Search Results for "cluster"
Sort By:
257 projects for "cluster" with 1 filter applied:
-
Managed MySQL, PostgreSQL, and SQL Databases on Google CloudCloud SQL is a fully managed relational database for MySQL, PostgreSQL, and SQL Server. We handle patching, backups, replication, encryption, and failover—so you can focus on your app. Migrate from on-prem or other clouds with free Database Migration Service. IDC found customers achieved 246% ROI. New customers get $300 in credits plus a 30-day free trial.
-
Deploy Apps in Seconds with Cloud RunCloud Run is the fastest way to deploy containerized apps. Push your code in Go, Python, Node.js, Java, or any language and Cloud Run builds and deploys it automatically. Get fast autoscaling, pay only when your code runs, and skip the infrastructure headaches. Two million requests free per month. And new customers get $300 in free credit.
-
1
Kubernetes Capsule
Multi-tenancy and policy-based framework for Kubernetes
...To overcome this, cluster admins tend to provision a dedicated cluster for each groups of users, teams, or departments. As an organization grows, the number of clusters to manage and keep aligned becomes an operational nightmare, described as the well known phenomena of the clusters sprawl. -
2
Another Redis Desktop Manager
A faster, better and more stable Redis desktop manager
AnotherRedisDesktopManager is a cross-platform GUI client for Redis that simplifies connecting, browsing, and manipulating data. It supports standalone, Sentinel, and Cluster modes, plus SSH tunneling and ACL credentials for secure access in varied environments. The UI provides tree and table views of keys with inline editors for strings, hashes, lists, sets, sorted sets, and streams, including TTL management and batch operations. Built-in monitoring lets you watch stats, slow logs, and command activity while an integrated console executes raw Redis commands. ... -
3
Inspektor Gadget
The eBPF tool and systems inspection framework for Kubernetes
Inspektor Gadget is a collection of tools (or gadgets) to debug and inspect Kubernetes resources and applications. It manages the packaging, deployment, and execution of eBPF programs in a Kubernetes cluster, including many based on BCC tools, as well as some developed specifically for use in Inspektor Gadget. It automatically maps low-level kernel primitives to high-level Kubernetes resources, making it easier and quicker to find the relevant information. -
4
Horde
Horde is a distributed Supervisor and Registry
Horde provides a distributed, fault-tolerant Registry and DynamicSupervisor for Elixir applications, letting you run and manage processes across clustered nodes as if they lived on a single machine. It relies on conflict-free replicated data types (CRDTs) to converge membership and process ownership without a central leader, so cluster topology can change freely as nodes join or leave. With Horde.Registry you register processes globally and look them up anywhere, while Horde.DynamicSupervisor starts and migrates children across nodes, rebalancing as capacity or health changes. Because everything runs under OTP supervision, failures are isolated and recoveries are automatic, even during network partitions or rolling deploys. ... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
5
Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
6
spring-cloud-gateway
A Gateway built on Spring Framework and Spring Boot
Spring Cloud provides tools for developers to quickly build some of the common patterns in distributed systems (e.g. configuration management, service discovery, circuit breakers, intelligent routing, micro-proxy, control bus, one-time tokens, global locks, leadership election, distributed sessions, cluster state). Coordination of distributed systems leads to boiler plate patterns, and using Spring Cloud developers can quickly stand up services and applications that implement those patterns. They will work well in any distributed environment, including the developer’s own laptop, bare metal data centres, and managed platforms such as Cloud Foundry. ... -
7
Prom-Client
Prometheus client for node.js
Prom-Client is a Prometheus client for Node.js that allows developers to instrument their applications and expose metrics, facilitating the monitoring of application performance and resource usage. -
8
Redis
An in-memory database that persists on disk
...Redis has built-in replication, Lua scripting, LRU eviction, transactions, and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster. You can run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing an element to a list; computing set intersection, union and difference; or getting the member with highest ranking in a sorted set. To achieve top performance, Redis works with an in-memory dataset. Depending on your use case, you can persist your data either by periodically dumping the dataset to disk or by appending each command to a disk-based log. -
9
MongoDB Community Kubernetes Operator
MongoDB Community Kubernetes Operator
The MongoDB Kubernetes Operator is an open-source controller that automates deploying and managing MongoDB clusters on Kubernetes, enabling developers and operators to run production-grade MongoDB in cloud-native environments. By defining custom resource definitions (CRDs) for MongoDB resources, the operator lets you declare cluster topology, configuration, and scaling policies as Kubernetes manifests that can be applied with standard tools like kubectl and Helm. The operator handles provisioning, failover, backups, upgrades, and monitoring hooks, dramatically reducing manual operational burden while improving reliability and consistency. It supports replica sets and sharded clusters, giving operators the flexibility to choose architectures that match their availability and performance needs. ... -
$300 in Free Credit for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credit—no hidden charges. Test, build, and deploy without risk. Use your credit across the Google Cloud platform to find what works best for your needs. After your credits are used, continue building with free monthly usage products. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
10
Akamai Application Platform (for LKE)
