--- title: "v1.0.0 Release Notes" description: "What's new in Koios v1.0.0 — custom components, expression tags, a redesigned interface, and much more" source_url: https://ai-ops.com/docs/release-notes/v1-0-0 --- # Koios v1.0.0 We are thrilled to announce **Koios v1.0.0** — the biggest release in the platform's history. This milestone brings powerful new capabilities for building custom logic, creating calculated data points, managing AI models at scale, and monitoring your entire system from a completely redesigned interface. > [!TIP] Upgrading from v0.10.x? > Koios v1.0.0 is fully backward-compatible with existing v0.10.x deployments. Your devices, tags, models, and configuration will be automatically migrated during the upgrade. See [Migrating to v1.0.0](https://ai-ops.com/docs/updates/v1-0-0.md) for the step-by-step upgrade guide. --- ## Component Engine Deploy your own custom Python logic directly into the Koios runtime — no external services or infrastructure required. **Components** are reusable Python packages that execute in real-time alongside your devices and models. Wire them together to build processing pipelines for control algorithms, data transformations, state machines, and custom protocol adapters. - **Visual wiring** — connect component inputs and outputs to tags, models, or other components through the UI - **Configurable scan rates** — execute components from every 100ms to once per hour - **Multiple environments** — organize components into independent execution environments with separate scan rates - **Component libraries** — upload packaged component libraries (`.kcl` files) and manage versions - **Component Builder** — build your own components using the published Python library with typed inputs, outputs, and configuration fields - **Full audit trail** — every component execution and configuration change is logged > [!NOTE] Getting Started with Components > The Component Builder provides base classes, field descriptors, and a CLI tool for packaging your components into uploadable libraries. Contact your Koios representative for access and documentation. See [Components](https://ai-ops.com/docs/components/introduction.md) for the full guide to libraries, environments, and wiring. --- ## Expression Tags Create calculated data points using formulas and logic — no code required. Expression tags let you define computed values that reference real-time data from across your entire Koios deployment. They evaluate continuously at configurable scan rates and their results are available everywhere: in dashboards, as model inputs, or as inputs to other expressions. - **Cross-entity references** — combine values from tags, devices, and AI models in a single expression - **Arithmetic and logic** — full support for math operators, conditionals (`if`/`then`/`else`), and boolean logic (`AND`/`OR`/`NOT`) - **Configurable precision** — set decimal places per expression for clean display - **Historical tracking** — expression results are stored in the time-series database for trending and analysis - **Safe evaluation** — expressions run in a sandboxed evaluator with no risk of code injection ```text Example: if(tag:30:status == 1, tag:10:value * 0.85 + tag:20:value, 0) ``` See [Expression Tags](https://ai-ops.com/docs/tags/expressions.md) for the full syntax reference. --- ## AI Model Enhancements Major improvements to how you configure, run, and monitor AI models. ### Scan Groups Group related models for synchronized, batched execution. Scan groups share on-demand read/write settings, ensuring all models in a group see the same fresh data snapshot. This improves throughput and consistency when running multiple models against the same set of devices. See [Scan Groups](https://ai-ops.com/docs/models/scan-groups.md) for details. ### Memory-Only Mode Run models in ultra-low-latency mode by skipping historical storage of inference results. Ideal for real-time control loops where you need sub-10ms scan rates and don't need to retain every output value. Memory-only models still write live values for dashboards and downstream consumption. See [Configuring a Model](https://ai-ops.com/docs/models/configuring-a-model.md) for details. ### Advanced Normalization Expanded normalization options give data scientists precise control over how input values are prepared for inference: | Normalization Type | Description | |---|---| | **None** | Raw values passed directly | | **Min/Max** | Scale to 0–1 range using tag or custom bounds | | **Symmetric** | Scale to -1 to 1 range | | **Z-Score** | Standardize using mean and standard deviation | Each binding can use either the tag's configured range or custom values, giving you full control over normalization parameters without modifying the model file. See [Assigning Bindings](https://ai-ops.com/docs/models/assigning-bindings.md) for configuration details. ### Rate-of-Change Detection Configure per-binding thresholds that flag when input values change too quickly. Supports both absolute and percentage-based thresholds with configurable detection windows and direction filtering. Useful for catching anomalous spikes, equipment failures, or sensor drift before they impact inference quality. See [Assigning Bindings](https://ai-ops.com/docs/models/assigning-bindings.md) for configuration details. ### Reset from Metadata When uploading a new model file version, use **Reset from File** to automatically apply settings embedded in the model's metadata (sample rate, model type, normalization parameters) while preserving your existing tag assignments. This streamlines the model update workflow for data scientists iterating on model versions. See [Managing Model Files](https://ai-ops.com/docs/models/model-files.md) for details. ### On-Demand Inference Models and scan groups can now trigger fresh device reads before each inference cycle and write outputs back to devices immediately after. This ensures models always operate on the latest data and can close control loops in a single scan cycle. See [On-Demand Inference](https://ai-ops.com/docs/models/on-demand-inference.md) for configuration details. --- ## Redesigned