Monitoring of machines, containers, services, logs, ...
Monitoring in this case means gathering and showing information on how services
or machines or containers are running.
Can be cpu, io, ram, disk use... can be number of http requests, errors,
results of backups, or a world map showing location of IP addresses
that access your services.
Prometheus deals with metrics. Loki deals with logs.
Grafana is there to show the data on dashboards.
Most of the prometheus stuff here is based off the magnificent stefanprodan/dockprom.
- Core prometheus+grafana - nice dashboards with metrics of a docker host and containers
- Pushgateway - push data to prometheus from anywhere
- Alertmanager - setting alerts and getting notifications
- Loki - prometheus for logs
- Minecraft Loki example - logs, grafana alerts and templates
- Caddy reverse proxy monitoring - metrics, logs and geoip map
Good youtube overview of Prometheus.
Prometheus is an open source system for monitoring and alerting,
written in golang.
It periodically collects metrics from configured targets,
makes these metrics available for visualization, and can trigger alerts.
Prometheus is relatively young project, it is a pull type monitoring.
- Prometheus Server is the core of the system, responsible for
- pulling new metrics
- storing the metrics in a database and evaluating them
- making metrics available through PromQL API
- Targets - machines, services, applications that are monitored.
These need to have an exporter.- exporter - a script or a service that gathers metrics on the target, converts them to prometheus server format, and exposes them at an endpoint so they can be pulled
- Alertmanager - responsible for handling alerts from Prometheus Server, and sending notifications through email, slack, pushover,.. In this setup ntfy webhook will be used.
- pushgateway - allows push type of monitoring. Meaning a machine anywhere in the world can push data in to your prometheus. Should not be overused as it goes against the pull philosophy of prometheus.
- Grafana - for web UI visualization of the collected metrics
/home/
└── ~/
└── docker/
└── monitoring/
├── 🗁 grafana_data/
├── 🗁 prometheus_data/
├── 🗋 docker-compose.yml
├── 🗋 .env
└── 🗋 prometheus.yml
grafana_data/
- a directory where grafana stores its dataprometheus_data/
- a directory where prometheus stores its database and data.env
- a file containing environment variables for docker composedocker-compose.yml
- a docker compose file, telling docker how to run the containersprometheus.yml
- a configuration file for prometheus
The three files must be provided.
The directories are created by docker compose on the first run.
- Prometheus - The official image used. Few extra commands passing configuration. Of note is 240 hours(10days) retention policy.
- Grafana - The official image used. Bind mounted directory for persistent data storage. User sets as root, as it solves issues I am lazy to investigate, likely me editing some files as root.
- NodeExporter - An exporter for linux machines,
in this case gathering the metrics of the docker host,
like uptime, cpu load, memory use, network bandwidth use, disk space,...
Also bind mount of some system directories to have access to required info. - cAdvisor - An exporter for gathering docker containers metrics,
showing cpu, memory, network use of each container
Runs inprivileged
mode and has some bind mounts of system directories to have access to required info.
Note - ports are only expose
, since expectation of use of a reverse proxy
and accessing the services by hostname, not ip and port.
docker-compose.yml
services:
# MONITORING SYSTEM AND THE METRICS DATABASE
prometheus:
image: prom/prometheus:v2.42.0
container_name: prometheus
hostname: prometheus
user: root
restart: unless-stopped
depends_on:
- cadvisor
command:
- '--config.file=/etc/prometheus/prometheus.yml'
- '--storage.tsdb.path=/prometheus'
- '--web.console.libraries=/etc/prometheus/console_libraries'
- '--web.console.templates=/etc/prometheus/consoles'
- '--storage.tsdb.retention.time=240h'
- '--web.enable-lifecycle'
volumes:
- ./prometheus_data:/prometheus
- ./prometheus.yml:/etc/prometheus/prometheus.yml
expose:
- "9090"
labels:
org.label-schema.group: "monitoring"
# WEB BASED UI VISUALISATION OF METRICS
grafana:
image: grafana/grafana:9.4.3
container_name: grafana
hostname: grafana
user: root
restart: unless-stopped
env_file: .env
volumes:
- ./grafana_data:/var/lib/grafana
expose:
- "3000"
labels:
org.label-schema.group: "monitoring"
# HOST LINUX MACHINE METRICS EXPORTER
nodeexporter:
image: prom/node-exporter:v1.5.0
