4.6 out of 5 stars
(479 Ratings)
Uptime.com provides comprehensive, unified visibility into the availability and performance of critical services. Monitoring tools empower engineering, operations and SRE teams to maintain oversight of their web stack and respond to outages through customizable alerting channels.
Uptime.com offers a broad set of monitoring capabilities, including web, network, and email. API and transaction checks offer synthetic monitoring to perform multi-step validations of critical flows and services. Monitor public and private resources through a unified interface that streamlines configuration and alerting.
Set up and customize Status Pages with your company branding to communicate incidents and maintenance to both customers and internal teams. Provide a single-page overview that shows your overall service health at a glance.
Robust and customizable SLA reporting allows stakeholders to stay informed on incidents and downtime.
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4.6 out of 5 stars
(165 Ratings)
NetCrunch is commercial, self-hosted, agentless network and IT infrastructure monitoring software for Windows Server. It monitors network devices, servers, virtualization platforms, cloud services, applications, websites, logs, telemetry, and network traffic across on-premises and hybrid IT environments. Network traffic analysis supports NetFlow, sFlow, IPFIX, and other flow technologies.
NetCrunch supports 680+ monitoring targets and provides 270+ ready-to-use Monitoring Packs for devices, applications, and operating systems. Licensing is based on monitored nodes and network interfaces rather than individual sensors, checks, or metrics.
Real-time dashboards, policy-based monitoring, advanced alerting, and 40+ automated response actions—including remote script execution, service restart, process termination, and device reboot—support centralized monitoring and automated remediation.
NetCrunch runs on Windows Server and can monitor infrastructure deployed on-premises, in the cloud, or across hybrid environments.
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Apache Spark
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
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