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Autoscaling, also spelled auto scaling or auto-scaling, and sometimes also called automatic scaling, is a method used in cloud computing that dynamically adjusts the amount of computational resources in a server farm - typically measured by the number of active servers - automatically based on the load on the farm. For example, the number of ...
Container clusters need to be managed. This includes functionality to create a cluster, to upgrade the software or repair it, balance the load between existing instances, scale by starting or stopping instances to adapt to the number of users, to log activities and monitor produced logs or the application itself by querying sensors.
Amazon EC2 price varies from $2.5 per month for "nano" instance with 1 vCPU and 0.5 GB RAM on board to "xlarge" type of instances with 32 vCPU and 488 GB RAM billed up to $3997.19 per month. The charts above show how Amazon EC2 pricing is compared to similar Cloud Computing services: Microsoft Azure, Google Cloud Platform, Kamatera, and Vultr. [69]
Kubernetes (/ ˌ k (j) uː b ər ˈ n ɛ t ɪ s,-ˈ n eɪ t ɪ s,-ˈ n eɪ t iː z,-ˈ n ɛ t iː z /, K8s) [3] is an open-source container orchestration system for automating software deployment, scaling, and management.
Network function virtualization defines these terms differently: scaling out/in is the ability to scale by adding/removing resource instances (e.g., virtual machine), whereas scaling up/down is the ability to scale by changing allocated resources (e.g., memory/CPU/storage capacity). [9]
Amazon introduces Elastic Load Balancing (ELB) (which makes it easy for users to distribute web traffic across Amazon EC2 instances), Auto Scaling (which allows users to scale policies driven by metrics collected by Amazon CloudWatch), and Amazon CloudWatch (for tracking per-instance performance metrics including CPU load). [31] 2009: May 21
High Instance Density: Run numerous Android instances on a single machine, maximizing the use of cloud infrastructure. Elastic Scaling: Scale up or down dynamically depending on the workload, with support for automated operations. Full Automation: Easily deploy and manage large-scale Android environments, with minimal manual intervention.
OpenFaaS (management and auto-scaling of compute) NATS (asynchronous message bus/queue) Kubernetes (declarative, extensible, scale-out, self-healing clustering) SMACK [10] Apache Spark (big data and MapReduce) Apache Mesos (node startup/shutdown) Akka (toolkit) (actor implementation) Apache Cassandra (database) Apache Kafka T-REx [30]