With 20,500+ GitHub stars and over 6,000 organizations running it in production — including a Fortune 100 company ingesting more than 4 PB per day — OpenObserve is the open-source observability platform that replaces your entire Datadog, Splunk, or ELK stack with a single Rust binary deploying in under two minutes. Apache Parquet columnar storage with zstd compression on S3-compatible object storage delivers 140x lower storage costs than Elasticsearch while providing better query performance on a quarter of the hardware. Ingest logs, metrics, and distributed traces via native OpenTelemetry OTLP endpoints with no vendor lock-in. Query logs and traces with standard SQL, metrics with SQL or PromQL — no proprietary query language to learn. The built-in dashboard builder offers 19 chart types including time-series graphs, heatmaps, gauges, tables, and top-K lists with drag-and-drop layout combining data from all signal types. Data pipelines process, enrich, redact, or normalize ingestion streams using Vector Remap Language for real-time transformations including PII redaction and logs-to-metrics conversion. Real User Monitoring captures frontend performance with session replay. The Service Catalog provides topology-based trace analysis with side-panel drill-downs into database queries and error details. Alerting supports real-time and scheduled rules with SQL and PromQL conditions. Native multi-tenancy isolates organizations and streams with complete data separation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Small server, small monitoring. Statlite watches your applications and their host with a single binary that idles at about 15 MiB, so the observer never becomes the heaviest thing on the box. Point it at a Spring Boot Actuator endpoint and it polls health plus a fixed, curated set of Micrometer metrics: request traffic, latency, CPU, and runtime memory, all drawn as clean charts. Quarkus, Micronaut, and anything else that can answer a fixed JSON metrics profile can join the same dashboard. History lives in one local SQLite file, raw samples only, kept for 90 days by default, so yesterday's latency spike is still there when you go looking. The dashboard also watches the host itself: processor load, memory pressure, and filesystem capacity, including a warning before the metrics database fills its own disk. Restart detection tells you when an application bounced, and per-target Basic Auth support lets you poll protected Actuator endpoints safely. Configuration is one YAML file listing your targets and polling interval, friendly to systemd and Docker alike. Everything is deliberately scoped: no alert manager, no external service, no observability platform to operate. Just open the page and see whether your apps are healthy. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

OpenSearch is a search and analytics platforms, powering full-text search, log analytics, observability, and AI-powered vector retrieval at petabyte scale. The distributed engine provides BM25 full-text search alongside k-NN vector search using NMSLIB, Faiss, and Lucene libraries, enabling semantic search, hybrid search combining keyword and vector scoring through normalization processors, neural sparse search, and retrieval-augmented generation workflows with built-in ML Commons for model hosting. OpenSearch Dashboards delivers interactive visualization with Discover for log exploration, custom dashboards, alerting, anomaly detection using Random Cut Forest algorithms, and Security Analytics with detection rules mapped to MITRE ATT&CK. Native Prometheus integration with full PromQL support unifies metrics alongside logs and traces in a single observability interface, while Data Prepper handles telemetry ingestion from OpenTelemetry collectors, Fluent Bit, and Logstash-compatible pipelines. SQL and Piped Processing Language queries with a visual PPL builder enable analysts to query data without learning the native DSL. Index State Management automates index lifecycle with rollover, shrink, and delete policies, while cross-cluster replication and searchable snapshots on S3-compatible storage provide disaster recovery. Scoped API keys, field-level security, document-level security, and audit logging deliver enterprise-grade access control. Docker Compose deploys multi-node clusters alongside the Kubernetes operator for orchestrated production environments. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Trusted by millions of engineers and deployed on over 80,000 GitHub stars worth of community confidence, Netdata delivers true real-time monitoring at per-second granularity — 10-60x faster than Prometheus, Datadog, or any conventional monitoring stack that averages away the transient anomalies lasting 2-10 seconds where most production incidents originate. A single installation command deploys the agent with zero configuration, automatically discovering every running process, container, systemd service, network connection, disk, and application on the host within seconds. Unsupervised machine learning trains multiple models per metric directly at the edge, detecting anomalies without thresholds, baselines, or manual tuning. The distributed Parent-Child architecture scales horizontally from a single Raspberry Pi to fleets exceeding 100,000 nodes while maintaining sub-2-second visualization latency and storing metrics at approximately 0.5 bytes per sample through tiered compression. Native network monitoring provides live topology maps, NetFlow and sFlow analytics, SNMP device polling across 200+ profiles, and trap handling — capabilities that typically require a separate NPM product. Hundreds of pre-configured alerts cover systems and applications out of the box, with AI-powered root cause analysis surfacing correlated metrics through natural language via MCP-compatible AI assistants. The agent supports Linux, macOS, FreeBSD, Kubernetes, and Docker with eBPF-based kernel observability requiring no application instrumentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL v3+ licensed.

