Search results for prometheus

trickster-1.09-1.lbn25.x86_64

Trickster is a reverse proxy cache for the Prometheus HTTP APIv1 that dramatically accelerates dashboard rendering times for any series queried from Prometheus.

prometheus-node-exporter-0.18.0-0.lbn25.x86_64

Prometheus exporter for machine metrics, written in Go with pluggable metric collectors. Collectors There is varying support for collectors on each operating system. The tables below list all existing collectors and the supported systems. Which collectors are used is controlled by the --collectors.enabled flag. Enabled by default Name Description OS conntrack Shows conntrack statistics (does nothing if no /proc/sys/net/netfilter/ present). Linux cpu Exposes CPU statistics FreeBSD diskstats Exposes disk I/O statistics from /proc/diskstats. Linux entropy Exposes available entropy. Linux filefd Exposes file descriptor statistics from /proc/sys/fs/file-nr. Linux filesystem Exposes filesystem statistics, such as disk space used. FreeBSD, Dragonfly, Linux, OpenBSD loadavg Exposes load average. Darwin, Dragonfly, FreeBSD, Linux, NetBSD, OpenBSD, Solaris mdadm Exposes statistics about devices in /proc/mdstat (does nothing if no /proc/mdstat present). Linux meminfo Exposes memory statistics. Dragonfly, FreeBSD, Linux netdev Exposes network interface statistics such as bytes transferred. Dragonfly, FreeBSD, Linux, OpenBSD netstat Exposes network statistics from /proc/net/netstat. This is the same information as netstat -s. Linux stat Exposes various statistics from /proc/stat. This includes CPU usage, boot time, forks and interrupts. Linux textfile Exposes statistics read from local disk. The --collector.textfile.directory flag must be set. any time Exposes the current system time. any vmstat Exposes statistics from /proc/vmstat. Linux Disabled by default Name Description OS bonding Exposes the number of configured and active slaves of Linux bonding interfaces. Linux devstat Exposes device statistics FreeBSD gmond Exposes statistics from Ganglia. any interrupts Exposes detailed interrupts statistics. Linux, OpenBSD ipvs Exposes IPVS status from /proc/net/ip_vs and stats from /proc/net/ip_vs_stats. Linux ksmd Exposes kernel and system statistics from /sys/kernel/mm/ksm. Linux logind Exposes session counts from logind. Linux megacli Exposes RAID statistics from MegaCLI. Linux meminfo_numa Exposes memory statistics from /proc/meminfo_numa. Linux ntp Exposes time drift from an NTP server. any runit Exposes service status from runit. any supervisord Exposes service status from supervisord. any systemd Exposes service and system status from systemd. Linux tcpstat Exposes TCP connection status information from /proc/net/tcp and /proc/net/tcp6. (Warning: the current version has potential performance issues in high load situations.) Linux Textfile Collector The textfile collector is similar to the Pushgateway, in that it allows exporting of statistics from batch jobs. It can also be used to export static metrics, such as what role a machine has. The Pushgateway should be used for service-level metrics. The textfile module is for metrics that are tied to a machine. To use it, set the --collector.textfile.directory flag on the Node exporter. The collector will parse all files in that directory matching the glob *.prom using the text format.

prometheus-alertmanager-0.19.0-5.git7aa5d19.lbn25.x86_64

The Alertmanager handles alerts sent by client applications such as the Prometheus server. It takes care of deduplicating, grouping, and routing them to the correct receiver integration such as email, PagerDuty, or OpsGenie. It also takes care of silencing and inhibition of alerts.

prometheus-2.14.0-1.lbn25.x86_64

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

BastionLinux/Grafana manual page

grafana-tempo-2.7.0-0.1.gitb0da6b4.lbn36.x86_64

Grafana Tempo is an open source, easy-to-use and high-scale distributed tracing backend. Tempo is cost-efficient, requiring only object storage to operate, and is deeply integrated with Grafana, Prometheus, and Loki. Tempo can be used with any of the open source tracing protocols, including Jaeger, Zipkin, OpenCensus, Kafka, and OpenTelemetry. It supports key/value lookup only and is designed to work in concert with logs and metrics (exemplars) for discovery. Tempo is Jaeger, Zipkin, Kafka, OpenCensus and OpenTelemetry compatible. It ingests batches in any of the mentioned formats, buffers them and then writes them to Azure, GCS, S3 or local disk. As such it is robust, cheap and easy to operate!

grafana-mimir-2.15.0-0.1.git24e4281.lbn36.x86_64

Grafana Mimir is an open source software project that provides a scalable long-term storage for Prometheus. Some of the core strengths of Grafana Mimir include: Easy to install and maintain: Grafana Mimir’s extensive documentation, tutorials, and deployment tooling make it quick to get started. Using its monolithic mode, you can get Grafana Mimir up and running with just one binary and no additional dependencies. Once deployed, the best-practice dashboards, alerts, and playbooks packaged with Grafana Mimir make it easy to monitor the health of the system. Massive scalability: You can run Grafana Mimir's horizontally-scalable architecture across multiple machines, resulting in the ability to process orders of magnitude more time series than a single Prometheus instance. Internal testing shows that Grafana Mimir handles up to 1 billion active time series. Global view of metrics: Grafana Mimir enables you to run queries that aggregate series from multiple Prometheus instances, giving you a global view of your systems. Its query engine extensively parallelizes query execution, so that even the highest-cardinality queries complete with blazing speed. Cheap, durable metric storage: Grafana Mimir uses object storage for long-term data storage, allowing it to take advantage of this ubiquitous, cost-effective, high-durability technology. It is compatible with multiple object store implementations, including AWS S3, Google Cloud Storage, Azure Blob Storage, OpenStack Swift, as well as any S3-compatible object storage. High availability: Grafana Mimir replicates incoming metrics, ensuring that no data is lost in the event of machine failure. Its horizontally scalable architecture also means that it can be restarted, upgraded, or downgraded with zero downtime, which means no interruptions to metrics ingestion or querying. Natively multi-tenant: Grafana Mimir’s multi-tenant architecture enables you to isolate data and queries from independent teams or business units, making it possible for these groups to share the same cluster. Advanced limits and quality-of-service controls ensure that capacity is shared fairly among tenants.

grafana-loki-3.5.0-0.1.git4b16bc4.lbn36.x86_64

Loki: like Prometheus, but for logs. Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate. It does not index the contents of the logs, but rather a set of labels for each log stream. Compared to other log aggregation systems, Loki: does not do full text indexing on logs. By storing compressed, unstructured logs and only indexing metadata, Loki is simpler to operate and cheaper to run. indexes and groups log streams using the same labels you’re already using with Prometheus, enabling you to seamlessly switch between metrics and logs using the same labels that you’re already using with Prometheus. is an especially good fit for storing Kubernetes Pod logs. Metadata such as Pod labels is automatically scraped and indexed. has native support in Grafana (needs Grafana v6.0). A Loki-based logging stack consists of 3 components: promtail is the agent, responsible for gathering logs and sending them to Loki. loki is the main server, responsible for storing logs and processing queries. Grafana for querying and displaying the logs. Loki is like Prometheus, but for logs: we prefer a multidimensional label-based approach to indexing, and want a single-binary, easy to operate system with no dependencies. Loki differs from Prometheus by focusing on logs instead of metrics, and delivering logs via push, instead of pull.

python3-prometheus_client-0.13.1-1.fc36.noarch

Python client for Prometheus.

python3-django-prometheus-2.3.1-1.lbn36.noarch

Django middlewares to monitor your application with Prometheus.io. Python 3 version.