container_name: nodeexporter
hostname: nodeexporter
restart: unless-stopped
command:
- '--path.procfs=/host/proc'
- '--path.rootfs=/rootfs'
- '--path.sysfs=/host/sys'
- '--collector.filesystem.mount-points-exclude=^/(sys|proc|dev|host|etc)($$|/)'
volumes:
- /proc:/host/proc:ro
- /sys:/host/sys:ro
- /:/rootfs:ro
expose:
- "9100"
labels:
org.label-schema.group: "monitoring"
# DOCKER CONTAINERS METRICS EXPORTER
cadvisor:
image: gcr.io/cadvisor/cadvisor:v0.47.1
container_name: cadvisor
hostname: cadvisor
restart: unless-stopped
privileged: true
devices:
- /dev/kmsg:/dev/kmsg
volumes:
- /:/rootfs:ro
- /var/run:/var/run:ro
- /sys:/sys:ro
- /var/lib/docker:/var/lib/docker:ro
- /cgroup:/cgroup:ro #doesn't work on MacOS only for Linux
expose:
- "3000"
labels:
org.label-schema.group: "monitoring"
networks:
default:
name: $DOCKER_MY_NETWORK
external: true
.env
# GENERAL
DOCKER_MY_NETWORK=caddy_net
TZ=Europe/Bratislava
# GRAFANA
GF_SECURITY_ADMIN_USER=admin
GF_SECURITY_ADMIN_PASSWORD=admin
GF_USERS_ALLOW_SIGN_UP=false
# GRAFANA EMAIL
GF_SMTP_ENABLED=true
GF_SMTP_HOST=smtp-relay.sendinblue.com:587
[email protected]
GF_SMTP_PASSWORD=xzu0dfFhn3eqa
All containers must be on the same network.
Which is named in the .env
file.
If one does not exist yet: docker network create caddy_net
Contains the bare minimum settings of targets from where metrics are to be pulled.
prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'nodeexporter'
static_configs:
- targets: ['nodeexporter:9100']
- job_name: 'cadvisor'
static_configs:
- targets: ['cadvisor:8080']
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
Caddy v2 is used, details
here.
Caddyfile
graf.{$MY_DOMAIN} {
reverse_proxy grafana:3000
}
prom.{$MY_DOMAIN} {
reverse_proxy prometheus:9090
}
- Login admin/admin to
graf.example.com
, change the password. - Add Prometheus as a Data source in Configuration
Set URL tohttp://prometheus:9090
- Import dashboards from json files in this repo
These dashboards are the preconfigured ones from
stefanprodan/dockprom
with few changes.
Docker host dashboard did not show free disk space for me, had to change fstype
from aufs
to ext4
.
Also included is a fix
for host network monitoring not showing traffick. In all of them
the default time interval is set to 1h instead of 15m
- docker_host.json - dashboard showing linux docker host metrics
- docker_containers.json - dashboard showing docker containers metrics,
except the ones labeled as
monitoring
in the compose file - monitoring_services.json - dashboar showing docker containers metrics
of containers that are labeled
monitoring
My understanding of this shit..
- Prometheus stores metrics, each metric has a name, like
cpu_temp
. - the metrics values are stored as time series, just simple - timestamped values
[43 @1684608467][41 @1684608567][48 @1684608667]
. - This metric has labels
[name="server-19", state="idle", city="Frankfurt"]
.
These allow far better targeting of the data, or as they say multidimensionality.
Queries to retrieve metrics.
cpu_temp
- simple query will show values over whatever time period is selected in the interface.cpu_temp{state="idle"}
- will narrow down results by applying a label.
cpu_temp{state="idle", name="server-19"}
- multiple labels narrow down results.
A query can return various data type, kinda tricky concept is difference between:
-
instant vector - query returns a single value with a single timestamp. It is simple and intuitive. All the above examples are instant vectors.
Of note, there is no thinking about time range here. That is few layers above, if one picks last 1h or last 7 days... that plays no role here, this is a query response datatype and it is still instant vector - a single value in point of time. -
range vector - returns multiple values with a single timestamp
This is needed by some query functions but on its own useless.
A useless example would becpu_temp[10m]
. This query first looks at the last timestamp data, then it would take all data points within the previous 10m before that one timestamp, and return all those values. This colletion would have a single timestamp.
This functionality allows use of various functions that can do complex tasks.
Actual useful example of a range vector would bechanges(cpu_temp[10m])
where the function changes() would take that range vector info, look at those 10min of data and return a single value, telling how many times the value of that metric changed in those 10 min.
Links
- Stackoverflow - Prometheus instant vector vs range vector
- The Anatomy of a PromQL Query
- Why are Prometheus queries hard?
