Case Studies Applying Sumo Logic to machine data ensures the highest service levels for the world’s biggest financial institutions

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	Applying Sumo Logic to machine data ensures the highest service levels for the world’s biggest financial institutions

Applying Sumo Logic to machine data ensures the highest service levels for the world’s biggest financial institutions

Technology Category	Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Exchange & Integration Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries	Finance & Insurance Software
Applicable Functions	Business Operation Quality Assurance
Use Cases	Machine Condition Monitoring
Services	Cloud Planning, Design & Implementation Services System Integration Training
Challenge	Maintaining separate, dedicated information processing environments for financial institutions is an exceptionally intricate endeavor that generates massive amounts of machine data. Cardlytics sought a comprehensive, technology-backed strategy to aggregate and manage this information across the entire organization. The new solution would need to enable users to correct defects without requesting extensive hand-holding; it would also need to satisfy stringent support and service level obligations for the company’s most important clients. Read More
About Customer	Cardlytics is an advertising platform built within the banks’ digital channels. Through its partnership with financial institutions worldwide, the company has insight into purchase data from more than 100 million monthly active users, representing two in five card swipes, or roughly $2.3 trillion in annual spend. Each night the company ingests all of this raw data. This then serves as the source for deep analytics carried out by a team of 70 specialists to identify which consumers may be interested in receiving certain rewards based on their past spend. Once the detailed analysis is complete, Cardlytics uses this purchase intelligence to create offers and target marketing campaigns for a broad array of advertisers within the banks’ digital channels. These programs are more widely known as ‘Chase Offers’ or ‘BankAmeriDeals’ as two examples. Consumers activate the advertisers’ offers within their bank’s online banking site or mobile app. Later, when they shop at those merchants using their credit or debit card, they will see the reward credit on their next bank statement. Through this process, Cardlytics has saved consumers more than $245 million to date. Read More
Solution	Cardlytics replaced an internally maintained open source Elasticsearch, Logstash, and Kibana (ELK) stack with cloud-native machine data analytics platform Sumo Logic. The company immediately began ingesting machine data for billions of API transactions per day. With the upgraded application in place, Cardlytics then granted access to Sumo Logic to multiple teams within the organization. From the start, the company defined two primary use cases for Sumo Logic: dashboard visualization and alerting. Cardlytics created individual dashboards for each financial institution. These dashboards monitor client-specific key metrics, such as load per Web server, response times for Web servers, error rates, response times that exceed certain thresholds, and SLA compliance. To power its extensive alerting needs, Cardlytics configured several Sumo Logic alerts that run against log files. These alerts create notifications if there’s a deviation from normal response times and traffic patterns. Should a priority 1 support incident arise, Sumo Logic features prominently in the company’s ‘war room’ and is one of the key resources that the team consults when trying to address the issue. In many cases, Cardlytics has been able to leverage Sumo Logic to find and fix flaws before customers even notice that something has gone awry. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Finance & Insurance

Software

Applicable Functions

Business Operation

Quality Assurance

Use Cases

Machine Condition Monitoring

Services

Cloud Planning, Design & Implementation Services

System Integration

Training

Challenge

Maintaining separate, dedicated information processing environments for financial institutions is an exceptionally intricate endeavor that generates massive amounts of machine data. Cardlytics sought a comprehensive, technology-backed strategy to aggregate and manage this information across the entire organization. The new solution would need to enable users to correct defects without requesting extensive hand-holding; it would also need to satisfy stringent support and service level obligations for the company’s most important clients.

About Customer

Cardlytics is an advertising platform built within the banks’ digital channels. Through its partnership with financial institutions worldwide, the company has insight into purchase data from more than 100 million monthly active users, representing two in five card swipes, or roughly $2.3 trillion in annual spend. Each night the company ingests all of this raw data. This then serves as the source for deep analytics carried out by a team of 70 specialists to identify which consumers may be interested in receiving certain rewards based on their past spend. Once the detailed analysis is complete, Cardlytics uses this purchase intelligence to create offers and target marketing campaigns for a broad array of advertisers within the banks’ digital channels. These programs are more widely known as ‘Chase Offers’ or ‘BankAmeriDeals’ as two examples. Consumers activate the advertisers’ offers within their bank’s online banking site or mobile app. Later, when they shop at those merchants using their credit or debit card, they will see the reward credit on their next bank statement. Through this process, Cardlytics has saved consumers more than $245 million to date.

Solution

Cardlytics replaced an internally maintained open source Elasticsearch, Logstash, and Kibana (ELK) stack with cloud-native machine data analytics platform Sumo Logic. The company immediately began ingesting machine data for billions of API transactions per day. With the upgraded application in place, Cardlytics then granted access to Sumo Logic to multiple teams within the organization. From the start, the company defined two primary use cases for Sumo Logic: dashboard visualization and alerting. Cardlytics created individual dashboards for each financial institution. These dashboards monitor client-specific key metrics, such as load per Web server, response times for Web servers, error rates, response times that exceed certain thresholds, and SLA compliance. To power its extensive alerting needs, Cardlytics configured several Sumo Logic alerts that run against log files. These alerts create notifications if there’s a deviation from normal response times and traffic patterns. Should a priority 1 support incident arise, Sumo Logic features prominently in the company’s ‘war room’ and is one of the key resources that the team consults when trying to address the issue. In many cases, Cardlytics has been able to leverage Sumo Logic to find and fix flaws before customers even notice that something has gone awry.

Impact #1	Sumo Logic’s pervasive data collection and dashboards have provided instant visibility into all aspects of the company’s technology environment.
Impact #2	Users are now able to derive value from machine data without needing assistance from IT.
Impact #3	This has equipped customer support, developers, and operational staff with the tools they need to more quickly resolve problems - often even before customers are aware of any issues.

Impact #1

Sumo Logic’s pervasive data collection and dashboards have provided instant visibility into all aspects of the company’s technology environment.

Impact #2

Users are now able to derive value from machine data without needing assistance from IT.

Impact #3

This has equipped customer support, developers, and operational staff with the tools they need to more quickly resolve problems - often even before customers are aware of any issues.

Benefit #1	Cardlytics rolled out Sumo Logic by ingesting 75 GB of log information per day.
Benefit #2	This machine data was the outcome of 2 billion daily API calls: approximately 4,000 transactions per second generated by consumers.
Benefit #3	Over 100 people – representing software development, DevOps, product support, and administrators – soon incorporated Sumo Logic into their daily activities.

Benefit #1

Cardlytics rolled out Sumo Logic by ingesting 75 GB of log information per day.

Benefit #2

This machine data was the outcome of 2 billion daily API calls: approximately 4,000 transactions per second generated by consumers.

Benefit #3

Over 100 people – representing software development, DevOps, product support, and administrators – soon incorporated Sumo Logic into their daily activities.

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Overview

Applying Sumo Logic to machine data ensures the highest service levels for the world’s biggest financial institutions

Operational Impact

Quantitative Benefit