Struggling to Scale On-Premises Data Workloads Keeping Pace With Cloud Innovation?
SQL Server 2022 CU10 Delivers Breakthrough Capabilities Bridging Deployments.
While cloud data platforms continue rapid innovation, many organizations still run mission-critical workloads on-premises requiring parity to future-proof analytics.
SQL Server 2022 Cumulative Update 10 closes gaps with groundbreaking enhancements achieving cloud-scale local processing, storage and flexibility.
As Azure SQL Database and Synapse Analytics blaze trails with new features, SQL Server deployments risk feeling dated lacking platform advancements.
But with upwards of 70% of overall data not yet migrated to the public cloud, many rely on on-premises systems for the foreseeable future.
Hire SQL server developer experts, Upgrading to SQL Server 2022 Cumulative Update 10 proves a pivotal milestone in achieving functional convergence through cloud-inspired scale, intelligence and governance helping transition complexity at your pace.
Microsoft made sizable engineering investments ensuring the newest SQL Server release brings the the best of the cloud on-premises.
Breakthroughs like vertically scaled instances, integrated Spark engines and granular multi-cluster management build familiar bridges easing future cloud adoption while maximizing existing infrastructure investments currently.
Think common data platform and flexible deployment. Now let’s break down key innovations!
1) Achieve Unprecedented Scale On-Premises
Traditionally, scaling workloads involved expensive horizontal sharding across servers exacerbating management complexity.
Now with 2023 advanced support for vertical scaling, a single server accommodates unprecedented data volumes with simplerOps.
Break Processing Limits with Vertical Instances
New architecture supports tailoring vCores, memory and temporary resource pools specifically optimized vertically to eliminate physical server sprawl.
Scale up workloads in one box.
Accelerate Performance with Advanced Buffer Pool Extensions
Further amplify speeds leveraging pooled SSD memory supplementing default cache sizes for hot data avoiding storage access lag retrieving from disks.
Extensions pool across instances too preventing isolated server limits.
Lower TCO Through Server Consolidation
Collapsing horizontal compute clusters into leaner vertical footprints reduces operational overheads around patching, upgrades, availability groups and failovers via fewer systems to maintain. Shared management simplifies.
On-premises workloads can now expand to cloud capacity levels within singular servers instead of ballooning farms supporting legacy constraints.
Vertical focus streamlines administration cutting TCO as the new on-premises cloud foundation.
2) Boost Hybrid Analytics and ML Capabilities
Modern insights require analytics spanning historical reporting to predictions. SQL Server 2023 introduces Azure cloud-inspired ML augmentations on-premises:
Operationalize Models with Python and Java
Natively execute Python and Java code within SQL for the first time no longer needing external runtimes.
Streamlines deploying machine learning models scoring data in real-time at query runtime enriched through predictions.
Process Big Data with Integrated Apache Spark
Leave Hadoop behind with fully integrated Spark clusters now within core instances.
Finally, handle big data transformations with high-performance distributed processing without needing dedicated infrastructure just for large workload support.
Automate ML Lifecycles with Azure Machine Learning
Orchestrate on-premises data through cloud Azure ML tooling even from local SQL Server instances.
Enables no code model training Azure portals against private data then automates deployment back behind firewalls keeping data local.
Gain Real-time Insights with Stream Analytics
Ingest and process real-time telemetry analysis from applications, sensors and devices using integrated Azure Stream Analytics event processing. Low latency data feeds real-time alert personalizations.
3) Extend Data Estate Governance Reach
Governing analytics behaviours balancing enterprise access needs while securing sensitive data remains a capacity stone unchanged either on-premises or cloud.
SQL Server 2023 focuses on enhancements around finer governance controls through:
Dynamic Data Masking
Natively integrate data obfuscation techniques into views and reports tailoring actual values displayed per user while protecting underlying raw tables without performance hit at runtime calculation.
Field Level Encryption
Encrypt sensitive columns like personal account details while keeping other analytic data in clear text.
Allows wider dataset sharing without exposing restricted fields to all recipients by default.
Azure Purview Integration
Scan data estate using Azure Purview data discovery, classification and lineage capabilities even for on-prem SQL Server cataloguing sensitive data and monitoring usage.
Syncs metadata system-of-record avoiding stale indicators only updated intermittently raising risk.
