Google Compute Engine
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
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StarTree
StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment.
StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark.
StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.
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AWS Auto Scaling
AWS Auto Scaling continuously observes your applications and automatically modifies capacity to ensure consistent and reliable performance while minimizing costs. This service simplifies the process of configuring application scaling for various resources across multiple services in just a few minutes. It features an intuitive and robust user interface that enables the creation of scaling plans for a range of resources, including Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, as well as Amazon Aurora Replicas. By providing actionable recommendations, AWS Auto Scaling helps you enhance performance, reduce expenses, or strike a balance between the two. If you are utilizing Amazon EC2 Auto Scaling for dynamic scaling of your EC2 instances, you can now seamlessly integrate it with AWS Auto Scaling to extend your scaling capabilities to additional AWS services. This ensures that your applications are consistently equipped with the appropriate resources precisely when they are needed, leading to improved overall efficiency. Ultimately, AWS Auto Scaling empowers businesses to optimize their resource management in a highly efficient manner.
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Amazon CloudWatch
Amazon CloudWatch serves as a comprehensive monitoring and observability tool designed specifically for DevOps professionals, software developers, site reliability engineers, and IT administrators. This service equips users with essential data and actionable insights necessary for overseeing applications, reacting to performance shifts across systems, enhancing resource efficiency, and gaining an integrated perspective on operational health. By gathering monitoring and operational information in the forms of logs, metrics, and events, CloudWatch delivers a cohesive view of AWS resources, applications, and services, including those deployed on-premises. Users can leverage CloudWatch to identify unusual patterns within their environments, establish alerts, visualize logs alongside metrics, automate responses, troubleshoot problems, and unearth insights that contribute to application stability. Additionally, CloudWatch alarms continuously monitor your specified metric values against established thresholds or those generated through machine learning models to effectively spot any anomalous activities. This functionality ensures that users can maintain optimal performance and reliability across their systems.
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