Jae Pasha Consulting is a hands-on engineering partner. We build SQL reliability systems, Azure data platforms, and AI automation that stays auditable, fast, and resilient under real load.
Critical alert detection
Log Analytics retention
CPU gain from automation
Capacity runway mapped
We help teams with SQL Server estates, Azure platforms, and AI automation run faster, safer, and with clear telemetry.
Automation for health checks, index and stats maintenance, and audit ready operations on SQL Server and Azure SQL.
Azure Monitor, Log Analytics, and KQL driven incident response with 5 minute evaluation windows.
Lake to medallion to warehouse architecture using ADLS Gen2, Databricks, ADF, Synapse or Snowflake.
Power BI reporting with M scripts and KQL exports for long term performance trends and forecasting.
Capacity planning, cost tuning, and secure environments with RBAC, policy, and compliance-ready logging.
AI agents that automate reporting, monitoring, and operational triage with clear human oversight.
Client experience across enterprise, SaaS, and integration heavy environments.
Think of these as dedicated pages within one experience: AI, data, and cloud.
Decision trees linked to KQL and SQL checks for CPU, blocking, and storage incidents.
Automated HTML health summaries with clear owner actions and escalation paths.
PowerShell runbooks and Logic Apps used as the control plane for safe AI adoption.
ADLS Gen2, Databricks medallion layers, and ADF silver transformations.
KQL exports to M scripts feeding Power BI for long term forecasting.
Daily performance datasets posted to SharePoint via Logic Apps for reporting.
HTML health emails with CPU, blocking, deadlocks, failed jobs, and storage snapshots.
Critical and warning rules for CPU, vCore, storage, deadlocks, and connectivity.
12 to 18 month growth projections with tiering and scaling options.
Real outcomes from production environments and long running platforms.
Azure Automation + PowerShell health pipeline with daily HTML email for CPU, blocking, deadlocks, failed jobs, and space.
Documented 362 tables, 486.6M records, and 268 foreign keys with diagrams and glossary.
6 alert rules with 5 minute evaluation, action groups for SMS and email, and incident playbooks.
Index and stats maintenance runbooks with CommandLog audit trails and off peak schedules.
Plain language metrics for P50, P95, P99 latency, deadlocks, blocking, and timeouts.
Operational decision trees for high CPU, long queries, blocking, and storage pressure.
Historical growth analysis, 12 to 18 month runway projections, and tiering options.
Extended Log Analytics retention to 730 days, KQL exports to M scripts, and trend reporting.
PowerShell runbook exports with Logic App delivery to SharePoint for BI ready datasets.
Daily performance snapshots and top query tracking stored as CSV time series.
A clear delivery flow that moves from assessment to measurable outcomes.
Environment review, telemetry map, risk assessment, and prioritized delivery plan.
Runbooks, alerting, data pipelines, and dashboards shipped in production with tests.
Capacity reviews, cost tuning, and continuous reliability improvements.
Direct delivery led by Jamal Pasha. Cloud and data engineering, end to end.