Logs are vital health indicators for your IT systems and applications. Every log infers something, even missing ones. Don't risk discarding mundane or unknown logs. Simply feed your logs through our HLMs for multi-modal drift detection and fault prediction.
FFWD embeds the full ensemble of log-features: rates, volume, sequences, structured data values, unstructured contents, missing and new contents, to auto-train deep-learning Transformer AI and cutting-edge ML algorithms.
Every IT system is different. HLMs are uniquely tailored and trained to the logs in your environments.
Many tasks in observability are extremely tedious, complex and time consuming to human operators. FFWD has integrated a multitude of different ai-agents, each autonomously specialising in specific tasks ranging from log parsing, metrics categorisation, graphing, visualisation, alert correlation to root-cause advisory.
With cutting-edge ai-agentic workflow architecture, FFWD truly naturalises AI into observability, turbo boosting productivity and trouble-shooting abilities of human operators.
Real-time log processing for AI demands very high-performance underlying data foundations.
We recognise that machine automation data is very different from business analytics data. Stop paying the high prices on systems built for business and marketing analytics.
Perform essential operational analytics, search, and transformations in real-time as event-data is processed through FFWD.
FFWD is purpose built for very high-speed, low-cost automation and machine-generated events data.
Data pipelining for AI projects is often messy part of the battle.
Real-time events collection and pipelining are often the problematic areas of analytics and monitoring projects.
We recognise these known challenges and have integrated convenient event data collection, parsing, transform and shipping functions.
FFWD-UC (Universal Collector) together with FFWD combines essential analytics and real-time pipelining into a single powerful end-to-end system.
Easily construct and perform complex queries in seconds, across billions of events. No prior syntax knowledge required.
Don't waste compute resources on background queries unknowingly. FFWD efficiently and progressively query across billions of events, without putting stress on the underlying compute resources.
User can pause/start a query to validate response, or to quit query once search results are found.
It is not always possible to manually set alerting thresholds for datasets dependent on varying environmental conditions.
FFWD learns from your past data to make predictions on future incoming data within set confidence bounds. Monitor your data beyond basic thresholds to catch anomalies and outliers.
Our unique, scalable and efficient implementation makes Anomaly Detection monitoring possible across thousands of graph-panels with little impact on underlying compute resources.
FFWD contains a built-in Prometheus metric backend.
Send your native metrics to our Prometheus Remote-Write endpoint, or real-time transform heavy, raw log events into lightweight numeric and actionable metrics.
Configure your dashboard to suit the way you work.
Organize and maintain multiple pages of dashboards, visualise data and monitor across multiple graph panels.
Thousands of graphs maybe monitored and visualised at any instance.
During a disaster event, it is common for seemingly unrelated datasets to exhibit high-level of correlation.
FFWD empowers you to compare and correlate trends visually across multiple datasets, and suggest potential correlated events to help in troubleshooting.
You can trigger an alert from a single log event; Set a threshold alert over a graph panel; Or be notified when ML Anomaly Detection catches an outlier event.
Easily attach log or metric thresholds, and anomaly alerts, receive notifications on email, slack or webhook, and download your full record of alert histories.
Mistakes are often made when setting up regex parsers, simply because it is technically difficult.
Our unique web-UI managed parsing method eliminates the complexity and difficulty in working with regex parsing.
In addition, FFWD-UC enables integrated parse-and-route action in a single easy workflow, making it possible to route logs to different destinations based on content format.
Centrally managed pipeline configuration, deployment and collection functions.
With FFWD-UC you can easily manage configurations and monitor the health of thousands of event collectors spread across hundreds of sites in real-time.
Remote deployment is done via Kubernetes or Docker.
FFWD-UC is equipped with built-in connectors to receive events from many popular event sources.
Raw events and logs can be instantly collected with convenience.
FFWD is also equipped with a range of popular data destination connectors so you can conveniently forward data in real-time to your desired destinations such as Object Storage and Splunk.
You can now easily perform filtering, enrichment, field masking, field insertion, field rename, field removal and deduplication tasks via our unique web-UI.
Transformation configurations are centrally managed and effective in real-time.
FFWD event collection, routing, forwarding and transformation is built on multi-threaded high-performance, while consuming as little compute resources as possible.
FFWD-UC is designed to run on constraint compute sites with only a few MB RAM to spare!
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