So how can you reduce the memory usage of Prometheus? A query may be buggy in query.yaml\n VALUE = {{ $value }}\n LABELS, pg_replication_lag > 30 and ON(instance) pg_replication_is_replica ==, Postgresql replication lag (instance {{ $labels.instance }}), PostgreSQL replication lag is going up (> 30s)\n VALUE = {{ $value }}\n LABELS, time() - pg_stat_user_tables_last_autovacuum > 60 * 60 *, Postgresql table not vaccumed (instance {{ $labels.instance }}), Table has not been vaccum for 24 hours\n VALUE = {{ $value }}\n LABELS, time() - pg_stat_user_tables_last_autoanalyze > 60 * 60 *, Postgresql table not analyzed (instance {{ $labels.instance }}), Table has not been analyzed for 24 hours\n VALUE = {{ $value }}\n LABELS, sum by (datname) (pg_stat_activity_count{datname!~"template. Any assitance or nudge in the right direction would be much appreciated. Prometheus remote read and write API support. System Update. How to download and install the WMI exporterfor Windows servers; 3. Execute a Prometheus query. Now,my prometheus server manager the exporter of number more than 160,including node-exporter,cAdvisor and mongodb-exporter. Please see the dedicated guide to use Beamium.. It is a wrapper around the prometheus-exporter monitor that provides a restricted but expandable set of metrics. Today I want to tackle one apparently obvious thing, which is getting a graph (or numbers) of CPU utilization. and then click Import. The WMI exporter is an awesome exporter for Windows Servers. Prometheus has various metric types such as Counter, Gauge, Histogram and Summary. InfluxDB v2.0 is the latest stable version. It is this headless service which will be used by the Thanos Querier to query data across all Prometheus instances. Please check OSDs, change weight or reconfigure CRUSH rules.\n VALUE = {{ $value }}\n LABELS, Ceph PG unavailable (instance {{ $labels.instance }}), Some Ceph placement groups are unavailable.\n VALUE = {{ $value }}\n LABELS, SpeedTest Slow Internet Download (instance {{ $labels.instance }}), Internet download speed is currently {{humanize $value}} Mbps.\n VALUE = {{ $value }}\n LABELS, SpeedTest Slow Internet Upload (instance {{ $labels.instance }}), Internet upload speed is currently {{humanize $value}} Mbps.\n VALUE = {{ $value }}\n LABELS, OpenEBS used pool capacity (instance {{ $labels.instance }}), OpenEBS Pool use more than 80% of his capacity\n VALUE = {{ $value }}\n LABELS, Minio disk offline (instance {{ $labels.instance }}), Minio disk is offline\n VALUE = {{ $value }}\n LABELS, disk_storage_available / disk_storage_total * 100 <, Minio disk space usage (instance {{ $labels.instance }}), Minio available free space is low (< 10%)\n VALUE = {{ $value }}\n LABELS, SSL certificate probe failed (instance {{ $labels.instance }}), Failed to fetch SSL information {{ $labels.instance }}\n VALUE = {{ $value }}\n LABELS, SSL certificate OSCP status unknown (instance {{ $labels.instance }}), Failed to get the OSCP status {{ $labels.instance }}\n VALUE = {{ $value }}\n LABELS, SSL certificate revoked (instance {{ $labels.instance }}), SSL certificate revoked {{ $labels.instance }}\n VALUE = {{ $value }}\n LABELS, ssl_verified_cert_not_after{chain_no="0"} - time() < 86400 *, SSL certificate expiry (< 7 days) (instance {{ $labels.instance }}), Certificate is expiring in 7 days\n VALUE = {{ $value }}\n LABELS, Juniper switch down (instance {{ $labels.instance }}), The switch appears to be down\n VALUE = {{ $value }}\n LABELS, rate(junos_interface_transmit_bytes[1m]) * 8 > 1e+9 *, Juniper high Bandwith Usage 1GiB (instance {{ $labels.instance }}), Interface is highly saturated. It trickles down to selecting blocks according to the specified time range. As a quick explanation, this query provides a rate of the disk read operations over a period of 5 seconds, for my vda disk in megabytes per second. We are trying to calculate the storage requirements but is unable to find the values needed to do the calculation for our version of Prometheus (v2.2). Building an efficient and battle-tested monitoring platform takes time. This page documents an earlier version of InfluxDB. In which order does Windows Explorer sort folders when sorting the results of the search by size? (> 0.90GiB/s)\n VALUE = {{ $value }}\n LABELS, Interface is getting saturated. *"} >, Host Network Interface Saturated (instance {{ $labels.instance }}), The network interface "{{ $labels.interface }}" on "{{ $labels.instance }}" is getting overloaded.