pushgateway | Push acceptor for ephemeral and batch jobs | Continuous Deployment library

Grafana Agent works with the same metric format Prometheus does. It is focused on scraping metrics instead of Prometheus and pushing them (remote_write) to the Prometheus instance that Grafana Cloud hosts for you. This is mentioned in the list of product features.

You can use Prometheus PHP library to create metrics and avoid troubles with the raw format. The best practices are also applicable.

Once you are done with creating metrics, you need to instruct the agent to scrape them from your server. Use these docs (one, two) for reference.

What you probably (!?) want is something that:

1. Provides an HTTP(s) (e.g. /metrics) endpoint
2. Producing metrics in Prometheus' exposition format
3. From Zendesk's API

NOTE curl only gives you #3

There are some examples of solutions that appear to meet the requirements but none is from Zendesk:

https://www.google.com/search?q=%22zendesk%22+prometheus+exporter

There are >2 other lists of Prometheus exporters (neither contains Zendesk):

• https://prometheus.io/docs/instrumenting/exporters/
• https://github.com/prometheus/prometheus/wiki/Default-port-allocations

I recommend you contact Zendesk and ask whether there's a Prometheus Exporter already. It's surprising to not find one.

It is straightforward to write a Prometheus Exporter. Prometheus Client libraries and Zendesk API client are available and preferred. While it's possible, bash is probably sub-optimal.

If all you want to do is GET that static endpoint, get a 200 response code and confirm that the body is [], you may be able to use Prometheus Blackbox exporter

NOTE Logging and monitoring tools often provide a higher-level tool that provides something analogous to a "universal translator", facilitating translation from 3rd-party systems' native logging|monitoring formats into some canonical form using config rather than code. Although in the logging space, fluentd is an example. To my knowledge, there is no such tool for Prometheus but I sense that there's an opportunity for someone to create one.

You can use metric_relabel_configs to rewrite labels after scraping. An example:

If your problem is too complex, divide it into smaller, more manageable pieces and see what they do. Start by analysing output from the awk part.

AWK can be a bit of a handful.

Try a simpler approach:

This problem has always existed, However, it was not described in the previous v1.13 documents. you can see the pull request to get more info.

If you want to use push model in your Flink cluster, i recommend use influxdb.

Accordingly, to the Loki documentation, metrics must be pushed to Prometheus, Cortex, or Thanos:

With recording rules, you can run these metric queries continually on an interval and have the resulting metrics written to a Prometheus-compatible remote-write endpoint. They produce Prometheus metrics from log entries.

At the time of writing, these are the compatible backends that support this:

• Prometheus (>=v2.25.0)
• Cortex
• Thanos (Receiver)

In general, it's hard to modify the output of a Helm chart. You can configure things the chart author has specifically allowed using Helm template syntax but not make arbitrary changes.

Typically I would expect a chart to not include an explicit namespace: at all, and to honor the helm install --namespace option (helm template has a similar option). Configuring a Service is extremely common and I would expect the chart to have settings for that.

If you're using the official GitLab cloud native Helm Chart then it has a lot of settings, including specifically for the GitLab Shell chart. In your values.yaml file you should be able to specify

With what you afforded as next, in fact you are using multi-stage-build, but only the last image will be act as the base image of final produced image. The final produced image won't have anything which in the former 3 images, unless you explicitly copy things to the last stage. So this definitely won't meet your requirement:

First of all, the rate() function calculate the per-second rate of increase of a counter. That is, even if your counter values were accurate, you would get the number of deployments happening per second (during the past 24 hours), and not per day.

If you want to calculate the number of deployments during the past 24 hours, there's the increase() function: increase(deployments_count[24h]).

But the reason that your current expression yields 0, is that the counter value always is 1. A counter must be incremented on every occurrence of an event (see Prometheus docs).

That is, you must somehow keep track of the current value of the counter and increment it on every deployment before pushing it to the Pushgateway, rather than just pushing 1 on every event. The latter approach doesn't work and it looks to Prometheus as if the value never changes.

There are two possible approaches for addressing this:

1. Not using a Pushgateway

Are you sure you need a Pushgateway or can you incorporate a Prometheus client library in your code? Check When to use the Pushgateway, and, in particular, a Pushgateway is not a distributed counter. In essence, the use case for a Pushgateway is for ephemeral jobs that need to deposit their metrics somewhere before they terminate.

If your code is permanently running, on the other hand, a Prometheus client library takes care of the counter incrementation logic and exposes the metric so that it can be directly scraped by Prometheus.

2. Keep track of counter value

If you must use a Pushgateway, you need to keep track of the current counter value so that you can increment it. You can either do it in your code, or query the current value from the Pushgateway itself, increment it, and push it back. Both of these approaches run into problems when there are multiple processes contributing to the counter (i.e. concurrent updates, race conditions).