[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-github-qdrant-vertical-scaling":3,"mdc-l8sby3-key":47,"related-repo-github-qdrant-vertical-scaling":367,"related-org-github-qdrant-vertical-scaling":471},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":28,"repoUrl":29,"updatedAt":30,"license":31,"forks":32,"topics":33,"repo":42,"sourceUrl":45,"mdContent":46},"qdrant-vertical-scaling","guide Qdrant vertical scaling decisions","Guides Qdrant vertical scaling decisions. Use when someone asks 'how to scale up a node', 'need more RAM', 'upgrade node size', 'vertical scaling', 'resize cluster', 'scale up vs scale out', or when memory\u002FCPU is insufficient on current nodes. Also use when someone wants to avoid the complexity of horizontal scaling.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"github","GitHub","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgithub.png",[12,16,19,22,25],{"name":13,"slug":14,"type":15},"Architecture","architecture","tag",{"name":17,"slug":18,"type":15},"Qdrant","qdrant",{"name":20,"slug":21,"type":15},"Database","database",{"name":23,"slug":24,"type":15},"Capacity Planning","capacity-planning",{"name":26,"slug":27,"type":15},"AI Infrastructure","ai-infrastructure",36978,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","2026-04-18T04:46:15.120383",null,4632,[34,35,36,37,38,39,40,41],"agent-skills","agents","ai","awesome","custom-agents","github-copilot","hacktoberfest","prompt-engineering",{"repoUrl":29,"stars":28,"forks":32,"topics":43,"description":44},[34,35,36,37,38,39,40,41],"Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Ftree\u002FHEAD\u002Fskills\u002Fqdrant-scaling\u002Fscaling-data-volume\u002Fvertical-scaling","---\nname: qdrant-vertical-scaling\ndescription: \"Guides Qdrant vertical scaling decisions. Use when someone asks 'how to scale up a node', 'need more RAM', 'upgrade node size', 'vertical scaling', 'resize cluster', 'scale up vs scale out', or when memory\u002FCPU is insufficient on current nodes. Also use when someone wants to avoid the complexity of horizontal scaling.\"\n---\n\n# What to Do When Qdrant Needs to Scale Vertically\n\nVertical scaling means increasing CPU, RAM, or disk on existing nodes rather than adding more nodes. This is the recommended first step before considering horizontal scaling. Vertical scaling is simpler, avoids distributed system complexity, and is reversible.\n\n- Vertical scaling for Qdrant Cloud is done through the [Qdrant Cloud Console](https:\u002F\u002Fcloud.qdrant.io\u002F)\n- For self-hosted deployments, resize the underlying VM or container resources\n\n## When to Scale Vertically\n\nUse when: current node resources (RAM, CPU, disk) are insufficient, but the workload doesn't yet require distribution.\n\n- RAM usage approaching 80% of available memory (OS page cache eviction starts, severe performance degradation)\n- CPU saturation during query serving or indexing\n- Disk space running low for on-disk vectors and payloads\n- A single node can handle up to ~100M vectors depending on dimensions and quantization\n- For non-production workloads, which are tolerant to single-point-of-failure and don't require high availability\n\n\n## How to Scale Vertically in Qdrant Cloud\n\nVertical scaling is managed through the Qdrant Cloud Console.\n\n- Log into [Qdrant Cloud Console](https:\u002F\u002Fcloud.qdrant.io\u002F) or use [CLI tool](https:\u002F\u002Fgithub.com\u002Fqdrant\u002Fqcloud-cli)\n- Select the cluster to resize\n- Choose a larger node configuration (more RAM, CPU, or both)\n- The upgrade process involves a rolling restart with no downtime if replication is configured\n- Ensure `replication_factor: 2` or higher before resizing to maintain availability during the rolling restart\n\n**Important:** Scaling up is straightforward. Scaling down requires care -- if the working set no longer fits in RAM after downsizing, performance will degrade severely due to cache eviction. Always load test before scaling down.\n\n\n## RAM Sizing Guidelines\n\nRAM is the most critical resource for Qdrant performance. Use these guidelines to right-size.