Monitoring

Uptime Kuma93.3k★

Uptime Kuma watches your websites, APIs, servers and containers and alerts you through Telegram, Discord, Slack, email or 90+ other services the moment one goes down. It's the self-hosted answer to UptimeRobot and Better Stack's uptime checks. MIT licensed, and there is no paid tier at all. Setup is one docker run with the louislam/uptime-kuma:2 image (the old latest tag is deprecated and stuck on v1). Add HTTP, TCP, ping, DNS or Docker monitors checked as often as every 20 seconds, and publish status pages on your own domain. Since 2.1 it can also run ping and HTTP checks through Globalping's community probes, so you're not limited to checking from one box. Solo and small teams: free. Bigger teams: still free, but 2.x has a single admin login with no roles. Multi-user is still an open request; the 3.0 auth rework is nightly-only. The catch: you own the patching. This year brought a template-injection bug that let a logged-in user read server files (the first fix was incomplete) and an unauthenticated denial of service fixed in 2.5.4. Upgrading from v1 is a one-way migration that can take hours. And if its server dies, your alerts die with it.

Netdata81.3k★

Netdata puts live server dashboards in front of you right after install: CPU, memory, disk, network and containers, updated every second. No weekend spent wiring up a monitoring stack first. It also ships hundreds of built-in alerts and machine-learning anomaly detection out of the box. The agent is GPLv3 and runs on Linux, macOS, FreeBSD, Windows, Docker and Kubernetes. It's light but not free: the README puts it at about 5% CPU and 150MiB of RAM per server by default, under 1% with ML and alerts turned off. Metrics stay on your own disk in tiers (per-second, per-minute, per-hour), so a few gigabytes holds more than a year of history. Netdata Cloud adds multi-server views, and your data still stays on your servers. Community is free for 5 nodes, and Homelab is $90 a year flat for unlimited nodes. Netdata labels both non-commercial. Business is $4.50/node/mo billed annually ($6 monthly) and carries SSO, RBAC and audit logs. Ten servers: $45/mo, against $150 on Datadog's Pro tier. Solo: the free agent. Teams: Business. The catch is the license line. Only the agent is open source. The dashboard UI and Cloud are closed-source, free to use but not yours to fork. prometheus/prometheus plus grafana/grafana is the fully open route.

Grafana77.7k★

Grafana turns data that lives somewhere else into dashboards and alerts. Prometheus, Loki, Postgres, CloudWatch: it queries each source where it sits, even several in one graph. Self-hosted Grafana OSS is AGPLv3 and free, with no user cap. Grafana itself is light: 512 MB of RAM and one CPU core minimum. The weight is underneath, because Grafana stores no telemetry. A real stack means running Prometheus or Mimir for metrics, Loki for logs and Tempo for traces, each with its own sizing guide. Patch often: October 27 brought four security fixes, one a high-severity SSO bypass. Grafana Cloud's free tier gives 10k metric series, 50 GB each of logs, traces and profiles, and 3 active users, all at 14-day retention. Pro is $19/month plus usage: $8 per active user, $6.50 per 1k series, and logs billed per GB processed, written and retained. Enterprise starts at a $25,000/year commit. Solo and small teams: free. Medium: Pro, after the calculator. Large: self-host or negotiate. The catch: Cloud bills on a lot of axes. Enterprise plugins are their own line at $55 per user, and logs queried beyond 100 times what you wrote get billed too. The $19 is the cover charge.

Prometheus67.0k★

Prometheus is the default way to collect metrics in cloud-native infrastructure. It pulls numbers like CPU, request counts and error rates from your apps and servers on a schedule, stores them as time series, and lets you query and alert on them with PromQL. Apache 2.0, a CNCF project, and there is no paid tier. Setup is one binary or container plus a config file listing what to scrape. Pair it with Grafana for dashboards and Alertmanager to route alerts. Version 3 added a new UI, native OTLP ingestion for OpenTelemetry metrics, and Remote Write 2.0. Retention defaults to 15 days, and the docs say plainly that local storage is not clustered or replicated, so long-term or multi-cluster setups bolt on Thanos, Mimir or VictoriaMetrics. It's free at every team size: you pay in servers and attention. Rather not run it? Amazon's managed Prometheus charges $0.90 per 10M samples ingested. The catch: Prometheus's own security model assumes untrusted users can read its HTTP endpoint, and auth is opt-in. In April that bit people: CVE-2026-42151 exposed Azure AD remote-write client secrets in plain text on the config endpoint until 3.11.3. Pull-based scraping also fits short-lived jobs badly.

