Our next-gen architecture is built to help you make sense of your ever-growing data Watch a 4-min demo video!

Cred Header

Case Study

How CRED moved their logging platform to Coralogix to improve error alerts, speed up debugging, and lower costs


End-user customers


Engineering users


Applications monitored


About the Company

CRED, founded in 2018, is a transparent and fully digital platform for highly trusted individuals, brands, and institutions. CRED, with its empathetic approach to design, makes financial decisions visible and rewarding for its members, facilitating access to a better life in the form of exclusive rewards and experiences. Admission to CRED is based on credit scores for individuals.

Members can manage multiple cards, access and analyse their credit scores, make bill, utility and monthly recurring payments, avail a credit line, shop or book a travel package, make UPI payments and more on the app.


CRED has a subscriber base of over 10 million users who use its services daily via a mobile application. The Site Reliability Engineering team manages the cloud stack. This function manages cloud infrastructure for the CRED ecosystem and involves facilitating various teams across the org and implementing best practices to manage their stacks effectively. All engineering teams at CRED use Coralogix.

Migration Journey

CRED was using the popular tool Datadog as its primary tool for logging. Additionally, as a Fintech company, they had to adhere to data localization rules and hence needed to keep the logs for PCI-compliant microservices within the Amazon Web Services India region. They used Amazon CloudWatch logs for this use case. 

CRED identified four challenges that needed to be addressed: 

  1. Tool sprawl: Multiple logging solutions to maintain across the incumbent observability tool and Amazon CloudWatch.
  2. Scale: The log volumes increased as the company and tech teams grew. This impacted performance (basically searching a pattern inside logs from Amazon CloudWatch).
  3. Cost: The scale also escalated overheads, and cost issues became a bottleneck.
  4. Data Sovereignty: The popular observability provider did not have an India region to support data localization requirements.

CRED decided to look for an alternative solution after considering the above challenges of the incumbent solution. They found the Pattern Search in Amazon CloudWatch’s log stream particularly cumbersome. In cases where the data range is longer than seven days, it took a long time to process. Moreover, it did not have the Live Tail feature available.

Prajith Cred

Prajith Kumar P
Head - Site Reliability Engineering (Data)

We defined the success criteria to choose a new logging solution, like live tail, alerting, saved views, log tracing based on Trace ID, and an India region presence. Coralogix was able to meet all our requirements.

Ease of Implementation

CRED found the migration process very straightforward. They used Amazon ECS as their Container Orchestrator and AWS FireLens to send logs to the Coralogix platform. 

The Coralogix team helped a lot with the initial implementation, and then CRED converted the changes into an AWS Cloudformation template. Since their deployments were through Infrastructure as Code (IAC), the change was relatively easy to implement and took between 3-6 months to complete the migration. They also saw value in finding Log Patterns using Coralogix’s Loggregation©, which is an automatic log clustering feature that condenses millions of log entries into a narrow set of patterns using machine learning.

Current Environment

Today there are 450+ users of Coralogix at CRED. The main data sources hosting the primary application layer are Amazon ECS, Amazon EC2, and AWS Fargate containers, along with a small set of Amazon EKS.

Value Derived from Coralogix

As per the technical leads at CRED, they see value derived from Coralogix in 3 areas:

  1. Coralogix TCO Optimizer – This allows CRED to suppress or prioritize certain log types, helping to control log volume while maintaining the desired service level.  This was important for cost optimization.
  2. Coralogix Alerts feature – To identify high error rates or anomalies in the count for a specific log pattern.
  3. Amazon S3 Direct Query – This option helped in querying archived logs directly without rehydrating.


After migrating to Coralogix, CRED now finds that log-based alerting is faster than the previous solution. They felt that Coralogix had enabled faster debugging, because of features like Live Tail and easy searches, without bloating up the cost. Most importantly, developers who work on multiple services do not have to switch to different consoles to observe service logs. CRED is now looking forward to exploring Coralogix as a metrics solution.

Vaitheeswaran Cred

Vaitheeswaran S
Head - Cloud Infra & Site Reliability Engineering

We have always received great support from Coralogix. Issues can come up with any platform, but what earns the customer’s trust is the empathy shown in resolving those issues.

Your data is telling yesterday’s story —
Find out what it can tell you today.