20 posts tagged with "monitoring"

Introduction​

The role of third-party SaaS and cloud services in the modern software development stack needs no explanation. Primarily due to the ease of setting up and hooking them together, they make the software development lifecycle (SDLC) much easier than it was 10 years ago. No more managing the overhead of installing, configuring, maintaining, backing up, and scaling of source code repos, virtual machines, and CI/CD systems. Some services don't have any in-house options, e.g. payment gateways.

This dependency on third-party services also brings in risk. The more such services in the chain, the more likely it is that a failure in one of them will impact or even cripple your smoothly running development and deployment pipeline. And by extension, your business and customers.

You have vetted and chosen reliable services. However, outages happen. The best you can do is to prepare for them and know when they occur. This article is about the knowing part.

Introduction​

For the last two months, we have focused on improving the onboarding experience for users so that they can get started with monitoring with minimal effort. We have also added several improvements in the backend to make the service more robust and reliable. Some of the usability improvements are driven by user feedback. Others incorporate what we would personally like to see in such a monitoring service. We have also improved the dashboard user experience.

Introduction​

This article is part of a series on setting up an end-to-end monitoring and alerting stack using Prometheus.

Continuing our series on setting Prometheus in a Docker container, we will add a Grafana instance to our Prometheus setup.

Please refer to the previous article where we use docker compose to run Prometheus and Alertmanager together as that forms the basis to run multiple related containers. We will add a container to run Grafana to the same compose file in this article.

Introduction​

A status page forms a key part of your incident communication strategy. When it comes to setting up a status page, you have two options:

• Host your own - using either an open source project or a custom solution.
• Use a managed status page provider.

We will examine the pros and cons of each option along these dimensions:

1. Feature Set
2. Service Related

For 1, if you choose a self-managed, open-source or custom solution, it's in your control. For a managed solution, you are limited by the provider's feature set.

For 2, if you choose a self-managed solution, your team is responsible for the quality of the service. For a managed solution, you are dependent on the provider's service quality.

In most cases, you are better off using a managed solution from a reputed provider, unless you have:

• Specific requirements that are not met by the vendor.
• Budget constraints.

Introduction​

If you manage applications running on cloud platforms, you likely depend on multiple cloud vendors and services. These could be infrastructure providers like AWS, GCP or Azure. A vulnerability in any of these services could potentially impact your applications and your users.

A cloud platform has many moving parts, many of which are dependent on other third-party providers. For example:

• Operating system images for VMs which are maintained by third-party vendors.
• Container images which are hosted on external repositories.
• Software stacks which are maintained by other vendors but available for deployment on the cloud provider.
• Libraries used by the cloud provider's internal software which are maintained by other developers or organizations.
• Control plane software like Kubernetes.
• Hardware, like processors, which are provided by the manufacturer.
• Hypervisors which are developed and maintained by third-party vendors.
• Networking hardware manufactured by other vendors.

Introduction​

This article is part of a series on setting up an end-to-end monitoring and alerting stack using Prometheus.

Continuing our series on setting up Prometheus in a container, this article provides a step-by-step guide for how to configure alerts in Prometheus. We will add alerting rules and deploy Prometheus Alertmanager with Slack integration.

If you follow the steps in this article, you will end up with a containerized setup for:

1. A Prometheus instance with alerting rules.
2. An Alertmanager instance which can send alerts originating from those rules to a Slack channel.

Let's get started.

Introduction​

This article is part of a series on setting up an end-to-end monitoring and alerting stack using Prometheus.

There are different ways you can use to deploy the Prometheus monitoring tool in your environment. One of the fastest ways to get started is to deploy it as a Docker container. This guide shows you how to quickly set up a minimal Prometheus on your laptop. You can then extend that setup to add a monitoring dashboard, alerting, and authentication.

Introduction​

This article is part of a series on setting up an end-to-end monitoring and alerting stack using Prometheus.

The Prometheus monitoring tool can store its metrics either locally or remotely. You can configure a remote data store using the remote_write configuration. This article describes the various data store options available as well as how to set up a remote store.

Overview of Remote Storage​

By default, Prometheus stores data locally wherever it is installed. The data directory can be configured by using the --storage.tsdb.path command line option when starting Prometheus. In practice you can use a separate disk for higher performance attached to the machine where Prometheus is running.

However, this may not be possible or optimal in all situations as you might want a data store that is more suited for time series data, and has larger storage capabilities for higher data retention. Prometheus would usually run in a standalone VM or a Kubernetes pod or a Docker container, and it would not have access to such data stores by default.

A remote store can add these capabilities to Prometheus. The remote storage option can be set by using the remote_write key in the Prometheus configuration YAML file.

Introduction​

This article is part of a series on setting up an end-to-end monitoring and alerting stack using Prometheus.

Service discovery (SD) is a mechanism by which the Prometheus monitoring tool can discover monitorable targets automatically. Instead of listing down each and every target to be scraped in the Prometheus configuration, service discovery acts as a source of targets that Prometheus can query at runtime.

Service discovery becomes crucial when there are dynamically changing hosts, especially in microservices architectures and environments like Kubernetes. In Prometheus parlance, service discovery is a way of discovering "scrape targets".

For example, pods are created dynamically in Kubernetes as a result of new services being deployed and undeployed, autoscaling events, and errors causing pods to crash and go away. If you are using Prometheus for scraping pods in such an environment, Prometheus has to know which pods are running and scrapable at any given point in time. The Kubernetes service discovery pluging enables this. Similarly, there are SD plugins for other common environments.

You can use service discovery in Prometheus with the predefined plugins, or write your own custom ones using file or HTTP, depending on the situation.

Introduction​

Maintaining transparent communication about service availability is crucial for businesses of all sizes. Status pages are an important part of your communication strategy during times of outages and maintenance events.

You can choose to go with a fully managed status page provider, or host an open-source one yourself.

Open source status page providers offer a cost-effective and customizable solution. However, then can come with their own drawbacks. This guide explores open source status page providers in 2024 to help you choose the right tool for your needs.