Sentry45.7k★

Sentry catches errors in production and tells you exactly where they happened: stack trace, request, user, and the release that broke it. It also does tracing, session replay, profiling, logs, uptime and cron monitoring, with SDKs for most languages and frameworks. The code is source-available under the Functional Source License, and each release becomes Apache 2.0 two years later. Self-hosting runs on Docker Compose with a heavy stack (Kafka, ClickHouse, Redis, Postgres, Snuba, Relay and more) and wants 4 cores and 16 GB of RAM plus 16 GB of swap, ideally 32 GB. An errors-only profile cuts that to about 7 GB. Sentry itself pitches self-hosted for low-volume and proof-of-concept use, and it leaves out the Seer AI debugger, spike protection and some mobile symbolication. The cloud free plan is one user with 5,000 errors, 5 million spans and 50 replays a month. Team is $29 a month ($26 billed annually) for unlimited users and 50,000 errors; Business is $89 ($80 annually) with the same base quotas plus SAML and SCIM, unlimited dashboards and advanced quota management. Seer is $40 per active contributor on top. Solo: free cloud. Small teams: Team is cheap insurance. Large orgs: Business for SAML and SCIM. The catch: the license. You can self-host for internal use, but you can't offer Sentry, or anything substantially similar built on it, as a commercial product, so it isn't open source until each version's two-year clock runs out. GlitchTip (glitchtip/glitchtip-backend) is the lighter, open option.

SigNoz32.5k★

SigNoz puts traces, metrics, and logs in one dashboard, the three pillars of observability you'd otherwise stitch together from separate tools. It's built on OpenTelemetry, the open standard for collecting this data, so your instrumentation isn't locked to a proprietary SDK and works with any compatible backend. The self-hosted version is free and holds nothing back: same codebase as the cloud, every feature included. Running it yourself means running ClickHouse, which is the real ops consideration. ClickHouse is fast but hungry, so plan for a VM with 8GB+ of RAM and storage that grows with your data. Docker or Kubernetes, a couple of hours to stand up. If you have the ops capacity, this is where the savings live. Solo developers: the cloud free tier or a small self-hosted box is plenty. Small teams with ops capacity: self-host. Everyone else: SigNoz Cloud starts at $49/mo for the Teams plan plus usage ($0.30/GB for logs and traces, $0.10 per million metric samples), and it still undercuts a Datadog bill many times over. That's the whole pitch, Datadog-level visibility without the Datadog invoice. The catch is maturity. SigNoz is younger than the Grafana and Prometheus stack, and its plugin and integration ecosystem is smaller. If you need hundreds of prebuilt dashboards and integrations, Grafana still wins. If you want one clean unified platform instead of three tools duct-taped together, SigNoz is the better shape.

SkyWalking25.0k★

Apache SkyWalking traces requests end-to-end across your microservices so you can find where things are slow, failing, or misbehaving. It's an Application Performance Monitoring (APM) system that shows you traces, metrics, and logs across your entire architecture. Apache 2.0, CNCF project. SkyWalking supports auto-instrumentation for Java.NET, Node.js, Python, Go, and more, meaning you often don't need to change your code. Agents attach to your services and report back to the SkyWalking backend. Fully free. No paid tier, no commercial edition. You self-host everything: the OAP (Observability Analysis Platform) server, the UI, and the storage backend (Elasticsearch, BanyanDB, or PostgreSQL). The catch: SkyWalking is powerful but operationally heavy. You need the OAP server, a storage backend, and agents on every service. The Java auto-instrumentation is excellent; other languages vary in coverage. The UI is functional but not as polished as Datadog or Grafana. And the documentation assumes familiarity with distributed tracing concepts, not beginner-friendly.

Jaeger23.4k★

It's a distributed tracing platform: it tracks requests as they flow through your services, showing you exactly where time is spent. Service A calls Service B calls Service C, and Jaeger draws the full timeline. CNCF graduated project, originally built by Uber. It collects traces from your services, stores them, and gives you a UI to search and visualize request flows. Supports OpenTelemetry natively, which means you instrument your code once and can switch tracing backends later. Apache 2.0. Fully free, no paid tier. The catch: running Jaeger in production is real ops work. You need a storage backend (Elasticsearch, Cassandra, or Kafka), and those have their own operational costs. The UI is functional but not pretty; teams that want polished dashboards often export traces to Grafana. For small deployments, SigNoz bundles tracing, metrics, and logs in one tool and may be simpler to start with.