- Prometheus Cheat Sheet - Basics (Metrics, Labels, Time Series, Scraping)
- Learning Prometheus and PromQL - Learning Series
- Prometheus from A to Y
- The official
Gives freedom to push information in to prometheus from anywhere.
Be aware that it should not be abused to turn prometheus in to push type monitoring. It is only intented for specific situations.
To add pushgateway functionality to the current stack:
-
New container
pushgateway
added to the compose file.docker-compose.yml
services: # PUSHGATEWAY FOR PROMETHEUS pushgateway: image: prom/pushgateway:v1.5.1 container_name: pushgateway hostname: pushgateway restart: unless-stopped command: - '--web.enable-admin-api' expose: - "9091" networks: default: name: $DOCKER_MY_NETWORK external: true
-
Adding pushgateway to the Caddyfile of the reverse proxy so that it can be reached at
https://push.example.com
Caddyfile
push.{$MY_DOMAIN} { reverse_proxy pushgateway:9091 }
-
Adding pushgateway as a scrape point to
prometheus.yml
Of note is honor_labels set to true, which makes sure that conflicting labels likejob
, set during push are kept over labels set inprometheus.yml
for the scrape job. Docs.prometheus.yml
global: scrape_interval: 15s evaluation_interval: 15s scrape_configs: - job_name: 'pushgateway-scrape' scrape_interval: 60s honor_labels: true static_configs: - targets: ['pushgateway:9091']
To test pushing some metric, execute in linux:
echo "some_metric 3.14" | curl --data-binary @- https://push.example.com/metrics/job/blabla/instance/whatever
- Visit
push.example.com
and see the metric there. - In Grafana > Explore > query for
some_metric
and see its value there.
In that command you see the metric itself: some_metric
and it's value: 3.14
But there are also labels being set as part of the url. One label named job
,
which is required, but after that it's whatever you want.
They just need to be in pairs - label name and label value.
The metrics sit on the pushgateway forever, unless deleted or container shuts down. Prometheus will not remove the metrics after scraping, it will keep scraping the pushgateway, every X seconds, and store the value that sits there with the timestamp of scraping.
To wipe the pushgateway clean
curl -X PUT https://push.example.com/api/v1/admin/wipe
Linked above is a guide-by-example with more info on pushgateway setup.
A real world use to monitor backups, along with pushing metrics
from windows in powershell.
To send a notification about some metric breaching some preset condition.
Notifications channels used here are email and
ntfy
Note
I myself am not planning on using alertmanager.
Grafana can do alerts for both logs and metrics.
To add alertmanager to the current stack:
-
New file -
alertmanager.yml
to be bind mounted in alertmanager container.
This is the configuration on how and where to deliver alerts.
Correct smtp or ntfy info needs to be filled out.alertmanager.yml
route: receiver: 'email' receivers: - name: 'ntfy' webhook_configs: - url: 'https://ntfy.example.com/alertmanager' send_resolved: true - name: 'email' email_configs: - to: '[email protected]' from: '[email protected]' smarthost: smtp-relay.sendinblue.com:587 auth_username: '<[email protected]>' auth_identity: '<[email protected]>' auth_password: '<long ass generated SMTP key>'
-
New file -
alert.rules
to be bind mounted in to prometheus container
This file defines at what value a metric becomes an alert event.alert.rules
groups: - name: host rules: - alert: DiskSpaceLow expr: sum(node_filesystem_free_bytes{fstype="ext4"}) > 19 for: 10s labels: severity: critical annotations: description: "Diskspace is low!"
