Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the ajax-load-more-anything domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home/devwp/public_html/p225-newweb/wp-includes/functions.php on line 6114

Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the wordpress-seo domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home/devwp/public_html/p225-newweb/wp-includes/functions.php on line 6114
How to obtain the metrics for SLO tracking - Vsceptre

How to obtain the metrics for SLO tracking

5 May 2023

Blog, News

How to obtain the metrics for SLO tracking
This is part 2 of the 3 part series “The path to your first SLO”.

When you have a clear understanding of what metrics to gather for SLO, the next question is how to obtain and gather those metrics. Basically the metrics can be obtained by the following methods.

Metrics from commercial APM/ Observability tools,
Commercial monitoring tools offer one stop shop to gather infrastructure metrics from machine agents, cluster agents or in terms of public cloud platforms, those will be metrics from AWS CloudWatch or Azure Monitor. For application metrics, usually the same APM agent can generate application specific metrics derived from logs or traces. Usually these contribute to the 4 golden signals we discussed in the previous post.
You can now build dashboards directly from the commercial APM tools to utilize those metrics. Metrics can also be retrieved through APIs for external consumption.

Metrics from siloed data sources
They are usually from systems in your organization that have no full featured APM tools in place. Today it is common for applications to expose Prometheus compatible metrics ( a de facto standard to allow metrics to be scrapped for monitoring by Prometheus ) to fulfill simple monitoring use cases. Grafana then fills the gap on time series visualization and alerting.

Metrics from E2E testing and synthetic tools
Synthetic testing tools can provide valuable insight on service availability, response time and customer experience. These metrics can also be a source of SLO. Commercial solutions include ThousandEyes and SolarWinds PingDom.

If you have multiple monitoring tools it is wise to consolidate all these metrics into a single dashboard for alerting and visualization. Examples are Grafana and Nobl9 which can help to
Consolidate metrics from multiple tools into a single dashboard.
Offers pre-built SLO dashboards or flexibility to easily build SLO dashboards
As a summary, the goal is to streamline the process of obtaining the metrics from multiple systems and quickly realize the benefits of SLO tracking. In the next article, we will look at a real example of utilizing Nobl9 for a simple service availability SLO.

New to SLO?
#SLOconf is a free, virtual event focused on #SLOs! 🔥
Whether you are doing SRE, SLO, or DevOps, or Ops, or a Dev – SLOconf is the perfect platform to share insights and ideas on the latest trends and developments in SRE/SLO.
Vsceptre is a sponsor at SLOconf 2023, hosted by Nobl9! 📢
For more details & speaker lineup, register here: 👇
www.sloconf.com

Related Articles

Demystifying Log to Trace correlation in DataDog

Demystifying Log to Trace correlation in DataDog

At around end of March, I want to get my hands on the old raspberry pi cluster again as I need a testbed for K8S, ChatOps, CI/CD etc. The DevOps ecosystem in 2023 is more ARM ready compared with 2020 which makes building a usable K8S stack on Pi realistic. I upgraded from a 4 nodes cluster to a 7 Pi4 nodes with POE capabilities, SSD, USB and sitting inside a nice 1U rack. Then spending the next two months’ time on testing various OS. Re-installing the whole stack multiple times and struggling with the home router is fun. At the end the cluster is up with all platform engineering tools deployed.

Log Sensitive Data Scrubbing and Scanning on Datadog

Log Sensitive Data Scrubbing and Scanning on Datadog

In today’s digital landscape, data security and privacy have become paramount concerns for businesses and individuals alike. With the increasing reliance on cloud-based services and the need to monitor and analyze application logs, it is crucial to ensure that sensitive data remains protected. Datadog offers robust features to help organizations track and analyze their logs effectively.

Monitoring temperature of my DietPi Homelab cluster with Grafana Cloud

Monitoring temperature of my DietPi Homelab cluster with Grafana Cloud

At around end of March, I want to get my hands on the old raspberry pi cluster again as I need a testbed for K8S, ChatOps, CI/CD etc. The DevOps ecosystem in 2023 is more ARM ready compared with 2020 which makes building a usable K8S stack on Pi realistic. I upgraded from a 4 nodes cluster to a 7 Pi4 nodes with POE capabilities, SSD, USB and sitting inside a nice 1U rack. Then spending the next two months’ time on testing various OS. Re-installing the whole stack multiple times and struggling with the home router is fun. At the end the cluster is up with all platform engineering tools deployed.

This site is registered on wpml.org as a development site.

Notice: ob_end_flush(): failed to send buffer of zlib output compression (1) in /home/devwp/public_html/p225-newweb/wp-includes/functions.php on line 5464

Notice: ob_end_flush(): failed to send buffer of zlib output compression (1) in /home/devwp/public_html/p225-newweb/wp-includes/functions.php on line 5464