VictoriaMetrics18.0k★

VictoriaMetrics is a Prometheus drop-in replacement that uses 7-10x less memory and compresses data up to 70x better. Same PromQL queries, same Grafana dashboards, just cheaper to run. Apache 2.0, Go. It accepts data from Prometheus remote write, InfluxDB line protocol, OpenTelemetry, Graphite, and more. Single-binary deployment, no ZooKeeper, no dependencies. Download, run, point Prometheus at it. Single-node version is fully free with no feature restrictions. The cluster version (horizontal scaling) is also open source. VictoriaMetrics Cloud offers managed hosting starting around $0.01/1K active time series/month. Self-hosting ops: trivial for single-node. Download the binary, set a data directory, done. 1-2 hours/month. Cluster mode bumps that to moderate. You manage vmselect, vminsert, and vmstorage components. Solo through medium teams: single-node handles millions of time series on modest hardware. Large orgs: cluster mode or VictoriaMetrics Cloud. The catch: VictoriaMetrics is optimized for time series, not general-purpose queries. Some advanced PromQL features behave slightly differently. And while the community is growing, Prometheus + Thanos has a larger ecosystem of integrations and community knowledge.

Zipkin17.5k★

Zipkin shows you exactly where time is spent when a request crosses multiple services. It's a distributed tracing system: each service reports timing data, and Zipkin stitches it into a visual timeline showing the full request journey. When something is slow, you see which service is the bottleneck. Fully free under Apache 2.0. It's been around since 2012 (originally from Twitter) and is battle-tested at enormous scale. Storage backends include in-memory, MySQL, Cassandra, and Elasticsearch. The UI is simple but functional: search traces by service, duration, or tags. The catch: Zipkin is traces-only. No metrics, no logs, no dashboards. Modern observability stacks (Grafana + Tempo, SigNoz, Uptrace) bundle all three. If you're starting fresh, Jaeger (also CNCF, also free) has a more modern architecture and better Kubernetes integration. Zipkin's advantage is maturity and simplicity: it does one thing and has been doing it for over a decade.

systeminformer16.4k★

System Informer is what Windows Task Manager should have been. It shows every process, thread, DLL, network connection, and service on your machine with real-time graphs and drill-down detail that Microsoft's built-in tools never bothered to provide. This is the successor to Process Hacker, rebuilt from the ground up. No installation required. It runs portable from a USB stick. You get per-process CPU, memory, disk, and network breakdowns. Kernel-mode stack traces and .NET process inspection are built in. You can see exactly which process is holding a file lock. The plugin system lets you extend it. Developers debugging performance issues on Windows need this. Sysadmins diagnosing rogue processes need this. Security researchers analyzing malware behavior need this. It replaces Task Manager, Resource Monitor, and most of Sysinternals Process Explorer in a single tool. The catch: Windows only, local only. No remote monitoring, no fleet management, no centralized dashboard. Monitoring servers across a network requires something else entirely.

cachet15.3k★

Cachet is a self-hosted status page system that lets you communicate downtime and incidents to your users without depending on a third-party service. It handles components, incidents, scheduled maintenance, metrics, and subscriber notifications. Clean UI, straightforward setup. Runs on PHP 8.2+ with MySQL, PostgreSQL, or SQLite. Docker setup is available. The v3 rewrite modernized the codebase, but the project has had stretches of slow development. If you are comfortable with Laravel apps, maintaining this is routine. If not, expect some hands-on time with PHP dependency management. Solo devs and small teams: this is free and covers the basics well. For larger orgs, you lose the integrations that paid tools like Statuspage offer out of the box (deep PagerDuty/Datadog hooks, SLA reporting, global CDN distribution). The catch: development has been inconsistent. The v3 rewrite took years. If you need an actively maintained status page with guaranteed updates, look at Upptime or Gatus instead.