-
Changed
prometheus.yml
. Added alerting section that points to alertmanager container, and also set path to arules
file.prometheus.yml
global: scrape_interval: 15s evaluation_interval: 15s scrape_configs: - job_name: 'nodeexporter' static_configs: - targets: ['nodeexporter:9100'] - job_name: 'cadvisor' static_configs: - targets: ['cadvisor:8080'] - job_name: 'prometheus' static_configs: - targets: ['localhost:9090'] alerting: alertmanagers: - scheme: http static_configs: - targets: - 'alertmanager:9093' rule_files: - '/etc/prometheus/rules/alert.rules'
-
New container -
alertmanager
added to the compose file and prometheus container has bind mount rules file added.docker-compose.yml
services: # MONITORING SYSTEM AND THE METRICS DATABASE prometheus: image: prom/prometheus:v2.42.0 container_name: prometheus hostname: prometheus user: root restart: unless-stopped depends_on: - cadvisor command: - '--config.file=/etc/prometheus/prometheus.yml' - '--storage.tsdb.path=/prometheus' - '--web.console.libraries=/etc/prometheus/console_libraries' - '--web.console.templates=/etc/prometheus/consoles' - '--storage.tsdb.retention.time=240h' - '--web.enable-lifecycle' volumes: - ./prometheus_data:/prometheus - ./prometheus.yml:/etc/prometheus/prometheus.yml - ./alert.rules:/etc/prometheus/rules/alert.rules expose: - "9090" labels: org.label-schema.group: "monitoring" # ALERT MANAGMENT FOR PROMETHEUS alertmanager: image: prom/alertmanager:v0.25.0 container_name: alertmanager hostname: alertmanager user: root restart: unless-stopped volumes: - ./alertmanager.yml:/etc/alertmanager.yml - ./alertmanager_data:/alertmanager command: - '--config.file=/etc/alertmanager.yml' - '--storage.path=/alertmanager' expose: - "9093" labels: org.label-schema.group: "monitoring" networks: default: name: $DOCKER_MY_NETWORK external: true
-
Adding alertmanager to the Caddyfile of the reverse proxy so that it can be reached at
https://alert.example.com
. Not necessary, but useful as it allows to send alerts from anywhere, not just from prometheus, or other containers on same docker network.Caddyfile
alert.{$MY_DOMAIN} { reverse_proxy alertmanager:9093 }
Once above setup is done, an alert about low disk space should fire
and a notification email should come.
In alertmanager.yml
a switch from email to ntfy can be done.
Useful
- alert from anywhere using curl:
curl -H 'Content-Type: application/json' -d '[{"labels":{"alertname":"blabla"}}]' https://alert.example.com/api/v1/alerts
- reload rules:
curl -X POST https://prom.example.com/-/reload
stefanprodan/dockprom has more detailed section on alerting worth checking out.
Loki is a log aggregation tool, made by the grafana team.
Sometimes called a Prometheus for logs, it's a push type monitoring.
It uses LogQL for queries, which is similar to PromQL in its use of labels.
The official documentation overview
There are two ways to push logs to Loki from a docker container.
- Loki-docker-driver
installed on a docker host and log pushing is set either globally in
/etc/docker/daemon.json
or per container in compose files.
It's the simpler, easier way, but lacks fine control over the logs being pushed. - Promtail deployed as an another container, with bind mount of logs it should scrape, and bind mount of its config file. This config file is very powerful, giving a lot of control how logs are processed and pushed.
-
New container -
loki
added to the compose file.
Note the port 3100 is actually mapped to the host, allowinglocalhost:3100
from driver to work.docker-compose.yml
services: # LOG MANAGMENT WITH LOKI loki: image: grafana/loki:main-0295fd4 container_name: loki hostname: loki user: root restart: unless-stopped volumes: - ./loki_data:/loki - ./loki-config.yml:/etc/loki-config.yml command: - '-config.file=/etc/loki-config.yml' ports: - "3100:3100" labels: org.label-schema.group: "monitoring" networks: default: name: $DOCKER_MY_NETWORK external: true
-
New file -
loki-config.yml
bind mounted in the loki container.
The config here comes from the official example with some changes.- URL changed for this setup.
- Compactor section is added, to have control over data retention.
- Fixing error - "too many outstanding requests", discussion
here.
It turns off parallelism, both split by time interval and shards split.
loki-config.yml
auth_enabled: false server: http_listen_port: 3100 common: path_prefix: /loki storage: filesystem: chunks_directory: /loki/chunks rules_directory: /loki/rules replication_factor: 1 ring: kvstore: store: inmemory # --- disable splitting to fix "too many outstanding requests" query_range: parallelise_shardable_queries: false # --- compactor to have control over length of data retention compactor: working_directory: /loki/compactor compaction_interval: 10m retention_enabled: true retention_delete_delay: 2h retention_delete_worker_count: 150 limits_config: retention_period: 240h split_queries_by_interval: 0 # part of disable splitting fix # ------------------------------------------------------- schema_config: configs: - from: 2020-10-24 store: boltdb-shipper object_store: filesystem schema: v11 index: prefix: index_ period: 24h ruler: alertmanager_url: http://alertmanager:9093 analytics: reporting_enabled: false
-
-
Install loki-docker-driver
docker plugin install grafana/loki-docker-driver:latest --alias loki --grant-all-permissions
To check if it's installed and enabled:docker plugin ls
-
Containers that should be monitored usind loki-docker-driver need
logging
section in their compose.docker-compose.yml
services: whoami: image: "containous/whoami" container_name: "whoami" hostname: "whoami" logging: driver: "loki" options: loki-url: "http://localhost:3100/loki/api/v1/push"
-
-
-
Containers that should be monitored with promtail need it added to their compose file, and made sure that it has access to the log files.