\n VALUE = {{ $value }}\n LABELS, node_nf_conntrack_entries / node_nf_conntrack_entries_limit >, Host conntrack limit (instance {{ $labels.instance }}), The number of conntrack is approching limit\n VALUE = {{ $value }}\n LABELS, (node_timex_offset_seconds > 0.05 and deriv(node_timex_offset_seconds[5m]) >= 0) or (node_timex_offset_seconds < -0.05 and deriv(node_timex_offset_seconds[5m]) <= 0), Host clock skew (instance {{ $labels.instance }}), Clock skew detected. We tried the following: This site suggest prometheus_local_storage_chunk_ops_total, but we do not have this metric. Prometheus stateful set is labelled as thanos-store-api: true so that each pod gets discovered by the headless service, which we will create next. It is a very powerful monitoring system suitable for dynamic environments. Prometheus 2 memory usage instead is configured by storage.tsdb.min-block-duration which determines how long samples will be stored in memory before they are flushed (the default being 2h). Prometheus is written in Go and supports Go/Java/Ruby/Python clients. We can predefine certain thresholds about which we want to get notified. https://metrics:[WRITE_TOKEN]@prometheus. #1.1.5. Prometheus is a native data store for Grafana, so configuration is very simple. Prometheus is using the pull-based approach to gather metrics. This may add significant jitter in replication delay. # Indicate the queue name in dedicated label. # Indicate the exchange name in dedicated label. Prometheus Query Result - Graphical . Prometheus web interface It indicates a slower storage backend access or too complex query.\n VALUE = {{ $value }}\n LABELS, min_over_time(prometheus_notifications_queue_length[10m]) >, Prometheus notifications backlog (instance {{ $labels.instance }}), The Prometheus notification queue has not been empty for 10 minutes\n VALUE = {{ $value }}\n LABELS, PrometheusAlertmanagerNotificationFailing, rate(alertmanager_notifications_failed_total[1m]) >, Prometheus AlertManager notification failing (instance {{ $labels.instance }}), Alertmanager is failing sending notifications\n VALUE = {{ $value }}\n LABELS, Prometheus target empty (instance {{ $labels.instance }}), Prometheus has no target in service discovery\n VALUE = {{ $value }}\n LABELS, prometheus_target_interval_length_seconds{quantile="0.9"} >, Prometheus target scraping slow (instance {{ $labels.instance }}), Prometheus is scraping exporters slowly\n VALUE = {{ $value }}\n LABELS, increase(prometheus_target_scrapes_exceeded_sample_limit_total[10m]) >, Prometheus large scrape (instance {{ $labels.instance }}), Prometheus has many scrapes that exceed the sample limit\n VALUE = {{ $value }}\n LABELS, increase(prometheus_target_scrapes_sample_duplicate_timestamp_total[5m]) >, Prometheus target scrape duplicate (instance {{ $labels.instance }}), Prometheus has many samples rejected due to duplicate timestamps but different values\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_checkpoint_creations_failed_total[1m]) >, Prometheus TSDB checkpoint creation failures (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} checkpoint creation failures\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_checkpoint_deletions_failed_total[1m]) >, Prometheus TSDB checkpoint deletion failures (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} checkpoint deletion failures\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_compactions_failed_total[1m]) >, Prometheus TSDB compactions failed (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} TSDB compactions failures\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_head_truncations_failed_total[1m]) >, Prometheus TSDB head truncations failed (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} TSDB head truncation failures\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_reloads_failures_total[1m]) >, Prometheus TSDB reload failures (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} TSDB reload failures\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_wal_corruptions_total[1m]) >, Prometheus TSDB WAL corruptions (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} TSDB WAL corruptions\n VALUE = {{ $value }}\n LABELS, increase(prometheus_tsdb_wal_truncations_failed_total[1m]) >, Prometheus TSDB WAL truncations failed (instance {{ $labels.instance }}), Prometheus encountered {{ $value }} TSDB WAL truncation failures\n VALUE = {{ $value }}\n LABELS, node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes * 100 <, Host out of memory (instance {{ $labels.instance }}), Node memory is filling up (< 10% left)\n VALUE = {{ $value }}\n LABELS, Host memory under memory pressure (instance {{ $labels.instance }}), The node is under heavy memory pressure. This may be due to a a server restart or an admin typing commands at the pgbouncer console.\n VALUE = {{ $value }}\n LABELS, increase(pgbouncer_errors_count{errmsg="no more connections allowed (max_client_conn)"}[30s]) >, PGBouncer max connections (instance {{ $labels.instance }}), The number of PGBouncer client connections has reached max_client_conn.\n VALUE = {{ $value }}\n LABELS, Redis down (instance {{ $labels.instance }}), Redis instance is down\n VALUE = {{ $value }}\n LABELS, (count(redis_instance_info{role="master"}) or vector(0)) <, Redis missing master (instance {{ $labels.instance }}), Redis cluster has no node marked as master.\n VALUE = {{ $value }}\n LABELS, count(redis_instance_info{role="master"}) >, Redis too many masters (instance {{ $labels.instance }}), Redis cluster has too many nodes marked as master.