Saturday, April 20, 2024

Statsig Reaches 7.5M QPS In Memorystore for Redis Cluster

They at Statsig are enthusiastic about trying new things. Their goal is to simplify the process of testing, iterating, and deploying product features for businesses so they can obtain valuable insights into user behavior and performance.

With Statsig, users can make data-driven decisions to improve user experience in their software and applications. Statsig is a feature-flag, experimentation, and product analytics platform. It’s vital that their platform can handle and update all of that data instantly. Their team expanded from eight engineers using an open-source Redis cache, so they looked for a working database that could support their growing number of users and their high query volume.

Redis Cluster Mode

Statsig was founded in 2021 to assist businesses in confidently shipping, testing, and managing software and application features. The business encountered bottlenecks and connectivity problems and realized it needed a fully managed Redis service that was scalable, dependable, and performant. Memorystore for Redis Cluster Mode fulfilled all of the requirements. Memorystore offers a higher queries per second (QPS) capacity along with robust storage (99.99% SLA) and real-time analytics capabilities at a lower cost. This enables Statsig to return attention to its primary goal of creating a comprehensive platform for product observability that optimizes impact.

Playing around with a new database

Their data store used to be dependent on a different cloud provider’s caching solution. Unfortunately, the high costs, latency slowdowns, connectivity problems, and throughput bottlenecks prevented the desired value from being realized. As loads and demand increased, it became increasingly difficult to see how their previous system could continue to function sustainably.

They chose to experiment by following in the footsteps of their platform and search for a solution that would combine features, clustering capabilities, and strong efficiency at a lower cost. they selected Memorystore for Redis Cluster because it enabled us to achieve they objectives without sacrificing dependability or affordability.

Additionally, since the majority of their applications are stateless and can readily accommodate cache modifications, the transition to Memorystore for Redis Cluster was an easy and seamless opportunity to align their operations with their business plan.

Statsig

Improving data management in real time

Redis Cluster memorystore has developed into a vital tool for Statsig, offering strong scalability and flexibility for thryoperations. Its capabilities are effectively put to use for things like read-through caching, real-time analytics, events and metrics storage, and regional feature flagging. Memorystore is also the platform that powers their core Statsig console functionalities, including event sampling and deduplication in their streaming pipeline and real-time health checks.

The high availability (99.99% SLA) of the memorystore for Redis Cluster guarantees the dependable performance that is essential to they services. They can dynamically adjust the size of their cluster as needed thanks to the ability to scale in and out with ease.

There is no denying the outcomes, as quantifiable advancements have been noted in several important domains

Enhanced database speed

They are more confident in the caching layer with Memorystore for Redis Cluster, as it can support more use cases and higher queries per second (QPS). In order to keep up with their customers as they grow,they can now easily handle 1.5 million QPS on average and up to 7.5 million QPS at peak.

Increased scalability

Memorystore for Redis Cluster‘s capacity to grow in or out with zero downtime has enabled us to support a variety of use cases and higher QPS, putting us in a position to expand their clientele and offerings.

Cost effectiveness and dependability

They have managed to cut expenses significantly without sacrificing the quality of their services. When compared to the costs of using they previous cloud provider for the same workloads, the efficiency of their database running on Memorystore has resulted in a 70% reduction in Redis costs. Their requirements for processing data in real time have also benefited from Memorystore’s dependable performance.

Improved monitoring and administration

Since they switched to Memorystore, they no longer have to troubleshoot persistent Redis connection problems with they database management. Memorystore’s user-friendly monitoring tools allowed they developers to concentrate on platform innovation rather than spend as much time troubleshooting database problems.

Integrated security

An additional bit of security is always beneficial. The smooth integration of Memorystore with Google Cloud VPC improves .Their security posture.

Memorystore for Redis Cluster

A completely managed Redis solution for Google Cloud is called Memorystore for Redis Cluster. By using the highly scalable, accessible, and secure Redis service, applications running on Google Cloud may gain tremendous speed without having to worry about maintaining intricate Redis setups.

A collection of shards, each representing a portion of your key space, make up the memorystore for Redis Cluster instances. In a Memorystore cluster, each shard consists of one main node and, if desired, one or more replica nodes. Memorystore automatically distributes a shard’s nodes across zones upon the addition of replica nodes in order to increase performance and availability.

Examples

Your data is housed in a Memorystore for Redis Cluster instance. When speaking about a single Memorystore for a Redis Cluster unit of deployment, the words instance and cluster are synonymous. You need to provide enough shards for your Memorystore instance in order to service the keyspace of your whole application.

Anticipating the future of Memorystore

They are confident that Memorystore for Redis Cluster will continue to be a key component of .Their services a database they can rely on to support higher loads and increased demand and they are expanding they use of it to enable smarter and faster product development as they customer base grows. In the future, they will continue to find applications for Memorystore’s strong features and consistent scalability.

Thota nithya
Thota nithya
Thota Nithya has been writing Cloud Computing articles for govindhtech from APR 2023. She was a science graduate. She was an enthusiast of cloud computing.
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