Many of the world’s leading companies run on SAP—and deploying it on Google Cloud extends the benefits of SAP even further. Migrating your current SAP S/4HANA deployment to Google Cloud—whether it resides on your company’s on-premises servers or another cloud service—provides your organization with a flexible virtualized architecture that lets you scale your environment to match your workloads, so you pay only for the compute and storage capacity you need at any given moment. Google Cloud includes built-in features, such as Compute Engine live migration and automatic restart, that minimize downtime for infrastructure maintenance. And it allows you to integrate your SAP data with multiple data sources and process it using Google Cloud technology such as BigQuery to drive data analytics.

SAP server-side architecture consists of two layers: the SAP HANA database, and the Netweaver application layer. In this blog post, we’ll look at the options and steps for moving the database layer to Google Cloud as a lift and shift or rehost, a straightforward approach that entails moving your current SAP environment unchanged onto Google Cloud.

Deploying an SAP HANA system on Google Cloud

Google Cloud offers SAP-certified virtual machines (VMs) optimized for SAP products, including SAP HANA and SAP HANA Enterprise Cloud, as well as dedicated servers for SAP HANA for environments greater than 12TB. (For a complete list of VM and hardware options, visit the Certified and Supported SAP HANA Hardware Directory.)

Before proceeding with a rehost migration to Google Cloud, your current (source) environment and Google Cloud (target) environments should meet these specifications:

Prerequisites:  

• The configuration of the Google Cloud environment (i.e., VM  resources, SSD storage capacity) should be identical to that of the source environment. If the underlying hardware is different, however, you must use Option 2 for your migration, detailed below.
• Both environments should be running the same operating system (SUSE or RHEL Linux).
• The HANA version, instance number, and system ID (SID) should be identical.

• Schema names must remain the same.
• Establishing the network connection between the on-premises environment and Google Cloud will be required in this phase to support rehost of the SAP application.you can use Cloud VPN or Dedicated Interconnect. Learn more about Dedicated Interconnect and Cloud VPN.

Note: Depending on your internet connection and bandwidth requirements, we recommend using a Dedicated Interconnect over Cloud VPN for production environments. 

We offer a number of automated processes to accelerate your cloud journey. To deploy the SAP HANA system on Google Cloud, you can use the Google Cloud Deployment manager or Terraform and Ansible scripts available on GitHub with configuration file templates to define your installation. For more details, see the Google Cloud SAP HANA Planning Guide.

Note: To deploy SAP HANA on Google Cloud machine types that are certified by SAP for production, please review the Certification for SAP HANA on Google Cloud page. 

Moving an SAP HANA Database to Google Cloud

There are two different options you can use to rehost your SAP HANA database to Google Cloud, and each has pros and cons that you should consider when deciding on your approach.

Option 1: Asynchronous replication uses SAP’s built-in replication tool to provide continuous data replication from the source system (also known as the primary system) to the destination or secondary system—in this case residing on Google Cloud. It’s best for mission-critical applications for which minimum downtime is a high priority, and for large databases. In addition, the high level of automation means that the process requires less manual intervention. Here’s where you can learn more on HANA Asynchronous Replication.

Option 2: Backup and restore relies on SAP’s backup utility to create an image of the database that is then transferred to Google Cloud, where it is restored in the new environment. Downtime for this method varies by database size, so large databases may require more downtime via this method vs. asynchronous replication. It also involves more manual tasks. However, it requires fewer resources to perform, making it an attractive option for less urgent use cases. Here’s where you can learn more on SAP HANA database Backup and restore.

How to migrate the SAP HANA database to Google Cloud using Asynchronous Replication

1. Create and configure Dedicated Interconnect or Cloud VPN between the current environment and Google Cloud.
2. Set up SAP HANA asynchronous replication. You can configure system replication using SAP HANA Cockpit, SAP HANA Studio, or hdbnsutil. See Setting Up SAP HANA System Replication in the SAP HANA Administration Guide.
3. Be sure to use the same instance number and HANA SID in the template as the primary instance.
4. Configure the Google Cloud instance as the secondary node for using HANA Asynchronous replication.
5. Perform data validation once full data replication is completed to the SAP HANA database in Google Cloud. To learn more: HANA System Replication overview.  
6. Perform an SAP HANA takeover on your standby database. This switches your active system from the current primary system onto the secondary system on Google Cloud. Once the takeover command runs, the system on Google Cloud becomes the new primary system.To learn more: HANA Takeover. 

