C1000-142 Exam Dumps : IBM Cloud Advocate v2

etcd is an open source distributed key-value store used to hold and manage the critical information that distributed systems need to keep running. etcd’s performance is heavily dependent upon storage disk speed, so it’s highly recommended to use SSDs in etcd environments. Redis (for REmote DIctionary Server) is an open-source, in-memory, NoSQL key-value store that is used primarily as an application cache or quick-response database. Redis supports multiple data structures, built-in Lua scripting, multiple levels of on-disk persistence, and high availability. Redis is an in-memory data store and can function as a database, cache, or message broker. In-Correct Answers : MongoDB is an open source, non-relational database management system that uses flexible documents to process and store various forms of data. A NoSQL solution, MongoDB provides an elastic data model that enables users to store and query multivariate data types with ease. This not only simplifies database management for developers but also creates a highly scalable environment for applications and services. MongoDB uses documents or collections of documents as its basic unit of data. Formatted as JSON objects, these documents can store various types of data and be distributed across multiple systems. MongoDB offers a few capabilities that make it stand out from other database management systems, including load balancing, ad hoc database queries, and multi-language support. PostgreSQL, commonly pronounced “Post-GRES,” is an open-source database that has a strong reputation for its reliability, flexibility, and support of open technical standards. PostgreSQL provides the ability to restore databases to a specific moment in time because it maintains a write-ahead log that logs every database change. PostgreSQL features built-in support for multiple procedural languages.

Serverless computing is a cloud computing execution model that provisions computing resources on demand and offloads all responsibility for common infrastructure management tasks. They are auto-scalable so it can handle extremely active traffic periods.

Serverless computing does-not means there are no physical servers utilized, of course there are servers, but we don't have to manage them, in background cloud provider manage (provisioning, scheduling, scaling, patching and more) for us, this gives developers more time to develop and optimize their front-end application code and business logic. And with serverless, customers never pay for idle capacity. They pay only for the resources required to run their applications, and only when those applications are running.

Serverless is a polyglot environment, enabling developers to code in any language or framework - Java, Python, node.js - with which they're comfortable. Because serverless scales up and down on demand in response to workload, it offers significant cost savings for spiky workloads. But it does not offer the same savings for workloads characterized by predictable, steady or long-running processes; in these cases, a traditional server environment might be simpler and more cost-effective.

Serverless Implementations differ across service providers, and capabilities vary, including supported runtimes, authentication, scaling and monitoring.

Serverless architectures are well-suited for event-driven, IOT and stream-processing workloads most notably open-source Apache Kafka event streaming platform.

Benefits:

- Pay only for the time for our code will run.

- Developer don't have to take care of servers or infrastructure, it maintains by cloud provider, so they can focus more on development and business logic.

- API Management & Integrated event sources.

- Serverless scales up and down on demand in response to workload

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