GridGain
GridGain is a Unified Real-Time Data Platform created by the original developers of Apache Ignite. It provides enterprises with a simplified and highly optimized data architecture that supports extreme speed, massive scale, and high availability for their data ecosystems. GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics with ultra-low latencies. It is designed to seamlessly integrate both streaming data in-motion and historical data at-rest, enabling complex analytical and transactional workloads. The platform supports deployment across on-premises, public cloud, hybrid-cloud, and multi-cloud environments. GridGain is widely used in industries such as financial services, telecommunication, transportation, and logistics for real-time risk management, smart decisioning, and high-performance online transactional processing (OLTP), among other use cases.
In-Memory Computing • In-Memory Data Grid • Apache Ignite • Stream Processing • High Performance Transaction Processing
Senior Cloud DevOps Engineer
December 11, 2024
GridGain
GridGain is a Unified Real-Time Data Platform created by the original developers of Apache Ignite. It provides enterprises with a simplified and highly optimized data architecture that supports extreme speed, massive scale, and high availability for their data ecosystems. GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics with ultra-low latencies. It is designed to seamlessly integrate both streaming data in-motion and historical data at-rest, enabling complex analytical and transactional workloads. The platform supports deployment across on-premises, public cloud, hybrid-cloud, and multi-cloud environments. GridGain is widely used in industries such as financial services, telecommunication, transportation, and logistics for real-time risk management, smart decisioning, and high-performance online transactional processing (OLTP), among other use cases.
In-Memory Computing • In-Memory Data Grid • Apache Ignite • Stream Processing • High Performance Transaction Processing
📋 Description
• Work to automate deployment and management processes for various public cloud providers such as AWS, GCP, Azure • Communicating with the dedicated GridGain Nebula support team to share your experience in solving various issues with public cloud providers
🎯 Requirements
• Expert skills in working with public or private clouds ( AWS / GCP / OpenStack, etc.) • Expert skills in working with K8s , Docker , Docker Compose • Experience with automation tools for public cloud deployment (ansible, terraform, etc.) • Good knowledge of network configuration (static routing, subnets, gateways) • English level – upper-intermediate and above • Experience with Apache Ignite™ • Java programming experience • SQL experience • Experience with network utilities (traceroute, ping, nmap, nslookup) • Experience with monitoring tools (Zabbix, ELK, etc.)
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