Trusted by thousands of organizations processing billions of time series data points and backed by 17,000+ GitHub stars, VictoriaMetrics delivers a monitoring and time series database that outperforms Prometheus by 16x on query speed while consuming 2.5x less disk space through its optimized compression and storage engine. The architecture supports both single-node deployments handling 10M+ active time series and a horizontally scalable cluster version with vminsert, vmstorage, and vmselect components providing multi-tenancy, replication, and independent namespace isolation. Data ingestion accepts both push protocols including InfluxDB line protocol, Graphite plaintext, OpenTSDB HTTP, CSV, and OpenTelemetry OTLP alongside pull-based Prometheus scraping and remote write, enabling drop-in replacement of existing monitoring stacks without reconfiguring exporters. MetricsQL extends standard PromQL with additional functions, subqueries, and implicit time range alignment while maintaining full backward compatibility with existing Prometheus alerts and Grafana dashboards. The vmalert component processes recording and alerting rules with Alertmanager integration, while vmbackup and vmrestore enable point-in-time snapshots to S3, GCS, and Azure Blob Storage. Stream aggregation operates as a StatsD alternative for pre-aggregating high-cardinality metrics before storage. NFS-compatible storage backends including Amazon EFS and Google Filestore allow shared persistent volumes across cluster nodes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Backed by 44,000 GitHub stars and trusted by over four million developers, Sentry is the debugging platform that captures errors, traces, replays, profiles, and metrics from your applications and connects them all through distributed tracing. The error tracking engine captures full stack traces with source context, breadcrumbs, and automatic demangling for native crashes, while intelligent grouping consolidates duplicate events into actionable issues with regression detection and automatic assignment. Performance monitoring instruments your frameworks automatically, capturing every database query, API call, cache hit, and queue operation as spans within distributed traces that flow across frontend, backend, and mobile boundaries. Session Replay produces video-like recordings of real user sessions showing DOM interactions, network requests, console messages, and errors on a synchronized timeline, with AI-powered summaries that describe what happened without watching the full replay. Continuous profiling captures CPU execution data at the function and line level for Node.js, Python, iOS, and Android, linking slow spans directly to the exact code responsible. Cron monitoring tracks scheduled jobs for failures, missed runs, and duration anomalies. The alerting engine fires notifications through Slack, PagerDuty, Opsgenie, and webhooks on new issues, regressions, error spikes, or when latency and crash-free session rate thresholds are crossed. Self-hosted deployment runs as a Docker Compose stack with PostgreSQL, ClickHouse, Kafka, Redis, and Relay. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. FSL licensed.

With 4,500+ GitHub stars and version 1.0.92 released August 2026, xyOps delivers a complete operations platform that unifies workflow automation, job scheduling, server monitoring, alerting, and incident response in one self-hosted system. The platform uses a distributed architecture where a central conductor coordinates lightweight xySat satellite agents running on Linux, macOS, or Windows worker nodes via persistent WebSocket connections. The visual workflow builder lets you chain events, triggers, actions, and monitors into multi-step pipelines with conditional logic, fan-out/fan-in parallelism, multiplex controllers for fleet-wide execution, and configurable resource limits. QuickMon provides per-second CPU, memory, disk, and network visibility streamed live to the web UI, while user-defined monitor plugins sample metrics every minute with time-series storage at hourly, daily, monthly, and yearly resolutions. Alert triggers evaluate expressions against live data and fire notifications via email, webhook, or custom actions, with full server snapshots attached showing every running process, network connection, and resource utilization at the moment of detection. Failed jobs and alerts automatically create tickets with linked logs, metrics history, and context for end-to-end incident tracking. The plugin marketplace supports extensions written in any language, and the Docker plugin enables container-based job execution. Deploy via Docker with persistent volumes on port 5522 for the web UI and 5523 for API access, running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

