How Netmeds switched from Elasticache to Redis Enterprise and achieved zero downtime
Customer Company Size
Large Corporate
Region
- Asia
Country
- India
Product
- Redis Enterprise
- Amazon ElastiCache
- Twemproxy
- Dynomite
- HAProxy
Tech Stack
- Redis
- PHP
- AWS
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
- Digital Expertise
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- E-Commerce
- Pharmaceuticals
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Digital Twin
- Predictive Maintenance
- Remote Asset Management
Services
- System Integration
- Software Design & Engineering Services
About The Customer
Netmeds is an online pharmacy that ships products to every corner of the Indian market. The pharmaceutical’s omni-channel sales approach supports product orders via its website, mobile app, and call center. As a three-year-old company, Netmeds has been ramping up its marketing efforts in the very new space of pharmaceutical e-commerce. This has resulted in traffic spikes that caused its AWS ElastiCache instance to fail. Netmeds needed a solution that could handle the high availability and performance required by its hundreds of thousands of daily users.
The Challenge
With just three weeks to go before a big marketing event designed to deliver a significant increase in user activity, Netmeds was desperate to resolve the failure issues that were currently plaguing its Amazon ElastiCache. Huge spikes in user traffic were choking Redis with too many connections, causing it to fail. As a result, Netmeds would experience downtimes of up to an hour that easily lost them 750 orders every 30 minutes. Netmeds initially thought the issue could be resolved through clustering on ElastiCache, but the company’s PHP platform did not support clustering of Redis. Next, NetMeds evaluated connection management solutions as a way to reduce the number of open database connections. They looked at Twemproxy, Dynomite, and HAProxy in an attempt to set up connection pooling, but none of these solutions supported every command that Redis supported.
The Solution
A simple Google search brought Redis Labs to Netmeds’ attention. Pandit reached out immediately and received a response from Redis Labs the very next morning. With less than three weeks to go live with a resolution before their big marketing push, it was a huge relief to learn that Redis Enterprise’s connection pool manager supported every Redis command and that this would resolve their issue for the short term. In under three weeks, Redis Labs and Netmeds worked together to successfully migrate its caching and session store operations from ElastiCache to Redis Enterprise. Netmeds’ entire application system runs on AWS, with Redis Enterprise now sitting just behind the web app servers. With connection pooling in place, database downtime issues have been eliminated. Long term, Netmeds sees clustering and sharding as the permanent solution for high availability and performance. To that end, Pandit and his team have begun re-architecting their platform to get around its current clustering limitations. They are looking forward to unleashing the power of Redis Enterprise’s clustering and sharding features.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Case Study: Pfizer
Pfizer’s high-performance computing software and systems for worldwide research and development support large-scale data analysis, research projects, clinical analytics, and modeling. Pfizer’s computing services are used across the spectrum of research and development efforts, from the deep biological understanding of disease to the design of safe, efficacious therapeutic agents.
Case Study
Fusion Middleware Integration on Cloud for Pharma Major
Customer wanted a real-time, seamless, cloud based integration between the existing on premise and cloud based application using SOA technology on Oracle Fusion Middleware Platform, a Contingent Worker Solution to collect, track, manage and report information for on-boarding, maintenance and off-boarding of contingent workers using a streamlined and Integrated business process, and streamlining of integration to the back-end systems and multiple SaaS applications.
Case Study
Process Control System Support
In many automated production facilities, changes are made to SIMATIC PCS 7 projects on a daily basis, with individual processes often optimised by multiple workers due to shift changes. Documentation is key here, as this keeps workers informed about why a change was made. Furthermore, SIMATIC PCS 7 installations are generally used in locations where documentation is required for audits and certification. The ability to track changes between two software projects is not only an invaluable aid during shift changes, but also when searching for errors or optimising a PCS 7 installation. Every change made to the system is labour-intensive and time-consuming. Moreover, there is also the risk that errors may occur. If a change is saved in the project, then the old version is lost unless a backup copy was created in advance. If no backup was created, it will no longer be possible to return to the previous state if and when programming errors occur. Each backup denotes a version used by the SIMATIC PCS 7 system to operate an installation. To correctly interpret a version, information is required on WHO changed WHAT, WHERE, WHEN and WHY: - Who created the version/who is responsible for the version? - Who released the version? - What was changed in the version i.e. in which block or module of the SIMATIC PCS 7 installation were the changes made? - When was the version created? Is this the latest version or is there a more recent version? - Why were the changes made to the version? If they are part of a regular maintenance cycle, then is the aim to fix an error or to improve production processes? - Is this particular version also the version currently being used in production? The fact that SIMATIC PCS 7 projects use extremely large quantities of data complicates the situation even further, and it can take a long time to load and save information as a result. Without a sustainable strategy for operating a SIMATIC PCS 7 installation, searching for the right software version can become extremely time-consuming and the installation may run inefficiently as a result.
Case Study
Drug Maker Takes the Right Prescription
China Pharm decided to build a cloud-based platform to support the requirements of IT planning for the next five to ten years which includes a dynamic and scalable mail resource pool platform. The platform needed to have the following functions: all nodes support redundancy, ensuring service continuity and good user experience, simple and easy-to-use user interfaces for end users and administrators and good compatibility and supports smooth capacity expansion.
Case Study
ELI LILLY ADOPTS MICROMEDIA’S ALERT NOTIFICATION SYSTEM
Pharmaceutical production is subject to a strict set of enforced rules that must be adhered to and compliance to these standards is critically necessary. Due to the efforts of WIN 911’s strategic partner Micromedia, Lilly was able to adopt an alarm notification infrastructure that integrated smoothly with their existing workflows and emergency hardware and protocols. These raw energy sources enable the industrial process to function: electricity, WIN-911 Software | 4020 South Industrial Drive, Suite 120 | Austin, TX 78744 USA industrial steam, iced water, air mixtures of varying quality. Refrigeration towers, boilers and wastewater are monitored by ALERT. Eli Lilly identified 15000 potential variables, but limitations compelled them to chisel the variable list down to 300. This allowed all major alarms to be covered including pressure, discharge, quantity of waste water discharged,temperature, carbon dioxide content, oxygen & sulphur content, and the water’s pH.