Uniform App Access Controls
Consistent permissions model through group Managed Service Accounts (gMSA) allows managing account access uniformly across environments reducing privilege risks from disjointed identity sprawl.
Eliminates gaps through central controls even in heterogeneous ecosystems.
Equalizing enterprise software testing & security policy guardrails across cloud and on-premises minimizes administrative burdens through unified tooling while preventing uneven controls or access privilege gaps that increase exposure risks long term.
4) Streamline Smart Management with Azure Arc
Administering intricate on-premises environments challenges even sophisticated IT teams as complexity compounds.
Azure Arc streamlines cloud-inspired management conveniences bridging local infrastructure.
Apply Cloud Automation Rules
Through Azure Policy, implement governance rules enforcing organizational conventions like required database properties, TDE encryption standards, auditing configurations etc uniformly early preventing deviation and risks.
Standardize Deployments at Scale
Define and share Infrastructure as Code (IaC) templates standardized for SQL Server instances across dev, test and production environments bringing cloud repeatability on-premises.
Speed rollout and reduce configuration drift misalignment.
Monitor Holistically with Azure Monitor
Funnel health metrics into easy Azure Monitor tracking dashboards spanning cross premises to cloud resources giving singular pane of glass observability saving tremendous manual telemetry consolidation costs.
Lifecycle Management Automation
Finally leverage Azure Resource Manager (ARM) capabilities like automated patch scheduling, upgrades planning and version tracking of local SQL Server resources same as cloud database offerings. Evergreen maintenance.
5) Future-Proof with Cloud Native Security
Beyond core data and analytics, aggressively adopt cloud-native security innovations also available for on-premises parity protecting sensitive information in motion and at rest:
Always Encrypted
Cloud scale query processing even against encrypted data without keys leaving secure enclaves.
Critical for sensitive columns like healthcare records, financial information and PII.
Dynamic Data Masking
Proactively transform returned query results obscuring actual restricted values displayed per user while allowing analytic calculations leveraging original figures. Balance usability with tighter access controls.
Azure Defender Integration
Protect surface areas even on-premises using Microsoft threat intelligence identifying vulnerabilities, denying anomalous access attempts and recommending party containment or patch remediation across cyber attack kill chains.
Double Key Encryption
For ultimate lockdown, encrypt data twice - once close to the app with app keys then repeat near storage using distinct keys completely decoupling and isolating app vs. database access strictly needing both keys.
Added isolation hardens environments using cloud crypto innovations still surfacing on-premises.
6) Infuse Actionable Intelligence
Static reporting only reveals part of the insights equation. Evolving augmented and conversational analytics help frontline staff make informed data-driven decisions daily:
Natural Language Capabilities
Empower users exploring data through intuitive natural language queries as though conversing with a colleague translating sentences into executable semantic code fetching responsive views.
Advanced NLP understanding builds trust democratizing access.
Explainable Machine Learning
Increase user trust in model-scored predictions by generating reasons code explaining statistically how unique combinations of attributes factored into specific AI-recommended actions surfaced.
Build confidence combating blind black box outcomes.
Alert-driven Guidance
Configure smart tactical alerts triggered by defined metric thresholds or worrisome predictions pushing notifications to front-end systems or even individual mobile devices recommending actions resolving issues based on contextual data factors. Prescribe resolutions.
7) Extend Hybrid Deployment Options
While migrating fully or modernizing entirely both work strategically, pragmatic realities warrant maintaining connections across footprints through hybrid and cloud-native options offering transitional bridges:
Azure Arc Data Services
Manage data services spanning on-premises, edge and multi-cloud under a consistent Azure data services framework while benefiting from capabilities like backup, logging, security scanning and more regardless of where workloads ultimately land.
Azure SQL Managed Instance
For apps needing ultimate agility but data requiring residency controls, this offering container the apps within managed cloud services while connecting back to regulated backend databases still on-premises or in sovereign clouds.
Achieve cloud-like functionality without lifting and shifting data physically.
Azure Stack Family Appliances
Process select workloads on special hardware built ground-up focused on optimizing virtualization, storage and networking for hybrid cloud scenarios blending edge, on-prem and public Azure services consistently through integrated Azure Stack appliances and software.
