💥 Another feature update💥 Excited to announce Anyscale Job Queues Job Queues deliver improved utilization and simplified cluster management by running multiple concurrent jobs on a single cluster. • Users submit jobs to a specified queue, Anyscale automatically prioritizes and schedules them. • Jobs are executed based on their queue position, with limits on concurrent jobs per cluster. • Jobs run to completion, including retries, repeating until all jobs in the queue are completed or errored. Read full details here: https://lnkd.in/g3VfuApt And watch how it works below:
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🚀 Need to ingest a million rows per second? Check this out! In this post, Niklas shares a detailed methodology to fine-tune a setup for optimal indexing performance, handling 10 metrics per row with a target of 1 million rows per second. This approach involves a few iterations and can be applied to various ingestion requirements. Achieving 90% CPU utilization while avoiding queue overload in a cluster is no small feat, but this deep dive breaks down exactly how to surpass the million-row mark with just 5 nodes. Curious how it's done? Read the full story here: https://lnkd.in/ej5Vm3Ki #DataIngestion #PerformanceTuning #ClusterManagement
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Helping companies driving sales success and shaping strategic growth | Sales & Business Development Manager
Every minute, more and more data accumulates that overloads your file servers, budget, and staff... That growth never stops. 📈 The number of files and their changing relevance transcend traditional file servers and #NAS devices. 📁 Wondering how it's possible to keep these files for months, years, or decades 📅 at an affordable price 💵 while keeping them accessible when needed? This is easily possible with DataCore Software Swarm the scalable solution for affordable, long-term data retention #ActiveArchive. 💡 Discover how in the video: ▶️ https://lnkd.in/dfUGvRND LocalDisti Romania #datacore #localdisti #localdistiromania #swarm #objectstorage If you are interested or have any questions, do not hesitate to contact us: Marius Petcu | M: +40 750 130 819 | [email protected] | www.localdisti.cz/ro
Active Archive with Swarm Object Storage
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Discover the journey to better memory allocation with Libbeat output client and Elasticsearch! Check out this blog to find out how we reduced time of execution by 3%, memory consumption by 8%, and the number of allocations by -3% to help improve performance: https://lnkd.in/dRjC-wHU
Improving memory allocation with Libbeat output client and Elasticsearch
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#OCI Stack Monitoring discovers and monitors applications and underlying tech stacks. Join this session to learn how to enhance monitoring with new features that go beyond built-in metrics and resource types. https://lnkd.in/gAgCwiTk
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Lessons Learned from Building a Database Operator - Data on Kubernetes Community Speaker 6 proposes using L4 load balancers instead of going through ingress or adding one more hop between clients to the database, citing potential latency issues. Speaker 2 suggests splitting the problem into two parts: external connectivity and internal replication, and notes that MongoDB's wire protocol is built on top of TCP. He also mentions an optimization patch for the Q of DNS to avoid hotspotting in a replica set configuration. Speaker 1 adds that keeping deployments agnostic of underlying infrastructure, and mentions some users are running cilium as CNI and service mesh with single and multi-cluster setups successfully. Speaker 7 asks about latency thresholds for cross-region replication in multi-cluster setup, to which speaker 1 responds that while they're aware it might pose a limitation, they don't have a definitive answer yet. https://ift.tt/N682gth #news #cto #tech
Lessons Learned from Building a Database Operator - Data on Kubernetes Community Speaker 6 proposes using L4 load balancers instead of going through ingress or adding one more hop between clients to the database, citing potential latency issues. Speaker 2 suggests splitting the problem into two parts: external connectivity and internal replication, and notes that MongoDB's wire protocol is b...
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Discover the journey to better memory allocation with Libbeat output client and Elasticsearch! Check out this blog to find out how we reduced time of execution by 3%, memory consumption by 8%, and the number of allocations by -3% to help improve performance: https://lnkd.in/gA6_tMrs
Improving memory allocation with Libbeat output client and Elasticsearch
elastic.co
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Discover the journey to better memory allocation with Libbeat output client and Elasticsearch! Check out this blog to find out how we reduced time of execution by 3%, memory consumption by 8%, and the number of allocations by -3% to help improve performance: https://lnkd.in/gjt2HY_e
Improving memory allocation with Libbeat output client and Elasticsearch
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Decoding PromQL: A Deep Dive into Prometheus Query Language #monitoring #prometheus #promql #deepdive https://lnkd.in/etrCkyce
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Data and security professional leading the charge to help companies better leverage data and AI to search, observe and protect their organizations.
Discover the journey to better memory allocation with Libbeat output client and Elasticsearch! Check out this blog to find out how we reduced time of execution by 3%, memory consumption by 8%, and the number of allocations by -3% to help improve performance: https://lnkd.in/g-ThCjzC
Improving memory allocation with Libbeat output client and Elasticsearch
elastic.co
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