Load Prediction
Self learning future requests pattern prediction algorithm
Self learning future requests pattern prediction algorithm
Automating the scaling of the PostgreSQL DB based on the prediction model output
Realtime data sync between Postgres nodes to ensure the data consistency
Data validation and crash recovery for the PostgreSQL DB instances
Escála simplifies scale so that you don't have to think about it. It distributes data and workload demand automatically. Get rid of manual replication and complicated workarounds. See the entire journey of Escála.
A fully managed Postgres service that allows you to choose your cloud provider without being locked in. Escála provides everything you need for a production-grade database, so you don't have to worry:
Making programs portable with containers It's catching on. Docker is a popular containerization framework. A 2014 open-source container orchestration system. Public, private or hybrid clouds can run Kubernetes. Google used container orchestration to scale highland services. Microservices hype led to widespread containerized software adoption. Cloud computing has made Microservices a hot topic in Software Engineering. Architecturally, monolithic programs were preferred. Microservices architecture has been adopted to take advantage of cloud computing . It has also aided the expansion of financial services and streaming services like Netflix. Database technologies have not been tested due to their complexity and lack of persistence and consistency in the Kubernetes environment.
The need for database scaling in Kubernetes to facilitate high availability, performance, and best security, as well as efficient use of monitoring solutions for user convenience.
Kubernetes is a widely used container orchestration technology. But no application's state can be controlled. As a result, Kubernetes cannot handle stateful applications like databases. Although databases can be deployed on Kubernetes clusters, scaling them is difficult. The vast majority of current solutions are unrelated to databases and exclude key factors that should be included in a scaling mechanism. A scaling mechanism for containerized applications is required regardless of the technology used. High availability is critical when designing mission-critical systems. Previously, systems solved this issue by keeping a separate common database for each microservice. This may cause a system bottleneck or cause a single point of failure. While Kubernetes now has native scaling, the issue of databases retaining states remains. When scaling a system, extra considerations must be made. A novel method for scaling while maintaining a balanced workload distribution among nodes is presented in this study.
To give developers a highly accessible database that can be used with any application, regardless of their prior knowledge of Kubernetes, distributed architecture, or deployment management. A web application on the operator's front-end server allows users to set up a database cluster, allowing them to quickly get their apps up and running. After configuring the application to their liking, developers can monitor its health and performance using the frontend web application's administrative dashboards. As a result, developers will no longer need to worry about configuring or building a highly available PostgreSQL database on Kubernetes from scratch. A cloud database is one where the service provider is in charge of most of the operations and maintenance. Users have no control over database versions, updates, or scalability. For example, as shown in this study, running a database on Kubernetes gives greater control over database maintenance while still leveraging the benefits of cloud computing. Also, when it comes to database management, customers prefer to keep things simple.