minecraft-docker-compose.yml
services: minecraft: image: itzg/minecraft-server container_name: minecraft hostname: minecraft restart: unless-stopped env_file: .env tty: true stdin_open: true ports: - 25565:25565 # minecraft server players connect volumes: - ./minecraft_data:/data # LOG AGENT PUSHING LOGS TO LOKI promtail: image: grafana/promtail container_name: minecraft-promtail hostname: minecraft-promtail restart: unless-stopped volumes: - ./minecraft_data/logs:/var/log/minecraft:ro - ./promtail-config.yml:/etc/promtail-config.yml command: - '-config.file=/etc/promtail-config.yml' networks: default: name: $DOCKER_MY_NETWORK external: true
caddy-docker-compose.yml
services: caddy: image: caddy container_name: caddy hostname: caddy restart: unless-stopped env_file: .env ports: - "80:80" - "443:443" - "443:443/udp" volumes: - ./Caddyfile:/etc/caddy/Caddyfile - ./caddy_config:/data - ./caddy_data:/config - ./caddy_logs:/var/log/caddy # LOG AGENT PUSHING LOGS TO LOKI promtail: image: grafana/promtail container_name: caddy-promtail hostname: caddy-promtail restart: unless-stopped volumes: - ./caddy_logs:/var/log/caddy:ro - ./promtail-config.yml:/etc/promtail-config.yml command: - '-config.file=/etc/promtail-config.yml' networks: default: name: $DOCKER_MY_NETWORK external: true
-
Generic config file for promtail, needs to be bind mounted
promtail-config.yml
clients: - url: http://loki:3100/loki/api/v1/push scrape_configs: - job_name: blablabla static_configs: - targets: - localhost labels: job: blablabla_log __path__: /var/log/blablabla/*.log
-
- In grafana, loki needs to be added as a datasource,
http://loki:3100
- In Explore section, switch to Loki as source
- if loki-docker-driver then filter by
container_name
orcompose_project
- if promtail then filter by job name set in promtail config in the labels section
- if loki-docker-driver then filter by
If all was set correctly logs should be visible in Grafana.
What can be seen in this example:
- How to monitor logs of a docker container, a minecraft server.
- How to visualize the logs in a dashboard.
- How to set an alert when a specific pattern appears in the logs.
- How to extract information from log to include it in the alert notification.
- Basics of grafana alert templates, so that notifications actually look good, and show only relevant info.
Requirements - grafana, loki, minecraft.
The main objective is to get an alert when a player joins the server.
The secondary one is to have a place where recent "happening" on the server
can be seen.
Initially loki-docker-driver was used to get logs to Loki, and it was simple
and worked nicely. But during alert stage
I could not figure out how to extract string from logs and include it in
an alert notification. Specificly to not just say that "a player joined",
but to have there name of the player that joined.
Switch to promtail solved this, with the use of its
pipeline_stages.
Which was suprisingly simple and elegant.
Promtail container is added to minecraft's compose, with bind mount
access to minecraf's logs.
minecraft-docker-compose.yml
services:
minecraft:
image: itzg/minecraft-server
container_name: minecraft
hostname: minecraft
restart: unless-stopped
env_file: .env
tty: true
stdin_open: true
ports:
- 25565:25565 # minecraft server players connect
volumes:
- ./minecraft_data:/data
# LOG AGENT PUSHING LOGS TO LOKI
promtail:
image: grafana/promtail
container_name: minecraft-promtail
hostname: minecraft-promtail
restart: unless-stopped
volumes:
- ./minecraft_data/logs:/var/log/minecraft:ro
- ./promtail-config.yml:/etc/promtail-config.yml
command:
- '-config.file=/etc/promtail-config.yml'
networks:
default:
name: $DOCKER_MY_NETWORK
external: true
Promtail's config is similar to the generic config in the previous section.
The only addition is a short pipeline stage with a regex that runs against
every log line before sending it to Loki. When a line matches, a label player
is added to that log line.
The value of that label comes from the named capture group thats part of
that regex, the syntax
is: (?P<name>group)
This label will be easy to use later in the alert stage.
promtail-config.yml
clients:
- url: http://loki:3100/loki/api/v1/push
scrape_configs:
- job_name: minecraft
static_configs:
- targets:
- localhost
labels:
job: minecraft_logs
__path__: /var/log/minecraft/*.log
pipeline_stages:
- regex:
expression: .*:\s(?P<player>.*)\sjoined the game$
- labels:
player:
Here's regex101 of it,
with some data to show how it works and bit of explanation.
