Best IT Management Software for Apache Airflow

Stonebranch’s Universal Automation Center (UAC) is a Hybrid IT automation platform, offering real-time management of tasks and processes within hybrid IT settings, encompassing both on-premises and cloud environments. As a versatile software platform, UAC streamlines and coordinates your IT and business operations, while ensuring the secure administration of file transfers and centralizing IT job scheduling and automation solutions. Powered by event-driven automation technology, UAC empowers you to achieve instantaneous automation throughout your entire hybrid IT landscape. Enjoy real-time hybrid IT automation for diverse environments, including cloud, mainframe, distributed, and hybrid setups. Experience the convenience of Managed File Transfers (MFT) automation, effortlessly managing and orchestrating file transfers between mainframes and systems, seamlessly connecting with AWS or Azure cloud services.

Monitor your servers, containers, and applications, in high-resolution and in real-time. Netdata collects metrics per second and presents them in beautiful low-latency dashboards. It is designed to run on all of your physical and virtual servers, cloud deployments, Kubernetes clusters, and edge/IoT devices, to monitor your systems, containers, and applications. It scales nicely from just a single server to thousands of servers, even in complex multi/mixed/hybrid cloud environments, and given enough disk space it can keep your metrics for years. KEY FEATURES: Collects metrics from 800+ integrations Real-Time, Low-Latency, High-Resolution Unsupervised Anomaly Detection Powerful Visualization Out of box Alerts systemd Journal Logs Explorer Low Maintenance Open and Extensible Troubleshoot slowdowns and anomalies in your infrastructure with thousands of per-second metrics, meaningful visualisations, and insightful health alarms with zero configuration. Netdata is different. Real-Time data collection and visualization. Infinite scalability baked into its design. Flexible and extremely modular. Immediately available for troubleshooting, requiring zero prior knowledge and preparation.

Open source solutions that require no maintenance can save you time and money. Your engineers will enjoy working with data because it is integrated, managed and highly reliable. DoubleCloud offers a range of managed open-source services, or you can leverage the full platform's power, including data storage and visualization, orchestration, ELT and real-time visualisation. We offer leading open-source solutions like ClickHouse Kafka and Airflow with deployments on Amazon Web Services and Google Cloud. Our no-code ELT allows real-time data sync between systems. It is fast, serverless and seamlessly integrated into your existing infrastructure. Our managed open-source data visualisation allows you to visualize your data in real time by creating charts and dashboards. Our platform is designed to make engineers' lives easier.

Data warehouse metadata and tools that connect to it can be captured. You can track the workloads that matter to you and retroactively analyze user engagement, cost, performance, and performance of data products. You have complete visibility into your data platform. This includes who is accessing your data and how it's being used. We'll be sharing the secrets of how data teams create and deliver data products in these interviews. We also discuss tech stacks, best practices, and other lessons learned. Intermix.io provides end-to-end visibility through an easy-to use SaaS dashboard. You can collaborate with your entire team to create custom reports and get all the information you need to understand your data platform, cloud data warehouse, and the tools that connect it. Intermix.io, a SaaS product, collects metadata from your cloud data warehouse without any coding. We don't need access to any data you have copied into your data warehouse.

emma gives you the freedom to choose from the best cloud providers and environments to adapt to changing needs, without adding complexity. Cloud management is simplified by automating key tasks and unifying services, reducing complexity. Cloud resources are optimized automatically to ensure full utilization, while reducing overhead. Supporting open standards allows businesses to be more flexible and free from vendor lock-in. Monitors and optimizes real-time data traffic, preventing cost spikes through efficient resource reallocation. Create your cloud infrastructure using different providers and environments. Manage your unified cloud from a single intuitive interface. You can now gain the visibility needed to improve infrastructure performance, and reduce costs. Take control of your entire cloud environment to ensure regulatory compliance.

Beats is an open platform that allows single-purpose data shippers to use. They can send data from thousands or hundreds of machines and systems to Logstash and Elasticsearch. Beats are open-source data shippers that you can install on your servers to send operational information to Elasticsearch. Elastic offers Beats to capture data and event logs. Beats can send data directly via Elasticsearch or Logstash. There you can further process the data and enhance it before visualizing it in Kibana. You can quickly get up and running with infrastructure metrics monitoring or centralized log analytics. You can try the Metrics and Logs apps in Kibana. For more information, see Analyze metrics or Monitor logs. Filebeat allows you to easily forward and centralize logs from any source, including security devices, cloud containers, hosts, and OT.

Monitor your data health, and monitor your pipeline performance. Get unified visibility for all pipelines that use cloud-native tools such as Apache Spark, Snowflake and BigQuery. A platform for Data Engineers that provides observability. Data engineering is becoming more complex as business stakeholders demand it. Databand can help you catch-up. More pipelines, more complexity. Data engineers are working with more complex infrastructure and pushing for faster release speeds. It is more difficult to understand why a process failed, why it is running late, and how changes impact the quality of data outputs. Data consumers are frustrated by inconsistent results, model performance, delays in data delivery, and other issues. A lack of transparency and trust in data delivery can lead to confusion about the exact source of the data. Pipeline logs, data quality metrics, and errors are all captured and stored in separate, isolated systems.

Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.