Best IT Management Software for Stackable

Kubernetes (K8s), an open-source software that automates deployment, scaling and management of containerized apps, is available as an open-source project. It organizes containers that make up an app into logical units, which makes it easy to manage and discover. Kubernetes is based on 15 years of Google's experience in running production workloads. It also incorporates best-of-breed practices and ideas from the community. Kubernetes is built on the same principles that allow Google to run billions upon billions of containers per week. It can scale without increasing your operations team. Kubernetes flexibility allows you to deliver applications consistently and efficiently, no matter how complex they are, whether you're testing locally or working in a global enterprise. Kubernetes is an open-source project that allows you to use hybrid, on-premises, and public cloud infrastructures. This allows you to move workloads where they are most important.

Apache Kafka®, is an open-source distributed streaming platform.

Docker eliminates repetitive, tedious configuration tasks and is used throughout development lifecycle for easy, portable, desktop, and cloud application development. Docker's complete end-to-end platform, which includes UIs CLIs, APIs, and security, is designed to work together throughout the entire application delivery cycle. Docker images can be used to quickly create your own applications on Windows or Mac. Create your multi-container application using Docker Compose. Docker can be integrated with your favorite tools in your development pipeline. Docker is compatible with all development tools, including GitHub, CircleCI, and VS Code. To run applications in any environment, package them as portable containers images. Use Docker Trusted Content to get Docker Official Images, images from Docker Verified Publishings, and more.

Open-source monitoring solutions are able to power your alerting and metrics. Prometheus stores all data in time series. These are streams of timestamped value belonging to the same metric with the same labeled dimensions. Prometheus can also generate temporary derived times series as a result of queries. Prometheus offers a functional query language called PromQL, which allows the user to select and aggregate time series data real-time. The expression result can be displayed as a graph or tabular data in Prometheus’s expression browser. External systems can also consume the HTTP API. Prometheus can be configured using command-line flags or a configuration file. The command-line flags can be used to configure immutable system parameters such as storage locations and the amount of data to be kept on disk and in memory. . Download: https://sourceforge.net/projects/prometheus.mirror/

MinIO's high performance object storage suite is software-defined and allows customers to create cloud-native data infrastructures for machine learning, analytics, and application data workloads. MinIO object storage is fundamentally unique. It is 100% open-source and designed for performance and the S3 API. MinIO is ideal to host large, private cloud environments that have strict security requirements. It also delivers mission-critical availability across a wide range of workloads. MinIO is the fastest object storage server in the world. With READ/WRITE speeds up to 183 GB/s on standard hardware and 171GB/s on SSDs, object storage can be used as the primary storage tier for a variety of workloads, including Spark, Presto TensorFlow, Spark, TensorFlow, H2O.ai, and as a replacement for Hadoop HDFS. MinIO uses the hard-earned knowledge of web scalers to bring object storage a simple scaling model. MinIO scales with one cluster that can be federated to other MinIO clusters.

ZooKeeper is a central service that maintains configuration information, naming, distributed synchronization and provides group services. Distributed applications use all of these services in some way. There is a lot of work involved in fixing bugs and other race conditions. These kinds of services are difficult to implement so applications often skimp on them at the beginning. This makes them fragile and difficult to manage in the face of change. Even if the services are implemented correctly, there can be multiple implementations that lead to complexity in management when the applications are deployed.

Airflow is a community-created platform that allows programmatically to schedule, author, and monitor workflows. Airflow is modular in architecture and uses a message queue for managing a large number of workers. Airflow can scale to infinity. Airflow pipelines can be defined in Python to allow for dynamic pipeline generation. This allows you to write code that dynamically creates pipelines. You can easily define your own operators, and extend libraries to suit your environment. Airflow pipelines can be both explicit and lean. The Jinja templating engine is used to create parametrization in the core of Airflow pipelines. No more XML or command-line black-magic! You can use standard Python features to create your workflows. This includes date time formats for scheduling, loops to dynamically generate task tasks, and loops for scheduling. This allows you to be flexible when creating your workflows.