Data analysis, big data, and business intelligence
Found 388 articles
ScyllaDB pairs Cassandra-compatible queries with shard-per-core processing for Java systems that need horizontal scale and predictable performance.
The A3 framework assigns AI tasks to Assist, Automate or Avoid, with task-specific checks and monthly audits to catch drift before it reaches customers.
Senro turns pipelines into Go programs with immutable plans, step caching, monorepo fan-out, change-based filtering, and webhook trigger decisions.
Distributed requests expose the limits of chart-based monitoring, pushing SRE teams to seek clearer explanations of system failures.
Delta Lake UniForm, Unity Catalog and private connectivity can connect Snowflake to Databricks-owned data without nightly exports.
Architecture Review Boards are adding AI oversight for data governance, model lifecycle, explainability, security, and ongoing monitoring.
Regulatory data pipelines need to explain where each figure came from, who changed it and why—not just produce reports quickly.
MySQL can return related order data as one JSON document and apply edits back to relational tables, though writes have some sharp edges.
Mamori points to a lighter way for Go services to pick up Kubernetes config changes without dropping active requests or rebuilding connection pools.
Enterprise language choices need a business thesis: weigh delivery speed, operational risk, talent costs and cross-platform consistency.
Cloud Monitoring, Logging and Trace give teams a view of model usage, request latency, token consumption, errors and agent steps.
Flink’s built-in CEP finds ordered event patterns across time, addressing a class of real-time problems that filters and aggregates don’t cover.
METR’s estimate puts Claude Opus 4.6 at 17.8 hours on clean tasks and 6.4 on messy ones, highlighting the value of recovery and adaptation.
A 900 GB Prometheus deployment faced query timeouts, rising cardinality and SaaS costs, with little room for monitoring overhead.
Visa SRE Sai Joshitha Kathari moved Kubernetes health checks into Jenkins, giving teams faster rollout feedback and clearer paths to failures.
Kubernetes pods can remain stuck in a Pending state, highlighting the challenges of effective scheduling even when resources appear available.
Tackle SQL performance issues head-on with the Query Store tool, which retains valuable execution data even after server restarts.
Identify and eliminate unnecessary processing in Laravel to enhance performance before investing in infrastructure upgrades.
AI adoption is more than just access; it’s about effective integration into workflows. Here's how teams can measure true AI maturation.
Transitioning to ARM in Docker builds requires rigorous testing on ARM hardware to avoid costly runtime issues linked to architecture-specific dependencies.