Momento’s Post

Efficient systems demand smart architecture, and distributed caching is very important for driving scalability and performance. ByteByteGo’s latest piece dives deep into how caching accelerates query response times, reduces database load, and ensures seamless user experiences. For those building high-performing systems, understanding caching strategies like partitioning, replication, and cache invalidation is really important. A must-read for anyone scaling systems or optimizing distributed architectures: #ByteByteGo’s Article.

Step closer to disk less application architecture https://lnkd.in/gF4a4iCW

Are your caching systems buckling under pressure as you scale? The New Stack highlights the common pitfalls in evolving cache architectures, but Aerospike has the solution. With unmatched scalability and reliability, our platform simplifies complexity while enhancing performance. Visit us at AWS Re:Invent to discover how we can help you regain control. Read the full article here: https://lnkd.in/dCEq-4Rd #CacheScaling #Aerospike #AWSreInvent

Crafting a modern memory store. What makes our cache unique? Part 4 - Hot Key Propagation: Momento Cache leverages a tiered caching strategy that spans both the caching and gateway layers. Hot data is propagated outwards to gateway nodes in order to quickly clear requests and prevent pressure from building up the caching layer. This can be understood as a unique form of load shedding, in which excess requests are rejected with a value rather than an error. Curious? Read more here about our #serverless cache!

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.

This reference architecture describes the benefits of exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh. This guide is intended for platform administrators. You can increase the resiliency and redundancy of your services by deploying applications consistently across multiple GKE clusters, where each cluster becomes an additional failure domain. For example, a service with a service level objective (SLO) of 99.9% when deployed in a single GKE cluster achieves an SLO of 99.9999% when deployed across two GKE clusters (1 - (0.001)2). You can also provide users with an experience where incoming requests are automatically directed to the least latent and available mesh ingress gateway.