Thanos14.3k★

Thanos extends Prometheus into a highly available, horizontally scalable monitoring system with long-term retention and cross-cluster querying. It sits on top of your existing Prometheus setup and adds what Prometheus deliberately left out. You keep your Prometheus instances. Thanos adds a global query view across all of them, long-term storage in object storage (S3, GCS, Azure Blob), downsampling for historical queries, and high availability through deduplication. It's not a replacement; it's the scaling layer. Apache 2.0, CNCF project. Production-proven at companies running hundreds of Prometheus instances. The catch: Thanos adds real operational complexity. You're running Thanos Sidecar, Store Gateway, Compactor, Query Frontend. Each is a separate component to deploy and monitor. The irony of needing monitoring for your monitoring system is not lost on anyone. If you have fewer than 3 Prometheus instances, you probably don't need this yet.

keep12.5k★

Keep pulls alerts from every monitoring tool you use into one screen. Datadog, Grafana, CloudWatch, PagerDuty, Sentry: it connects to all of them with bi-directional integrations. The real value is noise reduction. It deduplicates alerts, correlates related incidents, and enriches them with context so your on-call engineer is not drowning in redundant pages at 3am. You get workflow automation that works like GitHub Actions for your monitoring stack: trigger responses, route alerts, escalate based on rules you define. The enterprise tier adds AI-powered correlation. Self-hosting gives you the full MIT-licensed core with unlimited alerts and integrations. The managed cloud starts free but caps you at 1 integration and 1 user, basically a demo. Growth tier at $199/month gets you 20 integrations and 10 users. PagerDuty and Opsgenie charge per-user and get expensive fast. Keep undercuts both if you self-host. The catch: the free cloud tier is too limited to evaluate properly. You need to self-host or commit to Growth to really test it.

healthchecks10.5k★

Healthchecks watches the jobs that fail silently: cron jobs, backups, scheduled scripts. Each job pings a unique URL or sends an email when it runs. When a ping doesn't arrive on time, Healthchecks alerts you over email, Slack, Telegram, PagerDuty or any of its 25+ integrations. It's the BSD-licensed code behind the hosted healthchecks.io: a Cronitor or Dead Man's Snitch you can run yourself, free. The Docker image runs the web app plus the alerting, reporting and inbound-email processes in one container. You bring Postgres, MySQL or MariaDB, an SMTP server for login links and alerts, and a reverse proxy. Self-hosted accounts get a 10,000-check limit, but ping history still keeps only 100 entries per check until you raise it in the admin panel. Hosted is free for 20 checks; Business is $20/month for 100 checks plus SMS, WhatsApp and phone-call credits. Solo: the free hosted plan. Small teams: self-host free, or pay $20/month and stop thinking about it. Larger teams: Business Plus at $80/month covers 1,000 checks. The catch: self-host it and you now monitor the monitor. SMS, WhatsApp and phone alerts need your own Twilio account. Signups are open by default, so close them on public servers.

prometheus-operator10.0k★

Prometheus Operator turns the fiddly job of running Prometheus on Kubernetes into something you declare instead of hand-wire. Prometheus is the default open source metrics system, and the pain has always been the setup. This operator lets you define scrape targets, alert rules, and Alertmanager config as native Kubernetes objects, then generates and reloads everything as pods come and go. Apache-2.0, completely free, maintained under the CNCF. Running it assumes you already run Kubernetes, and you still own everything Prometheus drags along: storage, retention, scaling, alert routing. The operator removes the config drudgery, not the operational weight. You size the time-series database, wire up long-term storage, and keep Alertmanager from melting down. A few of the custom resources still sit on beta and alpha API versions, so upgrades occasionally bite. At any real Kubernetes scale, this is the standard way to do Prometheus, and assembling the YAML by hand is a waste of time. Solo and small teams on one cluster: the kube-prometheus stack gets you dashboards and alerts in an afternoon, free. Large teams: still free, but budget real engineering hours for storage and federation. Not on Kubernetes? This does nothing for you. Want metrics without operating any of it? That is what Datadog, Grafana Cloud, and New Relic bill for. The catch: 'free' here means software cost only. You trade a monthly bill for the standing job of running a metrics platform, and that job is real. Done well, it costs far less than per-host SaaS. Done badly, it is a 2am page and a disk that filled up.