8) Infuse Developer Agility
Empowering IT delivery pace through DevOps practices raises deployment reliability and innovation velocity using cultural pillars like:
Standardize Infrastructure-as-Code
Repeatable configuration templates treat underlying environments like code for reusable, standardized SQL Server setup reducing reliance on tribal knowledge across teams and codifying best practices programmatically.
Promotes cloud-inspired consistency and documentation practices familiarizing teams with taking environments code first.
Automate Testing & Validation Suites
Develop extensive regression test suites running SQL Server upgrades and patches through simulated workflows ensuring expected outputs validate across features at scale rather than disjointed checking.
Reduces business disruption risk expediting IT change absorption even for mission-critical systems.
Enable Integrated CI/CD Pipelines
Finally empowers continuous integration and delivery even around database changes leveraging native source control integration, automated release gates and workflows reducing latency between developer commit and production deployment.
Safety first but the pace accelerates through modern SDLC automation possibilities previously prohibitive around databases.
9) Right Size and Evolve Analytical Storage
Traditionally businesses relied on enterprise data warehouses (EDWs) built for consistency supporting critical business processes with predictable workloads.
But analytical storage options now diverge meeting needs across exploratory, operational, streaming and predictive use cases. Modern capabilities serve wider demands:
HTAP Storage Patterns
Combine transactional responsiveness for customer-facing apps while enabling hybrid analytical and predictive performance from the same storage using capabilities like Azure SQL Database Hyperscale optimizing cost performance balance across combined workloads.
Change Data Capture Modules
Stream-only data changes from transactional systems minimizing volumes needed to propagate downstream to lower cost storage stacks dedicated purely for analytics and longer-term historical statistical modelling rather than constant overwrite.
Reduces data movement needs while keeping analytical systems refreshed incrementally.
Azure Synapse Pipelines
For ultimate flexibility, control analytical and machine learning workflows through enterprise Azure Synapse pipelines spanning limitless combinations of Azure native, Spark and SQL compute options.
Handles data volumes from MBs to PBs without migration burdens.
The expanding buffet of right-fit Azure data analytics and storage options offer tunable choices balancing criticality, concurrency, budget and access needs across modern cloud-inspired SLAs even for prudent on-premises modernization journeys.
10) Craft Evergreen Skills Strategies
Technology capability plays only one part in data estate modernization equations - competing also requires growing bench strengths as systems complexity compounds:
Incentivize Continuous Learning
Invest in ambitious talent eager for constant upskilling on the latest innovations related to their domains.
Sponsor specialization certifications, conference travels and regular digital course consumption keeping teams perpetually sharp.
Structure for Crosstown Mobility
IT professionals appreciate horizontal career runways spanning data, infrastructure and analytics spheres.
Construct centers of excellence less tethered to rigid org reporting structures enabling talent flow more fluidly to highest priority initiatives based on integrated technical and business priority combinations. Value well-rounded experience.
Maintain Alumni Talent Networks
Inevitable attrition still impacts all enterprises but departed colleagues represent valuable alumni networks as they diversify into new industries leveraging and enhancing accrued knowledge advantages from your data domains.
Sustain connections through newsletters, alumni groups and social channels for continued symbiotic joy spreading technical innovations positively impacting communities beyond any one organization.
Challenge with Cutting Edge Expeditionary Projects
Beyond daily demands, fuel talent passions by sponsoring R&D innovation labs for technically ambitious teams getting hands dirty on bleeding edge capabilities before mainstream viability.
Align experiential learning to long-range roadmaps and cultivate tool expertise over the horizon feeding back leading indicators influencing strategic platform directions.
Balancing modernized technology and empowered people craft a collaborative environment focused on exponentially positive possibilities - precisely the cultural cornerstone needed to write sample navigating waves of change headwinds confronting modern data teams.
Azure Arc unlocks stepping-stone capabilities steadily aligning standardised cloud management while integrating on-premissions environments at your own pace. The journeys continue!
Still, Weighing Migration vs. Modernization?
We covered immense ground from exponentially scaling processing within singular instances, expanding analytics and machine learning capabilities on-premises to orchestrating cloud-inspired management practices across existing infrastructure.
As modernization and migration pathways both continue maturing, what other considerations come to mind when assessing long-term platform planning?