Powering trading floors at firms processing millions of market data events per second and trusted by organizations including Airbus, Yahoo, and Copenhagen Atomics, QuestDB has earned over 17,000 GitHub stars as the time-series database that refuses to make you choose between ingestion speed and query latency. The column-oriented, time-partitioned storage engine processes millions of rows per second on ingest through write-ahead logging with instant durability, while SIMD-accelerated parallel execution returns analytical queries over billions of rows in milliseconds. Time-series SQL extensions add ASOF JOIN for point-in-time lookups across tables with misaligned timestamps, SAMPLE BY for downsampling at arbitrary time intervals, LATEST ON for last-value queries, and WINDOW JOIN for sliding window aggregations — all through standard SQL syntax accessible via the PostgreSQL wire protocol, REST API, or the QuestDB Wire Protocol (QWP) that streams Apache Arrow at 220 million rows per second. Multi-tier storage automatically moves data from the WAL through native columnar format to Parquet files on S3-compatible object storage, keeping hot data fast and cold data portable without manual tiering. The built-in web console provides an interactive SQL editor with syntax highlighting, autocomplete, and charting for quick data exploration. Views, materialized views, and n-dimensional arrays support real-time analytics, while native Parquet export enables direct integration with Python, DuckDB, and AI/ML frameworks. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

With 7,400+ GitHub stars and a feature set that replaces seven separate SaaS subscriptions — Pingdom for monitoring, StatusPage.io for status pages, PagerDuty for on-call, Incident.io for incident management, Datadog for APM, Loggly for logs, and Sentry for error tracking — OneUptime delivers every tool your reliability team needs in a single open-source platform that is genuinely 100% open source under Apache 2.0 (not open-core). Uptime monitoring runs synthetic checks against websites, APIs, ports, SSL certificates, and DNS records from distributed global probes with configurable intervals and thresholds. Branded status pages publish automatically when monitors detect issues, notifying subscribers via email, SMS, webhook, or RSS without manual intervention during an outage. On-call scheduling routes alerts through escalation policies to the right engineer via phone call, SMS, push notification, Slack, or Microsoft Teams. The incident management workflow handles declaration, triage, communication, resolution, and post-mortem generation in a unified timeline. APM collects traces and metrics via native OpenTelemetry integration — no proprietary agents required — while log management provides full-text search and alerting. An AI agent continuously monitors telemetry data, identifies root causes, and opens GitHub pull requests with proposed fixes for review. Deploy via Docker Compose or Kubernetes Helm charts with a Terraform provider for infrastructure-as-code configuration. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Instead of running an Elasticsearch or Loki cluster, VictoriaLogs stores and searches your logs from a single zero-config server. Ship from Filebeat, Fluent Bit, Fluentd, Logstash, Vector, Promtail, Telegraf, the OpenTelemetry Collector, or the Datadog Agent. Syslog, journald, and Splunk endpoints work too. Query with LogsQL: word, phrase, and prefix filters combine with pipes that extract fields from raw lines and compute stats, top values, and facets. See results as a table, grouped by stream, as raw JSON, or as a live tail. Chart them in Grafana, or work from a terminal with vlogscli and pipe output into grep, less, or jq. Events with hundreds of fields are supported. So are high-cardinality fields like trace_id and user_id. Late, out-of-order backfills are accepted. During an incident, stream_context pulls the lines around any match. Tenants are keyed by AccountID and ProjectID headers. vmalert evaluates LogsQL queries as alerting and recording rules. CEF messages sent over Syslog are parsed automatically for SIEM work. Retention defaults to 7 days and can be capped by disk space. Per-day partitions snapshot and copy out with rsync or rclone. Cluster mode splits ingestion, querying, and storage across nodes for logs that outgrow one server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