User Interface The entire Koios frontend has been rebuilt from the ground up as a modern single-page application. ### What Changed - **Instant navigation** — page transitions are immediate with no full-page reloads - **Faster live updates** — optimized polling and cache-based merging for smoother real-time device values, tag status, and model outputs - **Responsive layout** — works across desktop, tablet, and large monitoring displays - **Consistent design** — unified card layouts, status indicators, and action patterns across all pages - **Keyboard navigation** — full keyboard support for accessibility and power users ### New Pages | Page | Description | |---|---| | **System Health** | Real-time CPU, memory, and disk monitoring with configurable alarm thresholds | | **Live Log Viewer** | Stream service logs in real-time with color-coded output levels and pause/resume | | **Scan Groups** | Manage model execution groups with shared scan rates and on-demand settings | | **Component Environments** | Configure and monitor component execution environments | | **Component Libraries** | Browse, upload, and manage component library packages | ### Improved Tables All data tables now support: - **Bulk actions** — enable, disable, or delete multiple items at once with a single click - **CSV import and export** — bulk import devices, tags, and model configurations from spreadsheets - **Column sorting and filtering** — find what you need quickly in large deployments - **Progress indicators** — visual feedback during bulk operations ### Trend Customization The trend viewer now supports deep customization that is saved and persisted per trend: - **Per-trace styling** — assign a custom color to each trace and pin it to a specific Y-axis - **Multiple Y-axes** — add left and right axes with custom labels, colors, and independent min/max bounds - **Line style controls** — adjust line width, point radius, curve tension (sharp to smooth), and area fill with opacity - **Data aggregation** — choose between automatic or manual windowing with aggregation functions (mean, median, min, max, sum, first, last) - **Gap filling** — optionally fill missing data points for a continuous view - **CSV export** — export trend data for offline analysis All customizations are saved to the trend and available the next time you open it. ### Dashboard Improvements The dashboard has been overhauled with a flexible widget system for building custom monitoring views. - **Multiple dashboards** — create and switch between different dashboard layouts, each tailored to a specific role or process area - **Drag-and-drop grid** — reposition and resize widgets freely on a responsive 12-column grid - **8 widget types** — Tag Value, Tag Chart, Device Status, Device Uptime, Device Execution, Model Status, Model Uptime, and Model Execution - **Widget configuration** — customize each widget's appearance (font size, colors, decimal places, chart time range, line styles, and more) - **Live updates** — all widgets poll for live data automatically - **Default dashboard** — mark a dashboard as your default so it loads on login See [Dashboard](https://ai-ops.com/docs/dashboard/introduction.md) for the full guide. ### Event Storm Detection When many events fire in rapid succession (e.g., enabling hundreds of tags at once), the UI now intelligently groups them into a single summary notification instead of flooding your screen. High-frequency event storms are detected automatically and displayed as a consolidated alert. --- ## In-App Documentation Koios now ships with a complete help system built directly into the application — no external website or internet connection required. - **80+ help pages** covering installation, devices, tags, models, system administration, and more - **Full-text search** across all documentation - **Always in sync** — documentation updates ship with each Koios release - **Available offline** — accessible on air-gapped deployments with no internet access Access documentation at any time from the help menu in the navigation bar. --- ## Security and Deployment ### Unique Per-Installation Secrets Every Koios installation now generates its own unique internal credentials on first boot — database passwords, session signing keys, and service authentication tokens are all created automatically. No two installations share the same secrets. Upgrades from previous versions are handled seamlessly with no manual action required. ### Schema Version Compatibility A new compatibility check runs on every startup to prevent accidental data loss. If you attempt to run an older Koios version against a database that has been migrated to a newer schema, the system will block startup with a clear error message and instructions. A pre-migration backup is also created automatically before each upgrade. ### Multi-Architecture Support Koios Docker images are now built for both **x86_64 (AMD64)** and **ARM64** architectures. Deploy on standard servers, AWS Graviton instances, or ARM-based edge devices using the same image tag. ### Flexible TLS Configuration New environment variables (`ENABLE_TLS`, `HTTP_PORT`, `HTTPS_PORT`) let you configure TLS behavior to match your deployment topology. Run HTTPS directly, or disable TLS when Koios sits behind a load balancer that handles certificate termination. See [Environment Variables](https://ai-ops.com/docs/installation/environment-variables.md) for the full configuration reference. ### Improved Rate Limiting API rate limits have been increased and tuned per endpoint to better support dashboards with many simultaneous data streams while still protecting against abuse. --- ## Data Collection Improvements - **On-demand reads and writes** — request fresh values from devices on demand, outside the normal scan cycle. See [On-Demand Scanning](https://ai-ops.com/docs/devices/on-demand-scanning.md) for configuration. - **Tag value notifications** — real-time push notifications when tag values change, enabling faster dashboard updates - **Circuit breaker patterns** — automatic backoff and recovery when devices become unreachable, preventing cascading failures - **OPC-UA certificate management** — manage client certificates for secure OPC-UA connections directly from the UI. See [OPC-UA Certificates](https://ai-ops.com/docs/protocols/opc-ua-certificates.md) for details. --- ## Value Mapping Tag value mapping has been completely redesigned. The previous "Lookup Table" feature only supported exact string matching against a fixed dictionary. The new **Value Mapping** system introduces a rules-based engine with ordered evaluation, multiple match types, and flexible options. ### Match Types | Match Type | Description | Example | |---|---|---| | **Exact** | Value equals pattern | `"Off"` → `0` | | **Greater than / Greater or equal** | Numeric comparison | `> 100` → `1` | | **Less than / Less or equal** | Numeric comparison | `<= 0` → `0` | | **Between** | Numeric range (inclusive) | `10,50` → `1` | | **Glob** | Wildcard pattern (`*` any chars, `?