App Platform for Linode Kubernetes Engine
...Instead of assembling ingress, certificates, GitOps, secrets, and observability by hand, you install a single Helm chart and get a consistent, production-oriented baseline on LKE or any conformant Kubernetes cluster. The project provides a guided path after installation, post-install setup, and hands-on labs, so teams can go from a fresh cluster to shipping services with guardrails in place. It emphasizes developer self-service: creating app environments, deploying via Git-backed workflows, exposing services on the public internet, and wiring logs/metrics/dashboards without bespoke YAML. ... -
11
future
R package: future: Unified Parallel and Distributed Processing in R
...It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. It handles automatic exporting of needed global variables/functions, managing of packages, RNG, etc. Automatic detection and export of global objects and functions needed by future expressions, so the user doesn’t need to manage that manually. Ability to control how futures are resolved. -
12
redis-py
Redis Python client
redis-py is the official Python client for interacting with Redis, the in-memory data structure store. It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
13
kubectl tree
kubectl plugin to browse Kubernetes object hierarchies as a tree
...This is especially useful for understanding how complex workloads like Deployments, StatefulSets, Knative Services, or Agones Fleets fan out into lower-level resources across the cluster. The plugin is written in Go, packaged for easy installation via the krew plugin manager, and exposes flags to control namespace scoping, label selectors, and condition filters so you can narrow what’s shown. It defaults to searching namespaced objects in the same namespace as the root resource, but can also traverse cluster-wide objects when asked. -
14
Prometheus Operator
Prometheus Operator creates/configures/manages Prometheus clusters
The API, spec, status and other user facing objects may change, but in a backward-compatible way. The Prometheus Operator provides Kubernetes native deployment and management of Prometheus and related monitoring components. The purpose of this project is to simplify and automate the configuration of a Prometheus-based monitoring stack for Kubernetes clusters. Kubernetes Custom Resources: Use Kubernetes custom resources to deploy and manage Prometheus, Alertmanager, and related components.... -
15
SOFAJRaft
A production-grade java implementation of RAFT consensus algorithm
SOFAJRaft is a production-level, high-performance Java implementation based on the RAFT consistency algorithm that supports MULTI-RAFT-GROUP for high-load, low-latency scenarios. With SOFAJRaft you can focus on your business area. SOFAJRaft handles all RAFT-related technical challenges. SOFAJRaft is very user-friendly, which provides several examples, making it easy to understand and use. -
16
Hera
Hera is an Argo Python SDK
Hera is an Argo Python SDK. Hera aims to make the construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. -
17
Garnet
Garnet is a remote cache-store from Microsoft Research
Garnet is a remote cache‑store developed by Microsoft Research. It delivers high throughput and low‑latency performance, supports scalability via clustering (sharding, replication, key migration, checkpointing, failover, transactions), and seamlessly integrates with existing Redis clients. Garnet offers much better throughput and scalability with many client connections and small batches, relative to comparable open-source cache-stores, leading to cost savings for large apps and services.... -
18
Gatling
Modern Load Testing as Code
Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as... -
19
kagent
Kubernetes native framework for building AI agents
...It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. It supports multiple model providers through a dedicated configuration resource, allowing teams to switch providers or run mixed environments while keeping the agent spec stable. ... -
20
testkube
Kubernetes-native testing framework for test execution
Welcome to Testkube - Your friendly cloud-native testing framework for Kubernetes. Testkube natively integrates test orchestration and execution into Kubernetes and your CI/CD/GitOps pipeline. It decouples test artifacts and execution from CI/CD tooling; tests are meant to be part of your cluster's state and can be executed as needed. Out-of-the-box integrations with all popular testing tools and CI/CD systems mean no custom scripts are required to orchestrate your tests from any... -
21
Lettuce
Advanced Java Redis client for thread-safe sync, async, etc.
...Its simple yet powerful programming model allows you for trivial use-cases as well as for chained asynchronous flows. Redis Standalone, Master/Slave, Redis Sentinel and Redis Cluster. Lettuce connects with all operational models natively supported by Redis. Partition-tolerance, Read Slaves and Transport-Level-Security provide the required foundation for highly scalable applications. -
22
Apache Seata
High-performance, open source distributed transaction solution
Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and... -
23
kMCP
Kubernetes Controller for building, testing and deploying MCP servers
...It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD), allowing MCP servers to be represented as native Kubernetes objects you can operate with familiar kubectl-driven patterns. A key component is the transport adapter, which fronts MCP servers to provide routing and multi-transport support without requiring code changes in your server implementation. ... -
24
Argo Workflows
Workflow engine for Kubernetes
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition). Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using... -
25
DualPipe
A bidirectional pipeline parallelism algorithm
...The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap with communication. DualPipe addresses that by scheduling micro-batches from both ends of the pipeline in a bidirectional fashion—i.e. some micro-batches flow forward while others flow backward—so that computation on one partition can coincide with communication for another.
