This was an SAP webcast from last week. It was good to see a detailed update.
Overview of latest HANA product released to the market
How can you use it?
What are the use cases?
Features, benefits
Figure 1: Source: SAP
In this session, we want to introduce SAP HANA Cloud, the next evolutionary step of SAP HANA. You will see how customers will benefit from a cloud data platform that provides easy and immediate access to all data, with SAP HANA real-time processing and low TCO, while reducing the complexity of your system landscape. (abstract – SOURCE: SAP)
Link to road map https://roadmaps.sap.com/#/board?categoryItems=73554900100800002881 (S-user may be required)
Figure 2: Source: SAP
Subject to change, legal disclaimer applies
Figure 3: Source: SAP
Data growth in a data driven world
50% of data will reside in the cloud
Companies are recognizing this trend
Figure 4: Source: SAP
Strategic direction, migration to cloud is critical
Most customers are coming from on premise with complex infrastructures, data compliance challenges
On premise data center, create web application
Figure 5: Source: SAP
How customers describe their strategy today
How to set up, connect, performance, latency, SLA’s, secure access
How position HANA Cloud
Figure 6: Source: SAP
From on premise to cloud
HANA Cloud – data fabric and central data store
Connect on premise to HANA Cloud, use it as a gateway to other sources
Central store, central access to data sources
Figure 7: Source: SAP
Value proposition
Benefits – upper left – bring on premise with power of cloud – elasticity
HANA Cloud – cloud native database
Streamline access to developers, admins and users
Developer can access via unified access layer
Figure 8: Source: SAP
Differences between HANA on premise and cloud
Buy hardware, configure OS, backop (on premise)
With cloud, large part of stack is managed by SAP
HANA Cloud is a database as a service
You control access to database – SQL access, options to enable
“SAP is your single point of contact”
Figure 9: Source: SAP
Gray box is HANA instance; runs in Kubernetes cluster
Docker based
Containers in Docker
Orchestrated by Kubernetes
Hidden from customers
Multi-cloud enabled; every hyperscaler that can run Kubernetes can run this; not depend on a specific cloud infrastructure
Get HANA database with advanced analytical operations, machine learning
Enrich with virtualizations capabilities; beyond on-premise
Native Storage Extension (NSE) – transparent to you, can use it as it comes; enabled by default
Built-in Data Lake, using IQ technology
Integrated, built-in data lake, provisioned with in-memory database
Elastically scale with HANA Cloud
Known data protection surrounds blocks – data privacy, anonymization, encryption, auditing
On top of HANA Cloud, can connect your own applications and also SAC / DWC
DWC runs on HANA Cloud
S/4HANA, C/4HANA, are in process to use HANA Cloud for their apps (not there yet)
Figure 10: Source: SAP
Center of picture – fabric virtual table; gives you transparent access to remote sources and local datasets
Can toggle between remote and replica sets
Known network latency
Local access is faster – “smart toggling”
Start with remote virtual access; depend on performance can toggle to cached or replicated set
Figure 11: Source: SAP
Replication between HANA system
Built in native real time remote table replication
Third party sources – use smart data integration connectivity
Store replica sets in memory, in disk store, or data lake
Figure 12: Source: SAP
Different protocols for connectivity due to different customer infrastructures
Plan lightweight protocol to on premise this year
Figure 13: Source: SAP
Provide in memory as primary persistence class; includes persistent memory
– some depend on infrastructure providers
Use NSE, Data Lake, can use them depending on SLA’s
Frequently changed data should reside in memory to meet SLA’s
On disk, have latency
NSE – less frequent use data
Data lake – rarely used storage options
Cost performance trade off
Future innovations – an intelligence to give you recommendations for which storage options; based on SAP machine learning libraries
Figure 14: Source: SAP
Known technology
NSE – add buffer cache, managing page in and page out of data
Data from disk that is needed is loaded to buffer cache
Benefits of NSE – memory footprint reduction
Figure 15: Source: SAP
Built in data lake
Based on IQ technology
Optimized connection based on SDA technology
Single point of administration and management in HANA Cloud instance
Offload from HANA to cheaper storage
Figure 16: Source: SAP
Start with first version
Goal – move away from a fixed system size; move to dynamic resource management; start with an initial size and grow with work load
Figure 17: Source: SAP
2 dimensions, compute and storage
Lower left – scale up, scale down; one instance – can add/shrink
Add another compute (read only) node, scale out in compute direction, upper left – data set in cache, provides additional compute power
Storage – add more
Can scale with data lake or scale with nodes that can persist data
Start with lower left corner; next step (this year) to add or remove compute nodes; then come with scaling dimensions in 2021
Provisioning
Figure 18: Source: SAP
Facilitate by SCP (SAP Cloud Platform)
Use SCP for billing and invoicing
Figure 19: Source: SAP
Screen shot of provisioning wizard
Easy way to provision HANA cloud
Data lake is optional
Text box shows metrics, initial sizes in first version; will provide larger sizes later this year
Figure 20: Source: SAP
Database, instance,
See memory size, CPU size, data lake name
SQL access endpoint to configure connectivity string (secured)
Start and stop instance when needed
Security
Figure 21: Source: SAP
Security features, same features/scope as on-premise
Figure 22: Source: SAP
Shared responsibility for security
Migration
Figure 23: Source: SAP
Left side have NEO, Cloud Foundry, different versions, will provide a migration path so you can migrate your HANA services to HANA Cloud
Migrate SQL XS classic apps; HANA Cloud only supports XSA advanced
Not available yet; will come later this year
Use cases
Figure 24: Source: SAP
HANA Cloud is a data fabric that virtualizes others in the cloud so you can access
By default, not replicate data, just virtualize
Unified access layer via SQL to remote sources supported
Figure 25: Source: SAP
Next use case is to ingest data
Figure 26: Source: SAP
Next use case is expand to on premise with real time replication
Benefits include on demand set up, cover peak loads, data offloading, data federation
Figure 27: Source: SAP
Continue with HANA core, adding cloud native capabilities
3rd box shows innovation focus topics
Plan to provide IQ and ASE services (not data lake) – allow IQ on premise customers to transition to HANA Cloud
Unified development experience on HANA Cloud
Figure 28: Source: SAP
Milestones; GA March 27
Trial end of Q2 (limited time, limited size)
Bug fixes biweekly
Replay is available here.
Question & Answer (subset)
Q: How do you propose capitalizing in scale up and scale down model?
A: Relying on cloud infrastructure providers; they are taking care of infrastructure; just leverage infrastructure for HANA Cloud
Q: When will SAP Business App Studio support HANA Cloud?
A: Ongoing project; strategic development environment for cloud development, timeline is not fixed
Original Article:
https://blogs.sap.com/2020/04/28/sap-hana-cloud-overview-webcast-summary/