\n\n- Exact estimation of RAM usage is difficult; use this simple approximate formula: `num_vectors * dimensions * 4 bytes * 1.5` for full-precision vectors in RAM\n- With scalar quantization: divide by 4 (INT8 reduces each float32 to 1 byte) [Quantization](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F)\n- With binary quantization: divide by 32 [Binary quantization](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F?s=binary-quantization)\n- Add overhead for HNSW index (~20-30% of vector data), payload indexes, and WAL\n- Reserve 20% headroom for optimizer operations and OS cache\n- Monitor actual usage via Grafana\u002FPrometheus before and after resizing [Monitoring](..\u002F..\u002F..\u002Fqdrant-monitoring\u002FSKILL.md)\n\n\n## When Vertical Scaling Is No Longer Enough\n\nRecognize these signals that it's time to go horizontal:\n\n- Data volume exceeds what a single node can hold even with quantization and mmap\n- IOPS are saturated (more nodes = more independent disk I\u002FO)\n- Need fault tolerance (requires replication across nodes)\n- Need tenant isolation via dedicated shards\n- Single-node CPU is maxed and query latency is unacceptable\n- Next vertical scaling step is the largest available node size. You might need to be able to temporarily scale up to the larger node size to do batch operations or recovery. If you are already at the largest node size, you won't be able to do that.\n\nWhen you hit these limits, see [Horizontal Scaling](..\u002Fhorizontal-scaling\u002FSKILL.md) for guidance on sharding and node planning.\n\n\n## What NOT to Do\n\n- Do not scale down RAM without load testing first (cache eviction = severe latency degradation that can last days)\n- Do not ignore the 80% RAM threshold (performance cliff, not gradual degradation)\n- Do not skip replication before resizing in Cloud (rolling restart without replicas = downtime)\n- Do not jump to horizontal scaling before exhausting vertical options (adds permanent operational complexity)\n- Do not assume more CPU always helps (IOPS-bound workloads won't improve with more cores)",{"data":48,"body":49},{"name":4,"description":6},{"type":50,"children":51},"root",[52,61,67,91,98,103,131,137,142,193,204,210,215,276,282,287,320,333,339],{"type":53,"tag":54,"props":55,"children":57},"element","h1",{"id":56},"what-to-do-when-qdrant-needs-to-scale-vertically",[58],{"type":59,"value":60},"text","What to Do When Qdrant Needs to Scale Vertically",{"type":53,"tag":62,"props":63,"children":64},"p",{},[65],{"type":59,"value":66},"Vertical scaling means increasing CPU, RAM, or disk on existing nodes rather than adding more nodes. This is the recommended first step before considering horizontal scaling. Vertical scaling is simpler, avoids distributed system complexity, and is reversible.",{"type":53,"tag":68,"props":69,"children":70},"ul",{},[71,86],{"type":53,"tag":72,"props":73,"children":74},"li",{},[75,77],{"type":59,"value":76},"Vertical scaling for Qdrant Cloud is done through the ",{"type":53,"tag":78,"props":79,"children":83},"a",{"href":80,"rel":81},"https:\u002F\u002Fcloud.qdrant.io\u002F",[82],"nofollow",[84],{"type":59,"value":85},"Qdrant Cloud Console",{"type":53,"tag":72,"props":87,"children":88},{},[89],{"type":59,"value":90},"For self-hosted deployments, resize the underlying VM or container resources",{"type":53,"tag":92,"props":93,"children":95},"h2",{"id":94},"when-to-scale-vertically",[96],{"type":59,"value":97},"When to Scale Vertically",{"type":53,"tag":62,"props":99,"children":100},{},[101],{"type":59,"value":102},"Use when: current node resources (RAM, CPU, disk) are insufficient, but the workload doesn't yet require distribution.",{"type":53,"tag":68,"props":104,"children":105},{},[106,111,116,121,126],{"type":53,"tag":72,"props":107,"children":108},{},[109],{"type":59,"value":110},"RAM usage approaching 80% of available memory (OS page cache eviction starts, severe performance degradation)",{"type":53,"tag":72,"props":112,"children":113},{},[114],{"type":59,"value":115},"CPU saturation during query serving or