A year of searchable logs and traces no longer needs a metered logging service, because Rootprint keeps the whole index in a storage bucket you already own. A search matches any word on any line, since every log is indexed in full and no service name, stream, or label is needed first. A frequency histogram, one-click field filters, and saved views narrow the results, a fold mode collapses repeated lines, and exports arrive as NDJSON, CSV, or plain text, or as a share link. Open a trace from the log that emitted it, or paste a trace ID, and a waterfall shows per-span timing, attributes, events, and database calls grouped by query, with each span linking back to its logs. The trace explorer charts span volume, error rate, and p50, p95, and p99 latency, ranks the busiest operations, and filters spans by service, duration, and status. Every service gets its own page with request rate, error rate, operations, dependencies, and errors. Data arrives over OpenTelemetry from the Collector, Vector, or Fluent Bit, through a plain HTTP gateway, or by pulling from Kafka, Kinesis, or SQS, with guided setup for nine integrations. Indexes can live in S3, Google Cloud Storage, R2, MinIO, or Azure Blob. Teammates sign in with Google, GitHub, or any OpenID Connect provider, and scoped API keys serve scripts. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

A flight recorder for production code, Parca profiles CPU and memory continuously and keeps the history to query after something breaks. A slow memory leak or a momentary CPU spike is already on record by the time anyone looks. Point it at any service that exposes pprof endpoints, or deploy the eBPF-based Parca Agent to profile every process on a Linux host or Kubernetes node without touching application code. The agent covers C, C++, Rust, Go, and more. In the web UI, pick a profile type such as on-CPU, narrow it with Prometheus-style label selectors, sum or group by any label, and click a point on the time series to open its flame graph. Switch the same query to a table, add extra panels, or try the alpha Flame Chart and Sandwich views. After a deploy, open the Compare page, set two queries side by side by label or time range, and the functions that gained or lost CPU time stand out as a diff. Native binaries are symbolized from uploaded debuginfo or upstream debuginfod servers. Recent releases add support for OpenTelemetry eBPF profiler profiles and GPU profile types. Optional persistence keeps history across restarts, and a Prometheus-style scrape configuration with service discovery decides what gets profiled. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

With over 31,000 GitHub stars and native OpenTelemetry support that eliminates vendor lock-in from day one, SigNoz delivers full-stack observability covering metrics, traces, and logs in a single pane of glass without the per-host pricing model of commercial APM platforms. The platform ingests telemetry data through the OpenTelemetry Collector, supporting auto-instrumentation for Java, Python, Node.js, Go, Ruby, PHP, and .NET applications with zero code changes required for basic tracing. ClickHouse serves as the columnar storage backend, providing fast aggregation queries over billions of spans and log lines with configurable retention policies and tiered storage. The distributed tracing view renders flame graphs and Gantt charts showing request flow across microservices with latency breakdowns, error rates, and p99 percentile calculations. Custom dashboards support PromQL and ClickHouse SQL queries with time-series charts, bar graphs, tables, and value widgets. The log management pipeline supports structured and unstructured logs with full-text search, log pipelines for parsing and enrichment, and correlation with traces via trace IDs. Alert rules can be configured on any metric or log query with notification channels including Slack, PagerDuty, OpsGenie, webhooks, and email. The exceptions monitoring module automatically groups and tracks application errors with stack traces, occurrence counts, and first-seen timestamps. Service maps visualize inter-service dependencies with real-time latency and error rate overlays. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed with an enterprise edition available.

Holding internet service providers accountable for promised bandwidth requires continuous, automated measurement, and MySpeed turns any server into an always-on connection performance analyzer that tracks download speeds, upload throughput, ping latency, and jitter around the clock. Instead of running manual browser tests only when video calls stutter, you can schedule recurring speed checks using custom Cron expressions and switch freely between Ookla, LibreSpeed, and Cloudflare testing servers to verify routing performance across different upstream networks. Interactive statistics views render gradient speed timelines, ping and jitter graphs, hourly performance breakdowns that expose peak-hour congestion, and standard deviation consistency charts, using smart 300-bucket downsampling so multi-month histories load instantaneously. Failed tests are flagged with visual markers on the timeline, while built-in health checks dispatch instant alerts to Discord, Telegram, Signal, WhatsApp, Gotify, email, or custom webhooks whenever bandwidth drops below your target thresholds or outages occur. Administrators can link multiple remote MySpeed instances into a single dashboard to compare bandwidth across branch offices, pause scheduled runs during heavy file transfers, export historical logs, and scrape real-time telemetry into Prometheus and Grafana. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

