sealed-secrets VS prometheus

External-Secrets Operator : A Kubernetes operator that integrates external secret management systems like AWS Secrets Manager, HashiCorp Vault, Google Secrets Manager, and many more. The operator reads information from external APIs and automatically injects the values into a Kubernetes Secret (Alternatives : Vault, SOPS, Sealed Secrets)

If you have noticed, you are setting secrets in plain text on the application-configmap.yml file, which is not ideal and is not a best practice for security. The best way to do this securely would be to use AWS Secrets Manager, an external service like HashiCorp Vault, or Sealed Secrets. To learn more about these methods see the blog post Shhhh... Kubernetes Secrets Are Not Really Secret!.

Yeah documentation is hard and I'm guilty (as a former maintainer of SealedSecrets)

SealedSecrets was designed with "write only" secrets in mind.

Turns out a lot of people need to access the current secrets because they need to update a part of a "composite" secret.

There are two kinds of "composite" secrets, one easy and one harder, but if you don't know how to do it, even the easier is hard:

1. Secret with multiple data "items" (also called keys in K8s Secret jargon but that's confusing when there is encryption involved). I.e. good old "data":{"foo": "....", "bar": "..."}

2. Secrets where data within one item is actually a config file with cleartext and secrets mixed up in one single string (usually some JSON or YAML or TOML)

Case 1 is "easy" to deal with once you realize that sealed secrets files are just text files and you can just manually merge and update encryoted data items. We even created a "merge" and some "raw" encryption APIs to make that process a little less "copy pasta" but it's still hard to have a good UX that works for everyone.

Case 2 is harder. We did implement a data templating feature that allows you to generate a config file via a go-template that keeps the cleartext parts in clear and uses templating directives to inject the secret parts where you want (referencing the encrypted the items)

The main problem with case 2 is that it's undocumented.

The feature landed in 2021:

https://github.com/bitnami-labs/sealed-secrets/pull/580

I noticed that people at my current $dayjob used sealed secrets for years and it took me a while to understand that the reason they hated it was that they didn't know about that fundamental feature.

And how to blame them!? It's still undocumented!

In my defense I spent so much effort before and after I left VMware to lobby so that the project got the necessary staffing so it wouldn't die of bitrot that I didn't have much time left to work on documentation. Which is a bit said and probably just an excuse :-)

That said, I'm happy that the project is alive and the current maintainers are taking care of it against the forces of entropy. Perhaps some doc work would be useful too. Unfortunately I don't have time for now.

This might be OT, and forgive me, but I think one of the best practices for Encrypting and Managing secrets in Kubernetes is to use Sealed Secrets, they allow your secrets to be securely stored in git with the rest of the configuration and yet no one with access to the Git repository will be able to read them. I say this might be OT, because Sealed Secrets are trying to mitigate a different threat, the threat of the secrets at rest somewhere, and not "live in the cluster", where in theory all the ingredients to decrypt the secrets would still live.

The addition of Consul and Vault gives me a few things. For one, right now I'm handling secrets with a mixture of SOPS and Sealed Secrets. I use Vault in my professional life, and have used both Vault and Consul at my last job. Vault is a beast, so I may as well get better at it; plus its options for secret injection are better.

Use Sealed Secrets Operator.

sealed-secrets (sealed)

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

Prometheus: Open-source monitoring system. Often used together with Grafana.