\n VALUE = {{ $value }}\n LABELS, count without (instance, job) (redis_connected_slaves) - sum without (instance, job) (redis_connected_slaves) - 1 >, Redis disconnected slaves (instance {{ $labels.instance }}), Redis not replicating for all slaves. Prometheus collects metrics in a standard format via a pull method over HTTP. Prometheus monitoring is quickly becoming the Docker and Kubernetes monitoring tool to use. Prometheus contains a user-defined multi-dimensional data model and a query language on multi-dimensional data called PromQL. vmauth. GitHub Gist: instantly share code, notes, and snippets. Asking for help, clarification, or responding to other answers. I think your math may be off. You can also see the query results graphically by selecting the Graph tab underneath the Execute button. Swarmprom is a starter kit for Docker Swarm monitoring with Prometheus, Grafana, cAdvisor, Node Exporter, Alert Manager, and Unsee. Viewed 929 times 0. , Prometheus job missing (instance {{ $labels.instance }}), A Prometheus job has disappeared\n VALUE = {{ $value }}\n LABELS, Prometheus target missing (instance {{ $labels.instance }}), A Prometheus target has disappeared. It is a very powerful monitoring system suitable for dynamic environments. Lower scrape interval results in higher ingestion rate and in higher RAM usage for Prometheus, since more data points must be kept in RAM before they are flushed to disk. IV – Installing the WMI Exporter. In this tutorial, we will explain how to install Prometheus on Ubuntu 18.04 server. Request throughput may be to high.\n VALUE = {{ $value }}\n LABELS, avg_over_time(((sum by (proxy) (haproxy_server_max_sessions)) / (sum by (proxy) (haproxy_server_limit_sessions))) [2m]) * 100 >, HAProxy backend max active session (instance {{ $labels.instance }}), HAproxy backend {{ $labels.fqdn }}/{{ $labels.backend }} is reaching session limit (> 80%).\n VALUE = {{ $value }}\n LABELS, sum by (proxy) (rate(haproxy_backend_current_queue[2m])) >, HAProxy pending requests (instance {{ $labels.instance }}), Some HAProxy requests are pending on {{ $labels.fqdn }}/{{ $labels.backend }} backend\n VALUE = {{ $value }}\n LABELS, avg by (proxy) (haproxy_backend_max_total_time_seconds) >, HAProxy HTTP slowing down (instance {{ $labels.instance }}), Average request time is increasing\n VALUE = {{ $value }}\n LABELS, sum by (proxy) (rate(haproxy_backend_retry_warnings_total[1m])) >, HAProxy retry high (instance {{ $labels.instance }}), High rate of retry on {{ $labels.fqdn }}/{{ $labels.backend }} backend\n VALUE = {{ $value }}\n LABELS, HAProxy proxy down (instance {{ $labels.instance }}), HAProxy proxy is down\n VALUE = {{ $value }}\n LABELS, HAProxy server down (instance {{ $labels.instance }}), HAProxy backend is down\n VALUE = {{ $value }}\n LABELS, sum by (proxy) (rate(haproxy_frontend_denied_connections_total[2m])) >, HAProxy frontend security blocked requests (instance {{ $labels.instance }}), HAProxy is blocking requests for security reason\n VALUE = {{ $value }}\n LABELS, increase(haproxy_server_check_failures_total[1m]) >, HAProxy server healthcheck failure (instance {{ $labels.instance }}), Some server healthcheck are failing on {{ $labels.server }}\n VALUE = {{ $value }}\n LABELS, HAProxy down (instance {{ $labels.instance }}), HAProxy down\n VALUE = {{ $value }}\n LABELS, sum by (backend) rate(haproxy_server_http_responses_total{code="4xx"}[1m]) / sum by (backend) rate(haproxy_server_http_responses_total[1m]) * 100 >, sum by (backend) rate(haproxy_server_http_responses_total{code="5xx"}[1m]) / sum by (backend) rate(haproxy_server_http_responses_total[1m]) * 100 >, sum by (server) rate(haproxy_server_http_responses_total{code="4xx"}[1m]) / sum by (backend) rate(haproxy_server_http_responses_total[1m]) * 100 >, sum by (server) rate(haproxy_server_http_responses_total{code="5xx"}[1m]) / sum by (backend) rate(haproxy_server_http_responses_total[1m]) * 100 >, sum by (server) rate(haproxy_server_response_errors_total[1m]) / sum by (server) rate(haproxy_server_http_responses_total[1m]) * 100 >, sum by (backend) rate(haproxy_backend_connection_errors_total[1m]) >, sum by (server) rate(haproxy_server_connection_errors_total[1m]) >, ((sum by (backend) (avg_over_time(haproxy_backend_max_sessions[2m])) / sum by (backend) (avg_over_time(haproxy_backend_limit_sessions[2m]))) * 100) >, sum by (backend) haproxy_backend_current_queue >, avg by (backend) (haproxy_backend_http_total_time_average_seconds) >, rate(sum by (backend) (haproxy_backend_retry_warnings_total)) >, HAProxy backend down (instance {{ $labels.instance }}), HAProxy server is down\n VALUE = {{ $value }}\n LABELS, rate(sum by (frontend) (haproxy_frontend_requests_denied_total)) >, increase(haproxy_server_check_failures_total) >, count(traefik_backend_server_up) by (backend) ==, Traefik backend down (instance {{ $labels.instance }}), All Traefik backends are down\n VALUE = {{ $value }}\n LABELS, sum(rate(traefik_backend_requests_total{code=~"4.

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