indexing",{"type":53,"tag":72,"props":117,"children":118},{},[119],{"type":59,"value":120},"Disk space running low for on-disk vectors and payloads",{"type":53,"tag":72,"props":122,"children":123},{},[124],{"type":59,"value":125},"A single node can handle up to ~100M vectors depending on dimensions and quantization",{"type":53,"tag":72,"props":127,"children":128},{},[129],{"type":59,"value":130},"For non-production workloads, which are tolerant to single-point-of-failure and don't require high availability",{"type":53,"tag":92,"props":132,"children":134},{"id":133},"how-to-scale-vertically-in-qdrant-cloud",[135],{"type":59,"value":136},"How to Scale Vertically in Qdrant Cloud",{"type":53,"tag":62,"props":138,"children":139},{},[140],{"type":59,"value":141},"Vertical scaling is managed through the Qdrant Cloud Console.",{"type":53,"tag":68,"props":143,"children":144},{},[145,164,169,174,179],{"type":53,"tag":72,"props":146,"children":147},{},[148,150,155,157],{"type":59,"value":149},"Log into ",{"type":53,"tag":78,"props":151,"children":153},{"href":80,"rel":152},[82],[154],{"type":59,"value":85},{"type":59,"value":156}," or use ",{"type":53,"tag":78,"props":158,"children":161},{"href":159,"rel":160},"https:\u002F\u002Fgithub.com\u002Fqdrant\u002Fqcloud-cli",[82],[162],{"type":59,"value":163},"CLI tool",{"type":53,"tag":72,"props":165,"children":166},{},[167],{"type":59,"value":168},"Select the cluster to resize",{"type":53,"tag":72,"props":170,"children":171},{},[172],{"type":59,"value":173},"Choose a larger node configuration (more RAM, CPU, or both)",{"type":53,"tag":72,"props":175,"children":176},{},[177],{"type":59,"value":178},"The upgrade process involves a rolling restart with no downtime if replication is configured",{"type":53,"tag":72,"props":180,"children":181},{},[182,184,191],{"type":59,"value":183},"Ensure ",{"type":53,"tag":185,"props":186,"children":188},"code",{"className":187},[],[189],{"type":59,"value":190},"replication_factor: 2",{"type":59,"value":192}," or higher before resizing to maintain availability during the rolling restart",{"type":53,"tag":62,"props":194,"children":195},{},[196,202],{"type":53,"tag":197,"props":198,"children":199},"strong",{},[200],{"type":59,"value":201},"Important:",{"type":59,"value":203}," Scaling up is straightforward. Scaling down requires care -- if the working set no longer fits in RAM after downsizing, performance will degrade severely due to cache eviction. Always load test before scaling down.",{"type":53,"tag":92,"props":205,"children":207},{"id":206},"ram-sizing-guidelines",[208],{"type":59,"value":209},"RAM Sizing Guidelines",{"type":53,"tag":62,"props":211,"children":212},{},[213],{"type":59,"value":214},"RAM is the most critical resource for Qdrant performance. Use these guidelines to right-size.",{"type":53,"tag":68,"props":216,"children":217},{},[218,231,243,255,260,265],{"type":53,"tag":72,"props":219,"children":220},{},[221,223,229],{"type":59,"value":222},"Exact estimation of RAM usage is difficult; use this simple approximate formula: ",{"type":53,"tag":185,"props":224,"children":226},{"className":225},[],[227],{"type":59,"value":228},"num_vectors * dimensions * 4 bytes * 1.5",{"type":59,"value":230}," for full-precision vectors in RAM",{"type":53,"tag":72,"props":232,"children":233},{},[234,236],{"type":59,"value":235},"With scalar quantization: divide by 4 (INT8 reduces each float32 to 1 byte) ",{"type":53,"tag":78,"props":237,"children":240},{"href":238,"rel":239},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F",[82],[241],{"type":59,"value":242},"Quantization",{"type":53,"tag":72,"props":244,"children":245},{},[246,248],{"type":59,"value":247},"With binary quantization: divide by 32 ",{"type":53,"tag":78,"props":249,"children":252},{"href":250,"rel":251},"https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Fquantization\u002F?s=binary-quantization",[82],[253],{"type":59,"value":254},"Binary quantization",{"type":53,"tag":72,"props":256,"children":257},{},[258],{"type":59,"value":259},"Add overhead for HNSW index (~20-30% of vector data), payload indexes, and WAL",{"type":53,"tag":72,"props":261,"children":262},{},[263],{"type":59,"value":264},"Reserve 20% headroom for optimizer operations and OS cache",{"type":53,"tag":72,"props":266,"children":267},{},[268,270],{"type":59,"value":269},"Monitor actual usage via Grafana\u002FPrometheus before and after resizing ",{"type":53,"tag":78,"props":271,"children":273},{"href":272},"..