PatrickGallucci

Solucione problemas de controle de acesso do Microsoft Fabric Lakehouse, abrangendo funções de segurança do OneLake, permissões de endpoint de análise SQL, funções de workspace, funções de acesso a dados e vários recursos de segurança, como RLS, CLS, OLS e mascaramento dinâmico de dados.

Diagnose and resolve Microsoft Fabric OneLake performance issues including slow queries, cold cache latency, small file problems, Delta table fragmentation, V-Order optimization, Spark throttling, capacity SKU sizing, and cross-region data access. Use when remediate OneLake read/write performance, lakehouse query slowness, Direct Lake fallback, table maintenance failures, Spark concurrency limits,

Diagnostica e resolve problemas de desempenho em Funções de Dados do Usuário do Microsoft Fabric. Utilize quando as funções estiverem lentas, com timeout, retornando erros, consumindo capacidade excessiva ou apresentando latência de inicialização a frio, cobrindo desde timeouts de execução até otimização Python.

Diagnose and resolve Microsoft Fabric REST API performance issues including HTTP 429 throttling, long running operation (LRO) timeouts, pagination bottlenecks, and slow API response times. Use when remediate Fabric API latency, capacity throttling, retry-after handling, operation polling failures, bulk API call optimization, or automating Fabric REST API diagnostics with PowerShell. Covers api.fab

Diagnostica e resolve problemas de desempenho em notebooks do Microsoft Fabric com Apache Spark, abordando lentidão, timeouts, erros de throttling, distorção de dados, shuffles ineficientes, otimização de tabelas Delta Lake, configuração V-Order, alta utilização de capacidade, erros OOM e avisos do Spark Advisor.

Diagnose and resolve performance issues in Microsoft Fabric Real-Time Intelligence including Eventhouse, KQL databases, Eventstream, and ingestion pipelines. Use when asked to troubleshoot slow KQL queries, high Eventhouse CPU or memory, ingestion latency or failures, Eventstream throughput problems, capacity throttling (HTTP 430), cache policy tuning, materialized view lag, or Always-On configura

Diagnose and resolve Microsoft Fabric network performance issues including connectivity failures, latency, private endpoints, managed VNets, outbound access protection, gateway diagnostics, OneLake endpoint routing, service tag configuration, firewall allowlisting, DNS resolution, and Spark session startup delays. Use when remediate Fabric networking, slow Spark jobs, connection timeouts, private

Diagnose and resolve Microsoft Fabric Data Agent issues including tenant settings, data source configuration, query generation failures, cross-region capacity errors, XMLA endpoint setup, Power BI semantic model integration, lakehouse/warehouse/KQL connectivity, example query validation, publishing/sharing problems, and Azure AI Foundry integration. Use when asked to troubleshoot data agent, fix F

Diagnose and resolve Apache Spark performance issues in Microsoft Fabric notebooks and Spark Job Definitions. Use when PySpark jobs are slow, notebooks take too long, Spark stages are skewed, shuffles are excessive, out-of-memory errors occur, Delta Lake writes are slow, or Fabric capacity is throttled. Covers data skew, shuffle optimization, broadcast joins, partition tuning, VOrder, Optimized Wr

Diagnose and resolve Microsoft Fabric Data Factory pipeline performance issues. Use when pipelines are slow, copy activities timeout, dataflows stall, activities are stuck, throughput is low, capacity is throttled, or jobs queue indefinitely. Covers copy activity tuning (parallelCopies, DIU, ITO, partitioning), pipeline monitoring via Monitoring Hub and workspace monitoring, Spark job queueing, ca

Diagnose and resolve Microsoft Fabric Data Agent performance issues including slow query generation, capacity throttling (HTTP 430), Spark session startup delays, KQL/SQL/DAX query timeouts, data source misconfiguration, example query validation failures, resource profile tuning, VOrder optimization, autotune settings, and Lakehouse table maintenance. Use when asked to troubleshoot Fabric Data Age

Troubleshoot and optimize pandas performance in Microsoft Fabric Spark notebooks. Use when diagnosing slow pandas operations, toPandas() out-of-memory errors, pandas API on Spark (pyspark.pandas) bottlenecks, DataFrame conversion failures, collect() memory issues, driver memory exhaustion, notebook cell timeouts, or when optimizing pandas workloads for Fabric capacity. Covers pandas vs Spark DataF