tautulli.com

Monitoring is the practice of automatically checking a website or service on a schedule to confirm it is reachable and behaving as expected, then alerting someone when it is not. You need it whenever downtime or degraded performance has a real cost — lost signups, failed payments, or support tickets you hear about before your own dashboards do. A basic setup requires three things: something to check (an endpoint, port, or DNS record), a condition that defines "healthy," and a destination for alerts.

Monitoring vs. uptime vs. status pages

These three terms get used interchangeably, but they describe different layers of the same job:

Monitoring produces the data. Uptime is a summary of that data over time. A status page is a presentation layer on top of both. You can monitor without ever publishing a status page, and you can publish a status page that is updated manually — but automated monitoring is what makes the page trustworthy.

What monitoring actually checks

A check is a request plus an expected response. The most common types:

• HTTP/HTTPS endpoints — request a URL and verify the status code, response body, or response time. This is the default for web apps and APIs.
• DNS records — confirm a domain resolves to the expected address, catching expired records or misconfigured nameservers before users hit them.
• TCP ports — open a raw connection to a port to verify a database, mail server, or other non-HTTP service is listening.
• Custom conditions — evaluate the response against rules you define, such as "body contains "status":"ok"" or "response time under 500 ms."

The condition matters as much as the check. A 200 response with an error message in the body is still a failure from a user's perspective, which is why body and latency conditions exist.

How automated monitoring works

The loop is simple and repeats on an interval you choose:

1. Schedule — a timer triggers the check, typically every 30 seconds to 5 minutes depending on how fast you need to know.
2. Request — the monitor sends the HTTP request, DNS query, or TCP connection.
3. Evaluate — the response is compared against your conditions (status code, body content, latency threshold).
4. Record — the result is stored, building the history that uptime percentages are calculated from.
5. Alert — if the condition fails, a notification fires to email, Slack, PagerDuty, or a webhook.

Most tools add a confirmation step: a single failed check may not trigger an alert, but two or three consecutive failures will. This avoids waking someone up over a transient network blip.

Setting up basic monitoring

The exact steps depend on your tool, but the sequence is consistent:

1. Pick what to monitor. Start with your most critical user-facing URL — the homepage or a health endpoint — plus one dependency like your database port or DNS record.
2. Define the healthy condition. For a web app, that usually means HTTP 200 and a response body containing an expected string. For an API, check a specific field in the JSON.
3. Set the interval. Shorter intervals detect problems faster but generate more traffic and noise. One minute is a reasonable starting point for most sites.
4. Configure alerting. Choose a channel your team actually watches. Include the check name, the failure reason, and a link to the monitor in the alert message.
5. Add a confirmation threshold. Require two or three consecutive failures before alerting to filter out false positives.
6. Verify it works. Temporarily point the check at a URL you know will fail, confirm the alert arrives, then restore it.

If you are using an open-source tool like Gatus, the configuration is typically a YAML file where each endpoint gets a name, URL, interval, conditions, and alert destinations. The same structure applies whether you self-host or use a hosted service.

Common failures and how to troubleshoot them

False positives from transient errors. A single timeout during a deploy or a brief network hiccup can fire an alert. Fix: require consecutive failures before notifying.

Monitoring the wrong thing. A check that only confirms the server responds with 200 will miss a broken database connection that returns 200 with an error page. Fix: add body-content conditions, not just status codes.

Alert fatigue. If every minor latency spike pages someone, the team stops reading alerts. Fix: separate critical alerts (service down) from warnings (slow response) and route them to different channels.

Checks failing from the monitor's location but not for users. A firewall or geo-blocking rule may reject your monitor's IP. Fix: run checks from multiple regions, or whitelist the monitor's addresses.

No baseline, so you cannot tell if something is wrong. Without historical data, a 2-second response time looks fine until you realize it used to be 200 ms. Fix: let monitoring run long enough to establish normal ranges before setting latency thresholds.

The goal is not to monitor everything — it is to monitor what breaks in ways that matter, with conditions specific enough to catch real problems and thresholds loose enough to avoid crying wolf.