\u002F..\u002F..\u002Fqdrant-monitoring\u002FSKILL.md",[274],{"type":59,"value":275},"Monitoring",{"type":53,"tag":92,"props":277,"children":279},{"id":278},"when-vertical-scaling-is-no-longer-enough",[280],{"type":59,"value":281},"When Vertical Scaling Is No Longer Enough",{"type":53,"tag":62,"props":283,"children":284},{},[285],{"type":59,"value":286},"Recognize these signals that it's time to go horizontal:",{"type":53,"tag":68,"props":288,"children":289},{},[290,295,300,305,310,315],{"type":53,"tag":72,"props":291,"children":292},{},[293],{"type":59,"value":294},"Data volume exceeds what a single node can hold even with quantization and mmap",{"type":53,"tag":72,"props":296,"children":297},{},[298],{"type":59,"value":299},"IOPS are saturated (more nodes = more independent disk I\u002FO)",{"type":53,"tag":72,"props":301,"children":302},{},[303],{"type":59,"value":304},"Need fault tolerance (requires replication across nodes)",{"type":53,"tag":72,"props":306,"children":307},{},[308],{"type":59,"value":309},"Need tenant isolation via dedicated shards",{"type":53,"tag":72,"props":311,"children":312},{},[313],{"type":59,"value":314},"Single-node CPU is maxed and query latency is unacceptable",{"type":53,"tag":72,"props":316,"children":317},{},[318],{"type":59,"value":319},"Next vertical scaling step is the largest available node size. You might need to be able to temporarily scale up to the larger node size to do batch operations or recovery. If you are already at the largest node size, you won't be able to do that.",{"type":53,"tag":62,"props":321,"children":322},{},[323,325,331],{"type":59,"value":324},"When you hit these limits, see ",{"type":53,"tag":78,"props":326,"children":328},{"href":327},"..\u002Fhorizontal-scaling\u002FSKILL.md",[329],{"type":59,"value":330},"Horizontal Scaling",{"type":59,"value":332}," for guidance on sharding and node planning.",{"type":53,"tag":92,"props":334,"children":336},{"id":335},"what-not-to-do",[337],{"type":59,"value":338},"What NOT to Do",{"type":53,"tag":68,"props":340,"children":341},{},[342,347,352,357,362],{"type":53,"tag":72,"props":343,"children":344},{},[345],{"type":59,"value":346},"Do not scale down RAM without load testing first (cache eviction = severe latency degradation that can last days)",{"type":53,"tag":72,"props":348,"children":349},{},[350],{"type":59,"value":351},"Do not ignore the 80% RAM threshold (performance cliff, not gradual degradation)",{"type":53,"tag":72,"props":353,"children":354},{},[355],{"type":59,"value":356},"Do not skip replication before resizing in Cloud (rolling restart without replicas = downtime)",{"type":53,"tag":72,"props":358,"children":359},{},[360],{"type":59,"value":361},"Do not jump to horizontal scaling before exhausting vertical options (adds permanent operational complexity)",{"type":53,"tag":72,"props":363,"children":364},{},[365],{"type":59,"value":366},"Do not assume more CPU always helps (IOPS-bound workloads won't improve with more cores)",{"items":368,"total":470},[369,381,399,415,429,444,458],{"slug":370,"name":370,"fn":371,"description":372,"org":373,"tags":374,"stars":28,"repoUrl":29,"updatedAt":380},"qdrant-horizontal-scaling","guide Qdrant horizontal scaling decisions","Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[375,376,377,378,379],{"name":26,"slug":27,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:16.349561",{"slug":382,"name":382,"fn":383,"description":384,"org":385,"tags":386,"stars":28,"repoUrl":29,"updatedAt":398},"qdrant-indexing-performance-optimization","optimize Qdrant indexing performance","Diagnoses and fixes slow Qdrant indexing and data ingestion. Use when someone reports 'uploads are slow', 'indexing takes forever', 'optimizer is stuck', 'HNSW build time too long', or 'data uploaded but search is bad'. Also use when optimizer status shows errors, segments won't merge, or indexing threshold questions arise.