Here's
the stackoverflow answer that is the source for that config.
- If Loki is not yet added, it needs to be added as a datasource,
http://loki:3100
- In Explore section, filter, job =
minecraft_logs
, Run query button... this should result in seeing minecraft logs and their volume/time graph.
This Explore view will be recreated as a dashboard.
- New dashboard, new panel
- Graph type -
Time series
- Data source - Loki
- Switch from
builder
tocode
- query -
count_over_time({job="minecraft_logs"} |= `` [1m])
Query options
- Min interval=1m- Transform - Rename by regex
Match -
(.*)
Replace -Logs
- Title - Logs volume
- Transparent background
- Legend off
- Graph styles - bar
- Fill opacity - 50
- Color scheme - single color
- Save
- Graph type -
- Add another panel
- Graph type -
Logs
- Data source - Loki
- Switch from
builder
tocode
query -{job="minecraft_logs"} |= ""
- Title - empty
- Deduplication - Signature or Exact
- Save
- Graph type -
This should create a similar dashboard to the one in the picture above.
Performance tips for grafana loki queries
When a player joins minecraft server a log line appears "Bastard joined the game"
An Alert will be set to detect string "joined the game" and send
a notification when it occurs.
Now, might be good time to brush up on PromQL / LogQL and the data types they return when a query happens. That instant vector and range vector thingie. As grafana will scream when using range vector.
- 1 Set an alert rule name
- Rule name = Minecraft-player-joined-alert
- 2 Set a query and alert condition
- A - Switch to Loki; set Last 5 minutes
- switch from builder to code
count_over_time({job="minecraft_logs"} |= "joined the game" [5m])
- B - Reduce
- Function = Last
- Input = A
- Mode = Strict
- C - Treshold
- Input = B
- is above 0
- Make this the alert condition
- A - Switch to Loki; set Last 5 minutes
- 3 Alert evaluation behavior
- Folder = "Alerts"
- Evaluation group (interval) = "five-min"
- Evaluation interval = 5m
- For 0s
- Configure no data and error handling
- Alert state if no data or all values are null = OK
- 4 Add details for your alert rule
- Here is where the label
player
that was set in promtail is used
Summary ={{ $labels.player }} joined the Minecraft server.
- Can also pass values from expressions by targeting A/B/C/.. from step2
Description =Number of players that joined in the last 5 min: {{ $values.B }}
- Here is where the label
- 5 Notifications
- nothing
- Save and exit
- New contact point
- Name = ntfy
- Integration = Webhook
- URL =
https://ntfy.example.com/grafana
or if grafana-to-ntfy is already setup thenhttp://grafana-to-ntfy:8080
but also credentials need to be set. - Title =
{{ .CommonAnnotations.summary }}
- Message = I put in empty space unicode character
- Disable resolved message = check
- Test
- Save
- Edit default
- Default contact point = ntfy
- Save
After all this, there should be notification coming when a player joins.
For alerts one can use
ntfy
but on its own alerts from grafana are just plain text json.
Here's
how to setup grafana-to-ntfy, to make alerts look good.
Not really used here, but they are pain and there's some info
as it took embarrassingly long to find that
{{ .CommonAnnotations.summary }}
for the title.
- Testing should be done in contact point when editing, useful Test button that allows you to send alerts with custom values.
- To define a template.
- To call a template.
- My big mistake when playing with this was missing a dot.
In Contact point, in Title/Message input box.- correct one -
{{ template "test" . }}
- the one I had -
{{ template "test" }}
- correct one -
- So yeah, dot is important in here. It represents data and context
passed to a template. It can represent global context, or when used inside
{{ range }}
it represents iteration loop value. - This json structure is what an alert looks
like. Notice
alerts
being an array andcommonAnnotations
being object. For array theres need to loop over it to get access to the values in it. For objects one just needs to target the name from global context.. using dot at the beginning. - To iterate over alerts array.
- To just access a value -
{{ .CommonAnnotations.summary }}
- Then theres conditional things one can do in golang templates, but I am not going to dig that deep...
Templates resources
- Overview of Grafana Alerting and Message Templating for Slack
- youtube - Unified Alerting Grafana 8 | Prometheus | Victoria | Telegraf | Notifications | Alert Templating
- Dot notation
- video - Annotations and Alerts tutorial for Grafana with Timescale
What can be seen in this example:
- Use of Prometheus to monitor a docker container - caddy.
- How to import a dashobard to grafana.
- Use of Loki to monitor logs of a docker container.
- How to set Promtail to push only certain values and label logs.
- How to use geoip part of Promtail.