Albert Belle's career statistics are best understood by separating single-season lines from career totals, and by tracking which team he played for in each season. The fan site Ultimate Albert Belle (albertbelle.net) organizes this material into dedicated sections — Baseball Profile, Career Statistics, Home Runs, and Timeline — alongside team-specific pages for the Indians, White Sox, and Orioles. Those sections are the natural starting point if you want to see the numbers rather than just read about them.

What the site actually offers

The navigation on albertbelle.net lists, among other items:

• Baseball Profile
• Career Statistics
• Home Runs
• Timeline
• Team pages: Indians, White Sox, Orioles
• Supporting context: Biography, Quotes, Pictures, Articles, Links

This structure matters because Belle's career spans three franchises, and a single "career" page can blur which season belongs to which team. Using the team pages together with the career page lets you cross-check.

Reading the numbers: season vs. career

When you open a stats page, the first distinction to make is the row type.

A career total tells you the size of the pile. A season line tells you when he was most productive. If you only look at the career total, you lose the shape of the career — which is often the more interesting part.

Why the team split matters for Belle

Belle is listed on the site under Indians, White Sox, and Orioles themes, which reflects that his career is not tied to one uniform. Practically, this means:

• A stat line from a White Sox season should not be read as if it happened in Cleveland.
• Team pages are the right place to check which years belong to which club.
• The Timeline section helps place a season in context — what stage of his career it was, and what was happening around it.

If you are comparing two seasons, confirm they are from the same team context before drawing conclusions.

Common pitfalls when reading Belle's stats

• Mixing eras. Counting stats like home runs and RBI are shaped by the offensive environment of the season. A number from the late 1990s is not directly comparable to a number from a different run-scoring era without that context.
• Treating the site as official. The site states plainly that it is unofficial and not associated with Albert Belle. That does not make the numbers wrong, but it does mean you should treat it as a fan-maintained reference, not a league record.
• Ignoring the update date. The site's footer shows it was created June 25, 1999, and last updated January 29, 2024. A page last touched years ago may not reflect the most recent corrections.
• Confusing profile with statistics. The Baseball Profile page and the Career Statistics page serve different purposes. Read the profile for framing, the stats page for numbers.

Using the timeline to interpret the stats

The Timeline section is the tool for answering "why does this season look like that?" A stat line by itself does not explain a jump or a drop. Placing it on the timeline — alongside the team pages and the news items the site archives — gives you the surrounding facts. The site's news archive, for example, includes a January 29, 2024 note about an interview on the Chris Rose Rotation podcast, and a June 15, 2020 note about a White Sox Talk podcast interview covering his 1998 season. Those are context, not statistics, but they help you read the 1998 line with more understanding.

A practical way to work through the stats

1. Open Career Statistics and note the career totals.
2. Open the Timeline and identify the seasons you care about.
3. Use the Indians, White Sox, and Orioles pages to confirm which team each season belongs to.
4. Compare single-season lines against each other, not just against the career total.
5. Check the site's last-updated date before citing anything.

If you want the numbers themselves, go directly to the Career Statistics and Home Runs sections on albertbelle.net. If you want to understand what the numbers mean, read them alongside the Timeline and the team pages — that combination is what turns a list of figures into a career.

Tautulli is a free, third-party, Python-based web application that runs alongside your Plex Media Server to monitor activity and track statistics. It records what was watched, who watched it, when and where they watched it, and how it was played, then presents that data in tables and graphs through a browser interface. It suits Plex server owners who want watch history, per-user and per-library analytics, or event-driven notifications beyond what the Plex dashboard shows. It is not affiliated with Plex Inc., so treat it as a companion tool rather than an official feature.

What Tautulli actually does

Tautulli sits next to your Plex server and reads its activity. The official feature list covers:

• Monitoring — current activity on your Plex Media Server in real time.
• Statistics — usage statistics about your Plex library.
• History — a watch log for all of your users.
• Graphs — streaming trends shown visually.
• Notifications — trigger notifications or scripts from events on your Plex server.
• Recently Added — track when content is added to your library.
• Newsletters — create and send newsletters for recently added media.
• Sync — view and delete all synced content from your server.
• Media Info — detailed information on all of your media.

The site sums up the scope neatly: the statistics cover what, who, when, where, and how something was watched — everything except why.

The interface, by section

Tautulli's preview pages map closely to the questions a server owner tends to ask:

If your main question is "who has been watching what, and how much," the Users, User Statistics, and History sections are where you will spend most of your time.

