Amazon Web Services (AWS)

Every day we discover opportunities to expand the system landscape with additional components:

<ul>

  <li>a <a href=“https://aws.amazon.com/de/solutions/implementations/data-lake-solution/” target=“_blank”rel=“noopener”>Data Lake</a> for unstructured data,</li>

  <li>a <a href=“https://help.sap.com/viewer/107a6e8a38b74ede94c833ca3b7b6f51/2.0.3/de-DE/4a2e3fa51c450451e10000000a421937.html” target=“_blank” rel=“noopener”>Cold Store</a> for infrequently accessed data,</li>

  <li>multiple <a href=“https://docs.aws.amazon.com/sagemaker/latest/dg/notebooks.html” target=“_blank”rel=“noopener”>Data-Science environments</a> for the specialist department,</li>

  <li><a href=“https://blogs.sap.com/2019/12/06/build-a-custom-widget-in-sap-analytics-cloud-analytics-application/”>Web servers for the Custom Widget of the SAP Analytics Cloud</a>,</li>

  <li><a href=“https://blog.sap-press.com/15-steps-to-setting-up-sap-cloud-connector” target=“_blank”rel=“noopener”>Cloud Connector</a>,</li>

  <li><a href=“https://blogs.sap.com/2020/10/22/sap-data-warehouse-cloud-dp-agent-set-up-and-configuration/”target=“_blank” rel=“noopener”>Data Provision Agents</a> etc.</li>

</ul>

With all the possibilities and ideas, at the beginning it is often not clear whether we need them for a week, a year, or permanently. Frequently, the usage of these instances is not constant. Amazon Web Services (AWS) offers the necessary flexibility here.

<a href=“https://www.cubeserv.com/loesungen/sap-analytics-produkte/sap-analytics-cloud/” target=“_blank”rel=“noopener”>SAP Analytics Cloud</a> and <a href=“https://www.cubeserv.com/loesungen/sap-data-warehousing/sap-data-warehouse-cloud/” target=“_blank” rel=“noopener”>SAP Data Warehouse Cloud</a> are also operated by <ahref=“https://blogs.sap.com/2020/11/23/top-innovations-of-2020-for-sap-customers-in-the-aws-cloud/”>SAP</a> on AWS upon request. In this way, you can specifically improve data transfer costs and performance.

To insert the AWS infrastructure in an orderly manner into the existing system landscape, some preparatory steps are required. We recommend further developing your <a href=“https://www.cubeserv.com/blog/business-analytics-platform-data-governance/” target=“_blank” rel=“noopener”>Business Analytics strategy</a>. We are happy to support you in this. <strong><a href=“https://www.cubeserv.com/leistungen/cloud-integration/amazon-web-services-aws-kontakt/”target=“_blank” rel=“noopener”>Contact</a></strong> us to receive a tailor-made offer.

<a href=“https://d1.awsstatic.com/whitepapers/aws-overview.pdf” target=“_blank” rel=“noopener”>Amazon Web Services offers over 100 different services</a>. Presenting them here would go beyond the scope.

We would like to present three scenarios here by way of example:

<ol>

  <li><strong>Data-Science Toolbox</strong>: <a href=“https://docs.aws.amazon.com/sagemaker/latest/dg/nbi.html”target=“_blank” rel=“noopener”>Sagemaker Notebook</a> in combination with <ahref=“https://aws.amazon.com/de/s3/”>S3</a> (store data cost-effectively and centrally with integrated data life-cycle) and <a href=“https://aws.amazon.com/de/codecommit/” target=“_blank” rel=“noopener”>CodeCommit</a> (private GIT repository: store code permanently and centrally):

Data science projects typically require weeks or months initially. During this time, data is analyzed and prepared and various algorithms are tested. Data and algorithms form a unit. Therefore, for successful data science projects you have a separate data set, which although initially often comes from existing databases, then must be processed independently of the source. The S3 object store is ideal for this due to its cost structure and availability. The <a href=“https://jupyter.org/”target=“_blank” rel=“noopener”>Jupyter Notebook</a> offers an agile development environment due to its isolation from the production environment – plus its individual expansion with additional packages. A private (per company) GIT repository completes the setup with central code versioning.</li>

  <li><strong>Data-Lake Integration</strong> with the serverless database <a href=“https://aws.amazon.com/de/athena”target=“_blank” rel=“noopener”>Athena</a>:

We must probably live with data being stored in different places in the company. A complete integration into one location is not affordable for most companies and would additionally slow down the development process for new data. Therefore, the integration of the various data stores is essential for <a href=“https://www.cubeserv.com/blog/wie-business-analytics-erfolgreich-gestalten/” target=“_blank” rel=“noopener”>successful analytics</a> and a central element of the <ahref=“https://www.cubeserv.com/leistungen/analysen-und-konzepte/business-analytics-platform/” target=“_blank”rel=“noopener”>Business Analytics Platform</a>. Amazon Athena is an interactive query service that analyzes data in Amazon S3 using standard SQL. Athena is serverless, i.e. no infrastructure needs to be managed, and you pay only for the queries you run. Athena can be integrated as a data source into the <a href=“https://www.cubeserv.com/loesungen/sap-data-warehousing/sap-data-warehouse-cloud/” target=“_blank” rel=“noopener”>SAP Data Warehouse Cloud</a> and thus evaluate Data Lake (AWS S3) and SAP Enterprise Data Model (BW/4HANA / BW on HANA as well as S/4 HANA (Core Data Service) or SAP HANA) seamlessly.</li>

  <li><strong>Simple Dashboarding</strong> with QuickSight:

With <a href=“https://aws.amazon.com/de/quicksight/” target=“_blank” rel=“noopener”>QuickSight</a> you can create and publish interactive dashboards.

