Scalytics

Open source Kafka and AI infrastructure. Built in the EU. Operated by agencies and enterprises. Software that holds the line.

[Scalytics @scalyticsAI]

Centralized control planes fail for agentic AI deployed at the edge due to latency, intermittent connectivity and data sovereignty constraints. This article details how a Kafka-native Decision Fabric. Read the full post at https://t.co/Fe3NSBCLHA

[Scalytics @scalyticsAI]

EO data is generated across satellites, ground stations and institutes. Training models locally and aggregating only parameter updates scales global climate analytics while respecting data boundaries. https://t.co/xGEFrWcTl6

[Scalytics @scalyticsAI]

Google trains Gboard and Apple improves Siri by running federated learning on user devices. https://t.co/RtEJsaj3Ac

[Scalytics @scalyticsAI]

Most AI initiatives stall on data execution not models. Compute must move to where the data lives across warehouses streams and regulated domains. https://t.co/QE43ZBiFmi

[Scalytics @scalyticsAI]

Kafka just got a major upgrade. Streaming data is now storage-native:

Lives directly in S3
Stateless brokers
10x cheaper retention

KafScale - fully Kafka-compatible & open source.
Future of streaming = smarter storage.
Full post: https://t.co/2XyFdJHGyz
Ready for this? 👇

[Scalytics @scalyticsAI]

Digital twins create high-fidelity models of physical systems. Generative AI explores future states across thousands of scenarios to forecast events. https://t.co/EtQlKgXB54

[Scalytics @scalyticsAI]

Data centralization creates unavoidable compliance risk when crossing regulatory boundaries. https://t.co/ksk3I2Cvvd

[Scalytics @scalyticsAI]

The currency for AI is energy. Managing energy for AI loads is challenging. Was challenging. Meet Scalytics Helios => https://t.co/A2rmyI2miB

[Scalytics @scalyticsAI]

JulieOps does declarative Kafka config better than Confluent tools. Its community-only support means hybrid use with Strimzi and Control Center cuts configuration drift by 40 percent. https://t.co/Toa5ZgpeUO

[Scalytics @scalyticsAI]

The topic is the orchestrator. Kafka consumer groups handle load balancing and coordination. Partition lag provides natural backpressure and replay. https://t.co/ol94YeVCT2

[Scalytics @scalyticsAI]

Distributed data across units clouds and edges makes central warehouses a poor fit. The workable model moves compute to the data so pipelines run without copying raw sets or breaking Read: https://t.co/wI8EypisW9

[Scalytics @scalyticsAI]

Multi-agent systems fail in prod when one agent lags: central orchestrators become SPOFs, backpressure queues to OOM, retries duplicate. KafScale Read: https://t.co/oStX2UaN0p

[Scalytics @scalyticsAI]

Iceberg latency spikes in Kafka pipelines from silent Connect sink failures, dual offsets, and schema crashes. 47 GitHub issues map the real production pitfalls. https://t.co/A8S6JDbYEW

[Scalytics @scalyticsAI]

Generative AI amplifies biases from centralized, imbalanced training data. Federated learning trains models across distributed datasets, sharing only updates to boost Read: https://t.co/CAZvV54FPh

[Scalytics @scalyticsAI]

Data democratization via central lakes fails on fragmented enterprise data across on-prem, clouds, SaaS. Federated execution runs analytics and AI directly on silos, Read: https://t.co/P20RDj9xGC

[Scalytics @scalyticsAI]

Self-hosting high-throughput LLM inference with OpenAI-compatible APIs meant vendor stacks or reinventing vLLM tuning. Scalytics Connect CE OSSes the full enterprise engine under Apache Read: https://t.co/JNypYtlXJh

[Scalytics @scalyticsAI]

Enterprise data is exploding but fragmented, and ETL consolidation just piles on movement costs, stale queries, and new silos. In-situ federated execution processes it across sources without moving it. https://t.co/CCJuuer6LZ

[Scalytics @scalyticsAI]

Static context windows and maxtokens choke vLLM inference at scale. Scalytics 3.5.0 auto-detects them at runtime, Read: https://t.co/QgBJz1HvRV

[Scalytics @scalyticsAI]

Fintechs moving sensitive data to cloud for AI spikes exposure before DORA kicks in Jan 2025. Its 5 pillars demand ICT risk mgmt, incident reporting, resilience testing, third-party Read: https://t.co/P2hFG8Pj8X

[Scalytics @scalyticsAI]

Federated learning hides local data from servers, making poisoning attacks straightforward. Label flips, backdoors, or model tweaks degrade globals; targeted ones pass accuracy checks. Robust Read: https://t.co/5O5ayDw7C4