Setup context and requirements

Tautulli is cross-platform: it works on any system that supports Python. You run it alongside your existing Plex Media Server and use it through a web interface, which is why the project describes itself as a web application. The site also offers an official Tautulli Remote app for viewing activity and stats on the go.

The site does not publish detailed installation steps, system requirements, or pricing on the pages reviewed here. For setup specifics, use the Download and Support links on tautulli.com and the project's GitHub repository, which the site links to directly.

Notifications and automation

Beyond dashboards, Tautulli can trigger notifications or scripts when events occur on your Plex server, using your preferred notification agents. This is the feature that turns Tautulli from a reporting tool into something that can react — for example, alerting you when a new stream starts or when content is added. The site lists the capability but not the full agent catalog or script API details, so check the documentation before planning a specific integration.

Does it replace the Plex dashboard?

Not exactly — it extends it. Plex's built-in dashboard is fine for a quick look at current streams. Tautulli adds persistent watch history, per-user and per-library breakdowns, long-term graphs, newsletters, sync management, and event-driven notifications in one place. If you only ever check whether someone is streaming right now, the built-in view may be enough. If you want to answer "how many times has this user watched this show, and when," or you want automated alerts, Tautulli is built for that.

One caveat worth knowing before you commit: Tautulli is a third-party project maintained outside Plex, so its features and compatibility track Plex changes independently. The site is explicit that Tautulli is not affiliated with Plex Inc.

Quick decision guide

• Choose Tautulli if you want detailed watch history, per-user and per-library statistics, graphs, newsletters, or notifications and scripts triggered by Plex events.
• Skip it if the built-in Plex dashboard already answers your questions and you do not need historical or per-user reporting.
• Check first if you need a specific notification agent or script behavior — confirm support in the project documentation, since the site lists the capability without full configuration details.

Start at tautulli.com for the feature overview and download links, and use the linked GitHub repository for installation and configuration specifics.

Satellite tracking software predicts where a satellite is at any moment and when it will pass within range of your location, so you can point an antenna, schedule a contact, or just watch it cross the sky. The core inputs are simple: your observer coordinates and a current set of orbital data (TLEs). Gpredict is a free, real-time satellite tracking and orbit prediction program for Linux, Mac OS X, and Windows, and it is a useful concrete example of how these tools work. This explainer covers the mechanism, the setup steps, and the problems that most often break a tracking session.

What satellite tracking actually means

Tracking has two related meanings, and it helps to keep them apart:

• Position tracking — knowing where a satellite is right now, usually shown on a world map with its ground track and footprint (the area of Earth from which it is visible).
• Pass prediction — knowing when that satellite will rise above your local horizon, how high it will get (maximum elevation), and when it will set.

For radio work, a third layer matters: Doppler shift. As a satellite moves toward you and then away, the frequency you hear drifts. Tracking software calculates this offset so you can retune during a pass.

Why orbit data (TLEs) drives everything

Tracking software does not measure the satellite directly. It propagates an orbital model forward in time. The standard input is a TLE — a Two-Line Element set, a compact text description of a satellite's orbit at a given epoch.

Key consequences:

• TLEs go stale. Atmospheric drag and other forces make the real orbit drift from the prediction. A TLE a few days old may be fine for a rough look; for precise antenna pointing or Doppler tuning, fresher data is better.
• You need a current source. Most trackers can download TLEs automatically from a catalog such as Celestrak or Space-Track. The update interval is a setting worth checking.
• The epoch matters. If your software is using an old element set, your pass times will be off even if your clock and coordinates are perfect.

Core features to expect

Setting up a tracker like Gpredict

The general workflow is the same across most tracking programs:

1. Set your observer location. Enter latitude, longitude, and altitude. This is the single most common source of wrong results — a sign error or a swapped lat/long puts you on the other side of the planet.
2. Check your clock and time zone. Predictions are time-sensitive. Make sure the system clock is accurate and the time zone is correct, especially if you compare pass times with other people.
3. Load or download TLEs. Add the satellites you want and point the software at a current TLE source, or import a file you downloaded.
4. Refresh the elements. Set an update interval, or manually re-download before an important session.
5. Read the pass list. Look at start time, maximum elevation, and duration. Higher maximum elevation generally means a better, longer contact.
6. Optionally connect hardware. If you have a rotator or radio, configure the interface so the software can point the antenna and apply Doppler correction.

