Platform Capabilities

Enterprise-grade IoT infrastructure with real-time insights and complete control

Device Traffic Monitor

Real-Time Device Monitoring

Know exactly what's happening across your entire IoT fleet, instantly. See HTTP and MQTT traffic patterns, detect anomalies, and troubleshoot issues before they impact operations.

  • Live Traffic Analysis: Monitor HTTP requests and MQTT messages in real-time
  • Performance Metrics: Track latency, throughput, and connection health
  • Instant Alerts: Get notified when devices go offline or behave abnormally
  • Historical Trends: Identify patterns and optimize your infrastructure
MQTT WebSockets Redis Streams Prometheus
Security Dashboard

Enterprise Security & Access Control

Protect your IoT infrastructure with bank-grade security. Multi-tenant isolation, role-based access, and encrypted communications ensure your data stays secure and compliant.

  • JWT Authentication: RS256-signed tokens with automatic validation
  • RBAC: Granular permissions for admins, users, and viewers
  • Multi-Tenant Isolation: Kubernetes namespaces keep customers separated
  • VPN Tunneling: PKI-based certificates for secure device access
JWT OpenVPN PKI Kubernetes Network Policies
System Metrics Dashboard

Comprehensive System Analytics

Make data-driven decisions with deep insights into your IoT ecosystem. Monitor CPU, memory, disk, and custom metrics across all devices with beautiful, actionable dashboards.

  • Device Health Monitoring: Track resource usage and prevent failures
  • Custom Dashboards: Build visualizations for your specific KPIs
  • Historical Analysis: Compare trends over days, weeks, or months
  • Predictive Maintenance: Identify issues before they cause downtime
Grafana Prometheus InfluxDB Time Series

Zero-Loss Data Ingestion

Every reading matters. Our ingestion pipeline is built to capture millions of data points without dropping a single one — even under extreme load.

Why Zero Matters

In industrial monitoring, environmental compliance, and predictive maintenance, data gaps create blind spots. Regulations require complete audit trails. Machine learning models need continuous data to detect anomalies. Our pipeline guarantees completeness so your decisions are based on the full picture — not a best-effort sample.

0.0%
Data Loss
20K+
Readings / Second
40M+
Readings Verified

Built for Scale, Proven at Scale

IoT data is only valuable if it arrives complete. A missed temperature spike, a skipped pressure reading, a lost vibration event — any gap can mean a missed alarm or a flawed analysis. Our ingestion pipeline is engineered from the ground up for zero data loss, processing over 20,000 readings per second with every single value accounted for.

  • Zero-Loss Pipeline: Verified at 2 million messages and 40 million readings with 0.0% data loss
  • High Throughput: Sustained ingestion of 20,000+ readings per second on modest hardware
  • Stream-Buffered Architecture: Messages are buffered in-memory streams before database commit, so transient slowdowns never cause drops
  • Parallel Workers: Multiple ingestion workers process data concurrently, scaling with your workload
  • Real-Time and Historical: Data is queryable instantly for live dashboards and stored efficiently for long-term trend analysis
Ingestion Performance Dashboard

What Makes the Pipeline Fast

High throughput is not about brute-force hardware — it is the result of careful architectural decisions at every stage of the data path. Each component is purpose-built to eliminate bottlenecks and keep data flowing under pressure.

  • COPY-Based Bulk Insert: Large batches bypass row-by-row INSERT and use PostgreSQL COPY protocol, achieving near-native disk write speeds
  • Redis Stream Backpressure: Incoming MQTT messages land in a capped Redis Stream, decoupling broker throughput from database write latency
  • Parallel Worker Pool: Multiple independent workers drain the stream concurrently, each with its own database connection — no shared locks, no contention
  • Adaptive Batching: Workers accumulate readings and flush at optimal batch sizes, balancing latency against throughput automatically
  • Connection Pooling: A dedicated pool of persistent database connections eliminates per-query connection overhead
  • TimescaleDB Hypertables: Time-series data lands in automatically partitioned hypertables optimized for append-heavy workloads and fast range queries

Key Engineering Decisions

Performance at this level requires more than fast code. These are the design choices that separate a pipeline that survives a demo from one that survives production.

  • QoS 0 by Design: Eliminating MQTT acknowledgment overhead doubles effective broker throughput while the stream buffer guarantees no loss downstream
  • Backpressure Monitoring: Real-time stream depth metrics feed Grafana dashboards, making saturation visible before it becomes data loss
  • Graceful Degradation: If the database slows, the Redis Stream absorbs the burst — workers catch up automatically when capacity returns
  • Deterministic Testing: Every load test verifies row-level counts against expected totals, with broker-level message auditing to detect transport-layer gaps

Cloud Deployment

Multi-tenant SaaS infrastructure that scales from a single customer to thousands — with full namespace isolation and automated provisioning.

Automated Customer Provisioning

New customer signs up, pays through Stripe, and gets a fully isolated Kubernetes environment deployed automatically — API, dashboard, database, MQTT broker, and monitoring stack, all in their own namespace within minutes.

  • One-Click Deployment: Stripe checkout triggers Helm-based provisioning — no manual ops, no tickets
  • Namespace Isolation: Each customer runs in a dedicated Kubernetes namespace with network policies and resource quotas
  • Dedicated Databases: Per-customer PostgreSQL and Redis instances prevent noisy-neighbor issues
  • License-Gated Features: RS256-signed JWT tokens control access to premium capabilities per subscription tier
  • GitOps Managed: ArgoCD syncs every customer environment from Git — auditable, repeatable, and drift-free

Built to Scale

The platform is designed for horizontal scaling at every layer. Add customers without re-architecting. Scale individual tenants without affecting others. Run on any cloud.

  • Horizontal Pod Autoscaling: API and ingestion workers scale automatically based on CPU, memory, or custom metrics
  • Multi-Cloud Ready: Runs on AKS, EKS, or GKE — Helm charts abstract the underlying provider
  • Agent Fleet Scaling: StatefulSet-based agent fleets scale from 10 to 1,000+ simulated devices with predictable resource growth
  • Tiered Monitoring: Shared Prometheus for standard plans, dedicated Prometheus + Grafana stack for enterprise customers
  • Zero-Downtime Upgrades: Rolling deployments and pod disruption budgets keep customer services online during updates
Kubernetes Prometheus Grafana

Iotistica Agent

A lightweight container orchestrator and device management agent designed for IoT edge devices. Deploy and manage applications remotely with enterprise-grade reliability.

Edge Device Orchestration

Manage your IoT edge devices with a powerful agent that orchestrates containers, handles updates, and maintains secure connections to the cloud—all with minimal resource overhead.

  • Container Orchestration: Deploy Docker Compose or K3s Kubernetes workloads remotely
  • Remote Updates: MQTT-based agent updates with automatic rollback on failure
  • Secure VPN Tunnel: PKI certificate-based authentication with OpenVPN
  • Real-time Monitoring: Live metrics and logs streamed via MQTT to cloud dashboard
  • Multi-Architecture: Native support for ARM64, ARM32, and x86-64 platforms
  • Two Deployment Options: Docker container or native Systemd service
Docker K3s MQTT OpenVPN Raspberry Pi

Quick Installation:

curl -sfL https://get.iotistica.com/agent | sh

Ready to see it in action?

Schedule a live demo and we'll show you how these capabilities solve your specific challenges.

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