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[387,390,391,394,397],{"name":388,"slug":389,"type":15},"Data Engineering","data-engineering",{"name":20,"slug":21,"type":15},{"name":392,"slug":393,"type":15},"ETL","etl",{"name":395,"slug":396,"type":15},"Performance","performance",{"name":17,"slug":18,"type":15},"2026-04-18T04:46:02.766357",{"slug":400,"name":400,"fn":401,"description":402,"org":403,"tags":404,"stars":28,"repoUrl":29,"updatedAt":414},"qdrant-memory-usage-optimization","optimize Qdrant memory usage","Diagnoses and reduces Qdrant memory usage. Use when someone reports 'memory too high', 'RAM keeps growing', 'node crashed', 'out of memory', 'memory leak', or asks 'why is memory usage so high?', 'how to reduce RAM?'. Also use when memory doesn't match calculations, quantization didn't help, or nodes crash during recovery.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[405,408,409,412,413],{"name":406,"slug":407,"type":15},"Cost Optimization","cost-optimization",{"name":20,"slug":21,"type":15},{"name":410,"slug":411,"type":15},"Observability","observability",{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:01.525023",{"slug":416,"name":416,"fn":417,"description":418,"org":419,"tags":420,"stars":28,"repoUrl":29,"updatedAt":428},"qdrant-minimize-latency","minimize Qdrant query latency","Guides Qdrant query latency optimization. Use when someone asks 'search is slow', 'how to reduce latency', 'p99 is too high', 'tail latency', 'single query too slow', 'how to make search faster', or 'latency spikes'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[421,422,423,424,425],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},"Search","search","2026-04-18T04:46:10.126667",{"slug":430,"name":430,"fn":431,"description":432,"org":433,"tags":434,"stars":28,"repoUrl":29,"updatedAt":443},"qdrant-monitoring-debugging","debug Qdrant production issues with metrics","Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[435,438,440,441,442],{"name":436,"slug":437,"type":15},"Debugging","debugging",{"name":275,"slug":439,"type":15},"monitoring",{"name":410,"slug":411,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:06.450784",{"slug":445,"name":445,"fn":446,"description":447,"org":448,"tags":449,"stars":28,"repoUrl":29,"updatedAt":457},"qdrant-monitoring-setup","set up Qdrant monitoring and alerting","Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up monitoring', 'Prometheus config', 'Grafana dashboard', 'health check endpoints', 'how to scrape Hybrid Cloud', 'what alerts to set', 'how to centralize logs', or 'audit logging'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[450,451,452,453,454],{"name":26,"slug":27,"type":15},{"name":275,"slug":439,"type":15},{"name":410,"slug":411,"type":15},{"name":17,"slug":18,"type":15},{"name":455,"slug":456,"type":15},"SRE","sre","2026-04-18T04:46:05.217192",{"slug":459,"name":459,"fn":460,"description":461,"org":462,"tags":463,"stars":28,"repoUrl":29,"updatedAt":469},"qdrant-scaling-data-volume","scale Qdrant data volume","Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[464,465,466,467,468],{"name":26,"slug":27,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:07.684464",15,{"items":472,"total":593},[473,481,489,497,505,513,521,529,541,553,569,581],{"slug":370,"name":370,"fn":371,"description":372,"org":474,"tags":475,"stars":28,"repoUrl":29,"updatedAt":380},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[476,477,478,479,480],{"name":26,"slug":27,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"slug":382,"name":382,"fn":383,"description":384,"org":482,"tags":483,"stars":28,"repoUrl":29,"updatedAt":398},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[484,485,486,487,488],{"name":388,"slug":389,"type":15},{"name":20,"slug":21,"type":15},{"name":392,"slug":393,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"slug":400,"name":400,"fn":401,"description":402,"org":490,"tags