Expected result: a list of upcoming passes for your location, and a map showing the satellite's current position and footprint.

Common problems and how to spot them

• Stale TLEs — pass times drift by minutes. Symptom: the satellite is not where the software says. Fix: refresh the elements.
• Wrong observer coordinates — every pass looks wrong or the satellite never rises. Symptom: predictions that make no sense for your area. Fix: re-check latitude, longitude, and sign conventions.
• Time-zone or clock errors — pass times are offset by whole hours. Symptom: consistent shift between your software and a reference. Fix: verify system time and zone.
• Confusing UTC with local time — most tracking tools display UTC. Symptom: you show up an hour or more early or late. Fix: convert deliberately.
• Elevation mask too high or low — you either miss low passes or get unusable ones. Fix: adjust the minimum elevation setting to match your horizon and antenna.

A note on the source

The site at oz9aec.dk, which describes Gpredict as free, real-time satellite tracking and orbit prediction software for Linux, Mac OS X, and Windows, currently shows only an "under construction" page. Treat the description as the project's stated purpose rather than a live download or documentation source; for current files and instructions, look for the project's own distribution channel.

FileBot matches your movie and TV files against online databases and renames them into a structure Plex can read, using its built-in {plex} naming standard. The basic flow is: drag files into the Original Files list, pick a datasource, let FileBot generate New Names, check the matches, then hit Rename. If you want this to run without you, the same tool exposes a CLI and an amc script for unattended workflows. This guide covers both paths, plus what to do when a match goes wrong.

Before you start

You need FileBot installed (native installers and packages exist for all major operating systems, per the FileBot site), and your media files somewhere on disk. A license is required for continued use — the site lists a 1-year universal license at US$8.00 and a lifetime universal license at US$80.00, sold through Paddle. Nothing in the source material says the tool is free, so plan on a purchase.

Decide which datasource fits your library:

Renaming a batch with the GUI

1. Drag your movie or episode files into the Original Files list area. FileBot accepts files dropped in bulk, so you can queue hundreds at once.
2. Right-click the New Names list area and select your preferred datasource (TheMovieDB, TheTVDB, or AniDB).
3. Review the generated names. FileBot matches each file against the database automatically. This is the step worth slowing down for — a wrong match here becomes a wrong match in Plex.
4. Hit Rename. FileBot moves and renames the files into the standard structure.

The key setting is the naming scheme. You can build a custom scheme with MediaInfo support and language preferences, or keep it simple and stick to the {plex} naming standard — which is what you want if Plex is the target, since it produces the folder and filename layout Plex expects.

Fixing a bad match

Automatic matching is good but not infallible, especially with ambiguous titles, multi-episode files, or anime with alternate season numbering. When a file lands on the wrong entry:

• Manually search the database from within FileBot and pick the correct result.
• Re-check the New Names list before renaming — the preview exists precisely so you can catch this.
• If you already renamed, use the internal history to revert the rename operation and start over.

Automating it with the CLI and amc script

For an unattended setup, FileBot offers a simple CLI for common cases and a built-in scripting engine for more complex ones. The site's example for a basic rename is:

filebot -rename *.mkv

For a full media-center pipeline, the amc script is the intended tool. Per the FileBot site, one filebot command with amc can extract archives, identify and organize media files, fetch additional artwork and metadata, and update Plex. That makes it suitable for a scheduled or watch-folder-driven workflow where files land in a directory and get processed without intervention.

Subtitles and artwork

Subtitles are handled the same drag-and-drop way: drop files onto the drop area and hit Download to fetch from OpenSubtitles. FileBot can find matching subtitles via file hash, and it includes an integrated subtitle viewer for srt files, plus manual search, preview, and encoding fixes. Artwork and cover images are fetched alongside the rename when you use the matching features.

What to verify after renaming

• Plex picks up the new files and matches them without manual correction.
• Multi-episode or specials files landed in the season/episode slots you expect.
• Subtitles are attached to the right files and display correctly (check encoding if they don't).
• If anything is off, revert via history rather than renaming by hand — it keeps the library consistent.