` single char) | `"Error*"` → `-1` | | **Any** | Catch-all default (always matches) | `*` → `0` | Rules are evaluated in order from top to bottom — the first matching rule wins. Reorder rules using the arrow buttons in the editor, and use the **Any** match type as a fallback at the end. ### New Options - **Case-insensitive matching** — exact and glob matches ignore letter case - **Reverse mapping on write** — when writing values back to a device, automatically converts numeric outputs back to their original string representation ### Migration Existing lookup tables are automatically converted to the new rules format during upgrade. Simple key/value pairs become **Exact** match rules, and wildcard (`*`) entries become **Any** rules. No manual action is required. See [Value Mapping](https://ai-ops.com/docs/tags/value-mapping.md) for the full configuration guide. --- ## Backup and Restore A new built-in backup system lets you protect your Koios deployment directly from the UI at **System > Backup** — no SSH or Docker CLI required. - **Two backup tiers** — **Config** backups capture devices, tags, users, models, and settings in seconds. **Full** backups also include historical time-series data. - **Scheduled backups** — configure automatic daily or weekly backups at 2:00 AM with a configurable retention policy (1–50 backups kept) - **One-click restore** — upload a backup file, preview its contents, and restore with a single click. Full backups let you optionally include or exclude historical data. - **Download backups** — download backup archives to your local machine for off-site storage See [Backup & Restore](https://ai-ops.com/docs/system/backup.md) for the full guide. --- ## Network Diagnostics A new **System > Network** page gives you visibility into the server's network configuration and built-in tools for troubleshooting device connectivity — all from the browser. - **Interface overview** — see every network interface with its IP addresses, MAC address, link speed, and status - **Ping** — test basic connectivity and measure round-trip latency to any host - **Traceroute** — trace the network path to identify where packets are dropped or delayed - **DNS lookup** — query A, AAAA, MX, NS, TXT, CNAME, and other record types - **TCP port check** — verify that a device's communication port is reachable before configuring a connection (e.g., port 4840 for OPC-UA, port 502 for Modbus TCP) Results stream in real time to a terminal-style output panel with auto-scroll, pause/resume, and clear. See [Network Diagnostics](https://ai-ops.com/docs/system/network.md) for details. --- ## System Administration - **Service health monitoring** — real-time status of all platform services with category-based organization. See [Services](https://ai-ops.com/docs/system/services.md). - **Configurable alarm thresholds** — set warning and critical limits for CPU, memory, and disk usage. See [System Health](https://ai-ops.com/docs/system/performance.md). - **User and role management** — create users, define custom roles, and assign granular permissions. See [Users](https://ai-ops.com/docs/system/users.md) and [Roles & Permissions](https://ai-ops.com/docs/system/roles-permissions.md). - **API client management** — generate and manage credentials for external system integrations. See [API Clients](https://ai-ops.com/docs/system/endpoints.md). - **Data retention policies** — configure automatic cleanup rules for historical data and storage monitoring. See [Data Retention](https://ai-ops.com/docs/system/retention.md). --- ## Upgrading To upgrade from v0.10.x to v1.0.0: 1. **Back up your data** — use the in-app backup at **System > Backup**, or follow [Backing Up Docker Volumes](https://ai-ops.com/docs/installation/backup-restore.md) 2. **Update the service file** — v1.0.0 introduces a new `koios_secrets` volume for storing per-installation secrets (database password, Django secret key, etc.). Your existing service file from v0.10.x does not include this volume, so you need to add it before starting the new version. Open your service file: ```bash sudo nano /etc/systemd/system/docker.koios.service ``` Add the following line to the `ExecStart` section, after the existing volume mounts: ```text --mount source=koios_secrets,target=/var/www/koios/secrets \ ``` Then reload the service configuration: ```bash sudo systemctl daemon-reload ``` See [Running Koios as a Service](https://ai-ops.com/docs/installation/running-as-a-service.md#create-the-service-file) for the complete service file with all seven volume mounts. > [!NOTE] Existing secrets are preserved > On first startup, Koios detects that your database already exists and writes the legacy secret values to the new secrets volume. Your existing data and sessions continue to work — no manual secret migration is needed. 3. **Pull the new image:** ```bash docker pull aiopinc/koios:v1.0.0 ``` 4. **Restart the service:** ```bash sudo systemctl restart docker.koios.service ``` The first startup will run database migrations and generate per-installation secrets automatically. This may take a few minutes on large deployments. See [Migrating to v1.0.0](https://ai-ops.com/docs/updates/v1-0-0.md) for the full upgrade guide.