Highlight9.4k★

Highlight captures errors, session replays, and logs together so you see the full picture when something goes wrong in production. Basically Sentry plus LogRocket combined, but open source. TypeScript. Self-hostable via Docker. The session replay alone is worth evaluating: it records user interactions so you can see exactly what happened before an error. Plus error monitoring, log aggregation, and distributed tracing. Free tier on their cloud: 500 sessions, 1M logs, and 1M traces per month. That's enough for a small app. Self-hosting is free with no feature restrictions. Paid cloud starts at $150/mo for the Team plan with higher limits. Enterprise pricing is custom. The jump from free to paid is steep: $0 to $150/mo with nothing in between. Solo developers: the free cloud tier handles a side project easily. Self-hosting saves money but needs Docker Compose and a few hours of setup. Small teams (2-10): free tier might be tight; self-host or budget for Team plan. Growing teams: $150/mo for unified monitoring is actually reasonable vs buying Sentry + LogRocket + Datadog separately. The catch: the $0-to-$150 gap means growing startups either self-host or pay enterprise-adjacent prices. And while Highlight covers breadth, dedicated tools like Sentry (errors) or Grafana (dashboards) go deeper in their specific domains.

graylog2-server8.2k★

Graylog centralizes all your logs in one place so you can search, dashboard, and alert on them, instead of SSHing around to grep across servers. It ingests logs from anywhere (syslog, GELF, Beats, Kafka), indexes them in OpenSearch, and gives you a web UI to search and build alerts. The open edition is free to self-host, though it ships under SSPL, which is source-available rather than truly open source. Running it is heavy. Graylog itself is one piece; it also needs an OpenSearch (or Elasticsearch) cluster and MongoDB alongside it. That's three stateful systems to deploy, scale, tune, and back up. Budget real ops time, this is not a single container you set and forget. The free Open tier handles ingestion, search, dashboards, and alerting, which is enough for a lot of teams. The paid Enterprise and Security tiers add archiving and data tiering, compliance reports, SSO, correlation, and SIEM features, priced for companies (think five figures a year). Solo and small teams: Open is genuinely capable. Larger or regulated teams: the paid tiers, or a hosted option, start to make sense. This replaces Splunk for log management at a fraction of the cost, and covers the logs piece of Datadog or New Relic. The catch is the operational weight of OpenSearch plus MongoDB, and that SSPL doesn't give you the freedoms of a real open source license.

OpenTelemetry Collector7.7k★

The OpenTelemetry Collector is the vendor-neutral middleman that collects logs, metrics, and traces from your applications and routes them wherever you want. Instead of installing five different agents for five different observability tools, you install one Collector and configure where data goes. Switch backends without changing your app code. Apache 2.0. CNCF project backed by every major observability vendor. The Collector receives telemetry data, processes it (filter, transform, sample, batch), and exports it to one or more backends simultaneously. Fully free. No paid tier. The Collector itself is just the pipeline. You still need somewhere to send data (Grafana stack is free self-hosted, or pay for Datadog/New Relic/etc.). The Collector runs as a sidecar, DaemonSet, or standalone deployment. The contrib distribution includes 200+ receivers, processors, and exporters for every major backend. The catch: configuration is YAML-based and gets complex fast. Debugging pipeline issues (why aren't my traces showing up?) requires understanding the receiver-processor-exporter chain. And the Collector is infrastructure you need to monitor. Yes, you need observability for your observability pipeline.

Uptrace4.3k★

Uptrace gives you traces, metrics, and logs in one place so you can see which services are failing and how errors propagate. It's an APM (application performance monitoring) tool built on OpenTelemetry, which means it works with almost any language and framework. Self-hosting is free under AGPL-3.0. You get the full tracing UI, alerting, and dashboards. The setup requires ClickHouse for storage (that's the heavy part), but once running, it handles millions of spans without breaking a sweat. The catch: AGPL license means if you modify Uptrace and offer it as a service, you must open-source your changes. The hosted cloud version exists but pricing isn't publicly listed. You have to contact sales. And while OpenTelemetry compatibility is great, the ecosystem is still maturing. Expect some rough edges with auto-instrumentation for newer frameworks.

goalert2.9k★

GoAlert does the unglamorous core of PagerDuty: on-call schedules, rotations, escalation policies, and alerts that keep calling your phone until someone acknowledges. Target (yes, the retailer) built it for internal use and open sourced the whole thing under Apache 2.0. Every feature is free with no user limits. Self-hosting is a single Go binary plus Postgres, about as light as this category gets. The dependency that matters is Twilio: SMS and voice notifications go through your Twilio account, so a real deployment carries a small monthly bill for phone numbers and per-message fees. Slack, email, and webhook notifications work without it. Solo: overkill, you are the escalation policy. Small teams: GoAlert plus your existing Prometheus or Grafana alerting replaces the core of a PagerDuty bill. Teams that want incident timelines, status pages, and alert noise reduction should look at keephq/keep alongside it or keep paying. The catch: the feature set has stayed deliberately narrow for years. It pages people, and that's it. No incident management, no postmortems, no AI dedupe. That focus is either exactly what you want or a dealbreaker.

