![]() ![]() > There is an exporter for cloudwatch which exports the cloudwatch data to prometheus, but is there an opposite solution? While I collect data from other source to prometheus and publish it to cloudwatch? > On Wednesday, Octoat 2:02:17 PM UTC-7, Brian Brazil wrote: Finally, we will expose gathered metrics with “yield”.On Wednesday, Octoat 2:15:29 PM UTC-7, Brian Brazil wrote: We will loop over every function and gather metrics from working functions (If worker_pids exist this means function is running). We will define 4 metrics to gather function status (is it working or not), backlog value, failure, and the number of processed events for that function. ![]() We will check if “eventing” exists in installed services then we gather information from 8096 port /api/v1/stats endpoint. Now we can start with gathering eventing stats. responseNodesInfo = json.loads(requests.get(‘ auth= (‘User’, ‘Password’)).code(‘UTF-8’)) for cbnode in responseNodesInfo: if “thisNode” in cbnode: nodeServices = cbnode To find our local node in the list we will check if “thisNode” key exists. This endpoint returns all nodes in a cluster. ( Endpoint list) We will use nodes response from “/pools/nodes”. You can reach very useful stats via REST endpoints. To start, we need to get services installed in our local node. While it also provides a total count of observations and a sum of all observed values, it calculates configurable quantiles over a sliding time window. Summary: Similar to a histogram, a summary samples observations (usually things like request durations and response sizes). It also provides a sum of all observed values. Histograms: A histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. Gauges are typically used for measured values like temperatures or current memory usage, but also “counts” that can go up and down, like the number of concurrent requests. Gauges: A gauge is a metric that represents a single numerical value that can arbitrarily go up and down. For example, you can use a counter to represent the number of requests served, tasks completed, or errors. There are 4 metrics you can define in a client Counter, Gauge, Summary, and Histogram.Ĭounters: A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart. When you expose important metrics through a client, Prometheus scrapes those metrics’ current state in defined intervals. is the official Prometheus client python library to expose metrics over HTTP on the desired server. #Prometheus cloudwatch exporter installSecondly, we will install prometheus_client and requests to get and parse responses from Couchbase’s endpoints pip3 install prometheus_client pip3 install requests ![]() Let’s start by creating and activating a virtual env named “envcbexp” for our exporter in desired OS python3 -m venv envcbexp source. In this example, we will create a custom exporter which gets metrics from Couchbase REST endpoints and export those metrics with the Prometheus client for Python. You can do it with Prometheus client libraries. So you want to create your own exporter for some reason. But let's say there’s an urgent situation, you need to watch this metric very bad or this metric is about your app only. Of course, you can create an issue about it and wait for the next release or If you have experience with Open Source projects and the programming language of the project, you can make a contribution. For OS metrics we use node exporters and for database metrics we use exporters for Couchbase.īut sometimes, you may not find your “very important” metric in published exporters. Also, we are using Alertmanager to define alerts for our systems. In Trendyol, we are using Grafana and Prometheus as the primary monitoring solution. ![]()
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