How to migrate the SAP HANA database to Google Cloud using Backup and Restore

1. Create a full backup of your SAP HANA database in your current environment.
2. Create a new storage bucket in your Google Cloud environment. Visit Creating Storage Buckets in the Google Cloud Storage documentation. 
3. Download and install gsutil onto the source environment and run it to upload the HANA backup to the Google Cloud storage bucket. To install gsutil utility on any computer or server, visit Install gsutil in the Google Cloud Storage documentation.
   Note: You can run parallel multi thread/multi processing in gsutil to copy large files more quickly.
4. Recover the HANA database on Google Cloud using SAP’s RECOVER DATABASE statement. See RECOVER DATABASE Statement (Backup and Recovery) in the SAP HANA SQL Reference Guide for SAP HANA Platform.

Note: BackInt agent is an integrated SAP interface tool used for HANA database on Google Cloud.Backint agent for SAP HANA can be used to store and retrieve backups directly from Google Cloud Storage. It is supported and certified by SAP on Google Cloud. To learn more:  SAP HANA Backint Agent on Google Cloud. 

In summary, we recommend using Asynchronous Replication (Option 1) for mission-critical applications that require the lowest downtime window. For all other applications, we recommend Backup and Restore (Option 2), as this approach requires fewer resources. It’s also a great way to implement the backup and restore functionality on Google Cloud.

A rehost migration is the most straightforward path to getting your SAP on HANA system up and running on Google Cloud. And the sooner you migrate, the sooner you can take advantage of the many benefits Google Cloud brings to your SAP solution. For more information on the different migration options please review: SAP on Google Cloud: Migration strategies. 

Learn more about deploying SAP on Google Cloud. Technical resources can be found here.

For consulting companies such as EDI Environmental Dynamics Inc. (EDI), interactions among employees and customers are the direct drivers of value, and helping them collaborate has a tangible impact on the bottom line. However, connecting people from the field to work-from-home spaces to the office is no easy task.

EDI, an environmental consulting company that helps organizations assess environmental impacts and meet government regulations, has eight offices across Western and Northern Canada. Frontline workers account for 80% of its total employees, ranging from biologists and scientists to safety inspectors and project managers. EDI’s success is directly linked to its remote workforce’s ability to work effectively in the field and to collaborate with coworkers and clients across Western Canada. With the help of Google Workspace and AppSheet, EDI is enabling its mobile workforce to function more efficiently and collaboratively than ever before.

Bringing efficiency to its frontline workers

Just four years ago, much of EDI’s fieldwork was still being tracked with pen and paper, resulting in frequent challenges, from error-prone data retention to inefficient collaboration. Luckily, EDI was able to address this using AppSheet, Google Cloud’s no-code application development platform. 

With AppSheet, EDI has replaced the majority of its pen-and-paper processes with tailored apps. As EDI’s Director of IT, Dennis Thideman explains, “AppSheet allows us to be much more responsive to our field needs. Using it, we can spin up a basic industrial application, share it with our field workers, and have them adjust their workflows—all in just a few hours. Doing that from scratch might take weeks or months.”

For EDI, there are a couple of features that make AppSheet shine. First, AppSheet is platform-agnostic, meaning it works on most devices and most operating systems, so any employee can access their AppSheet apps. Secondly, because 90% of EDI’s projects involve working in remote areas, they can leverage AppSheet’s Offline Mode, allowing workers to collect data on their mobile devices in the field and have it automatically download when they reconnect to the internet. 

Eliminating the challenges associated with pen and paper has resulted in even more benefits than EDI leaders originally anticipated: namely, employees work faster across an unexpectedly wide range of use cases. For example, governmental regulations require EDI to complete a pre-trip safety evaluation before heading into the field. Before using AppSheet, this evaluation would take upwards of four hours to complete. By streamlining the process with an AppSheet app, EDI employees have reduced that time down to one hour. EDI averages over 850 evaluations every year, and they’ve realized over 2,550 hours in annual savings—savings that can be passed on to clients and allow staff to focus more time on other tasks. This is just one of more than 35 mission-critical applications that EDI has built with AppSheet.

Time savings is a huge benefit, but as Logan Thideman, an IT manager at EDI, explains “At the end of the day, we realized that the biggest benefits of AppSheet aren’t about time savings as much as they are about high-quality data.” Collecting and analyzing good data is critical to EDI’s operations, as most data collected in the field can never be replicated. For example, if a water quality sample for a certain day is lost (which can happen easily when using pen and paper), that information can never be retrieved again. AppSheet makes data collection easy. Employees are much less likely to lose a smart device than they are a paper form, and any data entered would be immediately uploaded to a Google Sheet or SQL database when they return from the field, meaning data is always backed up in the cloud. From there, information can quickly be analyzed by coworkers, passed on to the client, or shared with government agencies to ensure proper compliance.

Overall, EDI found that the more they could enable their field workers with AppSheet apps, the more those employees could focus on providing quality research and recommendations to their clients and gain a stronger competitive advantage in the market.