- How to create dashboard in grafana from data in Loki.
Requirements - grafana, loki, caddy.
Reverse proxy is kinda linchpin of a selfhosted setup as it is in charge of all the http/https traffic that goes in. So focus on monitoring this keystone makes sense.
Requirements - grafana, prometheus, loki, caddy container
Caddy has build in exporter of metrics for prometheus, so all that is needed is enabling it, scrape it by prometheus, and import a dashboard.
-
Edit Caddyfile to enable metrics.
Caddyfile
{ servers { metrics } admin 0.0.0.0:2019 } a.{$MY_DOMAIN} { reverse_proxy whoami:80 }
-
Edit compose to publish 2019 port.
Likely not necessary if Caddy and Prometheus are on the same docker network, but its nice to check if the metrics export works at<docker-host-ip>:2019/metrics
docker-compose.yml
services: caddy: image: caddy container_name: caddy hostname: caddy restart: unless-stopped env_file: .env ports: - "80:80" - "443:443" - "443:443/udp" - "2019:2019" volumes: - ./Caddyfile:/etc/caddy/Caddyfile - ./caddy_config:/data - ./caddy_data:/config networks: default: name: $DOCKER_MY_NETWORK external: true
-
Edit prometheus.yml to add caddy scraping point
prometheus.yml
global: scrape_interval: 15s evaluation_interval: 15s scrape_configs: - job_name: 'caddy' static_configs: - targets: ['caddy:2019']
-
In grafana import caddy dashboard
But these metrics are about performance and load put on Caddy,
which in selfhosted environment will likely be minimal and not interesting.
To get more intriguing info of who, when, from where, connects
to what service,.. well for that monitoring of access logs is needed.
Loki itself just stores the logs. To get them to Loki a Promtail container is used
that has access to caddy's logs. Its job is to scrape them regularly, maybe
process them in some way, and then push them to Loki.
Once there, a basic grafana dashboard can be made.
-
Have Grafana, Loki, Caddy working
-
Edit Caddy compose, bind mount
/var/log/caddy
.
Add to the compose also Promtail container, that has the same logs bind mount, along with bind mount of its config file.
Promtail will scrape logs to which it now has access and pushes them to Loki.docker-compose.yml
services: caddy: image: caddy container_name: caddy hostname: caddy restart: unless-stopped env_file: .env ports: - "80:80" - "443:443" - "443:443/udp" - "2019:2019" volumes: - ./Caddyfile:/etc/caddy/Caddyfile - ./caddy_data:/data - ./caddy_config:/config - ./caddy_logs:/var/log/caddy # LOG AGENT PUSHING LOGS TO LOKI promtail: image: grafana/promtail container_name: caddy-promtail hostname: caddy-promtail restart: unless-stopped volumes: - ./promtail-config.yml:/etc/promtail-config.yml - ./caddy_logs:/var/log/caddy:ro command: - '-config.file=/etc/promtail-config.yml' networks: default: name: $DOCKER_MY_NETWORK external: true
promtail-config.yml
clients: - url: http://loki:3100/loki/api/v1/push scrape_configs: - job_name: caddy_access_log static_configs: - targets: - localhost labels: job: caddy_access_log host: example.com agent: caddy-promtail __path__: /var/log/caddy/*.log
-
Promtail scrapes a logs, one line at the time and is able to do neat things with it before sending it - add labels, ignore some lines, only send some values,...
Pipelines are used for this. Bellow is an example of extracting just a single value - an IP address and using it in a tempalte that gets send to Loki and nothing else. Here's some more to read on this.promtail-config.yml customizing fields
clients: - url: http://loki:3100/loki/api/v1/push scrape_configs: - job_name: caddy_access_log static_configs: - targets: - localhost labels: job: caddy_access_log host: example.com agent: caddy-promtail __path__: /var/log/caddy/*.log pipeline_stages: - json: expressions: request_remote_ip: request.remote_ip - template: source: output # creates empty output variable template: '{"remote_ip": {{.request_remote_ip}}}' - output: source: output
-
Edit
Caddyfile
to enable access logs. Unfortunately this can't be globally enabled, so the easiest way seems to be to create a logging snippet calledlog_common
and copy paste the import line in to every site block.Caddyfile
(log_common) { log { output file /var/log/caddy/caddy_access.log } } ntfy.example.com { import log_common reverse_proxy ntfy:80 } mealie.{$MY_DOMAIN} { import log_common reverse_proxy mealie:80 }
-
at this points logs should be visible and explorable in grafana
Explore >{job="caddy_access_log"} |= "" | json
Promtail got recently a geoip stage. One can feed it an IP address and an mmdb geoIP database and it adds geoip labels to the log entry.