The de facto dashboard of observability: Grafana is the open-source frontend that turns the data stores you already run into interactive graphs. It does not store metrics itself; it connects to the data stores you already run and turns their contents into interactive dashboards. Supported sources number over 150 via plugins: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, PostgreSQL, Microsoft SQL Server, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring, and many more. Dashboards are built from a large library of panel types (time series, heatmaps, tables, gauges, logs) with template variables for reusable, parameterized views. Unified alerting evaluates rules against any connected data source, not just Prometheus, and routes notifications to Slack, PagerDuty, email, and other channels with grouping and silencing - unlike Prometheus Alertmanager, a single rule can combine a Loki log pattern, a PostgreSQL query result, and a CloudWatch metric. Dashboards serialize to JSON and data sources configure via provisioning files, so the entire observability setup can live in Git and deploy repeatably across environments. Explore mode adds ad-hoc querying outside dashboards, with split view for correlating a metric spike against the matching log lines, and access control spans organizations, teams, folder permissions, and OAuth, LDAP, and SAML integration. Written in Go and TypeScript, AGPL-licensed. Self-hosting gives you unlimited users, dashboards, and queries at flat hosting cost, without Grafana Cloud's usage-based pricing.

Keep users ahead of outages by consolidating infrastructure monitoring into Peekaping, a unified uptime monitoring and incident communication platform that alerts engineering teams to network and application failures before customers experience disruptions. Users can configure automated synthetic checks across HTTP endpoints, database engines, message queues, and container runtimes to verify response latency, payload integrity, and SSL certificate expiration. When performance thresholds degrade or connections drop, the platform broadcasts structured incident notices across twenty-two notification channels including Slack, Discord, Telegram, PagerDuty, and custom webhooks. Visual dashboards display live heartbeat timelines, historical latency percentiles, and rolling availability scores for each monitored endpoint. System administrators can assemble custom public status pages with custom domains, branded color schemes, and component grouping to inform external stakeholders during planned maintenance or unforeseen service degradations. Teams can schedule recurring maintenance windows to pause alert notifications during routine deployments and generate API tokens to automate monitor creation directly from CI/CD deployment pipelines. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Define a service level objective in a few lines of YAML and Pyrra writes the Prometheus recording rules and multi-window burn rate alerts for it, then tracks the remaining error budget in a web interface. An objective can be an error ratio or a latency target, declared as a Kubernetes custom resource or as a plain file read from disk when running under Docker or as binaries. Grouping labels fan one definition out into an objective per route or handler. The objectives page lists each SLO with its window, target, availability, and remaining budget, sorted so the worst offenders sit on top; columns can be sorted or hidden, and a search box or a click on any label filters the list. Opening an objective highlights availability and error budget, plots the budget over time, and charts requests, errors, and duration with a time range picker and absolute or relative scales. Below the charts, a table shows the four generated alerts with their severities. Generated alerts carry a link back to the objective's page, and severities can be overridden in the spec. Queries go to Prometheus, Thanos, or Mimir, with basic auth, bearer tokens, or tenant IDs, and ready-made Grafana dashboards chart the same objectives. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

GoAccess processes millions of web log entries in seconds and renders the results as interactive dashboards that update every 200 milliseconds in the terminal or every second via WebSocket-connected HTML reports. Written entirely in C with only ncurses as a dependency, it achieves exceptional performance even on resource-constrained servers, reducing memory usage by approximately 20% and parsing time by 35% in recent releases through optimized in-memory hash tables with on-disk persistence support. The analyzer parses virtually every web log format out of the box (Apache Combined and Common, Nginx, Amazon CloudFront, Amazon S3, AWS Elastic Load Balancing, Google Cloud Storage, Squid, W3C IIS, Caddy JSON, and Traefik) while supporting fully custom log format strings for non-standard configurations. The self-contained HTML dashboard displays 15+ interactive panels covering unique visitors, requested files, static files, 404 errors, referring sites, search keyphrases, geographic location with city-level GeoIP resolution, operating systems, browsers, HTTP status codes, time distribution, and virtual host metrics. WebSocket authentication via JWT provides secure remote access, and incremental log processing ensures data continuity across daemon restarts. Docker deployment requires a single command with volume-mapped access logs. Over 20,800 stars with active development since 2010. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.