BRK3178 - Maximize the power of SQL Azure with Dynamics AX Microsoft 2016 11/13/2018 10:48 AM BRK3178 BRK3178 - Maximize the power of SQL Azure with Dynamics AX Sunil Agarwal Christian Wolf © 2016 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

AGENDA Topology in the cloud or on premise using SQL Server 2016 #DynTech2016 AGENDA Topology in the cloud or on premise using SQL Server 2016 Managing cost performance Real time operational analytics In-memory OLTP for highly performant operations Dynamics AX Entity store and scenarios

TOPOLOGY IN CLOUD OR ON-PREMISE #DynTech2016 TOPOLOGY IN CLOUD OR ON-PREMISE

(Azure BizTalk Services) Dynamics Life Cycle Services Dynamics AX Platform Visual Studio 2015 IDE Identity Data App Client Tools Windows Universal App (w/EMS MAM) iOS Android HTML5 (Azure BizTalk Services) Dynamics Integrator Workspaces App Suite App Foundation App Platform Dynamics Life Cycle Services AX ODataV4 Telemetry Enabled Azure Compute Azure SQL (w/Operational Analytics) Power BI SSRS Azure Blob DocDB Cortana Analytics Azure AD

SQL Server in Dynamics AX topologies Microsoft 2016 11/13/2018 10:48 AM SQL Server in Dynamics AX topologies Feature parity in SQL Azure DB and SQL Server 2016 enables deployments in cloud and on premise AX AX Deploy AX One-Box Developer topology SQL Server 2016 AX Cloud topology SQL Azure DB © 2016 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Managing Cost/Performance

SQL Database Service Tiers Basic Standard Premium Intended Use Light transactional workloads Go-to option for most business applications High throughput and business-critical databases Workload Elasticity Isolated databases and elastic database pools Performance • •• ••• Business Continuity • •• ••• Programming Surface Fully compatible with SQL Server 2016 databases Availability 99.99%*

Predictable performance Build 2015 11/13/2018 10:48 AM Predictable performance Isolated databases are allocated isolated resources Scale up/down Databases remain online while scaling Hourly billing P11 P6 P4 P2 P1 S3 S2 S1 S0 B 5 10 20 50 100 125 250 500 1000 1750 DTUs © 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Elastic database pools Share resources dynamically among databases on the same server/pool Customer-managed over-provisioning makes pools cost-effective for unpredictable, sporadic workloads Well-matched to many database-per-tenant SaaS workloads Basic, Standard, and Premium tiers Databases can burst to the same level as isolated DBs in the same tier Pool size is scaled to support aggregate workload Hourly billing for the pool based on pool size and DB count Max per-database burst level eDTUs 200 400 800 1200

How HA is achieved in AzureDB SQL Azure provides high availability and Geo DR Azure DB provides 3 always on copies Data backup to blob store Primary Secondary same DC Secondary Geo Paired DC

REAL TIME OPERATIONAL ANALYTICS

Minimizing Data Latency for Analytics Microsoft Ignite 2015 11/13/2018 10:48 AM Minimizing Data Latency for Analytics Select ProduceName, ExpiryDate, Quantity, sum (sales) From <transactions> Where ProduceType =‘perishables’ Group By ProduceName, ExpiryDate Insert into <transactions> values (‘<upc-code>, ‘flowers’, $20.00) SQL Server 2016 Database Application Tier Presentation Layer IIS Server Benefits No Data Latency No ETL No Separate DW Challenges Minimizing Impact on OLTP workload Delivering Performant Analytics BI and analytics Dashboards Reporting This is Real-Time Operational Analytics SQL Server Analysis Server Add columnstore index © 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Real-time Analytics Btree Index Nonclustered Columnstore Index (NCCI) Relational Table (disk-based) (Clustered Index/Heap) Btree Index delta delta Nonclustered columnstore index (NCCI)

Real-time Analytics: Minimizing Columnstore overhead Real-time workload AlwaysOn Availability Group Analytics workload Primary Replica Secondary Replica Secondary Insert into <transactions> values (‘<upc-code>, ‘flowers’, $20.00) Select ProduceName, ExpiryDate, Quantity, sum (sales) From <transactions> Where ProduceType =‘perishables’ Group By ProduceName, ExpiryDate Key Points Mission Critical Real-time Workloads typically configured for High Availability using AlwaysOn Availability Groups You can offload analytics to readable secondary replica

Dynamics AX Data Read/write workloads Read only workloads Analytics workloads Read-only workloads: Charts, KPIs, Tiles, Operational Reports, NCCIs Sales Order entry, Sales confirmation, Print Invoices, NCCIs Predictions, Near real-time Power BI, CCIs Primary DB Secondary DB Entity Store Seconds Minutes Real Time Near Real-time

DEMO: How AX leverages SQL Server Operational Analytics Microsoft 2016 11/13/2018 10:48 AM DEMO: How AX leverages SQL Server Operational Analytics © 2016 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

DEMO: How LCS uses Query Store to enable a good troubleshooting experience

IN-MEMORY OLTP

Hardware Trends New CPU won’t run a short transaction much faster Moore’s Law on total CPU processing power holds but in parallel processing… New CPU won’t run a short transaction much faster CPU clock rate stalled… Because processors would melt… Meanwhile RAM cost continues to drop

How AX7 uses In-Memory OLTP Mark the table as Storage Mode = InMemory Set Durability: SchemaAndData: Data can be recreated after crash (from transaction log) Schema: Data is lost after crash System administrator has to accept the setup

DYNAMICS AX ENTITY STORE

Dynamics AX Data Read/write workloads Read only workloads Analytics workloads Sales Order entry, Sales confirmation, Print Invoices Read-only workloads: Charts, KPIs, Tiles, Operational Reports Predictions, Near real-time Power BI Primary DB Secondary DB Entity Store Seconds Minutes Real Time Near Real-time

Entity Store – key scenarios High volume, Near real-time Power BI reporting De-normalized schema, CCI to enable faster query responses, Incremental update from AX, Direct Query Power BI models Intelligent business processes with Cortana Analytics suite Stage data for Azure Data Factory pipelines, Consume in Azure Machine Learning IoT, external data integration Staging in Azure Data Lake and Azure Data warehouse

Entity store – key tenants Designed for analytical scenarios Azure DB entity store included in AX license AX manages deployment and refresh Optionally, customer can stage data in Azure DB, DL and DW for read-write scenarios Coming soon to AX2012 R3

Summary SQL capability How AX7 leverages … Benefit to AX7 SQL server 2016, Cloud or on-prem AX7 on-prem and Developer instances on SQL 2016 AX7 on public cloud uses Azure DB One AX7 platform – two deployment options Dynamic scaling of DB (Scaling DB, MALMO) Increase the DB size as your business grows (and shrinks) Multiple read-only DBs Data access stack able to address multiple read-only DBs Spread the load into multiple DB instances Operational Analytics Aggregate measurements NCCI table indexes Near real-time analytics on the same DB In-memory OLTP Set table properties Leverage quick table access for tables satisfying constraints.

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