-
Register a free account on maxmind.com.
-
Download one of the mmdb format databases
GeoLite2 City
- 70MB full geoip info - city, postal code, time zone, latitude/longitude,..GeoLite2 Country
6MB, just country and continent
-
Bind mount whichever database in to promtail container.
docker-compose.yml
services: caddy: image: caddy container_name: caddy hostname: caddy restart: unless-stopped env_file: .env ports: - "80:80" - "443:443" - "443:443/udp" - "2019:2019" volumes: - ./Caddyfile:/etc/caddy/Caddyfile - ./caddy_data:/data - ./caddy_config:/config - ./caddy_logs:/var/log/caddy # LOG AGENT PUSHING LOGS TO LOKI promtail: image: grafana/promtail container_name: caddy-promtail hostname: caddy-promtail restart: unless-stopped volumes: - ./promtail-config.yml:/etc/promtail-config.yml - ./caddy_logs:/var/log/caddy:ro - ./GeoLite2-City.mmdb:/etc/GeoLite2-City.mmdb:ro command: - '-config.file=/etc/promtail-config.yml' networks: default: name: $DOCKER_MY_NETWORK external: true
-
In promtail config, json stage is added where IP address is loaded in to a variable called
remote_ip
, which then is used in geoip stage. If all else is set correctly, the geoip labels are automaticly added to the log entry.geoip promtail-config.yml
clients: - url: http://loki:3100/loki/api/v1/push scrape_configs: - job_name: caddy_access_log static_configs: - targets: - localhost labels: job: caddy_access_log host: example.com agent: caddy-promtail __path__: /var/log/caddy/*.log pipeline_stages: - json: expressions: remote_ip: request.remote_ip - geoip: db: "/etc/GeoLite2-City.mmdb" source: remote_ip db_type: "city"
Can be tested with opera build in VPN, or some online site tester.
-
new panel, will be time series graph showing Subdomains hits timeline
- Graph type = Time series
- Data source = Loki
- switch from builder to code
sum(count_over_time({job="caddy_access_log"} |= "" | json [1m])) by (request_host)
- Query options > Min interval = 1m
- Transform > Rename by regex
- Match =
\{request_host="(.*)"\}
- Replace =
$1
- Match =
- Title = "Subdomains hits timeline"
- Transparent
- Tooltip mode = All
- Tooltip values sort order = Descending
- Legen Placement = Right
- Value = Total
- Graph style = Bars
- Fill opacity = 50
-
Add another panel, will be a pie chart, showing subdomains divide
- Graph type = Pie chart
- Data source = Loki
- switch from builder to code
sum(count_over_time({job="caddy_access_log"} |= "" | json [$__range])) by (request_host)
- Query options > Min interval = 1m
- Transform > Rename by regex
- Match =
\{request_host="(.*)"\}
- Replace =
$1
- Match =
- Title = "Subdomains divide"
- Transparent
- Legend Placement = Right
- Value = Last
-
Add another panel, will be a Geomap, showing location of machine accessing Caddy
- Graph type = Geomap
- Data source = Loki
- switch from builder to code
{job="caddy_access_log"} |= "" | json
- Query options > Min interval = 1m
- Transform > Extract fields
- Source = labels
- Format = JSON
-
- Field =
geoip_location_latitude
; Alias =latitude
- Field =
-
- Field =
geoip_location_longitude
; Alias =longitude
- Field =
- Title = "Geomap"
- Transparent
- Map view > View > Drag and zoom around > Use current map setting
-
Add another panel, will be a pie chart, showing IPs that hit the most
- Graph type = Pie chart
- Data source = Loki
- switch from builder to code
sum(count_over_time({job="caddy_access_log"} |= "" | json [$__range])) by (request_remote_ip)
- Query options > Min interval = 1m
- Transform > Rename by regex
- Match =
\{request_remote_ip="(.*)"\}
- Replace =
$1
- Match =
- Title = "IPs by number of requests"
- Transparent
- Legen Placement = Right
- Value = Last or Total
-
Add another panel, this will be actual log view
- Graph type - Logs
- Data source - Loki
- Switch from builder to code
- query -
{job="caddy_access_log"} |= "" | json
- Title - empty
- Deduplication - Exact or Signature
- Save
Manual image update:
docker-compose pull
docker-compose up -d
docker image prune
Using borg that makes daily snapshot of the entire directory.
- down the containers
docker-compose down
- delete the entire monitoring directory
- from the backup copy back the monitoring directory
- start the containers
docker-compose up -d