements & scaling — 512MB heap + 2 threads handles 100+ GB/day
- Rollback procedure —
helm uninstalltakes ~1 minute, no data loss
See the Edge FAQ for complete operational details, capacity planning, and deployment guidance.
