In the last7days series on this blog I’ll revisit interesting content from twitter from the last 7 days and I’ll add further comments or responses to feedback which I got. The list will have about 3-5 pieces of content to keep it crisp and I hope you like what you see!
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1) Grafana Incident: Smart incident management for your teams 🦍❤️ by @grafana
Grafana Incident: Smart incident management for your teams ( https://t.co/W3iitfyZ9z ) > myPOV: #grafana trying to get nearer to #pagerduty, #servicenow and the likes: I like grafana for its simple configurability— Daniel Koller (@dakoller) February 6, 2022
This is Grafana getting from a good dashboard getting into a full incident management tool. That’s obviously a crowded space, when looking at the screenshots the functionality looked to me me quite close to where tools like PagerDuty or ServiceNow are or want to be.
A nice feature is to see changes in metrics (that’s where Grafana is coming from) next to chat & AI insights. The tasks assigned to an incident look interesting however it looks like one has to define those tasks individually for every incident. Coming from a cloud provider incident handling handling point of view, you’d want to have standardized runbooks assigned to an incident.
Grafana incident also contains a chatbot now, which like one of the more sophisticated use cases for chatbots (some of you might know my early steps with Alexa chatbots).Curiosity remains how much Grafana incident has a meaningful API, which is important to extend the list of use cases.
Something which Grafana incident misses is any enterprise level incident coordination, I guess the products small to medium operations teams with no special process overhead like “Major incident handling” and similar things.
2) Launch HN: Ploomber (YC W22) – Quickly deploy data pipelines from Jupyter/VSCode by @ploomber
When I last checked I either captured data processing steps (I wouldn’t even call this real machine learning) in Python and Jupyter notebooks. Ploomber extends this concept now by putting these steps in reproducible workflows.
Especially interesting is that ploomber can get along with python code, Jupyter notebooks, SQL and R scripts, which might help you to integrate legacy data workflow code. Production deployment of the pipeline is possible via Kubernetes (via sooperviser), AWS Batch, Airflow, and SLURM.
3) [German only] Mein Coronavirus wurde zufällig sequenziert. by @stadtwildnis
Mein Nerd-Herz schlägt: Mein Coronavirus wurde zufällig sequenziert.— molo 3000 (@stadtwildnis) January 31, 2022
Schau ich mal, was da so drinsteckt.
This twitter thread is from a bio technology nerd, who got Corona and was lucky to get her virus DNA code sequenced. What follows is a ride through what the genetical code of the virus means and which information it contains. Interesting side conversation are the different involved tools and open standards.
I am happy to get feedback from you!