You can embed dashboards in your applications and provide your customers with powerful self-service analytics. QuickSight scales easily to tens of thousands of users without installing software, provisioning servers, or managing infrastructure.</li>

</ol>

Let’s <a href=”https://www.cubeserv.com/leistungen/cloud-integration/amazon-web-services-aws-kontakt/” target=”_blank” rel=”noopener”> sit down together </a> and discuss your use cases!

There are various reasons to migrate your SAP systems to the cloud: flexibility, security, focus on your own USP were decisive for the CubeServ Group to migrate all our systems to AWS.

The specific trigger was the lack of our own experts. Together with the support of AWS and the right partners, we succeeded in taking the step with approx. 50 systems in 100 days. After now more than a year of productive operation, we can recommend this step to every customer.

The high standardization of AWS solutions offers the best protection against the most diverse attacks on the IT infrastructure. When designing concrete solutions, we recommend using the “AWS Well-Architected Framework”.

The <a href=“https://docs.aws.amazon.com/wellarchitected/latest/framework/welcome.html” target=“_blank”rel=“noopener”>Well-Architected Framework</a> contains a number of general design principles that facilitate good design in the cloud:

<strong>Stop guessing your capacity needs:</strong> If you make a wrong capacity decision when deploying a workload, you may end up with expensive, unused resources or struggle with performance degradation due to limited capacity. With cloud computing, you can eliminate these problems. You can use as much or as little capacity as you need, and automatically increase or decrease capacity.

<strong>Test systems at production scale:</strong> In the cloud, you can create a test environment at production scale on demand, complete your tests, and then take the resources out of service. Because you only pay for the test environment when it is running, you can simulate your live environment at a fraction of the cost that on-premises tests would incur.

<strong>Automate to enable architectural experiments:</strong> Through automation, you can build and replicate your workloads cost-effectively and avoid the effort of manual work. You can track changes to your automation, review the impact, and, if necessary, revert to previous parameters.

<strong>Enable evolutionary architectures:</strong> In a traditional environment, architectural decisions are often implemented as static, one-time events, with only a few major versions of a system during its lifetime. As a company and its context continually evolve, these initial decisions can impair the system’s ability to meet changing business requirements. In the cloud, the ability to automate and test on demand reduces the risk of impact from design changes. In this way, systems can evolve over time, allowing companies to leverage the benefits of innovation as standard practice.

<strong>Improve your performance through game days:</strong> Test the performance of your architecture and processes by regularly scheduling game days to simulate events in production. This way, you can identify where improvements are possible and simultaneously gain organizational experience in handling events.

Customers such as <a href=“https://aws.amazon.com/de/solutions/case-studies/moderna-therapeutics/” target=“_blank”rel=“noopener”>Moderna</a> or <a href=“https://aws.amazon.com/de/solutions/case-studies/zalando-sap/”target=“_blank” rel=“noopener”>Zalando</a> have already moved their systems to AWS and <ahref=“https://aws.amazon.com/de/sap/” target=“_blank” rel=“noopener”>report</a> on their experiences.

Or do you want a fully managed SAP S/4HANA system? <span style=“font-size: 1rem; color: var( –e-global-color-text );”>Accelerate your ERP transition while reducing both cost and maintenance complexity with </span><a style=“font-size: 1rem; background-color: #ffffff;” href=“https://pages.awscloud.com/GLOBAL-partner-DL-SAP-PCE-Solution-Brief-2021-learn.html” target=“_blank” rel=“noopener”>RISE with SAP on AWS</a><span style=“font-size: 1rem; color: var( –e-global-color-text );”>.</span>

<strong><a href=“https://www.cubeserv.com/leistungen/cloud-integration/amazon-web-services-aws-kontakt/”target=“_blank” rel=“noopener”>Start</a> your own journey to AWS with CubeServ and its partners!</strong>

With PeoplePlan, we enable you to carry out personnel cost planning in real time. The entire personnel cost planning is built according to the principles of the <a href=“https://aws.amazon.com/de/architecture/well-architected” target=“_blank”rel=“noopener”>Well-Architected Framework</a>. All five pillars (“Operational Excellence”, “Security”, “Reliability”, “Performance and Efficiency” and “Cost Optimization”) were considered from the very beginning in the development of this SaaS solution. The positive feedback from our customers confirms this path.

More information: <a href=”https://PeoplePlan.eu” target=”_blank” rel=”noopener”>PeoplePlan.eu</a>

We prefer standard software wherever we can. Missing functions, different ideas about the user experience, or inflated licensing demands make it necessary to supplement standard software with our own applications.

A typical scenario is the entry of key figures (e.g. forecast of sales figures by tens of thousands of field service employees) or the maintenance of master data.
We help customers every day who are confronted with such scenarios. <a href=”https://www.cubeserv.com/leistungen/cloud-integration/amazon-web-services-aws-kontakt/” target=”_blank” rel=”noopener”><strong>Contact</strong></a> us to discuss your requirements.