clair VS Grafana

Besides pointing pentester tools like metasploit at yourself, there are some nice scanners out there.

https://github.com/quay/clair

https://github.com/anchore/grype/

Clair. Vulnerability Static Analysis for Containers.

https://github.com/quay/clair 9.4k stars, updated 17 hours ago

It scaled well compared to a naive graph abstraction implemented outside the database, but when performance wasn't great, it REALLY wasn't great. We ended up throwing it out in later versions to try and get more consistent performance.

I've since worked on SpiceDB[1] which takes the traditional design approach for graph databases and simply treating Postgres as triple-store and that scales far better. IME, if you need a graph, you probably want to use a database optimized for graph access patterns. Most general-purpose graph databases are just bags of optimizations for common traversals.

[0]: https://github.com/quay/clair

[1]: https://github.com/authzed/spicedb

Clair GitHub

Open source: Trivy, Gryp and Clair are widely used open source tools for container scanning.

Testing the image with github.com/fullhunt/log4j-scan and https://github.com/quay/clair shows no vulnerabilities

Amazon Elastic Container Registry is a fully-managed Docker container registry. It makes it easy for developers to store and manage Docker images inside their AWS environment. ECR supports two types of image scanning. Enhanced image scanning requires an integration with Amazon Inspector. It will scan your repositories continuously. Basic image scanning will use the Common Vulnerabilities and Exposures (CVEs) database (open-source Clair) to find vulnerabilities in your images. You can trigger scans on image push or manually.

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

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

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.