Enhancing collaboration everywhere

Enabling collaboration in remote environments can be difficult, but Google Workspace has made this easy for EDI. Google Workspace lets employees effortlessly share documents and work together in real time. Given its ease of use for mobile workers, Google Meet has become all-important and is used as EDI’s tool of choice for face-to-face collaboration. It became even more essential when COVID-19 arrived. As Dennis Thideman explains, “Google Meet allowed us to adapt to the COVID-19 environment quickly as we were already conversant with it. In just two days, we were able to transition our employees from office to home because of it.” By leveraging Google Meet and the rest of the Google Workspace platform, EDI employees are able to remain productive, regardless of where they’re working.

Google Workspace also makes it easy to collaborate with customers. Because many of EDI’s customers leverage Microsoft Office tools such as Word, Excel, and PowerPoint, EDI still needs to use them. Google Workspace makes it easy to continue using Microsoft products in its environment, allowing employees to store Microsoft Office files on Google Drive and open, edit and save them using Google Docs, Sheets, and Slides. 

AppSheet and Google Workspace’s deep integrations also make collaboration easy. Employees can update data in Google Sheets, save images and reports to Drive, and update Calendar events all from AppSheet apps. Together, the two platforms simplify many of the activities that consumed so much time in the past.

An empowered workforce

Empowering employees has been at the core of EDI’s success, and Google Workspace and AppSheet have given EDI a clear advantage. Collaboration has become easier and more agile using Google Workspace. Robust AppSheet apps have been built to streamline mission-critical processes. For unique project requirements, simple AppSheet apps are built in a matter of hours. As Dennis Thideman summarizes, Google Workspace and AppSheet “make managing a distributed, deskless workforce much simpler, giving EDI better growth opportunities and a competitive edge in the marketplace.”

Last year we launched our on-demand rides and delivery solution to help businesses improve operations as well as transform the driver and customer journey from booking to arrival or delivery. When it comes to on-demand rides and deliveries, every minute matters. When users book a ride or order food, they want a seamless experience and real-time accurate updates. Today, we’re taking a closer look into data quality improvements for location, time and distance accuracy, and motorbike routes. 

Machine learning helps drive location accuracy

Location accuracy stands at the base of our customers’ operation. The location signals that are coming from mobile devices can sometimes be off for various reasons and  a driver’s location can get stuck, or jump around. 

Recently we developed mechanisms in our fleet management product that can take in multiple location signals and determine the most reliable location to use for a given vehicle. With that, we noticed drastic improvements: 

• Eliminated long periods of location ‘stuckness’ almost completely; a vehicle is considered ‘stuck’ when we think it’s moving but the measured location is not
• Reduced the jumpiness of the location signal by 52%-86%: ‘jumpiness’ is when a vehicle shows a sudden and usually drastic change in location. A jump is determined to exist when the speed the vehicle had to go at in order to cover the distance it did is unrealistic 
• Reduced the average jump distance by 44%-86% : ‘jump distance’ is the distance between two consecutive location pings when we determined a ‘location jump’ has occurred. 

Dunzo, a local e-commerce platform in India, explains how integrating the order tracking capability within Google Maps Platform’s On Demand Rides and Delivery solution has helped reduce support calls by 90%. The out-of-the-box solution helped Dunzo’s motorbike delivery partners with updating location sync to reduce stuckness and jumpiness as well as deliver premium user experiences.

When the vehicle location is more reliable, the dispatch decision is of higher quality, meaning there is a higher chance you will be able to make the optimal decision. This can lead to less wait time for consumers, increased driver happiness and fewer cancellations. 

Improvements in ETA accuracy in motorbike routes

In many geographic areas, road space is limited and car ownership is prohibitively expensive so motorbike is a prominent transportation mode. Motorbike mapping requires unique routing, ETA models, and navigation capabilities. Improvements in motorbike routing and ETA estimation have enabled customers like Gojek to offer better overall services, even in geographies with poor wifi or missing roads.

Recently, we further improved ETA outcomes by developing new machine learning models trained specifically for motorbikes. These models help our systems account for differences in congestion and traffic flow that arise in different regions and scenarios.

Globally, we measured an ~8% improvement in ETA accuracy for riders in the general public, and a ~6% improvement in on-demand rides and deliveries ETA accuracy.  In this on-demand economy, where consumers are accustomed to real-time trip and order progress, these improvements will significantly improve their experience.

We will continue to innovate on both our car and motorbike on-demand rides and deliveries capabilities based on customer demand and requirements.  We are committed to the success of our customers by building a seamless experience for all parties—consumers, drivers, and fleet operators—in the rides and deliveries journey.
For more information on Google Maps Platform, visit our website.