Business Software for Beats - Page 5

Top Software that integrates with Beats as of July 2026 - Page 5

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  • 1
    AWS Budgets
    Businesses and organizations need to plan and set expectations around cloud costs. However, the cloud agility requires you to adapt your forecasting processes and tools to match the dynamic nature of your usage. Set up custom budgets and stay informed of how your cost and usage progress and respond quickly when cost or usage exceeds threshold. AWS Budgets allows you to set custom budgets to track your cost and usage from the simplest to the most complex use cases. With AWS Budgets, you can choose to be alerted by email or SNS notification when actual or forecasted cost and usage exceed your budget threshold, or when your actual RI and Savings Plans' utilization or coverage drops below your desired threshold. Create annual, quarterly, monthly, or even daily budgets depending on your business needs.
  • 2
    Pensando

    Pensando

    Pensando

    The massive expansion in the number and diversity of applications, as well as an explosion in the amount of data being generated and transported through enterprise data centers, has pushed the architectural limits of modern IT infrastructure to its breaking point. Traditional “scale-up” approaches, where infrastructure services are embedded into top-of-rack switches, networking and security appliances, are no longer able to keep up, making performance, agility and scale limitations a fact of life for many businesses. Pensando Systems was founded on the belief that there has to be a better way to address these complex issues. We have taken a ground up approach to build a platform that gives enterprises the unique ability to drive cloud-like agility, security and operational simplicity across their entire infrastructure with unmatched scale and performance.
  • 3
    Apache AntUnit

    Apache AntUnit

    Apache Software Foundation

    Initially all tests for Apache Ant tasks were written as individual JUnit test cases. Pretty soon it was clear that most tests needed to perform common tasks like reading a build file, initializing a project instance with it and executing a target. At this point BuildFileTest was invented, a base class for almost all task test cases. BuildFileTest works fine and in fact has been picked up by the Ant-Contrib Project and others as well. This approach has a couple of advantages, one of them is that it is very easy to translate an example build file from a bug report into a test case. If you ask a user for a testcase for a given bug in Ant, he now doesn't need to understand JUnit or how to fit a test into Ant's existing tests any more. AntUnit takes this approach to testing even further, it removes JUnit completely and it comes with a set of predefined <assert> tasks in order to reuse common kind of checks.
  • 4
    Apache Bigtop

    Apache Bigtop

    Apache Software Foundation

    Bigtop is an Apache Foundation project for Infrastructure Engineers and Data Scientists looking for comprehensive packaging, testing, and configuration of the leading open source big data components. Bigtop supports a wide range of components/projects, including, but not limited to, Hadoop, HBase and Spark. Bigtop packages Hadoop RPMs and DEBs, so that you can manage and maintain your Hadoop cluster. Bigtop provides an integrated smoke testing framework, alongside a suite of over 50 test files. Bigtop provides vagrant recipes, raw images, and (work-in-progress) docker recipes for deploying Hadoop from zero. Bigtop support many Operating Systems, including Debian, Ubuntu, CentOS, Fedora, openSUSE and many others. Bigtop includes tools and a framework for testing at various levels (packaging, platform, runtime, etc.) for both initial deployments as well as upgrade scenarios for the entire data platform, not just the individual components.
  • 5
    Azure DNS

    Azure DNS

    Microsoft

    Use Azure DNS to host your Domain Name System (DNS) domains in Azure. Manage your DNS records using the same credentials, and billing and support contract, as your other Azure services. Seamlessly integrate Azure-based services with corresponding DNS updates and streamline your end-to-end deployment process. Azure DNS Private Resolver (in preview) is a cloud-native, highly available, and DevOps-friendly service. It provides a simple, zero-maintenance, reliable, and secure DNS service to resolve and conditionally forward DNS queries from a virtual network to on-premises DNS servers and other target DNS servers without the need to create and manage a custom DNS solution. Resolve DNS names hosted in Azure DNS private zones from on-premises networks as well as DNS queries for your own domain names. This will make your DNS infrastructure work privately and seamlessly across on-premises networks and enable key hybrid networking scenarios.
  • 6
    Apache Aurora

    Apache Aurora

    Apache Software Foundation

    Aurora runs applications and services across a shared pool of machines, and is responsible for keeping them running, forever. When machines experience failure, Aurora intelligently reschedules those jobs onto healthy machines. When updating a job, Aurora will detect the health and status of a deployment and automatically rollback if necessary. Aurora has a quota system to provide guaranteed resources for specific applications, and can support multiple users to deploy services. Services are highly-configurable via a DSL which supports templating, allowing you to establish common patterns and avoid redundant configurations. Aurora announces services to Apache ZooKeeper for discovery by clients like Finagle.
  • 7
    Apache Airflow

    Apache Airflow

    The Apache Software Foundation

    Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.
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