":491,"stars":28,"repoUrl":29,"updatedAt":414},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[492,493,494,495,496],{"name":406,"slug":407,"type":15},{"name":20,"slug":21,"type":15},{"name":410,"slug":411,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"slug":416,"name":416,"fn":417,"description":418,"org":498,"tags":499,"stars":28,"repoUrl":29,"updatedAt":428},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[500,501,502,503,504],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},{"slug":430,"name":430,"fn":431,"description":432,"org":506,"tags":507,"stars":28,"repoUrl":29,"updatedAt":443},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[508,509,510,511,512],{"name":436,"slug":437,"type":15},{"name":275,"slug":439,"type":15},{"name":410,"slug":411,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"slug":445,"name":445,"fn":446,"description":447,"org":514,"tags":515,"stars":28,"repoUrl":29,"updatedAt":457},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[516,517,518,519,520],{"name":26,"slug":27,"type":15},{"name":275,"slug":439,"type":15},{"name":410,"slug":411,"type":15},{"name":17,"slug":18,"type":15},{"name":455,"slug":456,"type":15},{"slug":459,"name":459,"fn":460,"description":461,"org":522,"tags":523,"stars":28,"repoUrl":29,"updatedAt":469},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[524,525,526,527,528],{"name":26,"slug":27,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"slug":530,"name":530,"fn":531,"description":532,"org":533,"tags":534,"stars":28,"repoUrl":29,"updatedAt":540},"qdrant-scaling-qps","scale Qdrant query throughput","Guides Qdrant query throughput (QPS) scaling. Use when someone asks 'how to increase QPS', 'need more throughput', 'queries per second too low', 'batch search', 'read replicas', or 'how to handle more concurrent queries'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[535,536,537,538,539],{"name":26,"slug":27,"type":15},{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},"2026-04-18T04:46:08.905219",{"slug":542,"name":542,"fn":543,"description":544,"org":545,"tags":546,"stars":28,"repoUrl":29,"updatedAt":552},"qdrant-scaling-query-volume","scale Qdrant query volume and pagination","Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[547,548,549,550,551],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},"2026-04-18T04:46:11.371326",{"slug":554,"name":554,"fn":555,"description":556,"org":557,"tags":558,"stars":28,"repoUrl":29,"updatedAt":568},"qdrant-search-quality-diagnosis","diagnose Qdrant search quality issues","Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', or 'quality dropped after quantization'. Also use when search quality degrades without obvious changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[559,562,565,566,567],{"name":560,"slug":561,"type":15},"Analytics","analytics",{"name":563,"slug":564,"type":15},"Data Quality","data-quality",{"name":436,"slug":437,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},"2026-04-18T04:46:17.579894",{"slug":570,"name":570,"fn":571,"description":572,"org":573,"tags":574,"stars":28,"repoUrl":29,"updatedAt":580},"qdrant-search-speed-optimization","optimize Qdrant search speed","Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[575,576,577,578,579],{"name":560,"slug":561,"type":15},{"name":20,"slug":21,"type":15},{"name":395,"slug":396,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},"2026-04-18T04:46:03.987332",{"slug":582,"name":582,"fn":583,"description":584,"org":585,"tags":586,"stars":28,"repoUrl":29,"updatedAt":592},"qdrant-search-strategies","select optimal Qdrant search strategies","Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'BM25 or sparse vectors?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback', 'recommendation API', 'discovery API', 'ColBERT reranking', or 'missing keyword matches'",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[587,588,589,590,591],{"name":26,"slug":27,"type":15},{"name":560,"slug":561,"type":15},{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":426,"slug":427,"type":15},"2026-04-18T04:46:18.812306",45]