pyrra1.6k★

Pyrra turns a service level objective into working Prometheus alerts. An SLO is a promise like "99% of API requests succeed over two weeks," and doing it right by hand means writing a stack of recording rules and multi-burn-rate alerts. With Pyrra you write a short YAML object with the target, the window and the error and total metrics, and it generates the rules, four burn-rate alerts and a UI that sorts every SLO by remaining error budget. Apache 2.0, free, now part of the prometheus-community org. It's one binary that serves the UI, the API and the rule generator. On Kubernetes it runs as an operator watching SLO objects; anywhere else it reads YAML files from disk. It works with Thanos too, and can emit generic rules for its bundled Grafana dashboards. There's no paid tier, no cloud and no account. Solo: skip it, SLOs are overkill for side projects. Small teams with production services on Prometheus: free and worth an afternoon. Larger teams: free, and a clean way to standardize SLOs across services. Sloth is the closest alternative if you only want rule generation without a UI. The catch: it's only useful on top of Prometheus or Thanos, and alerts only help if someone acts on them. Pyrra does the math; the on-call discipline is yours.

newrelic-ruby-agent1.2k★

The New Relic Ruby agent instruments your app and sends telemetry to New Relic's platform. It's the data collector, not the dashboard. Apache 2.0. This is the open source agent that plugs into your Ruby app. The agent itself is free to use. What you pay for is the New Relic platform that stores, queries, and visualizes the data. New Relic's free tier gives you 100GB of data ingestion per month, one full-platform user, and unlimited basic users. That's generous. A small Rails app's telemetry easily fits in 100GB. Paid plans start at $0.35/GB ingested beyond the free tier, plus $49/user/mo for full-platform access. The catch: you're instrumenting your app for a proprietary SaaS platform. The agent is open source, but the value is in New Relic's platform, which is not. If New Relic changes pricing (they have before), you're locked in. For Ruby specifically, the agent adds overhead. Expect 2-5% latency impact. And the open source alternative ecosystem is strong: OpenTelemetry + Grafana gives you similar visibility without the vendor lock-in.

kuvasz670★

Kuvasz is a self-hosted uptime monitor. It checks your endpoints on a schedule, measures response times, and alerts you when something breaks. That's it. Does one thing, does it cleanly. Kotlin, Apache 2.0. Built on Quarkus (a Java framework optimized for containers). Supports HTTP monitoring with configurable check intervals, Slack and Telegram notifications, and SSL certificate expiry monitoring. Stores historical data in Postgres. Fully free, self-hosted only. No cloud version, no paid tier. Run it in Docker alongside a Postgres instance and you're set. Solo developers: Docker Compose with Kuvasz + Postgres monitors your side projects for the cost of a $5/mo VPS. Small teams: same setup, more endpoints. Medium to large teams: you'll likely want something with more features: dashboards, incident management, status pages. The catch: this is a small, niche project. The feature set is minimal compared to Uptime Kuma (which has a much larger community) or commercial tools. No status page, no multi-region checking, no advanced alerting rules. If basic HTTP monitoring and SSL checks are all you need, Kuvasz works. For anything more, look at the alternatives.

GlitchTip0★

GlitchTip is the lightweight Sentry alternative that uses Sentry's own SDKs. Swap one environment variable (the DSN endpoint) and your existing Sentry instrumentation starts sending errors to GlitchTip instead. Error grouping, deduplication, and a searchable issue queue cover the core workflow. Performance monitoring is included. Self-hosting needs just 256MB RAM for a minimal Docker setup with PostgreSQL. No Redis required for small deployments. One-click deploys are available on PikaPods and Railway. The Django backend keeps things simple and the unlimited projects/team members policy means no per-seat billing surprises. Small teams who only need error tracking without Sentry's full observability suite save real money here. Solo developers get production error monitoring for free. Teams outgrowing Sentry's free tier get unlimited events on self-hosted for the cost of a small VPS. The catch: the feature gap with Sentry is real. Session replay, profiling, AI-powered issue triage, and advanced performance tracing are all absent. GlitchTip covers core error aggregation well, but teams relying on Sentry's full platform will notice what's missing. Also hosted on GitLab, not GitHub, which means smaller community visibility.