DTEK Uses AWS and Real-Time Data to Proactively Solve Equipment Problems
DTEK uses AWS to prevent power plant equipment failures, gain real-time data access from sensors, scale SAP S/4HANA on demand, and meet data protection requirements. Based in Ukraine, DTEK Group is the largest private national investor in the Ukrainian energy sector. The company deployed its SAP S/4HANA environment for DTEK Oil & Gas on AWS, and it uses an AWS-based data lake to analyze power plant equipment problems in real time and help customers prevent failures.
Using the AWS data lake, we can better understand technical processes, improve equipment performance, and, in the long term, build predictive models of breakdowns, loads, etc.”
CIO and Head of the MODUS Program, DTEK
Striving to Meet Growth and Gain Data Access
DTEK is the largest private national investor that develops business in the energy sector in Ukraine. DTEK companies produce coal and natural gas, generate electricity at renewable and fossil-fueled power plants, and distribute and supply energy to customers. Combining engineering with technology, software, and data analytics, DTEK helps modernize the energy industry in the country, increasing its efficiency, reliability, and safety. The company launched the MODUS program to provide systemic digital transformation for all the company’s main production and administrative processes. As part of this program, DTEK is committed to cloud-based solutions that help accelerate business operations, increase the efficiency of sharing and saving data, provide operational analytics, enhance organizational flexibility and scalability, and centralize network security.
To support its digital transformation direction and cloud-first approach, DTEK needed a platform for its SAP S/4HANA solutions, a new technology to help the company process business-critical data on gas production and power plant efficiency. “DTEK uses a rather complex landscape of SAP solutions in various on-premises and cloud data centers,” says Oleksii Martynovych, SAP department head at DTEK. The organization’s Oil & Gas division deployed an S/4HANA system, based on the Amazon Web Services (AWS) Cloud, with four environments: development, QA, pre-production, and production. “The SAP system allows us to automate essential processes, including critical procedural and financial controls that were previously manual,” says Martynovych.In addition, DTEK wanted to gain access to data from sensors on equipment, organize that data, and get it ready to be used for enterprise needs. “Moving to the cloud is our strategic approach in all IT areas, including data gathering and data lake usage. Cloud infrastructure allows us to keep pace with the dramatically increasing volumes, speed, and variations of corporate data by quickly scaling storage areas and processing tools to an appropriate size,” says Yevgen Smertenko, head of data engineering at DTEK. If DTEK had to rely on an on-premises infrastructure, the company would have had to provision multiple servers, hire DevOps engineers, and spend time and money deploying and setting up big data clusters.
Using AWS to Support SAP Applications and a New Data Lake
DTEK chose Amazon Web Services (AWS), deploying SAP S/4HANA on Amazon Elastic Compute Cloud (Amazon EC2) instances. Smertenko says, “Deeply integrated cloud automation gives us the ability to quickly react to changes and provide an agile infrastructure that is always ready to be upgraded or, in case of disaster, rebuilt from scratch.” Dmytro Yatsenko, DTEK’s lead data engineer, adds, “The cloud also makes the whole system more transparent than an on-premises solution. All software and infrastructure are now defined in the source code that is available to security, operations, network, software, and all other engineers for inspection, testing, and improvement.”
DTEK worked closely with SE16N—an AWS Advanced Consulting Partner in the AWS Partner Network—to deploy its SAP S/4HANA environment in AWS. SE16N scaled the solution to meet DTEK’s unique business requirements and created a disaster recovery proposal based on SAP and AWS best practices.To address its data access challenges, DTEK built a data lake on AWS. The solution streams data from 20,000–100,000 sensors provided by different solar, wind, and thermal power plants via AWS IoT Core and Amazon Kinesis. It also stores both real-time and historical power plant equipment data on Amazon Simple Storage Service (Amazon S3). The company uses AWS IoT Greengrass to collect locally generated sensor data and relies on the fully managed Amazon SageMaker machine learning platform to create models for predictive maintenance.
Using Real-Time Data to Prevent Equipment Failures
DTEK has the ability to deploy data models and access updated equipment information from the data lake. As a result, the company’s business analysts can accurately analyze data from power plant equipment sensors in seconds instead of hours. “Using the AWS data lake, we can better understand technical processes, improve equipment performance, and, in the long term, build predictive models of breakdowns, loads, etc.,” says Dmytro Osyka, chief information officer and head of the MODUS program at DTEK.
Gaining Data Access and Experiencing the Power of Cloud Elasticity
The AWS solution enables fast access to an extensive set of analytics tools polished into reliable, high-performance services. The solution delivers nearly instant provisioning time instead of long and challenging procedures on traditional on-premises infrastructure. “Also, with the power of cloud elasticity, we are able to quickly set up new experiments with the data to obtain quick feedback that increases our agility and velocity,” says Yatsenko.
Scaling a Critical SAP Environment on Demand
By using AWS, DTEK can scale its business data as the company continues to grow. “It used to be difficult to provision server capacity to meet our growth,” says Martynovych. “Running SAP S/4HANA on AWS, we can scale on demand as we add more customers and data. We can also take advantage of the reliability of AWS to ensure 24/7 SAP application uptime.”
Improving the Digital Security Posture and Boosting Data Protection
DTEK can meet data protection regulations, such as General Data Protection Regulation (GDPR), by relying on the built-in security capabilities of AWS. “AWS security services are preconfigured, and their tuning and customization do not require in-depth knowledge,” says Yuriy Usmanov, chief high tech and digital IT infrastructure officer at DTEK. The company uses a line of security services running on AWS to enhance security, including AWS Identity and Access Management (IAM), Amazon Cognito, AWS Secrets Manager, AWS Config, and AWS CloudTrail.
Driving Future Growth
Moving forward, DTEK will continue to explore new data management capabilities on AWS. “Connectivity is the cornerstone of our digital transformation strategy. The scalable cloud platform enables the rapid development of applications and microservices, incorporating analytics and automation to deliver business model innovation, new customer experiences, and optimized business processes,” says Osyka. “With AWS, we see benefits from potential cost savings and operational improvements. Cloud-based solutions support industries transforming through software-defined machines and solutions that are connected, responsive, and predictive.”
DTEK Group is the largest private national investor in the Ukrainian energy sector through implementing innovative technologies, building new capacities, developing new businesses, and enabling production improvements.
Benefits of AWS
- Enables real-time data use to predict and prevent power plant equipment failures
- Reduces data access from hours to seconds
- Meets data protection regulatory requirements
- Gains elasticity and scalability to offer services on demand
AWS Services Used
AWS IoT Core
AWS IoT Core lets you connect IoT devices to the AWS cloud without the need to provision or manage servers.
AWS IoT Greengrass
AWS IoT Greengrass is an Internet of Things (IoT) open source edge runtime and cloud service that helps you build, deploy, and manage device software.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information.
Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.
Companies of all sizes across all industries are transforming their businesses every day using AWS. Learn more about IoT services for industrial, consumer, and commercial solutions, and start your own AWS Cloud journey today.